ArticlePDF AvailableLiterature Review

Health Psychology: The Search for Pathways between Behavior and Health

February 2008
Annual Review of Psychology 59(1):477-505

February 2008
59(1):477-505

DOI:10.1146/annurev.psych.59.103006.093643

Source
PubMed

Authors:

Howard Leventhal

Rutgers, The State University of New Jersey

John Weinman

King's College London

Elaine A Leventhal

Rutgers, The State University of New Jersey

L. Alison Phillips

Iowa State University

This review of the current status of theoretically based behavioral research for chronic illness management makes the following points: (a) Behavioral interventions have demonstrated effectiveness for improving health outcomes using biomedical indicators, (b) current interventions are too costly and time consuming to be used in clinical and community settings, (c) translation of the conceptual models generated from studies of the problem-solving processes underlying self-management and the relationship of these processes to the self system and cultural and institutional contexts suggest new avenues for developing effective and efficient cognitive-behavioral interventions, and (d) it is proposed that integration of the conceptual developments in self-management with new approaches to the design of clinical trials can generate tailored, behavioral interventions that will improve quality of care.

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ANRV331-PS59-18 ARI 5 November 2007 10:57

Health Psychology: The

Search for Pathways between

Behavior and Health

Howard Leventhal,

John Weinman,

Elaine A. Leventhal,

and L. Alison Phillips

Institute for Health, Health Care Policy and Aging Research, Rutgers, The State

University of New Jersey, New Brunswick, New Jersey 08901-1293;

Health

Psychology Section, Psychology Department, Institute of Psychiatry, King’s College

London, London SE1 9RT, United Kingdom; email: hleventhal@ifh.rutgers.edu

Annu. Rev. Psychol. 2008. 59:477–505

The Annual Review of Psychology is online at

http://psych.annualreviews.org

This article’s doi:

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0066-4308/08/0203-0477$20.00

Key Words

behavioral interventions, self-management, chronic illness

Abstract

This review of the current status of theoretically based behavioral

research for chronic illness management makes the following points:

(a) Behavioral interventions have demonstrated effectiveness for im-

proving health outcomes using biomedical indicators, (b) current in-

terventions are too costly and time consuming to be used in clinical

and community settings, (c) translation of the conceptual models

generated from studies of the problem-solving processes underlying

self-management and the relationship of these processes to the self

system and cultural and institutional contexts suggest new avenues

for developing effective and efﬁcient cognitive-behavioral interven-

tions, and (d ) it is proposed that integration of the conceptual de-

velopments in self-management with new approaches to the design

of clinical trials can generate tailored, behavioral interventions that

will improve quality of care.

477

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Contents

INTRODUCTION................. 478

WHY FOCUS ON PREVENTION

AND CONTROL OF

CHRONIC ILLNESS? .......... 479

EVIDENCE-BASED PRACTICE

AND BEHAVIORAL

INTERVENTIONS FOR

CONTROLLING CHRONIC

ILLNESSES ..................... 479

Translational Research and

Evidence-Based Medicine...... 479

The Diabetes Prevention Trials . . . 480

Do the Trials Meet Criteria for

Evidence-Based Practice? ...... 481

THE PROCESS OF

SELF-MANAGEMENT OF

CHRONIC ILLNESS ........... 481

Factors Affecting Chronic Illness

Management: Emotion and

Cognitive Traits ............... 482

Factors Affecting Chronic Illness

Management: Process

Analyses ...................... 484

Factors Affecting Chronic Illness

Management: Contextual

Factors of Self, Social

Networks, and Culture ........ 490

COGNITIVE-BEHAVIORAL

INTERVENTIONS TO

IMPROVE

SELF-MANAGEMENT ......... 494

Process Theories and Design

of Clinical Trials .............. 495

PAST, PRESENT, FUTURE:

CONCLUDING

COMMENTS ................... 496

INTRODUCTION

Health psychology research needs to satisfy

two goals: the development of theoretical

models describing the processes underlying

risky and healthy behaviors, and the creation

of effective procedures for behavioral change

that are usable in clinical and community

settings. The primary steps required for a

practice-oriented theory are to increase the

speciﬁcity and predictive power of theory by

adding concepts generated from observations

in clinical and community settings and to

develop increasingly complex models to

better understand how behavioral factors

contribute to health outcomes. The steps

required for practice are to develop interven-

tions that are theory-based and are usable

in clinical and community settings as well

as effective for helping individuals initiate

and sustain behaviors that will improve their

personal health. These goals are reﬂected in

the three major lines of research examined

in previous contributions to the Annual

Review of Psychology: biobehavioral studies

of direct pathways from behavior to illness

(e.g., stress illness research; Ader & Cohen

1993, Baum & Posluszny 1999), behavioral

interventions to control these direct pathways

(Kiecolt-Glaser et al. 2002, Schneiderman

et al. 2001), and behavioral studies focused

on the prevention and control of chronic

conditions (Rodin & Salovey 1989). This

review focuses on a subset of this third area

of behavioral studies: the processes involved

in initiating and maintaining behaviors for

reducing risk and controlling existent chronic

disease. These behaviors include lifestyle

changes such as diet, exercise, and adherence

to medication for reducing risk and control of

diabetes, hypertension, and congestive heart

failure. A narrow focus is necessary because

it is impossible to cover in the space allotted

the enormous number of behavioral studies

that have appeared since a previous and able

review by Rodin & Salovey (1989).

Our chapter is organized as follows: First,

we provide a brief justiﬁcation for focus-

ing on prevention and control of chronic

illnesses. We argue that the movement for

evidence-based practice in the medical ﬁeld

has created pressure on health psychologists

for effective and efﬁcient (usable) theory-

based behavioral interventions for the con-

trol of chronic illness. Second, we review

478 Leventhal et al.

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ANRV331-PS59-18 ARI 5 November 2007 10:57

models and evidence respecting the self-

management process, i.e., how people man-

age (control and prevent) chronic conditions

in their home settings. This section is orga-

nized around the proposition that the social-

cognitive-behavioral model, with an emphasis

on cognitive processes, is the most compre-

hensive model for understanding behavioral

processes relevant to health. Third, we brieﬂy

review new approaches to clinical trials for in-

creasing the effectiveness of behavioral inter-

ventions and whether integrating these inno-

vative approaches with self-regulation models

could create interventions that are usable in

clinical settings.

WHY FOCUS ON PREVENTION

AND CONTROL OF CHRONIC

ILLNESS?

Advances in public health and the economic

well-being of populations in the early twen-

tieth century in Western nations resulted in

chronic conditions, such as cardiovascular

diseases and cancers, replacing infectious

diseases as one of the top ten killers in

Western nations (Fries 2005, McKinlay &

McKinlay 1977). The recent surge in HIV

AIDS, an infectious condition, is not an

exception to this trend, because existing HIV

treatments are lifelong, i.e., chronic, and

require chronic, intensive self-management

(Siegel & Lekas 2002). Treatment of chronic

illnesses also absorbs well over half of the

health care budget of developed nations

(McKinlay & McKinlay 1977), and because

chronic conditions are more common with

advancing age, the ﬁnancial burden will

increase as the population ages. The focus of

this chapter on chronic illness management is

congruent, therefore, with a major problem

for society and the health care system. As

human behaviors, including food intake,

physical activity, and cigarette smoking, are

causally related to both vulnerability and

management of chronic conditions, it is fully

justiﬁed to focus on their prevention and

control (Baum & Posluszny 1999).

Narrowing the focus to behaviors for the

prevention and management of chronic dis-

eases sets constraints on how we cover the

pathways to chronic illness that have been

identiﬁed by social, behavioral, and biomed-

ical investigators. For example, although sta-

tistical models have shown direct effects to

health through economic, ecological, and cul-

tural pathways (House et al. 1992, Kaplan

1992), we argue that many of these effects are

produced by behavior. Failure to detect be-

havioral mediators at the individual level may

be due to deﬁcits in assessment of relevant

behaviors and to narrow deﬁnitions of behav-

ior that include only overt risky (smoking) or

healthy (exercise) behaviors and ignore gen-

eralized behaviors or sets such as chronic vig-

ilance. We also propose that direct pathways

from psychological traits such as trait negative

affect (trait NA) and cognitive competency

to health are often mediated by behavioral

factors, though many relationships between

traits and health indicators reﬂect interactions

of behaviors with third factors such as genetic

make-up and/or gene expression. All of the

pathways impact the individual and the indi-

vidual’s behaviors—healthy, risky, treatment

adherence, and lifestyle behaviors. It is rea-

sonable to expect, therefore, that the best way

to affect health outcomes will be through the

pathways inﬂuencing these behaviors.

EVIDENCE-BASED PRACTICE

AND BEHAVIORAL

INTERVENTIONS FOR

CONTROLLING CHRONIC

ILLNESSES

Translational Research and

Evidence-Based Medicine

Translational research is critical for both the-

ory and practice, and “the recasting of clinical

science along the principles of evidence-

based medicine provide[s] a better environ-

ment where translational research may now

materialize its goals” (Ioannidis 2004, p. 5).

The growth of evidence-based practice in

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•

Health Psychology 479

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ANRV331-PS59-18 ARI 5 November 2007 10:57

medicine has created pressure on health psy-

chologists for effective and efﬁcient theory-

based behavioral interventions for the con-

trol of chronic illness. Even though clinical

outcome trials provide information on the

efﬁcacy of treatments, the mechanisms for

change are not delineated in clinical outcome

studies, a fact that limits their use for prac-

tice and theoretical development, and so we

must move beyond clinical outcome stud-

ies to translational research that investigates

the effects of individual, theoretical compo-

nents (Lerman 2003). In this way, our re-

search can be translated for and used by those

in clinical practice. A broad literature search

was conducted using two Ovid information

sources, PsycINFO and Medline, for random-

ized, controlled trials of behavioral interven-

tions conducted in the past decade whose

purpose was to study the prevention and man-

agement of chronic conditions. General sub-

ject terms were used in both search engines,

including all terms that were related to “be-

havioral intervention” or “lifestyle interven-

tion,” “chronic illness,” and “randomized tri-

als.” A total of 137 studies were collected using

the speciﬁed search terms; the studies were

then cut down to only those that met criteria

of being behavioral interventions, using ran-

domized and controlled trials, and having to

do with chronic conditions in the past decade.

The search results were further eliminated if

they were related to drug addictions or smok-

ing rather than chronic illnesses such as dia-

betes and heart failure. After all inclusion and

exclusion criteria were implemented, 26 stud-

ies remained. Of these 26 trials, 21 reported

signiﬁcant and substantial beneﬁts from a be-

havioral intervention. Although these trials

are few in number, 80% of them produced

some or all of their predicted beneﬁts in health

outcomes. Thus, the best trials clearly satis-

ﬁed the key criterion for effectiveness—the

behavioral changes reduced the onset and/or

progression of chronic disease—but fell short

of a second criterion: They were not efﬁcient

and usable in the vast majority of clinical set-

tings, as has beenthe case for most effective in-

terventions (McDonald et al. 2002). In the fol-

lowing section, we focus on two diabetes pre-

vention trials that are excellent examples of ef-

fective behavioral interventions, and then we

address behavioral models that point to possi-

ble directions for achieving efﬁciency and/or

the clinical usability of such behavioral inter-

ventions. To be clinically usable, behavioral

interventions must be efﬁcient, not only ef-

fective, so that physicians, nurses, and health

institutions have the time and resources for

implementation.

The Diabetes Prevention Trials

The Finnish Diabetes Prevention Study

Group (Lindstr

om et al. 2003, Tuomilehto

et al. 2001), which conducted a randomized

trial comparing lifestyle with standard-care

treatment conditions, reported that 58%

fewer lifestyle participants became diabetic

relative to those in standard care over the

average four years of its intervention. Most

importantly, the beneﬁt of lifestyle change

was sustained for three years following

termination of the intervention, though the

effect shrank somewhat at ﬁnal follow-up

(58% to 46%). The trial of individuals at

high risk for diabetes that was conducted in

the United States (Diabetes Prev. Prog. Res.

Group 2002) conﬁrmed the Finnish ﬁndings;

58% fewer of the 1079 participants in the

lifestyle intervention became diabetic in the

2.8-year post-intervention period (average

per-participant observation) in comparison

with the 1082 standard-care participants.

The 1073 participants taking medication also

fared better than control participants, 31%

fewer became diabetic, though they fared

signiﬁcantly less well than the participants

in the lifestyle intervention. The quality of

these trials appears to be very high; adherence

to the interventions was excellent (80% or

more), and mediating factors, weight loss, and

hours engaged in physical activity increased

more in the lifestyle than in the control

conditions. Although it is difﬁcult to compare

the time demands and extent of coverage for

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ANRV331-PS59-18 ARI 5 November 2007 10:57

speciﬁc topics in these complex interventions,

the Finnish study appears to have been sig-

niﬁcantly less time demanding than that used

by the U.S. working group (for reviews, see

Heneghan et al. 2006,Tuomilehto et al. 2005).

Do the Trials Meet Criteria for

Evidence-Based Practice?

Although the incidence of diabetes is clearly

lower, and impressively so, for participants

in lifestyle interventions than for those in

control or medication treatment conditions

(see Gillies et al. 2007, Yamaoka & Tango

2005), support for lifestyle interventions as

an evidence-based practice requires that the

interventions meet additional benchmarks.

First, diabetes is a lifetime condition, and

although the seven-year follow-up in the

Finnish trial is encouraging, it remains to be

seen if the behavioral changes and their bene-

ﬁts will be sustained over a lifetime and can

be replicated in other trials. Second, there

are issues of cost effectiveness and usabil-

ity in clinical settings. The U.S. program

involved 16 one-on-one, hour-long sessions

with a cognitive-behavioral therapist as well

as meetings with nutritionists and nurses and

phone calls to reinforce and sustain behavior

change. Economic analyses of the U.S. and

a similar lifestyle program conducted in the

United Kingdom suggest they are cost effec-

tive for the health care system and for society

as a whole; the costs include direct medical

and nonmedical expenses and various indi-

rect costs (Diabetes Prev. Prog. Res. Group

2003, Teutsch 2003). Cost effectiveness on

a national scale does not, however, translate

into usability in clinical settings, where per-

sonnel skilled in the conduct of such inter-

ventions are lacking and the savings may go

to units (e.g., hospitals) other than those in

which interventions are conducted (e.g., spe-

cialty clinics). Furthermore, cost effectiveness

on a national scale does not necessarily trans-

late into cost effectiveness for the individual

patient, the people for whom the interven-

tion is aimed, because patient time is rarely

considered in cost analyses (Russell et al.

2005).

We propose that understanding the pro-

cesses underlying how patients act to detect

and manage chronic conditions will provide

ideas for effective and efﬁcient interventions.

This proposal is consistent with, although dif-

ferent from, efforts to tune interventions to

stages that deﬁne participants’ readiness for

change (Prochaska et al. 2005), to target the

intervention to groups of participants, or to

tailor the interventions to individuals’ needs

(De Bourdeaudhuij & Brug 2000). A review

of tailored informational interventions (Ryan

& Lauver 2002) concluded that they were sig-

niﬁcantly more effective than were standard

interventions for some but not all types of be-

havior (e.g., effective for dietary behaviors but

not for smoking behaviors), and these inter-

ventions were more likely to be effective when

they used ipsative feedback, which compares

a participant’s present and past behaviors. All

of the reviewed tailored informational inter-

ventions that were signiﬁcant had only very

small effect sizes. Therefore, although these

interventions may be more efﬁcient than the

lifestyle interventions to date, they are not

as effective. The challenge for interventions

is to be effective and efﬁcient, and therefore

usable.

THE PROCESS OF

SELF-MANAGEMENT

OF CHRONIC ILLNESS

The creation of effective and efﬁcient

evidence-based practices requires something

in addition to the translation of theory-

based interventions to practice settings: These

additions can be identiﬁed by the system-

atic investigation and conceptualization of

the processes underlying how patients use

treatments in their homes, workplaces, and

communities—their lived environments. We

propose that the incorporation of models and

concepts developed in ﬁeld settings into the

conceptual structure of behavioral theory de-

veloped in laboratory settings, i.e., translation

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Health Psychology 481

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from the ﬁeld to the laboratory, will facil-

itate the development and testing of efﬁ-

cient and effective interventions for enhanc-

ing healthy behaviors. Translation from the

ﬁeld is critical given that medical treatments

and lifestyle behaviors are performed in lived

environments.

