2012. Vol.3, No.9, 698-701
Published Online September 2012 in SciRes (
Copyright © 2012 SciRes.
Exploration of an Agentic Construct That Impacts Health
Behaviors in General Population
José L. Pais-Ribeiro
College of Psychology, Porto University, Porto, Portugal
Received June 16th, 2012; revised July 15th, 2012; accepted August 12th, 2012
Hope is defined as the perceived capability to derive pathways to desired goals. The aims of the present
study are to discuss hope as a self-regulation construct. Method: The study includes a convenience sample
of 615 individuals from the community, 51.1% females. They fill a questionnaire that includes demo-
graphic information, disease behavior, health satisfaction, quality of life, and the Hope Scale. Results:
Results suggest a statistically significant relation between hope and outcomes of good health. Conclusions:
We can conclude that hope, especially agency thinking, can be an interesting variable to be considered in
studies about subjective aspects of health.
Keywords: Hope; Health Education; Self Regulation; Health Outcomes
Health was defined at the constitution of the World Health
Organization (WHO), in 1948, as being a state of complete
physical, mental, and social well-being and not merely the
absence of disease or infirmity. Health is something the person
has, instead of the absence of disease, contrary to the traditional
health assessment procedures measuring symptoms and indi-
cators of disease.
In 1986 the World Health Organization organize de First In-
ternational Conference on Health Promotion in Ottawa, Canada,
creating the Ottawa Charter for Health Promotion. Here they
define health promotion as “the process of enabling people to
increase control over, and to improve, their health”. The key of
this process is the control of the route to improve health. It is
recognized that individuals should play an important role in
maintaining their own health, and that greater attention should
be paid to strategies of promoting health (Resnik, 2007). The
quality of health is heavily influenced by lifestyle habits. Health
habits are not changed by an act of will, but require the exercise
of motivational and self regulatory skills.
Researchers have attempted to classify and explain the mul-
titude of factors which can, and do, influence human behavior.
Some models/theories tended to dominate the health education
field in the past 20 - 30 years, like Health Belief Model (Rosen-
stock, 1974), Theory of Reasoned Action (Fishbein & Ajzen,
1975), Social Learning Theory or Social Cognitive Theory
(Bandura, 1982; Rotter, 1945), Stages of Change (Bunton,
Baldwin, Flynn, & Whitelaw, 2000), between others.
One of the models that can be useful to change behavior in a
new perspective is the Self Regulation Model. This model in-
cludes self-monitoring of health related behavior, more the
social and cognitive conditions necessary to engage in it, the
definition and adoption of goals, and self-motivating incentives
and appropriate social support (Bandura, 2005a).
Hope is one construct that deals with dimensions of self
regulation (Little et al., 2006), reason why we will focus on this
variable to explore its appropriateness for health promotion
In health assessment, patient-centered measures are more
broadly defined and capture health status as perceived by the
individual, and should be part of a continuous quality im-
provement cycle (Barr, 1995). Following the WHO health defi-
nition, health status assessment should include physical, emo-
tional and social domains.
During the last 40 years researchers are looking for good
measures (Belloc et al., 1971; Bergner, 1985; Patrick et al.,
1973), and continue nowadays (Breslow, 2006).
In general, measures of health perception focus on function-
ing, explains Bandura (2005a). Because health is something the
persons have, personal initiative contributes to health. Positive
expectancies seem to be associated with better health, and cur-
rent health is associated with higher subjective life expectancy
(Ross & Mirowsky, 2002).
Models of self-management seem to be important tools for
personal initiative. Self-management models develop the moti-
vational and self-regulatory skills which are rooted in an agen-
tic model of health promotion, promotes effective self-manage-
ment of health, keeping people healthy through their life course
(Bandura, 2005b).
Self-regulation, means systematic efforts to direct thoughts,
feelings, and actions, toward the attainment of one’s goals (de
Ridder & de Wit, 2006; Maes & Karoly, 2005; Rasmussen et
al., 2006; Zimmerman, 2000; Ziegelmann et al., 2006). Self-
regulation involves a dynamic motivational system of setting
goals, developing and enacting strategies to achieve those goals,
appraising progress, revising goals and strategies accordingly,
and with the organization of emotional responses, which are
intricately linked with cognitive processes (de Ridder & de Wit,
Hope construct is an important tool in self-regulation (Little
et al., 2006). It is defined as the perceived capability to derive
Pathways to desired goals, and motivate oneself via Agency
thinking to use those pathways (Snyder, 2002). Snyder has been
developing the construct and the way to measure it since the
mid-1980s. The hope construct includes agency thoughts that
“tapes the perceived capacity to initiate (causal capacity) and
sustain (agentic capacity and action-control beliefs) movement
toward desired goals” (Little et al., 2006: p. 72). High hope
individuals are “more likely to ascribe positive and affirming
internal pathways messages” to produce routes to those rotes.
