2012. Vol.3, No.12A, 1116-1124
Published Online December 2012 in SciRes (
Copyright © 2012 SciRes.
The Impact of Positive Psychology on Diabetes Outcomes:
A Review
Joyce P. Yi-Frazier1*, Marisa Hilliard2, Katherine Cochrane3, Korey K. Hood4
1Seattle Children’s Research Institute, University of Washington School of Medicine, Seattle, USA
2Johns Hopkins Adherence Research Center, Johns Hopkins University School of Medicine, Baltimore, USA
3Seattle Children’s Research Institute, Seattle, USA
4Madison Clinic for Pediatric Diabetes, University of California, San Francisco, USA
Email: *
Received September 29th, 2012; revised October 23rd, 2012; accepted November 25th, 2012
Background: Due to the intensive treatment requirements needed to maintain diabetes control, optimal
diabetes outcomes can be difficult to achieve for individuals with type 1 or type 2 diabetes from child-
hood through adulthood. While risk factors related to individual differences in outcomes have been stud-
ied in depth, there is a growing body of research that has revealed the effects of positive personal and en-
vironmental characteristics on diabetes management and glycemic control. The goal of this review is to
summarize the existent literature on the role of positive characteristics in diabetes outcomes. Method: Ex-
tensive literature searches were conducted using Medline, PsychInfo, and CINAHL to identify studies as-
sessing positive personal and environmental characteristics and diabetes outcomes. Included articles were
published between 1989 and 2012. Results: Across the lifespan, positive personal characteristics such as
self-efficacy, self-esteem, and adaptive coping were associated with diabetes management and glycemic
control. Positive environmental factors such as parental monitoring and support were also important pre-
dictors of good outcomes, particularly for adolescents. Conclusions: Positive personal and environmental
factors have been shown to be associated with diabetes outcomes and should be addressed in efforts to
improve outcomes at all life stages. Clinical research and practice may be enhanced through efforts to
evaluate and promote positive personal and environmental factors with the ultimate goal of reducing bar-
riers to optimal diabetes management and control.
Keywords: Positive Psychology; Diabetes
The beginning of the millennium signified an important turn-
ing point for health research. As highlighted in the January,
2000 American Psychologist issue dedicated to “positive psy-
chology,” a dramatic shift towards the study of “health” versus
“illness” was emerging (Seligman & Csikszentmihalyi, 2000).
As an alternative to the study of poor outcomes, the positive
psychology movement provided the springboard for health
researchers to begin to look at the other side of the coin: under-
standing the role of positive traits, experiences, and environ-
ments factors that contribute to wellness. Given the wide vari-
ability in how patients with chronic illness are able to manage
the daily behaviors needed to maintain physical and mental
well-being, positive psychology has provided a particularly
useful framework to identify the factors that promote successful
disease management.
Diabetes affects almost 26 million people and is the seventh
leading cause of death in the United States, with a total esti-
mated cost to society of $174 billion (Centers for Disease Con-
trol and Prevention, 2011). Nationally and internationally, the
incidence and prevalence of both type 1 and type 2 diabetes are
growing (DIAMOND Project Group, 2006; Fox et al., 2006).
Type 1 diabetes, often diagnosed in youth, is a disease in which
the body does not produce insulin, thus requiring regular insu-
lin administration and adjustment to mimic the function of the
pancreas. Type 2 diabetes, which can develop anytime but often
develops in adulthood, is much more common and is marked by
insulin resistance, in which the body produces insulin but does
not process it sufficiently. Type 2 diabetes treatment typically
includes lifestyle modifications (e.g., diet, physical activity)
and may or may not require medication and/or insulin admini-
stration. To manage diabetes optimally, intense efforts by the
patient are needed. Type 1 and type 2 diabetes are both com-
plex chronic diseases involving a variety of components of care,
including medication adherence, diet, exercise, glucose moni-
toring, and general disease awareness such as recognizing high
or low blood sugars, managing sick days, and social adjustment
at work or school. Inevitably, burnout, stress, or other life cir-
cumstances may provide a barrier to optimal diabetes manage-
ment and glycemic control, but debilitating complications can
occur if attention to one’s disease is neglected (Diabetes Con-
trol and Complications Trial Research Group, 1993; Polonsky,
Barriers to self-management occur at all stages of life. Al-
though much has been discussed about distress, depression, and
other predictors of poor outcomes in diabetes, more recently
there has been a rise of interest and publications on the positive
traits, mechanisms, and environments that associate with better
diabetes management and glycemic control (Christie & Barnard,
2012; Hilliard, Harris, & Weissberg-Benchell, 2012). This re-
*Corresponding author.
view focuses on the adoption and impact of positive psychol-
ogy in the area of diabetes care, specifically in regards to the
positive individual characteristics and environmental factors
that have been reported with diabetes management and/or gly-
cemic control.