Factors Affecting Chronic Illness

Management: Emotion and

Cognitive Traits

Studies of health care usage, disease risk

screening, and behavior for the prevention

and management of chronic conditions pro-

vide insights into mechanisms underlying

effective self-management behaviors. The

social-cognitive-behavioral framework that is

the basis for behavioral health research en-

compasses factors ranging from the cultural

and social environment through individual

or person factors, and most importantly, the

behavioral processes that initiate and sustain

healthy and risky behaviors. The framework

encompasses a multilevel set of control sys-

tems (Carver et al. 1989, Cooper & Shallice

2006, Powers 1973), with each level gener-

ating goals and strategies that inﬂuence ad-

jacent levels in the hierarchy. Understanding

how variables interact either within or across

levels is not captured by structural or hier-

archical statistical models that depict the ar-

chitecture of a system but do not describe its

software, i.e., how factors communicate with

one another. How factors communicate with

one another is critical information for the de-

sign of interventions. For example, there is

little evidence on how typical individual dif-

ference measures relate to within-individual

variation in behavior over time because indi-

vidual difference measures may not identify

and assess the self-perceptions and strategies

that control the temporal variation in intra-

person problem solving (Cervone 2004). We

illustrate these points below in our description

of what is known about the processes involved

in the regulation of treatment adherence

behaviors.

Emotion traits. For more than 30 years,

studies have reported on the relationship be-

tween individual differences in emotion char-

acteristics and healthy and risky behaviors

and health outcomes, e.g., mortality and mor-

bidity. Although measures of negative affect

such as trait anxiety are more or less con-

sistent predictors of morbidity and mortality

(Friedman & Booth-Kewley 1987), they are

somewhat less effective in predicting healthy

and/or risky behaviors (Mora et al. 2002,

2007). Individual differences in depressive af-

fect and angry/hostile behavioral styles are

somewhat an exception, as they have been

consistent predictors of morbidity and mor-

tality from cardiovascular disease (Barefoot

et al. 1983). Questions about these relation-

ships include the extent to which these con-

structs overlap with oneanother and with vari-

ables such as burnout and vital exhaustion, and

whether they affect health through the same

or through different physiological pathways

(Suls & Bunde 2005).

Although studies have generally failed to

detect robust direct effects of factors such as

neuroticism or trait anxiety on care seeking,

theory has suggested and data have identiﬁed

indirect pathways that merit further examina-

tion. One such path shows, as predicted, that

individuals with high scores on trait NA are

more likely to report asthma-speciﬁc health

worries that mediate the connection between

trait NA and the reporting of symptoms spe-

ciﬁc to asthma. Asthma-speciﬁc worries, how-

ever, do not affect the relationship of the

trait NA to reporting of generic, emotional

symptoms (Moral et al. 2007). Thus, being

high on trait NA increases susceptibility to

feeling fearful in response to illness threats

and focuses attention on the physical indi-

cators of threat, allowing the individual to

distinguish clearly between symptoms of ill-

ness and symptoms of emotional distress. Be-

cause illness-speciﬁc worry enhances atten-

tion to and accurate identiﬁcation of illness

symptoms, and because symptoms are power-

ful initiators of health behaviors, it is clear that

illness-speciﬁc worry should predict seeking

482 Leventhal et al.

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ANRV331-PS59-18 ARI 5 November 2007 10:57

health care; a speciﬁc worry, cancer worry,

has been shown to predict cancer screening

(Diefenbach et al. 1999, Hay et al. 2006).

Imaging studies have identiﬁed neural centers

that are likely the loci for memories that inte-

grate symptoms, subjective worry, and action

tendencies (Critchley 2005).

Depression appears to have direct effects

on a range of health behaviors. For exam-

ple, depression has been shown to reduce ad-

herence to treatment in patients who have

had a myocardial infarction (MI) (Ziegelstein

et al. 2000), to reduce attendance at programs

for lowering blood lipids post-MI and post-

bypass surgery (Sebregts et al. 2003), and to

delay care seeking following an MI (see re-

view by Dracup et al. 1995) and bowel ob-

struction (Bickell et al. 2005). The data sug-

gest, however, that these effects often reﬂect

only one of the components of depression,

i.e., its affective, cognitive, or somatic feature,

and not the entire construct. For example, a

cognitive component of depression, the be-

lief that other people disrespect and dislike

you, predicted reductions in perceived social

support over a two-year period in a sample

of 851 elderly individuals, whereas depressed

mood and somatic symptoms had no rela-

tionship to reductions in perceived support

(Maher et al. 2006). Social support is asso-

ciated with better health outcomes (Cohen

2004), and thus its erosion would increase risk

of illness, thereby deﬁning an indirect path-

way from depression to physical illness. Con-

sistent with prior data (Dracup et al. 1995), in-

terviews with 433 post-MI patients found that

patients reporting depressive symptoms two

weeks prior to hospitalization delayed longer

(40+ hours) before seeking care in compari-

son with patients who did not report depres-

sive symptoms (22+ hours; Bunde & Martin

2006). This direct effect however, was due

entirely to two items in the Patient Health

Questionnaire-9 depression measure: fatigue

and sleep disturbance. Delay was not related

to the other components of depression, mood,

anhedonia, or feeling bad about the self, or to

the neuroticism scale from the Big Five In-

ventory (Costa & McCrae 1992). The ﬁnd-

ings for white coat hypertension reported by

Spruill and colleagues (2007) resonate with

the Bunde & Martin (2006) data: situational

fear levels and not trait anxiety were associated

with (white coat) hypertension in the clinical

setting; white coat hypertension was detected

for individuals who had labeled themselves as

hypertensive regardless of their actual ambu-

latory blood pressure status. Kemeny’s (2003)

summary of multiple studies also shows that

situation-speciﬁc measures, and not general

measure of stress, predict HIV progression.

Thus, the results of these studies converge

in showing that situation-speciﬁc rather than

general conceptualizations and measurements

of emotion concepts are needed to predict

health outcomes (Leventhal et al. 2007a).

Cognitive/behavioral traits. The Big Five

factor of conscientiousness and its subfactor

of conventionality appear to have consistent,

modest relationships with lower levels of risky

and higher levels of healthy behaviors and bet-

ter health outcomes (Bogg & Roberts 2004).

A recent analysis of existent data found that

teacher ratings of conscientiousness were pos-

itively related to better health in their former

pupils 40 years later; some of the effect was

clearly indirect, i.e., from conscientiousness

through educational attainment and higher

levels of healthy and lower levels of risky

behaviors, although some of the relation-

ship was direct and unaccounted for by me-

diators in the best-ﬁtting model (Hampson

et al. 2007). Conscientiousness may affectself-

management at many points in the behavioral

process: It may affect risk aversion, nondis-

counting of remote rewards, skills in gener-

ating action plans, and/or adherence to well-

organized, nonrisky, and not overly complex

lifestyles (Park et al. 1999). Behavioral pro-

cesses related to conscientiousness may play a

role in the “healthy adherer effect” (Simpson

et al. 2006); participants adherent to proto-

col in placebo conditions have been found to

have outcomes as favorable as those of treated

patients.

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Health Psychology 483

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Summary comment. It is clear that person

traits are related to health. What is not well

understood is how person factors relate to

speciﬁc behaviors or biological vulnerabilities

that mediate these effects. The identiﬁca-

tion of the processes underlying how traits

inﬂuence problem solving (i.e., how health

threats are viewed, the strategies skills and

speciﬁc responses for threat management)

and how the outcomes of problem solving are

evaluated and translated into intermediate

beliefs (worries; strategies) requires analyses

that focus on intraindividual assessment

rather than individual-difference assessment.

As Cervone (2004) argues, stable factors

(traits) may have little or no relationship

to the process-level variables that affect the

day-by-day ﬂuctuation in health-relevant

behaviors. The identiﬁcation of relationships

to health behaviors and health outcomes

of speciﬁc health worries, components of

depression, or representations of speciﬁc self

vulnerabilities, and behavioral styles speciﬁc

to particular types of settings are consistent

with the proposition that domain-speciﬁc

person factors will better predict behavioral

episodes over time. This is true because they

are tuned to the speciﬁc cues, internal and

external, that activate behavioral processes

in that domain (Cervone et al. 2006). As we

argue in the ﬁnal section, understanding how

moderators such as traits affect process-level

variables will be critical for the development

of effective and efﬁcient interventions.

Factors Affecting Chronic Illness

Management: Process Analyses

Studies have identiﬁed a broad array of cul-

tural, community, and personal values and

beliefs and associated triggering factors that

initiate and sustain behaviors affecting the de-

velopment of chronic illnesses. For example,

obesity, a multiplier of risk factors for many

chronic conditions (Pi-Sunyer 1993), is af-

fected by factors ranging from availability and

cost of healthy foods to cultural values associ-

ated with portliness and thinness, to individ-

ual pathology affecting food intake (Wadden

et al. 2002). The picture for addictions, smok-

ing, and alcohol use is equally complex; cul-

tural, peer, and family environments as well

as individual propensity to risk taking and

emotional reactivity affect likelihood of ini-

tiation, rapidity of addiction, and difﬁculty

of cessation (Galea et al. 2004, Turner et al.

2004). Models depicting the processes in-

volved in healthy and risky behaviors typi-

cally place environmental factors (availabil-

ity; cost; socioeconomic status) on the far left,

belief variables such as personal vulnerability

next, then triggers that activate these beliefs

and motivate action, followed by response al-

ternatives and their associated expectations

(e.g., response efﬁcacy and self-efﬁcacy for

execution), a plan for action (Bandura 1989,

Leventhal 1970, MacGregor et al. 2006), and

post-action satisfaction (Baldwin et al. 2006,

Finch et al. 2005). Consistent with earlier data

(Leventhal 1970), a combination of motivat-

ing variables (attitudes, intentions) and action

variables, i.e., plans and efﬁcacy (Leventhal

et al. 1965, Sheeran & Orbell 2000), appears

to be essential for healthy or risk-reducing be-

haviors; neither set alone appears to be suf-

ﬁcient to generate behavior (Leventhal 1970,

Rothman 2000, Witte & Morrison 2000). For

example, a recent study of volunteer parent

participants in a smoking-cessation interven-

tion found that predictors of participation in

the program included recently receiving med-

ical care, a motivating factor, and planning

to make changes in smoking behavior (Mak

et al. 2006). Action plans play a key role in

converting attitudes to action; the associa-

tions are especially large with respect to per-

forming single, time-limited behaviors such as

screening for and inoculation against disease

threats (e.g., Orbell et al. 1997). Suggestions

as to how cultural-, social-, and person-level

factors affect the processes involved in self-

management of chronic illness are a central

concern of this review because interactions

among these factors are crucial for research

aiming to develop effective and efﬁcient in-

terventions. Since lifetime management of

484 Leventhal et al.

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ANRV331-PS59-18 ARI 5 November 2007 10:57

diseases such as asthma, diabetes, and hyper-

tension is highly dependent upon contact with

the medical care system, we concentrate on

empirical studies examining the processes un-

derlying the use of health care and adherence

to lifestyle behaviors and medication for the

control of chronic conditions.

Triggers. When we distinguish visits to

health care providers that are patient driven

from those that are routine annual exams—

practitioner or employer scheduled visits—it

is no surprise that patient-driven visits are the

visits triggered by somatic changes. For ex-

ample, new symptoms triggered use of care

for 100% of 121 elderly individuals whose use

of care was tracked over a year; only 30% of

their matched controls reported new symp-

toms (Cameron et al. 1995). The new symp-

toms reported by the 30% of noncare users

were seen as not severe or of sufﬁcient du-

ration to merit attention. Care-seeking de-

lay can be similarly predicted by a lack of

perceived relevance of a symptom to illness.

Burgess and colleagues (1998) found, for ex-

ample, that women who delayed care seeking

for breast cancer symptoms were more likely

to have nonlump symptoms than were those

who did not delay care seeking; that is, because

there was no lump in the breast, the women

who delayed seeking care did not realize the

severity of the initial, nonlump symptom.

Heuristics. The numerous empirical stud-

ies describing differences in how young and

elderly individuals evaluate and respond to

their symptoms (see Brody & Kleban 1983,

Stoller 1998) make up a vast repository of in-

formation with rich theoretical implications

for the appraisals that underlie seeking health

care. Investigators have begun to identify

the speciﬁc heuristics, or mental rules, that

people use to interpret somatic events and

to identify the illness schemata underlying

their use (Brownlee et al. 2000). Four classes

of heuristics have been identiﬁed (Leventhal

et al. 2007b): ﬁrst, heuristics involving in-

nate, spatial-temporal maps of symptoms into

cerebral architecture (e.g., location, duration,

severity); second, heuristics involving patterns

of symptoms based on prior experience (e.g.,

schema related—chest pain means a heart

problem), novelty (ambiguous or incongruous

with underlying schema), trajectory (worsen-

ing, ﬂuctuating), and control (e.g., did it or did

it not improve with self-care); third, heuris-

tics based upon cultural beliefs and social

experience (e.g., age-illness, gender stereo-

types, stress/illness, good feeling = good

health); and last, heuristics involvingactiveso-

cial comparisons (e.g., prevalence and severity

in one’s community, and similarity rules such

as similarity in exposure, temperament, phys-

ical characteristics). Heuristics give meaning

to somatic changes. For example, changes of

long duration and high severity imply that an

experienced somatic change may be a seri-

ous threat to function and/or life; both are

associated with high levels of care seeking

among elderly individuals (Mora et al. 2002).

Mild, chronic symptoms with unchanging tra-

jectories that lack a speciﬁc pattern and are

systemic rather than localized are readily at-

tributed to age rather than illness (Brody &

Kleban 1983, Prohaska et al. 1987). Since

multiple heuristics are involved in the inter-

pretation of a somatic event, it is possible to

predict interactions among them. For exam-

ple, in comparison to symptoms that are dis-

tinctive (e.g., patterned or in a speciﬁc lo-

cation, such as sore throats, stuffed nose, or

swelling), symptoms that are vague (e.g., in a

nonspeciﬁc location and/or lacking pattern,

such as fatigue or aching body) are readily

attributed to life stress and are unlikely to

trigger motivation for seeking medical care

(Cameron et al. 1995). However, when vague

symptoms were experienced in association

with life events a month or more in dura-

tion, care seeking was just as likely as it was

for distinctive symptoms. The perception that

vague symptoms may be indicators of illness

when associated with stressors of long dura-

tion is consistent with empirical data that pro-

longed stress increases the likelihood of de-

veloping a cold after exposure to rhinoviruses

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ANRV331-PS59-18 ARI 5 November 2007 10:57

(Cohen et al. 1998, Cohen & Williamson

1991). There are instances, therefore, in

which people’s mental tool boxes, that is,

their heuristics, provide rules in accord with

empirical data.

The studies of heuristics suggest at least

three directions for future research. First, in

their study of delay in care seeking follow-

ing a myocardial infarction, Bunde & Martin

(2006) found opposite effects on delay for

mental rules and depression: location (chest

pain), pattern (left chest and arm), and novelty

(sweating) reduced delay, whereas depression

increased delay. Consistent with the parallel-

processing assumption that underlies illness

cognition models (Leventhal 1970), the ef-

fects of heuristics and depression were inde-

pendent of one another; i.e., the bivariable re-

lationships of depression and/or heuristics to

delay were unchanged in multivariable mod-

els. The effect of context on the indepen-

dence or interdependence of heuristics and

affect needs to be studied. Second, an indi-

vidual will act differently when heuristics join

potentially unique experiences into a common

conceptual framework versus when they do

not; e.g., an individual will seek health care if

chest pain, sweating, and arm pain are framed

within the concept of “heart attack” and not as

discrete events. Concepts allow the individual

to see similarities over occasions (prior his-

tory was related to swift care seeking; Bunde

& Martin 2006, Dracup et al.1995),to see cur-

rent symptoms as signals for later ones, and to

regulate behavior in line with the expectations

associated with the more abstract, conceptual

framework of “heart attack.” By contrast, car-

diac diseases such as congestive heart failure

lack the features necessaryto be coded as coro-

nary events; the chronic symptoms are often

mild (breathlessness, fatigue, swollen legs), at-

tributed to age, and are not conceptualized as

heart related (Horowitz et al. 2004). Although

patients are told they have heart disease, fail-

ure to connect their symptoms to a cardiac

concept (absence of depth) results in failure to

see worsening of chronic symptoms as an in-

dicator that more severe symptoms are on the

horizon. Patients who say they do not under-

stand their conditions do not act to counter,

change, and avoid hospitalization. The con-

ditions necessary for linkage to occur, i.e., the

time needed to see relationships among em-

bedded experiences, require research.