Researchers agree that Hope seems to be an inherently future-
oriented concept (Aspinwall & Leaf, 2002). In the model of
Motivational Systems Theory, personal agency beliefs are the
most powerful pattern (Ford, 1992). Cockerham (2005) consi-
ders agency as a process in which individuals, influenced by
their past but also oriented toward the future, and the present
critically evaluate and choose their course of action.
In the field of primary prevention, Snyder (2002) postulated
that higher hope people may use information about physical
illness as a pathway for prevention efforts. He report empirical
studies in which high-hope women reported having stronger
intentions to engage in cancer prevention activities, or the high-
hope persons relative to the low-hope persons reported engage-
ing in more preventative behaviors, or higher hope gay men
were less likely to engage in high-risk sexual behaviors. In
secondary prevention also reported studies that have found that
higher hope is related to better adjustment in coping with severe
arthritis, with major burn injuries, with spinal cord injuries,
with fibromyalgia, with blindness, in the recovery after an ex-
tremely severe automobile accident, and in the adjustment to
breast cancer, and health perception. The studies report that
hopeful thought facilitate the improvement of strategies for
coping with the pain and the motivation to initiate and continue
the use of these strategies in patients with chronic pain; it seems
that high-hope persons adhere better to medical regimen. Other
researchers found that cancer patients with higher levels of
hope coped with the disease more effectively (Chi, 2007), that
high hope was associated with low risk for depression and a
more adaptive coping style, in people coping with spinal cord
injuries (Elliott et al. 1991), that hope correlated positively with
several measures of psychological adjustment, including opti-
mism, control perceptions, problem-solving, positive affect, and
self-esteem (Snyder et al., 1991). Others show that high hope
appears to be a potentially key cognitive-motivational con-
struct in the development of adolescents and youths, and that
hope reflects a psychological strength that can buffer against
the consequences of acute negative life events (Valle et al.,
In the late-20th century, social scientists have turned their
attentions to Hope. Researchers in this regard, have located at
least 26 theories or definitions, and a handful of validated
measures (Lopez et al., 2003). In the present study we assume
Snyder (2002) hope definition “as the perceived capability to
derive pathways to desired goals, and motivate oneself via
agency thinking to use those pathways” (p. 249).
The objective of the present study is to discuss the appropri-
ateness of the use of hope construct as a self regulation variable,
to identify the contribution of the hope construct for health
outcomes, and inspect the relation between hope, and its two
dimensions, and health satisfaction, quality of life perception
and disease behavior in a community non patient sample. Our
hypothesis is that hope will be positively associated with health
A convenience sample with people from the community, in-
cludes 615 individuals, 51.1% females, mean age 39.18 (be-
tween 17 and 80 years), 9.1 years of school (between 0 and 23),
19.3% single, 68.9% married, 9.6% divorced and 2.1% widow,
19.2% reporting having a disease (no mental disease).
Hope-Snyder et al. (1991) developed the adult Trait Hope
Scale to measure the construct. The scale includes 12 items and
consists of four Agency, four Pathways, and four distracter
items. Their responses on a 4-point Likert type scale ranging
from 1 (definitely false) to 4 (definitely true). In completing the
items, respondents are asked to imagine themselves across time
and situational contexts. The Portuguese version of the Hope
Scale shows similar internal reliability with the original version
(Cronbach Alpha of 0.79 for the overall scale—0.74 to 0.88 for
the original English version; 0.69 for Pathways—0.63 to 0.86
for the original version; and 0.73 for Agency—0.70 to 0.84 for
the original version. Researchers agree that the Hope items
seem to tap beliefs about self-regulatory competence (Aspin-
wall & Leaf, 2002).
Global self-ratings of satisfaction with health—measured
with one item, asking about “satisfaction with health”, answer
in a likert scale type with five positions between “very satis-
fied” and “very unsatisfied”: Higher scores means better satis-
faction with health. A review show that one item is an adequate
measure of health perception, and research shows that it is an
independent predictor of mortality in nearly all of the studies,
despite the inclusion of numerous specific health status indica-
tors and other relevant covariates known to predict mortality
(Idler & Benyamini, 1997).
Global quality of life—accessed with one item, asking “how
do you classify your quality of life?”, answer in a likert scale
type with five positions between “very good” and “very bad”:
Higher scores means better quality of life perception.
Disease behavior—defined as any action implemented by a
person feeling sick to clarify his condition and the treatment to
follow (Kasl & Cobb, 1966). In the present study we assess
disease behavior with four items asking the number of days,
during the last year: “where sick”; “stay at home because a
disease”; “stay in bed because a disease”; and “number of visits
the doctor”. The disease behavior score result from the crude
summation of the items (Cronbach Alpha = 0.82).
Existence of a disease—one question asking if they consider
that they have a disease in that moment, the name of the disease,
and the name of medication taken if any.
Demographic questionnaire—asking about gender, age, edu-
cation, and marital status.
Participants fill all the questionnaires by themselves, after
receiving information about the research, and being asked for
their voluntary, confidential, and anonymous participation.
After completion, they seal the questionnaire inside an enve-
lope and drop it into a ballot box near a previously defined
place (near their work or residence), or mail it to the research
team: the correct return rate is 93.34%. Answer all the ques-
Copyright © 2012 SciRes. 699
tions takes about 10 minutes.