Literature searches were conducted from Medline, CINAHL
and PsychInfo search engines between July and August 2012.
Table 1 outlines the operational definitions and measurement
tools used for the search terms used hypothesized to be related
to diabetes outcomes based on general positive psychology
literature (i.e., Seligman & Csikszentmihalyi, 2000).
The primary diabetes outcomes examined were diabetes
management and glycemic control. Measures of diabetes man-
agement generally capture information on self-care behaviors
such as checking blood glucose levels, frequency of exercise,
administering and adjusting insulin or other medications, and
meal planning. In some cases, non self-report data are used to
describe diabetes management, such as downloading a blood
glucose meter and gathering data such as the average number of
blood glucose checks per day.
Diabetes control, or glycemic control as referred henceforth,
is measured by the hemoglobin A1c value, which is obtained
from a blood sample. A1c is the definitive measure of glycemic
control as it approximates average blood glucose values over
the prior 2 - 3 months. It has been used in all major clinical
trials of diabetes (Diabetes Control and Complications Trial
Research Group, 1993) and is part of standard diabetes care. In
healthy persons, average A1c typically ranges from 4.0% -
6.0%, and the American Diabetes Association (ADA) recom-
mends an A1c level of <7.0% for most adults (American Dia-
betes Association, 2011). In youth, ADA recommendations are
<8.5 for youth < 6 years olds, <8.0 for 6 - 12 year olds, and
<7.5 for 13 - 18 year olds (Silverstein et al., 2005). As the
landmark Diabetes Control and Complications Trial showed,
A1c is directly related to the onset and severity of diabetes
complications. From a prevention standpoint, lowering A1c one
point confers a 40% risk reduction of retinopathy, a major com-
plication of diabetes (Diabetes Control and Complications Trial
Research Group, 1993). A1c is therefore the gold standard
measure of control in people with diabetes.
To capture the range of positive constructs that have been
studied in diabetes, research in both pediatric and adult litera-
ture were included, spanning type 1 and type 2 diabetes. Asso-
ciation statistics between the positive characteristics and diabe-
tes outcomes were presented when possible, thus qualitative
studies were excluded. Further, so that associations could be
generally compared, this review did not include studies that
Table 1.
Operational definitions and measurement tools of positive individual and environmental factors linked with diabetes outcomes.
Operational definition Examples of measurement tools used in cited research
Individual f actors:
Self-efficacy A person’s confidence in their ability to complete certain
diabetes-specific actions related to diabetes management
Self-efficacy for diabetes self-management, Perceived
diabetes self-management scale
Self-esteem An individual’s perception of self-worth Rosenberg self-esteem scale
Personality traits Traits such as extraversion, conscientiousness,
neuroticism, agreeableness, and openness NEO Personality Inventory, Personality Research Form
Resilience An individual’s capacity to maintain psychological and
physical well-being in the face of stress
Wagnild and Young Resilience Scale, or combination of
Adaptive coping Effectively dealing with a stressor
Responses to Stress Questionnaire, Coping Inventory for
Stressful Situations, Diabetes Coping measure, COPE,
Coping Styles, Emotional Approach Coping Scale
Internal locus of control The belief that outcomes depend on one’s own behavior,
as opposed to external forces or circumstances
Diabetes Locus of Control Scales, Multidimensional Health
Locus of Control Scales
Sense of coherence One’s enduring feeling of confidence to meet demands and
challenges across internal and external environments Sense of Coherence Scale
Optimism/Hope Expectations for positive outcomes Life Orientation Test
Children’s Hope Scale
Religion/ Spirituality Religious participation Specific questions re: participation
Environmental factors:
Family communication Positive, optimistic discussions about diabetes
management and possible complications
Family Communication about Diabetes and Future Health
Scale, Inventory of Parent and Peer Attachment
(Communication scale)
Parental involvement
Parental sole or shared (e.g., with youth) responsibility for
executing tasks of diabetes management and/or monitoring
and supervision of youth completion of diabetes
management tasks
Collaborative Parent Involvement Scale, Parental
Monitoring of Diabetes Care Scale, Diabetes Family
Responsibility Questionnaire
Family Environment Family characteristics including cohesion, adaptability,
and organization
Family Adaptability and Cohesion Evaluation Scales,
Family Environment Scale
Family and Social support Perception of care from others, including friends and
Diabetes Care Profile, Social support Questionnaire,
Diabetes Family Behavior Checklist, Diabetes Social
Support Interview, Mother-Father-Peer (acceptance scale)
Copyright © 2012 SciRes. 1117
incorporated an intervention to bolster positive characteristics.