The third direction for future research in

relevant health heuristics concerns the rela-

tionship of these illness-oriented heuristics to

cognitive-search rules, such as representative-

ness and availability, which are factors related

to limitations in processing capacity (Tversky

& Kahneman 1974). Within the illness cog-

nition framework, availability and represen-

tativeness are conceptualized as attributes of

the domain-speciﬁc rules. Thus, the availabil-

ity and representativeness of a somatic/health

heuristic is a function of the schemata or

database underlying the search process. Inves-

tigations in this domain will be important for

understanding the conditions involved in the

biases affecting self-appraisals and sustained

self-management of chronic conditions.

Schemata and illness representations.

The initial question likely addressed by

heuristic processing is, “Am I sick or am I

well?” Crossing the threshold from perceiv-

ing no illness to perceiving illness involves

consideration of alternative schemata on the

“sickness” side of the equation. Early mul-

tidimensional scaling and cluster analysis of

illness labels found four clusters of illness rep-

resentations in a two-dimensional space: con-

tagious illnesses that are a threat to life and

those that are not, and noncontagious illnesses

that are a threat to life and those that are not

(Bishop 1991). Although scaling did not assess

the availability or salience of these categories,

Bishop (1991) identiﬁed a clear indicator of

salience by showing that memory for illness

information was better retained if consistent

with an underlying prototype. Evidence that

prototypes affect behavioral management of

chronic conditions was clear in the early stud-

ies of hypertension showing that diagnostic

labeling was associated with symptom report-

ing both for patients (Meyer et al. 1985) and

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ANRV331-PS59-18 ARI 5 November 2007 10:57

for subjects in laboratory studies (Baumann

et al. 1989); the linkage of symptoms to a

label reﬂects the fundamental symmetry be-

tween the prototype and experience: “to be

sick means being symptomatic.” Patients hos-

pitalized for severe attacks of asthma agreed

that they “will have asthma all of their lives”

and then agreed that they “have asthma only

when they have symptoms” (Halmet al. 2006);

behavior was consistent with these beliefs as

they took both prevention medication (which

is to be used daily when asymptomatic) and

controller medication (which is to be used for

attacks) only when they were symptomatic.

Symptom management is also a pattern for

HIV, a contagious, chronic condition; when

symptoms clear up, patients with HIV are

likely to stop medication (Horne et al. 2004).

The schema most consistent with symp-

tom management is the acute illness model,

a schema with ﬁve domains identiﬁed by the

Illness Perception Questionnaire (Weinman

et al. 1996): (a) identity—symptoms and label,

(b) time line (time limited), (c) cause (external

cause), (d ) consequences (not life threaten-

ing), and (e) control via self-care or with medi-

cal treatment (Diefenbach & Leventhal 1996).

The acute representation is linked to pro-

cedures for management that alleviate (con-

trol) both symptoms and condition (identity),

are time limited (time line), nonthreaten-

ing (consequences), and work through routes

that are plausible given the underlying condi-

tion (cause; Horne 2003). The acute or time-

limited nature of symptom-focused models is

consistent with clinical observations and data

showing that patients stop treatment both

when symptoms resolve and when objective

indicators return to “normal values” (Horne

et al. 2004). An excellent study by Henderson

et al. (2007) showed that priming an illness

schema for the common cold (e.g., by writ-

ing about a recent experience with a cold) in-

creases color-naming response time to words

related to the common cold in the Stroop

color-naming test: Response times to neutral

words and words related to cardiovascular dis-

ease were unaffected. When a schema for car-

diovascular disease was primed, color-naming

response time was affected for words related

to cardiovascular disease but not to neutral

words or words related to the common cold.

Schemata are implicit, organized, and affect

behavior when activated.

Representations of treatment and health

behaviors. When a health threat is perceived

as imminent or as probable, procedures will be

entertained and elaborated for threat avoid-

ance and control (Wakslak et al. 2006). Thus,

stimulus events or inputs, such as symptoms,

physical dysfunctions, illnesses in others, and

a variety of social and media messages, ini-

tiate the development of mental representa-

tions of the output, or the behavioral side

of the control system for the regulation of a

chronic illness threat. Treatment behaviors,

whether prescribed or self-initiated, carry an

implicit set of expectations respecting their

consequences, time lines, efﬁcacy (control),

and route of action (causal), and these expec-

tations are appraised against both experiential

and abstract criteria. For example, patients in

the Meyer et al. (1985) study were adherent

to medication and in better blood pressure

control if they perceived that medication was

controlling symptoms they attributed to hy-

pertension; symptoms however, were not re-

lated to blood pressure. Jamison (1995) gives

numerous examples of the conﬂict between

abstract, verbalized expectations and implicit

concrete expectations in the treatment of de-

pression. Although depressed patients have

the abstract knowledge, i.e., they “know” it

will take several weeks for medication to work,

they experience medication symptoms at the

onset of treatment without an improvement

in mood. Experience overwrites knowledge:

They feel the medication is working (creating

symptoms) but they also feel it is not work-

ing (not improving mood) these feelings often

lead to nonadherence. Treatments are embed-

ded in implicit schemata or representations,

and a treatment schema is linked to the rep-

resentation of the illness that is the target for

control.

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Examinations of treatment beliefs held by

chronically ill patients have identiﬁed gen-

eral and speciﬁc concerns about medication

use (general: doctors overprescribe medica-

tion; speciﬁc: medication canbe addictive) and

about speciﬁc beliefs respecting its necessity

(efﬁcacy for maintaining health) and harm-

fulness (Horne & Weinman 1999). Endorse-

ment of these beliefs differs across chronic

conditions: Necessity of medication is more

strongly endorsed by patients with diabetes

than by patients with coronary and psychi-

atric conditions, and concerns about medi-

cation are somewhat higher among patients

with asthma (Horne & Weinman 1999). Since

these beliefs are focused on the response part

of the regulatory system, the data show, as

would be expected, that these beliefs about

treatments are more strongly associated with

treatment adherence than are related beliefs

about the illness. For example, adherence is

better among patients holding strong beliefs

about the necessity of their prescribed med-

ication than among patients who are highly

concerned about the illness but do not see the

medication as necessary (Horne & Weinman

1999, 2002). Medication beliefs were also re-

lated to participation in antiretroviral treat-

ment in the Highly Active Antiretroviral

Therapy study (Horne 2003, Horne et al.

2004) and to treatment adherence (Horne

et al. 2004).

The Theory of Planned Behavior (TPB;

Ajzen 1991) has been used to examine the

relationships of behavioral and/or treatment

beliefs to adherence for issues such as use

of condoms (Albarracin et al. 2001), mam-

mography (Tolma et al. 2006), screening for

colon-cancer (McCaffery et al. 2003), and

dietary and exercise behaviors (see Hagger

et al. 2002 and Smith 2004). In the major-

ity of TPB studies, as in several of the studies

from the perspective of self-regulation theory,

treatment/behavioral beliefs were found to be

more strongly related to behavioral intentions

and action than to illness beliefs. For example,

attendance at a colposcopy clinic for detection

of possible cervical dysplasia was predicted by

(a) the belief that one could readily attend,

(b) a belief of behavioral control, and (c) in-

tentions to attend. Measures of illness rep-

resentations did not predict behavior (Orbell

et al. 2006). Illness representations did predict

attendance as did perceptions of behavioral

control and intentions to act when attendance

at a colposcopy clinic was differentiated into

three categories of patients: did not attend, at-

tended when prompted, and attended without

prompting (Orbell et al. 2006, p. 611). Repre-

sentations of cancer, perceptions of behavioral

control, and intentions predicted attendance

for patients in need of prompting. Prompting

likely primed implicit illness models for these

patients.

In their ﬁne study, Orbell and colleagues

stated their major goal to be the compari-

son of “two theories of health behavior”: self-

regulation and TPB (Orbell et al. 2006). This

goal merits comment because the study and

others similar to it compare the predictive

power of measures, not theories. Moreover,

the selection of measures was inappropriate

for a comparison of theories. Comparing ill-

ness representations as the measure of self-

regulation theory to behavioral beliefs and in-

tentions as the measure of TPB is inadvisable

because it compares only the ﬁrst component

of the self-regulatory control loop and ig-

nores both treatment representations and out-

come expectations, components that are es-

sential for the completion of a self-regulatory

loop. A comparison of theories would assess

the action stage of the self-regulatory model

with the action components of TPB. And if

treatment beliefs (TPB) are conceptually the

same as treatment representations, then the

comparison would be between the two im-

plementations of these components and not

the entire theories. In addition, it is arbitrary

to include intention in TPB and to exclude

it from social-learning or self-regulation the-

ory; intentions are conscious verbalizations of

readiness to act; they are at home in any the-

ory that conceptualizes action readiness at im-

plicit and explicit levels. In summary, compar-

isons among measures are not equivalent to

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ANRV331-PS59-18 ARI 5 November 2007 10:57

comparisons among models (Leventhal et al.

2007c).

Coherence between illness and treat-

ment representations; converting schemas

into scripts. The concept of coherence, i.e.,

whether an individual can make sense of her

or his illness experience, was introduced by

Antonovsky (1993). The concept inﬂuenced

other investigators (Moss-Morris et al. 2002)

and provided a link between health research

and basic research in experimental psychol-

ogy (Broadbent et al. 2006). Whether a rep-

resentation of illness and a representation of

its possible treatments form a cohesive pat-

tern is a core issue for self-regulation theory.

Self-regulation theory would hypothesize that

coherence between illness and treatment rep-

resentations arises when the actions taken to

manage an illness are seen as congruent with

the treatment representation, that is, that they

are perceived to be effective treatments. Per-

ceived effectiveness emerges when the expe-

rienced outcome of treatment matches the

individual’s expectations for both subjective

and objective indicators; these indicators or

targets are generated from the representa-

tion of the illness. The importance of co-

herence, or “goodness of ﬁt,” between illness

and treatment representations can be seen in

studies of patients with hypertension. For ex-

ample, patients who believed treatment was

necessary (assessed using the Horne necessity

scale) were more adherent, and they perceived

their hypertension to have a longer time line,

more negative consequences, and to be more

amenable to control by treatment (Ross et al.

2004); their illness belief that treatment could

control their hypertension was coherent with

their treatment belief that their hypertension

medication was effective. Patients with coher-

ent asthma illness and treatment represen-

tations who saw treatment as necessary and

who were more adherent represented asthma

as a chronic condition. In contrast, patients

with noncoherent representations had con-

cerns about treatment, were less adherent, be-

lieved asthma to be less controllable, and per-

ceived their symptoms as side effects of treat-

ment (Horne & Weinman 2002). Patients re-

sist treatments that are inconsistent with their

illness representations; for example, patients

resisted the recommendation to exercise for

joint and back pain following myocardial in-

farction if they perceived excessive activity

as the cause of their heart attack (Weinman

et al. 2000). Rothman and colleagues (Baldwin

et al. 2006) found that maintenance of smok-

ing cessation was related to satisfaction with

the change is an alternative way of assessing

coherence.

Motivating behavioral change for disease

prevention may prove problematic for indi-

viduals identiﬁed as at genetic risk; behav-

ioral change may seem inappropriate for a

disease that is programmed in one’s genes.

For example, it was expected that testing

people at increased risk for familial hyper-

cholesterolemia would increase motivation

for medication and diet change among par-

ticipants with positive test ﬁndings, but this

was not the case (Marteau et al. 2004). Al-

though the evidence to date is not entirely

consistent, there are several indications that

people are likely to choose medical treat-

ment over lifestyle change (diet and exercise)

for risk reduction when an illnesses is per-

ceived as genetically caused (Marteau et al.

2004, Wright et al. 2006). It is sometimes the

case that simple communications can reverse

the lack of coherence between representations

of illness and treatment; women given a co-

herent explanation as to how smoking could

affect cervical cancer were more likely to un-

dergo cervical screening and express motiva-

tion for smoking cessation (Hall et al. 2004).

Unpacking the coherence concept suggests

that it might be better reframed as convert-

ing discrete representations, that of illness

and treatment, into behavioral scripts that are

generated when behavioral management pro-

duces an expected and satisfying outcome, i.e.,

when behaviors affect objective and subjec-

tive criteria as anticipated (Baldwin et al. 2006,

Finch et al. 2005, Meyer et al. 1985, Rothman

2000).

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Factors Affecting Chronic Illness

Management: Contextual Factors of

Self, Social Networks, and Culture

Illness and treatment representations are con-

structed within the perceived selfand may lead

to revised perceptions of the durability and

competence of the physical self and its abil-

ity to function in a variety of cognitive tasks

and social roles (Epstein 1973). Investigators

have focused on two aspects of the self con-

cept that are directly related to the problem-

solving process described in the prior section:

self-efﬁcacy and beliefs respecting control—

both oriented toward the behavioral compo-

nent of the regulatory system, and optimism

and disengagement—two factors affecting the

appraisal of movement toward goals. To this

point, however, relatively few studies have

explicitly examined how feedback from the

problem-solving level, that is, feedback from

illness management, affects these factors or

other aspects of the self system. There also

is little empirical data showing how aspects

of the self, e.g., self-assessments of health and

feelings of vulnerability to speciﬁc diseases,af-

fect the construction and content of illnesses

and treatment representations.

Self as context. Self-efﬁcacy, or the per-

ception that one is able to perform a speciﬁc

action in an efﬁcacious manner (Bandura

1989, 2004), and internal control, or the

perception of personal control over and

responsibility for daily events (Rodin &

Langer 1996), are two self system concepts

commonly used in health behavior research.

Although some studies have treated these

variables as traits, they are basically dynamic

concepts—beliefs that are shaped by behavior

and that in turn affect behavior. It is easier,

however, to identify studies that demonstrate

how efﬁcacy affects behavior than to identify

studies that examine how behavior affects ef-

ﬁcacy; for example, studies have looked at the

effect of level of self-efﬁcacy on taking med-

ication (e.g., Barclay et al. 2007), for healthy

eating (e.g., Shields & Brawley 2006), and for

exercising (e.g., Renner & Schwarzer 2005).

To be complete, studies of efﬁcacy should also

include how and the conditions under which

the behavior affects or mediates changes

in self-efﬁcacy (Maibach & Murphy 1995).

For example, exercise builds self-efﬁcacy for

exercise behaviors if the exerciser experiences

positive affect and social support during the

activity (e.g., Dechamps et al. 2007). Experi-

encing positive affect and engaging in social

comparison as a result of the behavior elab-

orates the meaning of the action in cognitive

and experiential memory; experience-based

positive feedback conveys the value of the

behavior to the cognitive system.

Treating self-efﬁcacy as a static trait in

research ignores two additional ﬁndings in

health research in addition to the data show-

ing how efﬁcacy is modiﬁed by action. First,

self-efﬁcacy may be more important for the

initiation than the maintenance of a be-

havioral change. For example, self-efﬁcacy

was important for initiating smoking cessa-

tion, but satisfaction with cessation, not ef-

ﬁcacy, was related to maintaining cessation

(Rothman 2000) (see Coherence Between Ill-

ness and Treatment Representation, above),

and neither self-efﬁcacy nor satisfaction was

related to long-term maintenance once non-

smoking became habitual (Baldwin et al.

2006). Second, efﬁcacy is domain speciﬁc;

thus, an individual’s self-efﬁcacy for regulat-

ing diet is ineffective for regulating exercise

(Baldwin et al. 2006). Domain-speciﬁc differ-

entiations of self-efﬁcacy have also proven es-

sential to understand the ﬁndings and pro-

cesses involved in rehabilitation following

myocardial infarction (Schwarzer & Fuchs

1995), initiation and maintenance of exer-

cise (Sallis et al. 1992), and in regulation

of healthy diets (Schwarzer & Fuchs 1995).