To the descriptive and inferential statistically analysis we use
the Statistical package for Social Sciences V. 15, and for effect
size the G*Power 3 (Faul et al., 2007). We inspect differences
between groups based on demographics and disease character-
istics, more the correlations (with post hoc power confirmation
analysis) for the relationship between the focus variable (Hope)
and the secondary variables.
No statistically significant differences where found for Hope
and it subscales (pathways and agency), quality of life and sat-
isfaction with health, between genders. For disease behavior
females show higher scores of disease behavior, M = 21.76,
than males, M = 10.77, t(613) = 2.23, p < .03. For Hope scale
and subscales we found differences between married and not
married people for Hope subscale agency t(613) = 3.41, p
< .001, with married with statistically significant better scores
M = 23.77, than not married M = 22.47. For satisfaction with
health we found differences between married and not married,
t(613) = 1.90, p = .05, with not married people expressing more
satisfaction with health M = 3.88, than married M = 3.75. For
people reporting having a disease (19.2%, report having a dis-
ease), we found statistically significant differences for Hope
scale t(612) = 2.70, p < .008, with the one reporting not have a
disease with higher Hope M = 46.93 than the ones reporting
having a disease M = 44.75; for the Hope subscale agency the
ones reporting without disease express higher Hope M = 23.67
than the ones reporting having a disease M = 22.05, t(612) =
3.65, p < .0001. The pathways subscale does not have statisti-
cally significant differences, suggesting that the Hope differ-
ences are based on agency subscale. For health satisfaction we
found statistically significant differences with the ones report-
ing having a disease with lower health perception M = 3.11
than the ones do not report having disease M = 3.95, t(612) =
11.85, p < .0001; for quality of life the same pattern with the
ones reporting having a disease with lower quality of life M =
3.22 than the ones do not report having disease M = 3.58, t(612)
= 5.53, p < .0001.
Relation between Variables
Results show that total Hope Scale and it dimensions Path-
ways and Agency is not correlated with age or education.
Hope Scale shows a low correlation with quality of life per-
ception (r(615) = .16, p < .0001), and with health satisfaction
(r(615) = .22, p < .0001), and no statistically significant corre-
lation with disease behavior: Agency shows a low correlation
with quality of life perception (r(615) = .22, p < .0001), a mod-
erate correlation with health satisfaction (r(615) = .30, p < .0001),
and no statistically significant correlation with disease behavior;
Pathways show a low correlation with quality of life (r(615) = .09,
p < .02), and no statistically significant correlation with health
satisfaction and disease behavior.
A post hoc power analysis, taken the conventional α error
probability α = .01, and considered that a rule of thumb and
generally accepted arbitrary statistical power value is .80, for
the present sample size (n = 615) and the correlation of r = .22,
between Agency and quality of life perception, the power is .99,
and between Agency and health satisfaction for a sample size (n
= 615) of r = .30, the power is .99, suggesting a large correla-
tion effect size.
Magaletta and Oliver (1999), found a similar pattern for
Hope and its dimensions in a research where the authors related
optimism, self efficacy and Hope with general well being. They
fond that the will component of Hope (Agency) seems to be the
best predictor of well being measured with Wheeler question-
naire (Wheeler, 1991), like in the present study.
The results found with the Hope scale in the study of its rela-
tionship with health, quality of life, and disease variables sug-
gest that it can be a promising variable to be studied in relation
with these fields. Hope variable is an emergent variable, more
than a latent variable (Ozer & Reise, 1994), and in the first
sense seems to be a useful variable to be included in programs
with healthy persons in the field of health promotion and pri-
mary prevention and with people with chronic diseases or other
conditions, to facilitate the adjustment to their disease or condi-
tion, including to optimize adherence to treatment processes. It
seems that the Hope construct with the two dimensions can
make a link with the Self-Regulation Model as Little et al.
(2006) defends.
Because human behavior seems to be self-regulated, and the
goal-directed actions are self-initiated and purposive activities
it seems important to teach people the skills they will need to
exert greater control over their lives: it includes problem-solv-
ing, goal-setting, and decision-making skills (Little et al., 2006).
From the results, the motivational dimension of Hope,
agency thinking, seems to be an interesting variable to be con-
sidered in studies about subjective aspects of health behavior.
As a limitation, the most important is the one item question-
naire used to assess health perception, and global quality of life.
However, one item measure is always a useful tool in the health
setting because it facilitates questioning people, and it is proved
that global self-rated health is an independent predictor of mor-
tality (Idler & Benyamini, 1997). It seems that self-rated health
can express different internal conditions that only the person it
self can feel, explains Idler and Benyamini (1997). The expres-
sion of the magnitude of statistics, as identified by power
analysis, as the probability of rejecting the null hypotheses,
shows that the significance of the association between agency
and the outcome variables “Global self-ratings of satisfaction
with health” and “Global quality of life” is enough to consider
that agency thinking, in the model of Hope, deserves to be con-
sidered when we design programs to implement an healthy life
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