Lastly, only articles written in English were included.
Over 80 distinct studies describing an association between
positive psychosocial factors and diabetes outcomes (diabetes
management and/or glycemic control) published between 1989
and 2012 in pediatric or adult diabetes settings were assessed
(Table 2). The following sections highlight the prominent posi-
tive individual characteristics and environmental factors that
have been reported.
Positive Individual Characteristics
Self-esteem, or perception of one’s self-worth, was fre-
quently cited as having positive impact on diabetes outcomes.
Self-esteem was associated with diabetes management and A1c
in youth with type 1 diabetes (rs = .41, –.36, ps < .001 respec-
tively, Schneider et al., 2009). For young adults with type 1
(Johnston-Brooks, Lewis, & Garg, 2002) and adults with type 1
and type 2 (Kneckt, Keinänen-Kiukaanniemi, Knuuttila, &
Syrjälä, 2001; Weinger, Butler, Welch, & La Greca, 2005),
self-esteem associated with diabetes management (i.e., β = .29,
p < .05 in young adults), but not A1c (Johnston-Brooks et al.,
Table 2.
The major positive psychosocial variables associated with diabetes outcomes across age groups and type 1 (T1) and type 2 (T2) diabetes populations,
as represented in the literature.
Youth/Adolescents (T1)
(age 18)
Young Adults (T1)
(specifically ages
18 - 35)
Adults (T1)
(ages 18+)
Adults (T2)
(all ages)*
Individual f actors:
Self-esteem Schneider et al., 2009 Johnston-Brooks,
Kneckt et al., 2001
Weinger et al., 2005
Fry et al., 2011
Weinger et al., 2005
Chih et al., 2010
Helgeson et al., 2011
Iannotti et al., 2006
de Ridder et al., 2004
Sousa et al., 2005
Weinger et al., 2005
Cherrington et al., 2009
Fry et al., 2011
Hunt et al., 2012
Nakahara, 2006
Nozaki et al., 2009
Sharoni & Wu, 2012
Sousa et al., 2005
Venkataraman et al., 2012
Weinger et al., 2005
Zulman et al., 2012
Personality traits
Helgeson & Palladino, 2012
Vollrath et al., 2007
Wheeler et al., 2012
Giles et al., 1992 Fry et al., 2011
Lane et al., 2000
Resilience Perfect et al., 2012 Yi et al., 2008
Yi-Frazier et al., 2010
DeNisco, 2010
Mertens et al., 2011
Yi et al., 2008
Yi-Frazier et al., 2010
Adaptive coping Jaser et al., 2012
Jaser and White, 2011
Bazzazian et al.,2012
Luyckx et al., 2010
Hartemann-Heurtier et al.,
Yi-Frazier et al., 2010
Smalls et al., 2012
Yi-Frazier et al., 2010
Environmental factors:
Family communication
Berg et al., 2011
Palmer et al., 2011
Wysocki et al., 2011
Anderson et al., 1997
Berg et al., 2008
Berg et al., 2011
Ellis et al., 2007
Helgeson et al., 2008
Horton et al., 2009
Palmer et al., 2011
Wysocki et al., 2009
Family Environment
Cohen et al., 2004;
Hanson et al., 1989;
Hauser et al., 1990;
Herge et al., 2012;
Jacobson et al., 1994
Family and Social support
Berg et al., 2011
Ellis et al., 2007
La Greca et al., 1995
Aalto et al., 1997
Boas et al., 2012
Brody et al., 2008
Hunt et al., 2012
Khan et al., 2012
Note: *Only manuscripts addressing adults with type 2 diabetes were found for this review.