The differentiation of efﬁcacy across do-

mains and its change over time is consistent

with its conceptualization as a dynamic fac-

tor rather than as a trait, and it is consistent

with the importance of speciﬁcity respect-

ing the assessment of affective and cognitive

traits.

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Investigators have questioned whether ef-

ﬁcacy is merely a correlate or is an ac-

tual causal mediator of performance—i.e.,

whether efﬁcacy has a functional relation-

ship to subsequent performance. Heggestad

& Kanfer’s (2005) studies show that prior be-

haviors can build efﬁcacy but that the indi-

vidual’s prior behavior and not efﬁcacy has a

causal relationship to subsequent behavior. It

has yet to be determined whether their ﬁnd-

ings will hold for maintenance of a health be-

havior versus only initiation of the health be-

havior and whether efﬁcacy can affect success

for some health behavior changes and not oth-

ers (Vancouver & Kendall 2006). When ef-

ﬁcacy is assessed as an ability to achieve an

outcome rather than an ability to perform a

speciﬁc act or sequence of actions, it might be

an indicator of coherence; i.e., as mentioned

in the prior section, it might be an indicator

that control has been scripted and is on the

way to becoming automatic.

In addition to factors such as efﬁcacy that

are related to performance skills, other aspects

of the self affect motivation for the initiation,

cessation, and/or maintenance of healthy and

risky behaviors. Three self-appraisals that af-

fect motivation for health behaviors are op-

timism (Carver et al. 1989), a self-regulation

strategy to conserve resources (e.g., not exer-

cising in order to conserve physical energy)

(Leventhal & Crouch 1997), and a strategy

for goal disengagement (e.g., giving up on an

unattainable goal by focusing on a new goal)

(Wrosch et al. 2003). For example, Duke et al.

(2002) found that community-dwelling older

adults who appraised themselves as optimistic

were more likely to initiate less vigorous activ-

ities (walking) to replace more vigorous activ-

ities (jogging) they had given up due to illness

a year earlier. These elderly adults were less

likely to make replacements, however, if they

believed it important to conserve resources.

In their examination of strategies for disen-

gagement, Wrosch and colleagues (2003) ar-

gue that failing to give up unattainable goals

can be a source of emotional distress that will

reduce quality of life and have adverse ef-

fects on health. Wrosch et al. theorize that el-

derly people high on internal control are more

likely to experience this syndrome of distress,

as well as reduced quality of life and negative

effects on their health, because they are more

likely to be motivated to reach for goals that

are unattainable within their limited remain-

ing life spans. In contrast, elderly people low

on control will more readily yield and identify

more attainable goals. Interestingly, Wrosch

and colleagues (2003) propose that internal

control beliefs will be beneﬁcial for giving up

and replacing goals among younger persons.

Finally, rather than focusing on speciﬁc strate-

gies, Heidrich and colleagues (1994) showed

that the discrepancy between ideal and per-

ceived self accounted for the effects of can-

cer and social adjustment; the discrepancy be-

tween how the individuals wanted to be and

how they saw themselves accounted for, i.e.,

mediated, their social adjustment and most of

the effects of their illness on depression. Al-

though these studies have clear implications

for behaviors to prevent and control chronic

illness, such as medication adherence, dietary

control, and exercise, few provide evidence di-

rectly related to these behaviors.

Comment on self studies. It is clear that

the perceived and conceptual self (Kihlstrom

1993) and its overall and speciﬁc properties

(Swann et al. 2007) are intimately related to

risk perception and behaviors for the pre-

vention and control of chronic illness. Few

studies, however, examine direct connections

between factors of the self and the problem-

solving processes involved in chronic illness

management. For example, heuristics such as

novelty (e.g., if a symptom is novel it is more

likely to be perceived as serious; Leventhal

& Scherer 1987), location (e.g., chest pain

is often assumed to indicate heart problems

rather than a lung problem, since the chest

is most salient as the location of the heart),

severity, and timeline are rules for apprais-

ing deviation from an underlying, stable im-

age of the bodily self, but little attention has

been given to this aspect of self by health

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ANRV331-PS59-18 ARI 5 November 2007 10:57

investigators (see Petrie & Weinman 1997

for examples). Self-appraisals such as opti-

mism, conservation of resources, and willing-

ness to yield life goals are coping strategies

that lead to the formation of coherent cog-

nitive, emotional, and expressive behavioral

scripts by encouraging similar and repeated

approaches to life and health problems. The

behavioral scripts and expressive behaviors as-

sociated with these self-ascribed orientations

could affect physical health outcomes through

the chronic activation of central autonomic

pathways. These issues need to be explored in

longitudinal studies that examine behavioral

processes at both psychological and physio-

logical levels. A possible approach to concep-

tualizing one aspect of the process involved

in communication between the self and ongo-

ing problem-solving processes would be to set

the social comparison process, i.e., whether

patients select upward or downward compar-

isons (Taylor & Lobel 1989), within the con-

text of patient models of disease and treat-

ment: upward when the representations and

current evidence suggest the need for acquir-

ing skills and hopeful outcomes, downward

when they point to a need to bolster self-

esteem. Finally, it is unclear whether person

factors, such as optimism or disengagement,

are traits and are less usable for predicting in-

traindividual outcomes or if they are prod-

ucts of domain-speciﬁc behavioral episodes

that capture both inter- and intraperson ef-

fects (Cervone 2004). Person factors gener-

ated within speciﬁc domains, such as conser-

vation of resources for physical survival, may

generalize to other areas at a conceptual level,

although instruments for assessment would

need to be worded to reﬂect the content of

each domain.

Cultural and social inﬂuences on health

outcomes. Historians and social scientists

alike have been quick to recognize the ef-

fects of environmental, cultural, and societal

resources on disease and longevity. Braudel’s

(1979, p. 39) sobering review of the expansion

and contraction in European and world popu-

lations illustrates how cycles of expansion and

contraction are related to changes in climate,

agricultural practices, and expanding trade.

Recent data show substantial associations be-

tween mortality, aging, and disease and risk in-

dicators with measures of social stratiﬁcation,

e.g., county of residence, income, education,

religious involvement, etc. (House et al. 1992,

Kaplan 1992). The data highlight the need for

further investigation in three areas. First, in-

formation is needed as to how speciﬁc cultural

and socioeconomic factors affect factors at the

individual/psychological level. Studies of reli-

gion and health provide a more detailed view

about how religious participation, spiritual-

ity, and a sense of self reduce risky behaviors

and encourage healthy behaviors that affect

health outcomes (See Schaie et al. 2004). It

is not always clear, however, whether or how

a particular feature of the ecological context

and/or culture, e.g., religious attendance, so-

cial engagement, prayer, spirituality, or the

body as a temple of God (Hill et al. 2006),

affect the speciﬁc beliefs and behaviors that

affect health outcomes. The association of

cultural factors with healthy and risky behav-

iors could be mediated by common, cultur-

ally generated personal traits, social relation-

ships, lifestyles, representations of illness and

treatments, and/or approaches to planning for

prevention and management of illness and ill-

ness risks. Second, when social and cultural

analyses identify the speciﬁc behavioral fac-

tors correlated with disease, there are often

ambiguities as to how these behaviors “get

under the skin,” that is, how they inﬂuence

the physiological pathways leading to disease

and mortality (Taylor et al. 1997). Thus, al-

though associations between disease risk and

factors such as ecology, socioeconomic sta-

tus, and religious involvement identify impor-

tant areas for research, the data often fail to

indicate whether one or some combination

of environmental or social factors might be

responsible for the increase in disease. The

importance of identifying mediators between

superordinate factors such as socioeconomic

status and disease indicators can be seen by

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ANRV331-PS59-18 ARI 5 November 2007 10:57

the changing relationship between a superor-

dinate factor, in this case gender, and lung can-

cer. Lung cancer rates declined among physi-

cian cigarette smokers approximately 20 years

after Doll & Hill’s (1950) report relating lung

cancer to smoking. A similar decline occurred

for men in the United States after the 1964

Surgeon General’s report (U.S. Dept. Health

Human Serv. 1964). Lung cancer rates and

prevalence of smoking gradually increased,

however, among women during this same pe-

riod, when marketing campaigns focused on

women and the “light cigarette” (Kozlowski

et al. 1998). Identifying mediators for these

changes, particularly for the failure to observe

a decline in smoking among women, is not a

simple issue. Depression was thought to be

responsible for greater difﬁculties in smok-

ing cessation among women than among men,

but meta-analyses cast doubt on this hypoth-

esis as at least one type of depression, major

depressive disorder, neither moderates short-

or long-term cessation nor affects gender dif-

ferences in ease of quitting (Hitsman et al.

2003). Variation across studies in identifying

mediators may reﬂect inadequacies in sam-

ple size and the conceptualization and time

of assessment of mediating variables. Diary

data are beginning to describe the details of

social interactions responsible for behavioral

and affective factors that may lead to adverse

health outcomes (Rook 2003). The task re-

mains, however, to identify the factors that

mediated the relationship of social marketing

to the social context and role deﬁnitions that

are involved in the gender differences in ini-

tiation and cessation of smoking. As many of

the physiological pathways relating smoking

to lung cancer have been described, the data

succeed in identifying speciﬁc factors bridging

the social environment and individual behav-

ior to “get under the skin.”

Cognitive-behavioral anthropologists

(see, e.g., Garro 2000) have described some

of the processes involved in the link of culture

to health behaviors by assessing whether

beliefs about speciﬁc illnesses are shared

by multiple individuals within a speciﬁc

ethnic community. Garro (2000) identiﬁed

a culturally shared schema or prototype

for hypertension and two prototypes for

diabetes—one Western in nature, the other

speciﬁc to ethnic beliefs and practices. Each

of the diabetes prototypes identiﬁed speciﬁc

causes and routes for treatment that made

sense to individuals and guided their man-

agement of diabetes. Narratives of personal

history with diabetes meld personal experi-

ence with cultural prototypes and reﬂect the

storyteller’s degree of belonging to ethnic or

Western cultures. Cultural beliefs and their

associated use of Western, traditional, and

alternative care have been examined in men-

tal health (Cabassa et al. 2007, Karasz et al.

2003), cancer genetic counseling (Eichmeyer

et al. 2005), and other conditions (Buchwald

et al. 2000). This research was stimulated in

part by Pachter’s (1994) paper, which alerted

medical practitioners to the effects of ethnic

disparities in representations of diseases

among patients and practitioners that lead

to conﬂict between doctors and patients

and ineffective use of medical treatments by

patients.

Comments on social factors. The empha-

sis on the cognitive and affective components

of beliefs and the individual acculturation to

Western practices is directly relevant to the

cognitive processes examined in the construc-

tion of illness and treatment representations

discussed in the section above on problem

solving processes in health and illness, The

Process of Self-Management of Chronic Ill-

ness. It is important, however, not to over-

look the role played by institutions in the for-

mation of patient representations of illness

and treatment: Culturally established institu-

tions train practitioners in the management

of illness, determine the mixture of folk and

Western biomedical models involved in the

training of practitioners, establish the appear-

ance of the health care system, and establish

how care is delivered (Chrisman & Kleinman

1983). Three points related to social factors

are worthy of mention for the present review.

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First, practitioners have been sensitized to the

role of acculturation as a factor in rates of life-

threatening chronic illnesses—the causal fac-

tors of illnesses such as prostate cancer and

obesity ranging from diet and stress in new

environments to issues in migration ( Jasso

et al. 2004). Second, an extensive literature

has emerged on the role of linguistic com-

petency (e.g., Ngo-Metzger et al. 2003) and

ethnic match of patient and practitioner (e.g.,

Tarn et al. 2005) in communication and trust

in primary care settings. Third, practition-

ers’ questions and procedures in the medical

examination reinforce the heuristics patients

use in self-appraisal. Asking, “Where does it

hurt,” “How long has it been going on,” and

“How does it feel” reinforces heuristics of lo-

cation, duration, and patternfor self-diagnosis

and management. For example, by examining

the lungs, legs, and feet (location heuristic) of

patients with congestive heart failure, doctors

reinforce to the patients that their illness is not

related to the heart but instead to respiratory

function and circulation in the legs and feet.

The detailed analysis of the processes involved

in the contacts between patients and practi-

tioners should be helpful for the development

of interventions that are both effective and ef-

ﬁcient for enhancing patients’ understanding

and management of chronic conditions.

COGNITIVE-BEHAVIORAL

INTERVENTIONS TO IMPROVE

SELF-MANAGEMENT

Our review of processes from problem solv-

ing through self and social contexts was

designed to raise questions and suggest direc-

tions for innovative approaches for interven-

tions that will meet criteria for effectiveness

and efﬁciency—i.e., for the development of

interventions that are as effective as those in

the diabetes prevention trials reviewed above

but simpler and less demanding of time and

skill by practitioners and patients. Current

ﬁndings provide both support and doubt as to

the feasibility of reaching this dual goal of ef-

ﬁciency and effectiveness. For example, meta-

analyses show that forming intentions and/or

plans for action (Leventhal 1970) are effective

for crossing the gap between intention to ac-

tion for simple, one-time behaviors, though

generally are ineffective for complex, time-

demanding behaviors that prevent and con-

trol chronic illnesses (exercise, dietary change;

Webb & Sheeran 2006). Moderate levels of

success have also been reported for behavioral

interventions for the control of chronic illness

that are implemented from a social-learning

framework (a process approach that is iden-

tical in many respects to the problem-solving

approach described in the present review) for

the control of some chronic conditions. For

example, hemoglobin A1c and blood sugar

levels for diabetes and blood pressure for hy-

pertension have been successfully controlled

through such interventions but symptoms of

osteoarthritis or rheumatoid arthritis have not

(Chodosh et al. 2005, Lorig et al. 2005). The

success of diabetes and hypertension interven-

tions is also balanced by mixed outcomes for

congestive heart failure—negative outcomes

have been obtained, including failure to pre-

vent recurrent episodes and hospitalization in

some sites (DeBusk et al. 2004), but positive

outcomes have been obtained in other sites

(Sisk et al. 2006).

The successes of social learning interven-

tions indicate that they have captured essen-

tial elements needed for improvement of hard

outcomes of chronic illnesses (Lorig et al.

1999). Although the interventions are less

complex and time demanding than the dia-

betes trials, their success rates are also less

impressive, due perhaps to the generality of

the interventions; they are not focused on

speciﬁc aspects of particular chronic condi-

tions (Wagner 2004). A central theme un-

derlying our review is that increasing the

speciﬁcity of behavioral management for par-

ticular diseases requires the addition of con-

cepts to self-regulation theory generated from

observations in the clinic and community,

i.e., bidirectional translation. This may en-

tail changes as simple as identifying the in-

valid subjective cues that patients use to guide

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ANRV331-PS59-18 ARI 5 November 2007 10:57

self-management (medication use) and devel-

oping behavioral procedures that teach them

to ignore subjective targets and use objective

indicators (blood pressure and/or blood sugar

readings) to guide self-management (Dunbar

2007). Other simple procedures may involve

reframing how a behavioral intervention is

implemented to insure, for example, that pa-

tients see their depressive symptoms as part

of their chronic physical illness and not as

a separate and unmanageable mental illness.

In short, current social learning interventions

may not have adequately considered how pa-

tients and their medical practitioners repre-

sent illnesses and how the treatment experi-

ence ﬁts with the patients’ representations of

their chronic conditions. Once such issues are

considered, the effectiveness of the interven-

tions may improve substantially.