Copyright © 2012 SciRes.
2002; Kneckt et al., 2001; Weinger et al., 2005).
Related to self-esteem, general self-efficacy can be defined
as a person’s confidence in their ability to complete certain
actions (Bandura, 1997), but this construct was most often op-
erationalized specific to diabetes management (Table 1). Scales
assessing diabetes self-efficacy, though varied, generally meas-
ured the perceived ability to perform various diabetes manage-
ment tasks. Among adolescents, self-efficacy associated with
better diabetes management for younger (ages 10 - 12) and
older (ages 13 - 16) type 1 youth, rs = .25, .37 respectively, ps
< .05; (Iannotti et al., 2006). Similarly, studies reported signifi-
cant associations between self-efficacy and A1c in this age
group (r = –.21, p < .05 for 13 - 16 year olds; Iannotti et al.,
2006; r = –.30, p < .05 in 12 - 20 year olds; Chih, Jan, Shu &
Lue, 2010). In fact, Chih et al. (2010) reported that patients
with higher self-efficacy scores were 1.63 times more likely to
achieve ADA targets for glycemic control, a feat that adoles-
cents rarely meet (Petitti et al., 2009).
In young adults, self-efficacy alone was the best predictor of
diabetes management (β = .63, p < .0005) and A1c (β = –.30, p
< .05), performing better as a predictor than self-esteem
(Johnston-Brooks et al., 2002). For older adults with type 2
diabetes, self-efficacy was associated with diabetes manage-
ment and glycemic control both cross-sectionally (Venkatara-
man et al., 2012; Zulman, Rosland, Choi, Langa, & Heisler,
2012) and longitudinally (Nakahara et al., 2006). One study in
individuals with type 2 diabetes reported a sex difference in the
association between self-efficacy and glycemic control, show-
ing a stronger effect for men versus women (Cherrington et al.,
2008). Both self-esteem and self-efficacy were associated with
a reduced risk for mortality in older adults with type 2 diabetes
(Fry & Debats, 2011).
Among general personality traits such as the “Big Five”, (the
five major dimensions of personality), agreeableness, the ten-
dency to value cooperation and social harmony, and conscien-
tiousness, the tendency to engage in self-discipline and be
achievement-oriented, were found to be associated with better
glycemic control in youth with type 1 diabetes (rs = –.31, –.35
respectively, ps < .05; Vollrath, Landolt, Gnehm, Laimbacher,
& Sennhauser, 2007). Conscientiousness and extraversion, the
tendency to be outgoing, positive, and seek social interactions,
were also found to be associated with better diabetes manage-
ment in adolescents with type 1 diabetes (rs = .48, .52, respec-
tively ps < .01; Wheeler, Wagaman, & McCord, 2012). Hel-
geson and Palladino (2012) reported that for adolescents with
type 1 diabetes, a positive orientation towards others (called
communion) was associated with both better self-management
and glycemic control. In adults with type 1 diabetes, personality
traits such as higher achievement and social desirability associ-
ated with better control (Giles, Strowig, Challis, & Raskin,
1992). For adults with type 2 diabetes, the traits of neuroticism
and perfectionism, which may not traditionally be considered
“positive”, associated with better outcomes (r = –.22, p < .05
for neuroticism/A1c association; Lane et al., 2000; relative risk
for mortality was 29% lower for those with high perfectionism
scores; Fry & Debats, 2011).
Resilience was also well-cited as an important individual
characteristic contributing to diabetes health. For this review,
resilience was distinguished as a personal resource, defined as a
“baseline” or “innate” characteristic as opposed to other defini-
tions of resilience that emphasize resilient outcomes (Hilliard et
al., 2012). In youth, resilience (as defined by sense of mastery
and optimism) was associated with A1c (rs = –.36, –.32 respec-
tively, p < .05; Perfect & Jaramillo, 2012). In adults, a study
using the Wagnild and Young Resilience Scale found resilience
to be associated with glycemic control in African American
women with type 2 diabetes (r = –.27, p < .05; DeNisco, 2011).
Yi, Vitaliano, Smith, Yi and Weinger (2008) reported resilience
(factor score of self-mastery, self-esteem, self-efficacy, opti-
mism) associated with 1-year follow-up A1c (β = –.39, p < .01)
in adults with type 1 and type 2 diabetes. In fact, higher levels
of resilience were found to buffer the effects of rising distress
on rising A1c.
As a follow-up to that study, the authors reported high levels
of resilience were also associated with adaptive coping
(Yi-Frazier et al., 2010). Studies showing adaptive coping as a
means towards better diabetes outcomes were prevalent (Har-
temann-Heurtier, Sultan, Sachon, Bosquet, & Grimaldi, 2001;
Yi-Frazier et al., 2010). In adolescents, coping was found to be
associated with outcomes such that primary control behaviors
(including problem solving, emotional expression, and emo-
tional regulation), and secondary control behaviors (including
acceptance, positive thinking, cognitive restructuring, and dis-
traction) were associated specifically with diabetes manage-
ment behaviors (rs = .37, .30 respectively, ps < .001), general
quality of life (rs range from .43 to .54, ps < .01) and A1c (rs
range from –.14 to –.43, ps < .05) across two studies (Jaser et
al., 2012; Jaser & White, 2011).
In young adults with type 1 diabetes, task oriented coping
predicted better adjustment to diabetes (Bazzazian & Besharat,
2012) and high levels of tackling spirit and diabetes integration,
subscales of an adaptive coping measure, associated with better
A1c (rs = –.22, –.17 respectively, ps < .05; Luyckx, Vanhalst,
Seiffge-Krenke, & Weets, 2010). In adults with type 2 diabetes
(Smalls et al., 2012), emotional processing and emotional ex-
pression were associated with diabetes management behaviors
(rs ranged from .13 to .23 on measures of adherence to general
diet, exercise, and blood sugar testing, all ps < .05).
Positive individual resources less-frequently mentioned in
the literature included locus of control, sense of coherence,
optimism, and spirituality. In a meta-analysis of internal locus
of control and glycemic control, the authors found no correla-
tion across 13 studies (r = –.01, p = n.s.; Hummer, Vannatta, &
Thompson, 2011). It seems that locus of control may be most
useful in the context of a more specific patient population, as
one study of adults with type 2 diabetes reported a significant
effect between locus of control and A1c for those with low
self-efficacy and high outcome expectancy (O’Hea et al., 2009).
Research on sense of coherence, one’s confidence to meet
demands, has shown associations with acceptance and well-
being in adults, but not with glycemic control (Lundman &
Norberg, 1993; Richardson, Adner, & Nordström, 2001).
However, Cohen and Kanter (2004) showed an indirect effect
from sense of coherence to glycemic control mediated by ad-
herence and Ahola et al. (in press) reported that patients with a
strong sense of coherence achieved an A1c level below 7.5%
more frequently than those with a weak sense of coherence.
Only a few studies exist that assess optimism or hope in rela-
tion to diabetes outcomes. In youth with type 1 diabetes, Lloyd,
Cantell, Pacaud, Crawford and Dewey (2009) found hope to be
associated with diabetes management and A1c (rs = .63, –.39
respectively, ps < .01). De Ridder, Fournier and Bensing (2004)
reported no association of optimism with either diabetes man-
agement or A1c for adults with type 1 diabetes (2004). One
Copyright © 2012 SciRes. 1119
research group (Yi-Frazier et al., 2010; Yi et al., 2008) assessed
optimism within a factor score they termed “resilience”, which
was previously discussed.
Lastly, spirituality was reported in one study of outpatients
with type 2 diabetes with a co-occurring mental disorder, and
found to be associated with quality of life, but not glycemic
control in these patients (Murray-Swank et al., 2007).