Process Theories and Design

of Clinical Trials

Investigators have recognized the need to in-

crease the effectiveness and efﬁciency of be-

havioral interventions and are proposing new

approaches to the analysis and design of clin-

ical trials. For example, Kraemer et al. (2002)

have discussed the need for assessments to de-

ﬁne subgroups of participants (moderators)

prior to the implementation of behavioral in-

terventions and to identify and measure medi-

ators, i.e., factors recorded post intervention

that affect treatment adherence. They indi-

cate the need for such analyses in completed

multicenter trials and the need for a theo-

retically based approach to implementation

of such measures in ongoing and proposed

large-scale trials (Kraemer et al. 2002). These

recommendations assume that interventions

targeting speciﬁc subgroups are potentially

more effective and more efﬁcient than inter-

ventions using common methods for all par-

ticipants. Cervone’s (2004) analysis suggests

the need for extreme caution, however, in ex-

pecting measures of traits or Diagnostic and

Statistical Manual of Mental Disorders (DSM)

categories to isolate the within-person fac-

tors that are responsible for the initiation and

maintenance of healthy and risky behaviors

in speciﬁc domains. Assessing factors such as

health worry that interact with speciﬁc situ-

ational triggers (Bem & Funder 1978) would

move individual-difference assessment closer

to the intraperson or process level by cap-

turing how participants experience and un-

derstand health threats and preventive and

treatment behaviors. Most clinical trials, how-

ever, have selected traits and/or DSM cate-

gories as moderators and therefore have not

assessed patients’ perceptions of their chronic

health problems, the psychological accom-

paniments of these problems, or the proce-

dures they have used or prefer to use for their

management. The deﬁcits associated with us-

ing interindividual differences as moderators

are seen in clinical trials testing whether re-

ducing depressive symptoms would increase

treatment adherence in comorbid conditions.

The expectation that addressing depression

would improve patient care of comorbid con-

ditions seems reasonable because medication

adherence has been observed to be poorer in

those who are depressed [e.g., aspirin was not

taken daily, as prescribed, by patients hospi-

talized with acute coronary syndrome who

scored higher on the Beck Depression In-

ventory (Gehi et al. 2005)]. The expectation

is also reasonable given that decline in de-

pression was associated prospectively with in-

creased adherence (Rieckmann et al. 2006).

Interventions to reduce depression have been

unsuccessful, however, in improving adher-

ence (Haynes et al. 2005). It is unclear pre-

cisely which aspects of patients’ physical ill-

ness or social and personal contexts elicit and

sustain these depressive states or which as-

pects of patients’ affective reactions are re-

sponsible for nonadherence. Inconsistent and

negative ﬁndings of depression interventions

may be the result of using measures of in-

terindividual difference rather than intraindi-

vidual, self-management processes for match-

ing patients to treatments (Sobell & Sobell

2000). Identiﬁcation of intraindividual mod-

erators at the level of process rather than trait

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calls for sophisticated, content-speciﬁc theory

and instruments (Cervone et al. 2006, Evans

2006) with sufﬁcient validity to identify and

assess these factors at the outset of a clinical

trial.

Two alternatives for the development of ef-

fective and efﬁcient behavioral interventions

that are now being tested are stepwise treat-

ment and self-assignment to treatment. In

stepwise treatments, all patients are assigned

to the least costly (with regard to time, ef-

fort, and negative side effects), highly effective

ﬁrst-step treatment; the second-step treat-

ment is reserved for patients for whom the

ﬁrst step of treatment fails. Second-step treat-

ments are often more tailored to the individ-

ual’s behavioral or biological system and are

often more intensive in terms of time and ef-

fort than are ﬁrst-step treatments. Stepwise

approaches to behavioral interventions may

have problems less frequently encountered in

medication trials. For example, patients in a

medical trial may be more likely to attribute

failure of a ﬁrst-step treatment to deﬁciencies

in the medication, whereas patients in behav-

ioral interventions may be likely to attribute

failure of a ﬁrst-step treatment to deﬁcien-

cies in themselves, a self-attribution that can

increase feelings of hopelessness and reduce

self-efﬁcacy and motivation for the second-

step treatment (Wilson et al. 2000). Improve-

ments in stepwise behavioral treatments will

require conditions that prime patients to at-

tribute initial failure to treatment rather than

to themselves; this is similar to the goals of

treatments for addictions, in which patients

demonstrate the “abstinence violation effect”

by blaming themselves for losing control over

the negative, addictive behavior (Curry et al.

1987).

A direct approach to patient perceptions

of illness and treatment is involved in clin-

ical trials in which patients select their pre-

ferred treatments; discussion of the conduct

and analysis of these trials is under way (see

TenHave et al. 2003, Thornett 2001). Assign-

ment to pharmacological- or psychological-

behavioral treatments that is inconsistent with

patients’ preferences has been shown to have

negative effects on the treatment alliance.

For example, the perceived treatment al-

liance improves over time for patients as-

signed to their preferred psychological treat-

ment but declines if these patients are assigned

to a nonpreferred pharmacological treatment

(Iacoviello et al. 2007). Consistency with pref-

erences does not seem to affect the alliance for

patients who prefer a pharmacological treat-

ment. Because positive alliances are associ-

ated with treatment beneﬁts (Martin et al.

2000), treating patients based on their pref-

erences may prove to be important for behav-

ioral interventions for chronic illnesses. It is

unknown whether the beneﬁts of consistency

in assignment are mediated by the patient’s

perception of congruity between the repre-

sentations of the illness and the treatment

or from improved communication allowing

practitioners and patients to develop shared

goals respecting beneﬁts in both subjective ex-

perience and objective function. In addition

to the above approaches to clinical trial de-

sign, Dunn & Bentall (2007) have proposed

the use of the instrumental variable method

to identify process variables in treatment in-

terventions. These methods are able to assess

not only whether an intervention is effective

but also are able to examine how it achieves

effectiveness. Thus, the method will allow

researchers to examine causal processes in-

volved in effective and efﬁcient interventions.

PAST, PRESENT, FUTURE:

CONCLUDING COMMENTS

Our view of the status of behavioral research

for chronic illness can be summarized as

follows. First, changes in behavior can im-

prove health outcomes. The reductions in

lung cancer (Ebbert et al. 2003) and breast

cancer and the intervention trials for individ-

uals at high risk for diabetes are examples of

the effectiveness of behavioral change. Sec-

ond, to this point in time, interventions fo-

cused on changing the behavior of individ-

ual patients that have proven effective for

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ANRV331-PS59-18 ARI 5 November 2007 10:57

long-term behavioral change are complex and

time consuming; they meet the effectiveness

criteria for evidence-based practice but are

not cost effective or usable in most practice

settings. Third, the development of theoret-

ical concepts supported by substantial data

show that patients represent speciﬁc chronic

illnesses and treatments based upon their ex-

perience and perception of somatic changes

in themselves and observations and expo-

sure to information about illness in others.

These exposures affect the behavioral strate-

gies they perceive to be effective and within

their competence to perform for the preven-

tion and control of chronic illness. Fourth,

the translation of what has been learned

about how patients self-regulate health into

effective and usable interventions is at be-

ginning stages; interventions work for some

diseases, though it is unclear which compo-

nents are necessary and/or sufﬁcient for suc-

cess. Finally, investigators are considering ap-

proaches to clinical trial design that may make

behavioral interventions more usable, i.e., ef-

ﬁcient and accessible to the clinical environ-

ment, and these innovative approaches ap-

pear to address models of the processes un-

derlying self-management. The integration of

self-regulatory models with new approaches

to clinical trials is, however, a nontrivial prob-

lem because the models suggest that interven-

tions must focus on practitioners and not just

on patients. How patients’ and practitioners’

models affect communication with one an-

other, with family members, and in response

to messages from the surrounding culture will

determine whether interventions for broad

lifestyle changes or for use of speciﬁc medi-

cations are successful in meeting expectations

for changes in objective as well as subjective

criteria of beneﬁt. Behavioral interventions of

the future may parallel the features of individ-

ualized medicine; the former involves treat-

ments matched to speciﬁc cognitive-affective

patterns of the individual patient, and the lat-

ter involves treatments matched to the spe-

ciﬁc expression of genes underlying the pa-

tient’s disease. Treatment effectiveness would

be evaluated by the accumulation of case-

by-case outcomes and, hopefully, the poste-

rior probabilities of success will exceed the

prior.

ACKNOWLEDGMENTS

This review was written with support from a National Institute of Aging grant, R24AG023958,

the Center for the Study of Health Beliefs and Behaviors. The authors thank Tamara Musumeci

for her help with the references.

LITERATURE CITED

Ader R, Cohen N. 1993. Psychoneuroimmunology: conditioning and stress. Annu. Rev. Psychol.

44:53–85

Ajzen I. 1991. The theory of planned behavior. Organ. Behav. Hum. Dec. Process. 50:179–211

Albarracin D, Johnson BT, Fishbein M, Muellerleile PA. 2001. Theories of reasoned action

and planned behavior as models of condom use: a meta-analysis. Psychol. Bull. 127:142–61

Am. Pyschol. Assoc. 2000. Diagnostic and Statistical Manual of Mental Disorders. Arlington, VA:

Am. Psychiatr. Publ. 4th ed., text rev.

Antonovsky A. 1993. The structure and properties of the Sense of Coherence Scale. Soc. Sci.

Med. 36:725–33

Baldwin AS, Rothman AJ, Hertel AW, Linde JA, Jeffery RW, et al. 2006. Specifying the

determinants of the initiation and maintenance of behavior change: an examination of

self-efﬁcacy, satisfaction, and smoking cessation. Health Psychol. 25(5):626–34

Bandura A. 1989. Self-regulation of motivation and action through internal standards and goal

systems. In Goal Concepts in Personality and Social Psychology, ed. LA Pervin, pp. 19–85.

Hillsdale, NJ: Erlbaum

www.annualreviews.org

•

Health Psychology 497

Annu. Rev. Psychol. 2008.59:477-505. Downloaded from arjournals.annualreviews.org

by Rutgers University Libraries on 08/04/09. For personal use only.

ANRV331-PS59-18 ARI 5 November 2007 10:57

Bandura A. 2004. Health promotion by social cognitive means. Health Educ. Behav. 31(2):143–

Barclay TR, Hinkin CH, Castellon SA, Mason KI, Reinhard MJ, et al. 2007. Age-associated

predictors of medication adherence in HIV-positive adults: health beliefs, self-efﬁcacy,

and neurocognitive status. Health Psychol. 26(1):40–49

Barefoot JC, Dahlstrom WG, Williams RB Jr. 1983. Hostility, CHD incidence, and total

mortality: a 25-year follow-up study of 255 physicians. Psychosom. Med. 45(1):59–63

Baum A, Posluszny DM. 1999. Health psychology: mapping biobehavioral contributions to

health and illness. Annu. Rev. Psychol. 50:137–63

Baumann L, Cameron LD, Zimmerman R, Leventhal H. 1989. Illness representations and

matching labels with symptoms. Health Psychol. 8:449–69

Bem DJ, Funder DC. 1978. Predicting more of the people more of the time: assessing the

personality of situations. Psychol. Rev. 85(6):485–500

Bickell BA, Federman AD, Aufses AH Jr. 2005. Inﬂuence of time on risk of bowel resection in

complete small bowel obstruction. J. Am. Coll. Surg. 201:847–54

Bishop GD. 1991. Understanding the understanding of illness: lay disease representations. In

Mental Representation in Health and Illness, ed. JA Skelton, RT Croyle, pp. 32–59. New

York: Springer-Verlag

Bogg T, Roberts BW. 2004. Conscientiousness and health-related behaviors: a meta-analysis

of the leading behavioral contributors to mortality. Psychol. Bull. 130(6):887–919

Braudel F. 1979. Civilization and Capitalism, 15th–18th Century, Vols. I, II, & III. New York:

Harper & Row

Broadbent E, Petrie KJ, Main J, Weinman J. 2006. The Brief Illness Perception Questionnaire.

J. Psychosom. Res. 60(6):631–37

Brody EM, Kleban MH. 1983. Day-to-day mental and physical health symptoms of older

people: a report on health logs. Gerontologist 23(1):75–85

Brownlee S, Leventhal EA, Leventhal H. 2000. Regulation, self-regulation and construction

of the self in maintaining physical health. In Handbook of Self-Regulation, ed. M Boekartz,

PR Pintrich, M Zeidner, pp. 369–416. San Diego, CA: Academic

Buchwald D, Beals J, Manson SM. 2000. Use of traditional health practices among native

Americans in a primary care setting. Med. Care 38(12):1191–99

Bunde J, Martin R. 2006. Depression and prehospital delay in the context of myocardial in-

farction. Psychosom. Med. 68:51–57

Burgess CC, Ramirez A, Richards M, Love S. 1998. Who and what inﬂuences delayed presen-

tation in breast cancer? Br. J. Cancer 77(8):1343–48

Cabassa LJ, Lester R, Zayas LH. 2007. “It’s like being in a labyrinth”: Hispanic immigrants’

perceptions of depression and attitudes toward treatments. J. Immigrant Health 9:1–16

Cameron L, Leventhal EA, Leventhal H. 1995. Seeking medical care in response to symptoms

and life stress. Psychosom. Med. 57(1):37–47

Carver CS, Scheier MF, Weintraub JK. 1989. Assessing coping strategies: a theoretically based

approach. J. Personal. Soc. Psychol. 56:267–83

Cervone D. 2004. Personality architecture: within-person structures and processes. Annu. Rev.

Psychol. 56:423–52

Cervone D, Shadel WG, Smith RE, Fiori M. 2006. Self-regulation: reminders and suggestions

from personality science. Appl. Psychol. Int. Rev. 55(3):333–85

Chodosh J, Morton SC, Mojica W, Maglione M, Suttorp MJ, et al. 2005. Meta-analysis: chronic

disease self-management programs for older adults. Ann. Intern. Med. 143:427–38

498 Leventhal et al.

Annu. Rev. Psychol. 2008.59:477-505. Downloaded from arjournals.annualreviews.org

by Rutgers University Libraries on 08/04/09. For personal use only.

ANRV331-PS59-18 ARI 5 November 2007 10:57

Chrisman NJ, Kleinman A. 1983. Popular health care, social networks, and cultural meanings:

the orientation of medical anthropology. In Handbook of Health, Healthcare, and the Health

Professions, ed. D Mechanic, pp. 569–90. New York: Free Press

Cohen S. 2004. Social relationships and health. Am. Psychol. 59(8):676–84

Cohen S, Frank E, Doyle WJ, Skoner DP, Rabin BS, Gwaltney JM Jr. 1998. Types of stressors

that increase susceptibility to the common cold in healthy adults. Health Psychol. 17(3):211–

Cohen S, Williamson GM. 1991. Stress and infectious disease in humans. Psychol. Bull.109(1):5–

Cooper RP, Shallice T. 2006. Hierarchical schemas and goals in the control of sequential

behavior. Psychol. Rev. 113(4):887–916

Costa PT Jr, McCrae RR. 1992. Normal personality assessment in clinical practice: the NEO

Personality Inventory. Psychol. Assess. 4:5–13

Critchley HD. 2005. Neural mechanisms of autonomic, affective, and cognitive integration.

J. Comp. Neurol. 493:154–66

Curry S, Marlatt GA, Gordon JR. 1987. Abstinence violation effect: validation of an attribu-

tional construct with smoking cessation. J. Consult. Clin. Psychol. 55(2):145–49

De Bourdeaudhuij I, Brug J. 2000. Tailoring dietary feedback to reduce fat intake: an interven-

tion at the family level. Health Educ. Res. 15(4):449–62

DeBusk RF, Miller NH, Parker KM, Bandura A, Kraemer HC, et al. 2004. Care management

for low-risk patients with heart failure. Ann. Intern. Med. 141:606–13

Dechamps A, Lafont L, Bourdel-Marchasson I. 2007. Effects of Tai Chi exercises on self-

efﬁcacy and psychological health. Eur. Rev. Aging Physical Activity 4(1):25–32

Diabetes Prev. Prog. Res. Group. 2002. Reduction in the incidence of type 2 diabetes with

lifestyle intervention or metformin. New Engl. J. Med. 346(6):393–403

Diabetes Prev. Prog. Res. Group. 2003. Within-trial cost-effectiveness of lifestyle intervention

or metformin for the primary prevention of type 2 diabetes. Diabetes Care 26:2518–23

Diefenbach MA, Leventhal H. 1996. The common-sense model of illness representation:

theoretical and practical considerations. J. Soc. Distress Homeless. 5(1):11–38

Diefenbach MA, Miller SM, Daly MB. 1999. Speciﬁc worry about breast cancer predicts mam-

mography use in women at risk for breast and ovarian cancer. Health Psychol. 18(5):532–36

Doll R, Hill AB. 1950. Smoking and carcinoma of the lung; preliminary report. Br. Med. J.