Positive Environmental Factors
Consistent with a social-contextual framework of adjustment
and self-management in chronic conditions, the friends and
families of individuals with diabetes play an important role in
their well-being, successful self-management, and achievement
of in-range glycemic control (Modi et al., 2012). As children
move through adolescence, maintaining effective family com-
munication and supportive parental involvement in diabetes
management are among the most critical processes in diabetes
management and control (Jaser & White, 2011; Palmer et al.,
2011; Wysocki, 2002). Optimistic, positive family communica-
tion about diabetes and its complications has been linked with
better diabetes management (rs range = .25 to .64, p < .01; Berg
et al., 2011; Wysocki, Lochrie, Antal, & Buckloh, 2011) and in
some cases glycemic control (rs range = –.11, p = n.s.; Berg et
al., 2011 to .42, p < .0001; Wysocki et al., 2011). Parent and
teen collaboration and shared responsibility for executing the
tasks of diabetes management have also been associated with
better diabetes management (rs = .25 - .29, p < .05; Anderson,
Ho, Brackett, Finkelstein, & Laffel, 1997) and control (Hel-
geson, Reynolds, Siminerio, Escobar, & Becker, 2008; Wy-
socki et al., 2009). Specifically, shared responsibility between
parents and youth has demonstrated up to 0.5% - 1.0% im-
provements in A1c (i.e., 9.0% vs 8.2%; Helgeson et al., 2008;
Wysocki et al., 2009). In adolescence, mother-, father-, and
teen-reports of parental monitoring of diabetes management
task completion (e.g., through direct observation, discussion, or
other methods of supervision), have been linked with better
diabetes management in the range of r = .13 (p = n.s.; Berg et
al., 2008) to .47 (most ps < .05; Berg et al., 2008; Berg et al.,
2011; Ellis et al., 2007; Horton, Berg, Butner, & Wiebe, 2009)
and with lower A1C in the range of r = .04 (p = n.s.; Ellis et al.,
2007) to –.31 (most ps < .05; Berg et al., 2008; Berg et al.,
2011; Horton et al., 2009).
Broadly, positive family relationships have demonstrated
links with better diabetes outcomes in youth, although less con-
sistently than negative family interaction patterns (e.g., conflict;
Laffel et al., 2003). Cohen, Lumley, Naar-King, Patridge and
Cakan (2004) report significant differences in diabetes man-
agement (p < .01) and in glycemic control (p < .01) among
children and adolescents with type 1 diabetes with higher ver-
sus lower levels of family cohesion. Others have found similar
results, with parental perceptions of family cohesion demon-
strating associations with better self-management (r = .32, p
< .05; Hauser et al., 1990) and with a faster rate of improve-
ment in boys’ (but not girls’) glycemic control over four years
(r = –.71, p < .001; Jacobson et al., 1994). While Hanson and
colleagues (Hanson, Henggeler, Harris, Burghen, & Moore,
1989) did not replicate the link between cohesion and glycemic
control (r = –.14, p = n.s.), they reported significant associa-
tions between glycemic control and adaptability, another posi-
tive family characteristic (r = –.25, p < .05). Cohen et al. (2004)
also evaluated adaptability and did not find significant links
with diabetes management or glycemic control. Finally, some
studies find associations between family organization and dia-
betes management (rs range .05, p = n.s. to .35, p < .05; Hanson
et al., 1989; Herge et al., 2012) and glycemic control (rs range
–.07, p = n.s. to –.16 p < .05; Herge et al., 2012; Jacobson et al.,
Specific parenting behaviors have been evaluated with rela-
tion to youths’ diabetes management and control and tend to
show stronger relations to diabetes management than to glyce-
mic control. While parental support (emotional, tangible, and
related to encouraging youth autonomy) has largely demon-
strated associations with better self-management (rs range
from .08, p = n.s., to .37, p < .05; Berg et al., 2011; Ellis et al.,
2007; La Greca, Swales, Klemp, Madigan, & Skyler, 1995;
Palmer et al., 2011), links with glycemic control have not al-
ways been significant (r range: –.03, p = n.s. to –.15, p < .05;
Berg et al., 2011; Ellis et al., 2007). Similarly, evaluations of
parental acceptance (Berg et al., 2008; Berg et al., 2011) and
empathy (Lloyd et al., 2009) generally show relations with
better diabetes management (rs range from .09, p = n.s. to .40,
most ps < .05), and inconsistent associations with better glyce-
mic control (rs range: –.13, p = n.s. to –.28, p < .05). Other
parent characteristics that have shown links with better diabetes
management and control, include authoritative parenting style,
with higher versus lower levels linked with better diabetes
management, p < .01 (Monaghan, Horn, Alvarez, Cogen, &
Streisand, 2012) and family knowledge about diabetes, which
independently predicts glycemic control after controlling for
other influences, p = .05 (Butler et al., 2008).