2(4682):739–48

Dracup K, Moser DK, Eisenberg M, Meischke H, Alonzo AA, Braslow A. 1995. Causes of

delay in seeking treatment for heart attack symptoms. Soc. Sci. Med. 40(3):379–92

Duke J, Brownlee S, Leventhal EA, Leventhal H. 2002. Giving up and replacing activities in

response to illness. J. Gerontol. Psychol. Sci. 57B(4):367–76

Dunbar L, Schneider SH, Burns E, Leventhal H. 2007. Does patient blood glucose monitor-

ing improve diabetes control: Always, sometimes, never? A systematic review from the

framework of the common-sense model. Diabetes Educ. In press

Dunn G, Bentall R. 2007. Modelling treatment effect heterogeneity in randomized con-

trolled trials of complex interventions (psychological treatments). Stat. Med. DOI:

10.1002/sim.2891

Ebbert JO, Yang P, Vachon CM, Vierkant RA, Cerhan JR, et al. 2003. Lung cancer risk

reduction after smoking cessation: observations from a prospective cohort of women.

J. Clin. Oncol. 21(5):921–26

Eichmeyer JN, Northrup H, Assel MA, Goka TJ, Johnston DA, Williams AT. 2005. An as-

sessment of risk understanding in Hispanic genetic counseling patients. J. Genet. Couns.

14(4):319–28

www.annualreviews.org

•

Health Psychology 499

Annu. Rev. Psychol. 2008.59:477-505. Downloaded from arjournals.annualreviews.org

by Rutgers University Libraries on 08/04/09. For personal use only.

ANRV331-PS59-18 ARI 5 November 2007 10:57

Epstein S. 1973. The self-concept revisited: or a theory of a theory. Am. Psychol. 28(5):404–16

Evans J St BT. 2006. The heuristic-analytic theory of reasoning: extension and evaluation.

Psychon. Bull. Rev. 13(3):378–95

Finch EA, Linde JA, Jeffery RW, Rothman AJ, King CM, Levy RL. 2005. The effects of

outcome expectations and satisfaction on weight loss and maintenance: correlational and

experimental analyses—a randomized trial. Health Psychol. 24(6):608–16

Friedman HS, Booth-Kewley S. 1987. The “disease-prone personality”: a meta-analytic view

of the construct. Am. Psychol. 42:539–55

Fries JF. 2005. The compression of morbidity. Milbank Q. 83(4):897–907

Galea S, Nandi A, Vlahov D. 2004. The social epidemiology of substance use. Epidemiol. Rev.

26(1):36–52

Garro LC. 2000. Remembering what one knows and the construction of the past: a comparison

of cultural consensus theory and cultural schema theory. Ethos 28(3):275–319

Gehi A, Haas D, Pipkin S, Whooley MA. 2005. Depression and medication adherence in

outpatients with coronary heart disease. Arch. Intern. Med. 165:2508–13

Gillies CL, Abrams KR, Lambert PC, Cooper NJ, Sutton AJ, et al. 2007. Pharmacological and

lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glucose

tolerance: systematic review and meta-analysis. Br. Med. J. 334:299

Hagger MS, Chatzisarantis NLD, Biddle SJH. 2002. A meta-analytic review of the theories

of reasoned action and planned behavior in physical activity: predictive validity and the

contribution of additional variables. J. Sport Exerc. Psychol. 24:3–32

Hall S, Weinman J, Marteau TM. 2004. The motivating impact of informing women smokers

of a link between smoking and cervical cancer: the role of coherence. Health Psychol.

23(4):419–24

Halm EA, Mora P, Leventhal H. 2006. No symptoms, no asthma: the acute episodic disease

belief is associated with poor self-management among inner city adults with persistent

asthma. Chest 129:573–80

Hampson SE, Goldberg LR, Vogt TM, Dubanoski JP. 2007. Mechanisms by which child-

hood personality traits inﬂuence adult health status: educational attainment and health

behaviors. Health Psychol. 26(1):121–25

Hay JL, McCaul KD, Magnan RE. 2006. Does worry about breast cancer predict screening

behaviors? A meta-analysis of the prospective evidence. Prev. Med. 42(6):401–8

Haynes RB, Yao X, Degani A, Kripalani S, Garg A, McDonald HP. 2005. In-

terventions to enhance medication adherence. Cochrane Database Syst. Rev. DOI:

10.1002/14651858.CD000011.pub2

Heggestad ED, Kanfer R. 2005. The predictive validity of self-efﬁcacy in training performance:

little more than past performance. J. Exp. Psychol. Appl. 11:84–97

Heidrich SM, Forsthoff CA, Ward SE. 1994. Psychological adjustment in adults with cancer:

the self as mediator. Health Psychol. 13:346–53

Henderson C, Hagger M, Orbell S. 2007. Does priming a speciﬁc illness schema result in an

attentional information-processing bias for speciﬁc illnesses? Health Psychol. 26:165–73

Heneghan C, Thompson M, Perera R. 2006. Prevention of diabetes: drug trials show promising

results, but have limitations. Br. Med. J. 333:764–65

Hill TD, Burdette AM, Ellison CG, Musick MA. 2006. Religious attendance and health be-

haviors of Texas adults. Prev. Med. 42:309–12

Hitsman B, Borrelli B, McChargue DE, Spring B, Niaura R. 2003. History of depression and

smoking cessation outcome: a meta-analysis. J. Consult. Clin. Psychol. 71(4):657–63

Horne R. 2003. Treatment perceptions and self-regulation. In The Self-Regulation of Health and

Illness Behavior, ed. LD Cameron, H Leventhal, pp. 138–53. London: Routledge

500 Leventhal et al.

Annu. Rev. Psychol. 2008.59:477-505. Downloaded from arjournals.annualreviews.org

by Rutgers University Libraries on 08/04/09. For personal use only.

ANRV331-PS59-18 ARI 5 November 2007 10:57

Horne R, Buick D, Fisher M, Leake H, Cooper V, Weinman J. 2004. Doubts about necessity

and concerns about adverse effects: identifying the types of beliefs that are associated with

nonadherence to HAART. Int. J. STD AIDS 15(1):38–44

Horne R, Weinman J. 1999. Patients’ beliefs about prescribed medicines and their role in

adherence to treatment in chronic physical illness. J. Psychosom. Res. 47(6):555–67

Horne R, Weinman J. 2002. Self-regulation and self-management in asthma: exploring the

role of illness perceptions and treatment beliefs in explaining nonadherence to preventer

medication. Psychol. Health 17(1):17–33

Horowitz CR, Rein SB, Leventhal H. 2004. A story of maladies, misconceptions and mishaps:

effective management of heart failure. Soc. Sci. Med. 58:631–43

House JS, Kessler RC, Herzog AR, Mero RP, Kinney AM, Breslow MJ. 1992. Social stratiﬁ-

cation, age, and health. In Aging, Health Behaviors, and Health Outcomes, ed. KW Schaie,

D Blazer, JS House, pp. 1–32. Hillsdale, NJ: Erlbaum

Iacoviello BM, McCarthy KS, Barrett MS, Rynn M, Gallop R, Barber JP. 2007. Treatment

preferences affect the therapeutic alliance: implications for randomized controlled trials.

J. Consult. Clin. Psychol. 75(1):194–98

Ioannidis J. 2004. Materializing research promises: opportunities, priorities and conﬂicts in

translational medicine. J. Transl. Med. 2:5–10

Jamison KR. 1995. An Unquiet Mind. New York: Knopf

Jasso G, Massey DS, Rosenzweig MR, Smith JP. 2004. Immigrant health: selectivity and accul-

turation. Work. Pap. 04/23, Inst. Fiscal Stud., London

Kaplan GA. 1992. Health and aging in the Alameda county study. In Aging, Health Behaviors, and

Health Outcomes, ed. KW Schaie, D Blazer, JS House, pp. 69–88. Hillsdale, NJ: Erlbaum

Karasz A, Sacajiu G, Garcia N. 2003. Conceptual models of psychological distress among

low-income patients in an inner-city primary care clinic. J. Gen. Intern. Med. 18:475–77

Kemeny MA. 2003. The psychobiology of stress. Curr. Direct. Psychol. Sci. 12:124–29

Kiecolt-Glaser JK, McGuire L, Robles TF, Glaser R. 2002. Emotions, morbidity, and mortal-

ity: new perspectives from psychoneuroimmunology. Annu. Rev. Psychol. 53(1):83–107

Kihlstrom JF. 1993. What does the self look like? In The Mental Representation of Trait and

Autobiographical Knowledge About the Self, ed. TK Srull, pp. 79–90. Hillsdale, NJ: Erlbaum

Kozlowski LT, Goldberg ME, Yost BA, White EL, Sweeney CT, Pillitteri JL. 1998. Smokers’

misperceptions of light and ultralight cigarettes may keep them smoking. Am. J. Prev.

Med. 15(1):78–79

Kraemer HC, Wilson T, Fairburn CG, Agras S. 2002. Mediators and moderators of treatment

effects in randomized clinical trials. Arch. Gen. Psychiatry 59(10):877–83

Lerman DC. 2003. From the laboratory to community application: translational research in

behavior analysis. J. Appl. Behav. Anal. 36:415–19

Leventhal EA, Crouch M. 1997. Are there differences in perceptions of illness across the

lifespan? In Perceptions of Health and Illness: Current Research and Applications, ed. KJ Petrie,

JA Weinman, pp. 77–102. Amsterdam, Netherlands: Harwood Acad.

Leventhal H. 1970. Findings and theory in the study of fear communication. Adv. Exp. Soc.

Psychol. 5:119–86

Leventhal H, Contrada R, Leventhal EA. 2007a. Lessons from white coat hypertension: Com-

ment on Spruill et al., “The Impact of Perceived Hypertension Status on Anxiety and the

White Coat Hypertension Effect.” Ann. Behav. Med. In press

Leventhal H, Forster R, Leventhal EA. 2007b. Self-regulation of health threats, affect, and the

self: lessons from older adults. In Handbook of Health Psychology and Aging, ed. CM Aldwin,

CL Park, A Spiro III, pp. 341–66. New York: Guilford

www.annualreviews.org

•

Health Psychology 501

Annu. Rev. Psychol. 2008.59:477-505. Downloaded from arjournals.annualreviews.org

by Rutgers University Libraries on 08/04/09. For personal use only.

ANRV331-PS59-18 ARI 5 November 2007 10:57

Leventhal H, Musumeci T,Contrada R. 2007c. Current issues andnew directions in psychology

and health: theory, translation, and evidence-based practice. Psychol. Health 22(4):381–86

Leventhal H, Scherer K. 1987. The relationship of emotion to cognition: a functional approach

to a semantic controversy. Cogn. Emot. 1(1):3–28

Leventhal H, Singer R, Jones S. 1965. Effects of fear and speciﬁcity of recommendation upon

attitudes and behavior. J. Personal. Soc. Psychol. 2(1):20–29

Lindstrom J, Louheranta A, Mannelin M. 2003. The Finnish Diabetes Prevention Study (DPS):

lifestyle intervention and 3-year results on diet and physical activity. Diabetes Care 26:3230–

Lorig KR, Hurwicz ML, Sobel D, Hobbs M, Ritter PL. 2005. A national dissemination of an

evidence-based self-management program: a process evaluation study. Patient Educ. Couns.

59:69–79

Lorig KR, Sobel DS, Stewart AL, Brown BW Jr, Bandura A, et al. 1999. Evidence suggesting

that a chronic disease self-management program can improve health status while reducing

hospitalization: a randomized trial. Med. Care 37(1):5–14

MacGregor K, Handley M, Wong S, Shariﬁ C, Gjeltema K, et al. 2006. Behavior-change action

plans in primary care: a feasibility study of clinicians. J. Am. Board Fam. Med. 19:215–23

Maher MJ, Mora PA, Leventhal H. 2006. Depression as a predictor of perceived social support

and demand: a componential approach using a prospective sample of older adults. Emotion

6(3):450–58

Maibach E, Murphy DA. 1995. Self-efﬁcacy in health promotion research and practice: con-

ceptualization and measurement. Health Educ. Res. 10(1):37–50

Mak YW, Loke AY, Lam TH, Abdullah AS. 2006. Predictors of the participation of smok-

ing parents in a proactive telephone-based smoking cessation program. Addict. Behav.

31(10):1731–43

Marteau T, Senior V, Humphries SE, Bobrow M, Cranston T, et al. 2004. Psychological impact

of genetic testing for familial hypercholesterolaemia in a previously aware population: a

randomised controlled trial. Am. J. Med. Genet. 128A:285–93

Martin DJ, Garske JP, Davis MK. 2000. Relation of the therapeutic alliance with outcome and

other variables: a meta-analytic review. J. Consult. Clin. Psychol. 68(3):438–50

McCaffery K, Wardle J, Waller J. 2003. Knowledge, attitudes, and behavioral intentions in

relation to the early detection of colorectal cancer in the United Kingdom. Prev. Med.

36(5):525–35

McKinlay JB, McKinlay SM. 1977. The questionable contribution of medical measures to the

decline of mortality in the United States in the twentieth century. Milbank Q. 55(3):405–28

McDonald HP, Garg AX, Haynes RB. 2002. Interventions to enhance patient adherence to

medication prescriptions: scientiﬁc review. JAMA 288(22):2868–79

Meyer D, Leventhal H, Gutmann M. 1985. Common-sense models of illness: the example of

hypertension. Health Psychol. 4:115–35

Mora PA, Halm EA, Leventhal H, Ceric F. 2007. Elucidating the relationship between negative

affectivity and symptoms: the role of illness-speciﬁc affective responses. Ann. Behav. Med.

In press

Mora PA, Robitaille C, Leventhal H, Swigar M, Leventhal EA. 2002. Trait negative affect

relates to prior week symptoms, but not to reports of illness episodes, illness symptoms

and care seeking among older people. Psychosom. Med. 64(3):436–49

Moss-Morris R, Weinman J, Petrie KJ, Horne R, Cameron LD, Buick D. 2002. The Revised

Illness Perception Questionnaire (IPQ-R). Psychol. Health 17(1):1–16

Ngo-Metzger Q, Massagli MP, Clarridge BR, Manocchia M, Davis RB, et al. 2003. Linguistic

and cultural barriers to care. J. Gen. Intern. Med. 18:44–52

502 Leventhal et al.

Annu. Rev. Psychol. 2008.59:477-505. Downloaded from arjournals.annualreviews.org

by Rutgers University Libraries on 08/04/09. For personal use only.

ANRV331-PS59-18 ARI 5 November 2007 10:57

Orbell S, Hagger M, Brown V, Tidy J. 2006. Comparing two theories of health behavior:

a prospective study of noncompletion of treatment following cervical cancer screening.

Health Psychol. 25(5):604–15

Orbell S, Hodgkins S, Sheeran P. 1997. Implementation intentions and the theory of planned

behavior. Personal. Soc. Psychol. Bull. 23(9):945–54

Pachter LM. 1994. Culture and clinical care: folk illness beliefs and behaviors and their impli-

cations for health care delivery. JAMA 271:690–94

Park DC, Hertzog C, Leventhal H, Morrell R, Leventhal E, et al. 1999. Medication adherence

in rheumatoid arthritis patients: older is wiser. J. Am. Geriatr. Soc. 47:172–83

Petrie KJ, Weinman JA. 1997. Perceptions of Health and Illness: Current Research and Applications.

Amsterdam: Harwood Acad.

Pi-Sunyer FX. 1993. Medical hazards of obesity. Ann. Intern. Med. 119(7):655–60

Powers WT. 1973. Feedback: beyond behaviorism. Science 179:351–56

Prochaska JO, Velicer WF, Redding C, Rossi JS, Goldstein M, et al. 2005. Stage-based expert

systems to guide a population of primary care patients to quit smoking, eat healthier,

prevent skin cancer, and receive regular mammograms. Prev. Med. 41:406–16

Prohaska TR, Keller ML, Leventhal EA, Leventhal H. 1987. Impact of symptoms and aging

attribution on emotions and coping. Health Psychol. 6:495–514

Renner B, Schwarzer R. 2005. The motivation to eat a healthy diet: how intenders and nonin-

tenders differ in terms of risk perception, outcome expectancies, self-efﬁcacy, and nutrition

behavior. Polish Psychol. Bull. 36(1):7–15

Rieckmann N, Gerin W, Kronish IM, Burg MM, Chaplin WF, et al. 2006. Course of depressive

symptoms and medication adherence after acute coronary syndromes. J. Am. Coll. Cardiol.