Social support and relationships have been found to be im-
pactful for adults as well. Dale, Williams, and Bowyer (in press)
conducted a systematic review of peer support interventions on
diabetes outcomes in adults and reported that of 13 RCTs that
used A1c as an outcome, three found peer support to be statis-
tically significant on A1c. Other positive health outcomes were
also reported, including better/improved blood pressure, cho-
lesterol, BMI, diabetes management, and psychological out-
comes. One study of rural African-American adults with type 2
diabetes showed an indirect association between social support
and A1c, through promotion of glucose monitoring (Brody,
Kogan, Murry, Chen, & Brown, 2008).
Summary Model
Based on this review, Figure 1 is proposed as a conceptual
model of how positive individual and environmental character-
istics may directly and indirectly relate to behavioral and bio-
logical diabetes outcomes. This model is based on other con-
ceptual models of individual and environmental factors im-
pacting health behaviors and outcomes (Hilliard et al., 2012;
Modi et al., 2012). At the far left, innate characteristics may
interact with environmental variables (as indicated with the
double-headed arrow) to both directly and indirectly associate
with diabetes outcomes (far right of Figure 1). Interactions
between individual and environmental factors were not detailed
in this review, as they are not routinely analyzed or reported.
However, consistent with social-ecological models of health
behavior (e.g., Modi et al., 2012), many studies evaluated both
sets of influences on diabetes management and control (Herge
et al., 2012, Berg et al., 2011; Ellis et al., 2007). Coping and
self-efficacy (Figure 1, center) are distinguished from the other
individual characteristics (i.e., self-esteem, resilience, and per-
Copyright © 2012 SciRes.
Copyright © 2012 SciRes. 1121
Innate Characteristics:
Personality Behavioral Mechanisms:
management Glycemic control
Environmental Characteristics:
Social support
Family dynamics
Figure 1.
Hypothesized path model of positive characteristics as they influence diabetes health outcomes.
sonality traits) as they represent behavioral processes by which
the innate and environmental characteristics theoretically im-
pact diabetes management and control. In addition, these
mechanisms are more likely to be modifiable through interven-
As noted above, several studies examined path models that
mirrored our conceptual model. For example, on an individual
level, Yi-Frazier and colleagues (2010) showed how resilience
may impact diabetes management and control through en-
hanced coping, and Johnston-Brooks and colleagues (2002)
showed similar associations between self-esteem, self-efficacy,
and diabetes outcomes. The associations of family-level posi-
tive factors were demonstrated by Herge and colleagues (2012),
who examined a path model linking family organization, self-
esteem, and diabetes management and control in youth. Both
diabetes management and glycemic control are important out-
comes, with robust evidence to support the order of effects
depicted here (i.e., Hood, Peterson, Rohan, & Drotar, 2009).
As evidenced by the numerous articles cited in this paper,
diabetes research has embraced the positive psychology move-
ment. Positive individual and environmental factors have been
explored and found to be impactful correlates of behavioral and
biologic diabetes outcomes across the lifespan. Numerous and
consistent reports were found demonstrating significant asso-
ciations between positive characteristics and diabetes self-care
and glycemic control. These findings were often supported
across diverse populations of age, race, location, and diabetes
When available, correlation or standardized coefficients were
reported to give a more precise picture as to the strength of the
associations between the positive characteristic and diabetes
outcomes. In general, association statistics were small to mod-
erate (rs most often ranged between .2 and .4) yet often statis-
tically significant. Clearly additional demographic, clinical, and
psychosocial factors are involved in predicting diabetes out-
comes, but the consistency and pervasiveness of the results for
the ones highlighted here support the role of these positive
variables in diabetes health outcomes.
Discrepancies in associations may be due to the variety of
measurements used to assess these factors, particularly those
that are not diabetes-specific. For example, many measures of
general family characteristics (e.g., cohesion, organization)
were used across studies, resulting in a particularly wide range
of association statistics for those variables. Also, diabetes
management was assessed in multiple ways, through self-report,
frequency of blood glucose monitoring, and/or interviews, each
of which may produce different values (Kichler, Kaugars,
Maglio, & Alemzadeh, 2012) and may have influenced the
strength of associations reported here.
Of all search terms for individual characteristics used for this
review, self-efficacy was the most prominent, both in quantity
of articles assessing the construct, and for the overall magnitude
and consistency of the associations with diabetes outcomes.