48(11):2218–22

Rodin J, Langer EJ. 1996. Long-term effects of a control-relevant intervention with the in-

stitutionalized aged. In Readings in Social Psychology: The Art and Science of Research, ed. S

Fein, S Spencer, pp. 175–80. Boston, MA: Houghton Mifﬂin

Rodin J, Salovey P. 1989. Health psychology. Annu. Rev. Psychol. 40:533–79

Rook KS. 2003. Exposure and reactivity to negative social exchanges: a preliminary investiga-

tion using daily diary data. J Gerontol. B Psychol. Sci. Soc. Sci. 58B(2):100–11

Ross S, Walker A, MacLeod MJ. 2004. Patient compliance in hypertension: role of illness

perceptions and treatment beliefs. J. Human Hypertens. 18:607–13

Rothman AJ. 2000. Toward a theory-based analysis of behavioral maintenance. Health Psychol.

19(Suppl.):64–69

Russell LB, Suh D, Safford MM. 2005. Time requirements for diabetes self-management: too

much for many? J. Fam. Pract. 54(1):52–56

Ryan P, Lauver DR. 2002. The efﬁcacy of tailored interventions. J. Nurs. Scholarsh. 34(4):331–

Sallis JF, Hovell MF, Hofstetter CR. 1992. Predictors of adoption and maintenance of vigorous

physical activity in men and women. Prev. Med. 21(2):237–51

Schaie KW, Krause N, Booth A, eds. 2004. Religious Inﬂuences on Health and Well-Being in the

Elderly. New York: Springer

Schneiderman N, Antoni MH, Saab PG, Ironson G. 2001. Health psychology: psychosocial

and biobehavioral aspects of chronic disease management. Annu. Rev. Psychol. 52:555–80

Schwarzer R, Fuchs R. 1995. Self-efﬁcacy and health behaviors. In Predicting Health Behaviour,

ed. M Connor, P Norman, pp. 163–96. Buckingham, UK: Open Univ. Press

Sebregts EH, Falger PR, Bar FW, Kester AD, Appels A. 2003. Cholesterol changes in coronary

patients after a short behavior modiﬁcation program. Int. J. Behav. Med. 10(4):315–30

www.annualreviews.org

•

Health Psychology 503

Annu. Rev. Psychol. 2008.59:477-505. Downloaded from arjournals.annualreviews.org

by Rutgers University Libraries on 08/04/09. For personal use only.

ANRV331-PS59-18 ARI 5 November 2007 10:57

Sheeran P, Orbell S. 2000. Using implementation intentions to increase attendance for cervical

cancer screening. Health Psychol. 19(3):283–89

Shields CA, Brawley LR. 2006. Preferring proxy-agency: impact on self-efﬁcacy for exercise.

J. Health Psychol. 11(6):904–14

Siegel K, Lekas HM. 2002. AIDS as a chronic illness:psychosocialimplications. AIDS 16(Suppl.

4):S69–76

Simpson SH, Eurich DT, Majumdar SR, Padwal RS, Tsuyuki RT, et al. 2006. A meta-analysis

of the association between adherence to drug therapy and mortality. Br. Med. J. 333:15–21

Sisk JE, Hebert PL, Horowitz CR, McLaughlin MA, Wang JJ, Chassin MR. 2006. Effects

of nurse management on the quality of heart failure care in minority communities. Ann.

Intern. Med. 145:273–83

Smith JL. 2004. Food, health and psychology: Competing recipes for research and understand-

ing. J. Health Psychol. 9:483–96

Sobell MB, Sobell LC. 2000. Stepped care as a heuristic approach to the treatment of alcohol

problems. J. Consult. Clin. Psychol. 68(4):573–79

Spruill TM, Pickering TG, Schwartz JE, Mostofsky, Ogedegbe G, et al. 2007. The impact of

perceived hypertension status on anxiety and the White Coat Hypertension Effect. Ann.

Behav. Med. In press

Stoller EP. 1998. Dynamics and processes of self-care in old age. In Self-Care in Later Life, ed.

MG Ory, GH DeFriese, pp. 24–61. New York: Springer

Suls J, Bunde J. 2005. Anger, anxiety, and depression as risk factors for cardiovascular disease: the

problems and implications of overlapping affective dispositions. Psychol. Bull. 131(2):260–

300

Swann WB, Chang-Schneider C, McClarty KL. 2007. Do people’s self-views matter? Am.

Psychol. 62(2):84–94

Tarn DM, Meredith LS, Kagawa-Singer M, Matsumura S, Bito S, et al. 2005. Trust in

one’s physician: the role of ethnic match, autonomy, acculturation, and religiosity among

Japanese and Japanese Americans. Ann. Fam. Med. 3:339–47

Taylor SE, Lobel M. 1989. Social comparison activity under threat: downward evaluation and

upward contacts. Psychol. Rev. 96(4):569–75

Taylor SE, Repetti RL, Seeman T. 1997. Health psychology: What is an unhealthy environment

and how does it get under the skin? Annu. Rev. Psychol. 48:411–47

TenHave TR, Coyne J, Salzer M, Katz I. 2003. Research to improve the quality of care

for depression: alternatives to the simple randomized clinical trial. Gen. Hosp. Psychia-

try 25(2):115–23

Teutsch S. 2003. The cost-effectiveness of preventing diabetes. Diabetes Care 26:2693–94

Thornett A. 2001. Assessing the effect of patient and prescriber preference in trials of treatment

of depression in general practice. Med. Sci. Monit. 7(5):1086–91

Tolma EL, Reininger BM, Evans A, Ureda J. 2006. Examining the theory of planned behavior

and the construct of self-efﬁcacy to predict mammography intention. Health Educ. Behav.

33:233–51

Tuomilehto J, Lindstrom J, Eriksson JG, Valle TT, Hamalainen H, et al. 2001. Prevention

of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose

tolerance. New Engl. J. Med. 344(18):1343–50

Tuomilehto J, Lindstom J, Qiao Q. 2005. Strategies for the prevention of type 2 diabetes and

cardiovascular disease. Eur. Heart J. Suppl. 7(Suppl. D):18–22

Turner L, Mermelstein R, Flay B. 2004. Individual and contextual inﬂuences on adolescent

smoking. Ann. NY Acad. Sci. 1021:175–97

504 Leventhal et al.

Annu. Rev. Psychol. 2008.59:477-505. Downloaded from arjournals.annualreviews.org

by Rutgers University Libraries on 08/04/09. For personal use only.

ANRV331-PS59-18 ARI 5 November 2007 10:57

Tversky A, Kahneman D. 1974. Judgement under uncertainty: heuristics and biases. Science

185(4157):1124–31

U.S. Dept. Health Human Serv. 1964. Smoking and Health: Report of the Advisory Committee

to the Surgeon General of the Public Health Service. Public Health Serv. Publ. No. 1103.

Rockville, MD: US GPO

Vancouver JB, Kendall LN. 2006. When self-efﬁcacy negatively relates to motivation and

performance in a learning context. J. Appl. Psychol. 91(5):1146–53

Wadden TA, Brownell KD, Foster GD. 2002. Obesity: responding to the global epidemic.

J. Consult. Clin. Psychol. 70(3):510–25

Wagner EH. 2004. Deconstructing heart failure disease management. Ann. Intern. Med.

141(8):644–46

Wakslak CJ, Trope Y, Liberman N, Alony R. 2006. Seeing the forest when entry is unlikely:

probability and the mental representation of events. J. Exp. Psychol. 4:641–53

Webb TL, Sheeran P. 2006. Does changing behavioral intentions engender behavior change?

A meta-analysis of the experimental evidence. Psychol. Bull. 132(2):249–68

Weinman J, Petrie KJ, Moss-Morris R, Horne R. 1996. The Illness Perception Questionnaire: a

new method for assessing the cognitive representation of illness. Psychol. Health 11(3):431–

Weinman J, Petrie KJ, Sharpe N, Walker S. 2000. Causal attributions in patients and spouses

following ﬁrst-time myocardial infarction and subsequent lifestyle changes. Br. J. Health

Psychol. 5(3):263–73

Wilson GT, Vitousek KM, Loeb KL. 2000. Stepped care treatment for eating disorders.

J. Consult. Clin. Psychol. 68(4):564–72

Witte K, Morrison K. 2000. Examining the inﬂuence of trait anxiety/repression sensitization

on individuals’ reactions to fear appeals. West. J. Commun. 64:1–27

Wright A, French D, Weinman J, Marteau T. 2006. Can genetic risk information enhance

motivation for smoking cessation? Health Psychol. 25:740–52

Wrosch C, Scheier MF, Carver CS, Schulz R. 2003. The importance of goal disengagement

in adaptive self-regulation: when giving up is beneﬁcial. Self Identity 2:1–20

Yamaoka K, Tango T. 2005. Efﬁcacy of lifestyle education to prevent type 2 diabetes. Diabetes

Care 28(11):2780–86

Ziegelstein RC, Fauerbach JA, Stevens SS, Romanelli J, Richter DP, Bush DE. 2000. Patients

with depression are less likely to follow recommendations to reduce cardiac risk during

recovery from a myocardial infarction. Arch. Intern. Med. 160:1818–23

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Annual Review of

Psychology

Volume 59, 2008

Contents

Prefatory

The Evolution of a Cognitive Psychologist: A Journey from Simple

Behaviors to Complex Mental Acts

Gordon H. Bower pppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppp1

Pharmacology and Behavior

Addiction and the Brain Antireward System

George F. Koob and Michel Le Moal pppppppppppppppppppppppppppppppppppppppppppppppppppppp29

Consummatory Behavior

The Brain, Appetite, and Obesity

Hans-Rudolf Berthoud and Christopher Morrison ppppppppppppppppppppppppppppppppppppppp 55

Sex

Neuroendocrine Regulation of Feminine Sexual Behavior: Lessons

from Rodent Models and Thoughts About Humans

Jeffrey D. Blaustein ppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppp93

Audition and Its Biological Bases

The Biological Basis of Audition

Gregg H. Recanzone and Mitchell L. Sutter pppppppppppppppppppppppppppppppppppppppppppp119

Color Perception

Color in Complex Scenes

Steven K. Shevell and Frederick A.A. Kingdom pppppppppppppppppppppppppppppppppppppppp143

Scene Perception, Event Perception, or Object Recognition

Visual Perception and the Statistical Properties of Natural Scenes

Wilson S. Geisler ppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppp167

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Cognitive Processes

The Mind and Brain of Short-Term Memory

John Jonides, Richard L. Lewis, Derek Evan Nee, Cindy A. Lustig,

Marc G. Berman, and Katherine Sledge Moore pppppppppppppppppppppppppppppppppppppp193

Memory

Relativity of Remembering: Why the Laws of Memory Vanished

Henry L. Roediger, III pppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppp

225

Reasoning and Problem Solving

Dual-Processing Accounts of Reasoning, Judgment,

and Social Cognition

Jonathan St. B.T. Evans ppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppp255

Comparative Psychology, Ethology, and Evolution

Putting the Altruism Back into Altruism: The Evolution of Empathy

Frans B.M. de Waal pppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppp279

Anxiety Disorders

Social Bonds and Posttraumatic Stress Disorder

Anthony Charuvastra and Maryl`ene Cloitre ppppppppppppppppppppppppppppppppppppppppppp301

Inference, Person Perception, Attribution

Spontaneous Inferences, Implicit Impressions, and Implicit Theories

James S. Uleman, S. Adil Saribay, and Celia M. Gonzalez ppppppppppppppppppppppppppp329

Social Development, Social Personality, Social Motivation, Social Emotion

Motives of the Human Animal: Comprehending, Managing, and

Sharing Inner States

E. Tory Higgins and Thane S. Pittman ppppppppppppppppppppppppppppppppppppppppppppppppp361

Cognition in Organizations

Gerard P. Hodgkinson and Mark P. Healey ppppppppppppppppppppppppppppppppppppppppppppp387

Selection and Placement

Personnel Selection

Paul R. Sackett and Filip Lievens ppppppppppppppppppppppppppppppppppppppppppppppppppppppp419

vi Contents

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Education of Special Populations

The Education of Dyslexic Children from Childhood to Young Adulthood

Sally E. Shaywitz, Robin Morris, and Bennett A. Shaywitz ppppppppppppppppppppppppppp451

Health Promotion and Disease Prevention

Health Psychology: The Search for Pathways Between Behavior

and Health

Howard Leventhal, John Weinman, Elaine A. Leventhal, and L. Alison Phillips pppp477

Emotion

Human Abilities: Emotional Intelligence

John D. Mayer, Richard D. Roberts, and Sigal G. Barsade pppppppppppppppppppppppppppp507

Data Analysis

Sample Size Planning for Statistical Power and Accuracy

in Parameter Estimation

Scott E. Maxwell, Ken Kelley, and Joseph R. Rausch pppppppppppppppppppppppppppppppppp537

Timely Topics

A Comprehensive Review of the Placebo Effect: Recent Advances

and Current Thought

Donald D. Price, Damien G. Finniss, and Fabrizio Benedetti pppppppppppppppppppppppp565

Children’s Social Competence in Cultural Context

Xinyin Chen and Doran C. French ppppppppppppppppppppppppppppppppppppppppppppppppppppp591

Grounded Cognition

Lawrence W. Barsalou ppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppp617

Neuroeconomics

George Loewenstein, Scott Rick, and Jonathan D. Cohen ppppppppppppppppppppppppppppp647

Indexes

Cumulative Index of Contributing Authors, Volumes 49–59 pppppppppppppppppppppppp673

Cumulative Index of Chapter Titles, Volumes 49–59 ppppppppppppppppppppppppppppppppp678

Errata

An online log of corrections to Annual Review of Psychology articles may be found at

http://psych.annualreviews.org/errata.shtml

Contents vii

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Identifying the active content of interventions targeting the psychological well-being of carers of people with motor neuron disease: A systematic review

Article

Full-text available

Jun 2024
Palliat Support Care

Objectives The primary aim of this research was to use a taxonomy of behavior change techniques (BCTTv1) to identify, map, and describe the active components of intervention and comparator groups in studies evaluating the psychological well-being (PWB) of motor neuron disease (MND) carers. Secondary aims were to (a) identify absent active ingredients and (b) explore whether variability in the effectiveness of interventions targeting the PWB of MND carers could be better explained through improved characterization of the active content of these interventions. Methods Mixed-methods systematic review based on Joanna Briggs Institute methodology for quantitative, qualitative, and mixed-methods reviews and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Content-coding of interventions targeting the PWB of MND carers using BCTTv1 was conducted. Results Sixteen manuscripts describing 14 studies were included. Forty-one of the possible 93 behavior change techniques (BCTs, 44%) were identified as active ingredients, while 52 BCTs (56%) were absent. BCTs were identified in all 14 intervention groups and 4 control groups. Four of the 16 overall BCTTv1 categories were absent. Eleven of the 14 studies demonstrated PWB benefits from their interventions. Significance of results Identified and absent BCTs and BCTTv1 categories were mapped for all study groups, enabling a transparent characterization of active intervention content associated with positive PWB outcomes. Directions to improve interventions in this nascent field of research included the investigation of relevant untested BCTs in this population and the management of reporting and methodological quality issues.