This was true spanning pediatric through older adult popula-
tions, for type 1 and type 2 diabetes, and across urban and rural
settings. Clearly one’s confidence in the ability to perform the
tasks needed to maintain optimal glycemia is critical. The abil-
ity to specify domains or types of self-efficacy (e.g. exercise
self-efficacy) make it amenable to precise, targeted intervention.
Indeed, these types of interventions have been shown to im-
prove self-efficacy and subsequent outcomes (George et al.,
2008; van der Heijden, Pouwer, Romeijnders, & Pop, 2012; Wu
et al., 2011). Coping is another area where interventions have
shown beneficial effects on diabetes management and control
through their impact on coping behaviors (Grey, Boland,
Davidson, Li, & Tamborlane, 2000; Grey, Jaser, Whittemore,
Jeon, & Lindemann, 2011). Our results indeed support inter-
vention efforts to promote adaptive coping, as consistent evi-
dence for the association of adaptive coping and outcomes was
found, particularly for self-care behaviors.
As self-efficacy and coping are generally thought to be
mechanisms of diabetes outcomes (Figure 1), it was interesting
that a handful of the more innate individual characteristics were
found to be similarly impactful on diabetes health. In particular,
self-esteem, resilience, and personality traits were fairly strong
correlates of outcomes, particularly with diabetes management.
As depicted in Figure 1, one hypothesis might be that the in-
nate characteristics influence the modifiable behavioral mecha-
nisms (e.g., coping and self-efficacy), which in turn affect dia-
betes management and A1c. Given the relative success of in-
terventions targeting personal resources (e.g., self-esteem, op-
timism) in other populations (i.e., Meevissen, Peters, & Alberts,
2011), more attention should be given to interventions bolster-
ing these resources among individuals with diabetes, with the
goal of strengthening behavioral mechanisms that facilitate
better diabetes management and control.
This review revealed that positive environments also affect
outcomes in children and adults with diabetes. Family charac-
teristics including cohesion, organization, and adaptability were
all linked with better youths’ diabetes outcomes. It may be that
positive family factors like these are components of a house-
hold that prioritizes diabetes management and provides the
structure for successful self-management, which can promote
self-efficacy and ultimately set the stage for effective family
teamwork in executing the multiple tasks of diabetes manage-
ment (Herge et al., 2012). Specific positive family behaviors
were also shown to have a robust relationship with youths’
diabetes outcomes. Just as conflict can hamper positive com-
munication and problem-solving, families who interact in posi-
tive, collaborative ways may encourage open communication
and thus make it possible for youth and their parents to col-
laborate in managing the multiple components of diabetes care.
Parents’ encouraging and supporting youth in completing their
own self-management may exert positive effects on diabetes
outcomes by providing opportunities for teens to gain experi-
ence coping with and solving diabetes-related challenges, there-
by supporting adolescents’ emerging autonomy (Berg et al.,
2011; Wysocki, 2002), and promoting their self-efficacy (Berg
et al., 2011). Thus, intervening at the level of the family to
promote a supportive, collaborative environment has consis-
tently demonstrated benefits for diabetes management and con-
trol (Anderson, Brackett, Ho, & Laffel, 1999; Laffel et al., 2003;
Wysocki et al., 2007; Wysocki et al., 2008).
In sum, the purpose of this paper was to provide a compre-
hensive synthesis of the developing literature on positive psy-
chology in diabetes research and practice. There is clear evi-
dence of the impact of the positive psychology framework on
the daily management and health outcomes of people with dia-
betes. In general, this suggests that our research and clinical
encounters for people with diabetes should equally focus on
what is going well as opposed to only the areas that need im-
provement. More specifically, clinicians and researchers should
1) implement measurements of wellness, and 2) target positive
areas in addition to deficits during our interventions in these
encounters. Much work is left to be done in achieving these
specific goals from both clinical and research perspectives. For
example, more work could be done to further explore how the
associations between individuals’ positive characteristics and
health outcomes may be influenced by characteristics of their
environments (e.g., perhaps high levels of family support am-
plify the impact of self-efficacy on diabetes management and
control). However, this review emphasizes the significant pro-
gress made thus far and shows that the field is indeed on the
right track toward optimizing health outcomes for this impor-
tant segment of our population.
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