Communication rules regarding support seeking in patients with a physical illness, according to people with a Surinamese or a Dutch cultural background

Article

Full-text available

May 2024

Objective People with different cultural backgrounds can evaluate the appropriateness of direct and indirect support seeking differently. In this study we explored how direct and indirect communication rules for verbal support seeking by patients with diabetes were perceived among Dutch and Surinamese female participants, and whether the appropriateness differed for the ingroup, outgroup and intercultural support seeker-support provider interactions. Methods The study applied a 2 (direct versus indirect support seeking) X 2 (Surinamese patient versus Dutch patient) X 2 (Surinamese support provider versus Dutch support provider)-design. Dutch and Surinamese participants (N = 686) were randomly assigned to one of the eight conditions in which they were provided with a depiction of the patient, the direct or indirect request for help, and the help provider. The main outcome was the rated appropriateness of the help-seeking request in the specific context. Results The results revealed a significant main effect of communication style: both, Surinamese and Dutch participants evaluated the direct help-seeking as more appropriate compared to indirect help-seeking, independent of patient or provider culture. This effect was particularly strong in participants who scored high on the individual difference in independent self, as shown by a significant interaction. Discussion Literature usually identifies that Surinamese and Dutch populations have different cultural backgrounds and values that express themselves in different attitudes, in general more collectivistic and more individualistic, respectively. However, with regard to help seeking preferences the study results did not verify this expectation. These findings underscore the importance of the support providers’ role in assessing and understanding the individuals’ communication style with regard to help-seeking, rather than assuming communication preferences on the basis of cultural background.

The Mediator Role of Illness Representations in Patients with Obstructive Sleep Apnea: A Preliminary Study

Article

Full-text available

Feb 2024

From Being Literate about Health to Becoming Capable of Achieving Health: Health literacy capabilities of Zimbabwean school youth

Article

May 2023

Food security is an enduring sustainability challenge in the Southern African region. Food availability, accessibility and affordability have profound health impacts and affect the quality of life of a substantial proportion of the world’s population. This article aims to explore, together with students in educational settings, questions about the relationships between food and health, including the contextual conditions of food availability, accessibility and affordability. This provides opportunities to re-embody food by contextualising it as part of natural and built environments, thus engaging with how challenges of human health intersect with animal and environmental health. The research centres on co-creating knowledge with youth based on their valued beings and doings about health and considers how their health goals relate to food and the sustainability challenges of antimicrobial resistance (AMR). By considering how youths’ understandings, evaluations and decisions regarding health, including setting health goals, intersect with the determinants of food, we come to consider their health literacy capabilities to achieve nonpredetermined health goals that align with their valued beings and doings. As such, the implementation gap between knowing and doing is bridged through practices of health and well-being contextually grounded in the lives and experiences of the student youth. Keywords: health literacy, health education, capabilities approach, antimicrobial resistance, knowledge co-creation

Sabotage, Collusion, and Being a Feeder: Towards a New Model of Negative Social Support and Its Impact on Weight Management

Article

Full-text available

Jun 2023

Purpose of Review Whilst research indicates the positive impact of social support across a number of health domains, including weight management, not all social support is beneficial. Recent Findings This paper reviews the evidence for both positive and negative social support in the context of behavioural interventions and surgery for obesity. It then presents a new model of negative social support focusing on sabotage (‘active and intentional undermining of another person’s weight goals’), feeding behaviour (‘explicit over feeding of someone when they are not hungry or wishing not to eat’), and collusion (‘passive and benign negative social support to avoid conflict’) which can be conceptualised within the context of relationships as systems and the mechanisms of homeostasis. Summary There is increasing evidence for the negative impact of social support. This new model could form the basis of further research and the development of interventions for family, friends, and partners to maximise weight loss outcomes.

Enhanced Recovery After Surgery (ERAS) Pathways for Aesthetic Breast Surgery: A Prospective Cohort Study on Patient-Reported Outcomes

Article

Full-text available

Jun 2023
AESTHET PLAST SURG

Background: Patients' expectations of an anticipated timeline of recovery and fear of anesthesia in aesthetic breast surgery have not been studied. Objective: This study aims to assess patient anxiety, expectations, and satisfaction after Enhanced Recovery after Surgery (ERAS) pathways for aesthetic breast surgery and the progress of postoperative recovery. Materials and methods: All consecutive patients who underwent aesthetic breast surgery between April 2021 and August 2022 were included in this single-center prospective cohort study. The ERAS protocol consists of more than 20 individual measures in the pre-, intra-, and postoperative period. Epidemiological data, expectations, and recovery were systematically assessed with standardized self-assessment questionnaires, including the International Pain Outcome Questionnaire (IPO), the BREAST-Q or BODY-Q, and data collection forms. Results: In total, 48 patients with a median of 30 years of age were included. Patients returned to most daily activities within 5 days. Eighty-eight percent of patients were able to accomplish daily activities sooner than expected. The time of return to normal daily activities was similar across all procedure types. There was no statistically significant difference regarding postoperative satisfaction between patients who recovered slower (12%) and patients who recovered as fast or faster (88%) than anticipated (p=0.180). Patients reporting fear of anesthesia in the form of conscious sedation significantly diminished from 17 to 4% postoperatively (p<0.001). Conclusion: Enhanced Recovery after Surgery (ERAS) pathways for aesthetic breast surgery are associated with rapid recovery and high patient satisfaction. This survey study provides valuable insight into patients' concerns and perspectives that may be implemented in patient education and consultations to improve patient satisfaction following aesthetic treatments. Level of evidence iv: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

From Being Literate about Health to Becoming Capable of Achieving Health: Health literacy capabilities of Zimbabwean school youth

Article

Full-text available

May 2023

Life is pain: Fibromyalgia as a nexus of multiple liability distributions

Article

Jun 2023
AM J MED GENET B

Fibromyalgia is a complex disease of unclear etiology that is complicated by difficulties in diagnosis, treatment, and clinical heterogeneity. To clarify this etiology, healthcare-based data are leveraged to assess the influences on fibromyalgia in several domains. Prevalence is less than 1% of females in our population register data, and about 1/10th that in males. Fibromyalgia often presents with co-occurring conditions including back pain, rheumatoid arthritis, and anxiety. More comorbidities are identified with hospital-associated biobank data, falling into three broad categories of pain-related, autoimmune, and psychiatric disorders. Selecting representative phenotypes with published genome-wide association results for polygenic scoring, we confirm genetic predispositions to psychiatric, pain sensitivity, and autoimmune conditions show associations with fibromyalgia, although these may differ by ancestry group. We conduct a genome-wide association analysis of fibromyalgia in biobank samples, which did not result in any genome-wide significant loci; further studies with increased sample size are necessary to identify specific genetic effects on fibromyalgia. Overall, fibromyalgia appears to have strong clinical and likely genetic links to several disease categories, and could usefully be understood as a composite manifestation of these etiological sources.

Sağlığın Teşviki ve Geliştirilmesinde Sağlık Psikolojisinin RolüThe integrative role of health psychology in health promotion

Article

May 2023

Psikoloji, tıp ve fizyoloji araştırmalarındaki gelişmeler, sağlık ve hastalık hakkında yeni bir düşünme biçimine yol açmıştır. Bu kavramsal ağ, sağlığı ve hastalığı bilim adamı ve uygulayıcının bakış açısındaki biyolojik yönlerin ana odak noktası olan biyomedikal yaklaşımdan yeni bir alana taşımıştır. Yeni perspektifte biyolojik özelliklerin yani genetik yatkınlık ile davranışsal faktörler olan yaşam tarzı, stres, sağlık inançları ve sosyal koşullar örneğin kültürel etkiler, aile gibi faktörlerin bir kombinasyonunun ürünü olarak gören biyopsikososyal modeli oluşturmuştur. Bu paradigma değişiminde psikolojinin bir sağlık uzmanlığı alanı olan sağlık psikolojisi (tıbbi psikoloji olarak da anılır) tıbbi uygulamalarda ki modern bir araştırma ve uygulama alanı olarak gelişim göstermiştir. Modern tıbbi uygulamalarda beden, zihin ve davranış ilişkisinin anlaşılması, tıbbi sistemi ve uygulamayı önemli ölçüde değiştirmiştir. Biyomedikal paradigmadan biyopsikososyal tıbba doğru olan bu değişim ayrıca mevcut bütüncül sağlık hizmeti modelini de karakterize etmektedir. İnsanların ruh sağlığı sağlayıcıları da dahil olmak üzere disiplinler arası bir ekipten tedavi ihtiyaçları giderek artmaktadır. Bu değişim süreci ise klinik uygulamalarda sağlık psikolojisinin bütüncül bakış açısına uygulama alanı açmıştır. Davranış ve zihinsel süreçlerin bilimi olarak psikoloji bu tür yönler, örneğin yaşam boyu gelişim, öğrenme, motivasyonlar, deneyimler, duygular, biliş, sosyal davranış ve tutumlar, kişilik gibi faktörler hakkında eğitimi ve bilgiyi irdelemektedir. Bu biyolojik, davranışsal ve sosyal faktörlerin sağlığı ve hastalığı nasıl etkilediğini anlamaya çalışmak ise sağlık psikolojisinin pratikte özel çalışma alanını oluşturmaktadır. Bu çalışmada ise modern tıptaki sağlık ve hastalık hakkında ki paradigma değişimi ekseninde Türkiye’de sağlığın teşviki ve geliştirilmesinde sağlık psikolojisinin rolü tartışılmıştır.

Epilogue: Naturalized Bioethics in Practice

Chapter

Oct 2008

Naturalized bioethics represents a revolutionary change in how health care ethics is practised. It calls for bioethicists to give up their dependence on utilitarianism and other ideal moral theories and instead to move toward a self-reflexive, socially inquisitive, politically critical, and inclusive ethics. Wary of idealisations that bypass social realities, the naturalism in ethics that is developed in this volume is empirically nourished and acutely aware that ethical theory is the practice of particular people in particular times, places, cultures, and professional environments. These essays situate the bioethicist within the clinical or research context, take seriously the web of relationships in which all human beings are nested, and explore a number of the different kinds of power relations that inform health care encounters. Naturalized Bioethics aims to help bioethicists, doctors, nurses, allied health professionals, disability studies scholars, medical researchers, and other health professionals address the ethical issues surrounding health care.

Stepped Care as a Heuristic Approach to the Treatment of Alcohol Problems

Article

Full-text available

Aug 2000

A stepped care approach to treatment decisions for alcohol problems consists of the application of decision rules derived from practice in other areas of health care. The treatment used should be (a) individualized, (b) consistent with the research literature and supported by clinical judgment, and (c) least restrictive but still likely to be successful. Used in this way, stepped care emphasizes serving the needs of clients efficiently but without sacrificing quality of care. Issues concerning stepped care are discussed, and the application of a stepped care approach to alcohol treatment services is described.

A Meta-Analytic Review of the Theories of Reasoned Action and Planned Behavior in Physical Activity: Predictive Validity and the Contribution of Additional Variables

Article

Full-text available

Mar 2002

The aim of the present study was to examine relations between behavior, intentions, attitudes, subjective norms, perceived behavioral control, self-efficacy, and past behavior across studies using the Theories of Reasoned Action (TRA) and Planned Behavior (TPB) in a physical activity context. Meta-ana-lytic techniques were used to correct the correlations between the TRA/TPB constructs for statistical artifacts across 72 studies, and path analyses were conducted to examine the pattern of relationships among the variables. Results demonstrated that the TRA and TPB both exhibited good fit with the corrected correlation matrices, but the TPB accounted for more variance in physical activity intentions and behavior. In addition, self-efficacy explained unique variance in intention, and the inclusion of past behavior in the model resulted in the attenuation of the intention-behavior, attitude-intention, self-efficacy-intention, and self-efficacy-behavior relationships. There was some evidence that the study relationships were moderated by attitude-intention strength and age, but there was a lack of homogeneity in the moderator groups. It was concluded that the major relationships of the TRA/TPB were supported in this quantitative integration of the physical activity literature, and the inclusion of self-efficacy and past behavior are important additions to the model.

Article

Messages for Clinicians: Moderators and Mediators of Treatment Outcome in Randomized Clinical Trials

Article

Mar 2016
AM J PSYCHIAT

Helena Chmura Kraemer

Many problems in randomized clinical trial design, execution, analysis, presentation and interpretation stem in part from an inadequate understanding of the roles of moderators and mediators of treatment outcome. As a result, 1) the results of clinical research are slow to have an impact on clinical decision making and thus to benefit patients; 2) it is difficult for clinicians or patients to apply randomized clinical trial results comparing two treatments (treatment versus control); 3) when such trials are conducted at various sites, the results often do not replicate; 4) when the results influence clinical decision making, the results clinicians obtain do not match what researchers report; and 5) the treatment effects comparing treatment and control conditions, particularly for psychiatric treatments, often seem trivial. In this review article, the author reviews and integrates the methodological literature concerning dealing with covariates in trials to emphasize their impact on clinical decision making. The goal of trials should ultimately be to establish who should get the treatment condition rather than the control condition (moderators) and to determine how to obtain the best outcomes with whatever is the preferred treatment (mediators). The author makes recommendations to clinicians as to which trials might best be ignored and which carefully considered, and urges clinical researchers to focus on studies best designed to reduce the burden of mental illness on patients.

PREDICTING MORE OF PEOPLE MORE OF TIME - ASSESSING PERSONALITY OF SITUATIONS

Article

Jan 1978

Understanding the Understanding of Illness: Lay Disease Representations

Chapter

Jan 1991

George D. Bishop

As health psychologists one of our primary goals is to understand the determinants of health-related behavior. Topics such as preventive health behavior, help seeking and the use of medical services, and compliance with medical recommendations occupy center stage in health psychology (Leventhal, 1983; Matarazzo, Weiss, Herd, Miller, & Weiss 1984; Stone, Cohen, & Adler, 1979). In each of these areas we seek to understand individuals’ responses to actual or perceived health threats. Further, we are concerned with developing interventions to promote desirable health-related behavior. In this chapter these issues are addressed through examination of cognitive representations of physical illness and the implications of these representations for specific health-related behaviors.

Judgment Under Uncertainty: Heuristics and Biases

Article

Jan 1982

Many decisions are based on beliefs concerning the likelihood of uncertain events such as the outcome of an election, the guilt of a defendant, or the future value of the dollar. Occasionally, beliefs concerning uncertain events are expressed in numerical form as odds or subjective probabilities. In general, the heuristics are quite useful, but sometimes they lead to severe and systematic errors. The subjective assessment of probability resembles the subjective assessment of physical quantities such as distance or size. These judgments are all based on data of limited validity, which are processed according to heuristic rules. However, the reliance on this rule leads to systematic errors in the estimation of distance. This chapter describes three heuristics that are employed in making judgments under uncertainty. The first is representativeness, which is usually employed when people are asked to judge the probability that an object or event belongs to a class or event. The second is the availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development, and the third is adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available.

What does the self look like?

Article

Jan 1993

John Kihlstrom

Pharmacological and lifestyle interventions to prevent or delay type 2 DM in people with IGT: Systematic review and meta-analysis

Article

Jan 2007

Influence of time on risk of bowel resection in complete small bowel obstruction

Article

Dec 2005

BACKGROUND: Little is known about the effect of passing time on risk of resection among patients with complete small bowel obstruction. We sought to provide a benchmark of the relationship of time from symptom onset to surgical treatment on the need for resection in patients with complete small bowel obstruction. STUDY DESIGN: We performed an observational study of patients with surgically treated complete small bowel obstruction at an inner-city urban tertiary referral center and a municipal hospital. Patients were sampled randomly retrospectively (n = 60), and prospectively (n = 81), for a final sample of 141. Detailed clinical and time data were abstracted from medical records including out-of-hospital examinations. Risk of resection was calculated using actuarial life table methods. Linear regression was used to determine factors affecting time to treatment. RESULTS: All patients were treated surgically for obstruction; 45% underwent resection. Resected patients had longer (11 days versus 8 days; p = 0.01) and more complicated (31% versus 14% in ICU; p = 0.01) hospital stays. The risk of resection was 4% among patients with 24 hours of unresponsive symptoms; it increased to 10% to 14% through 96 hours, then dropped slightly but did not disappear. Patients treated first with a tube had longer times between first examination and operation, system-time (40.6 hours versus 10.2 hours; p = 0.0007), but this was not associated with an increased resection risk. System-times were shorter among patients seen first in the emergency department (median: 25.7 hours versus 59.7 hours; p = 0.0001). CONCLUSIONS: Physicians should be cautious in postponing surgery beyond 24 hours in patients with unresponsive symptoms from complete obstruction. The risk of resection rises dramatically, remains elevated through 96 hours of unresolved symptoms, then declines but does not disappear.

Health Psychology: The Search for Pathways between Behavior and Health

Abstract

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