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Development and psychometric evaluation of a measure of intuitive eating

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Intuitive eating is characterized by eating based on physiological hunger and satiety cues rather than situational and emotional cues and is associated with psychological well-being. This study reports on the development and initial psychometric evaluation of the Intuitive Eating Scale (IES) with data collected in 4 studies from 1,260 college women. Exploratory factor analysis uncovered 3 factors: unconditional permission to eat, eating for physical rather than emotional reasons, and reliance on internal hunger/satiety cues; confirmatory factor analysis suggested that this 3-factor model adequately fit the data after 4 items with factor loadings below .45 were deleted. IES scores were internally consistent and stable over a 3-week period. Supporting its construct validity, IES scores were (a) negatively related to eating disorder symptomatology, body dissatisfaction, poor interoceptive awareness, pressure for thinness, internalization of the thin ideal, and body mass; (b) positively related to several indexes of well-being; and (c) unrelated to impression management. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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Development and Psychometric Evaluation of a Measure
of Intuitive Eating
Tracy L. Tylka
Ohio State University
Intuitive eating is characterized by eating based on physiological hunger and satiety cues rather than
situational and emotional cues and is associated with psychological well-being. This study reports on the
development and initial psychometric evaluation of the Intuitive Eating Scale (IES) with data collected
in 4 studies from 1,260 college women. Exploratory factor analysis uncovered 3 factors: unconditional
permission to eat, eating for physical rather than emotional reasons, and reliance on internal hunger/
satiety cues; confirmatory factor analysis suggested that this 3-factor model adequately fit the data after
4 items with factor loadings below .45 were deleted. IES scores were internally consistent and stable over
a 3-week period. Supporting its construct validity, IES scores were (a) negatively related to eating
disorder symptomatology, body dissatisfaction, poor interoceptive awareness, pressure for thinness,
internalization of the thin ideal, and body mass; (b) positively related to several indexes of well-being;
and (c) unrelated to impression management.
Keywords: intuitive eating, eating behaviors, college women, assessment, psychometrics
In the field of psychology, the study of eating behaviors largely
has been a pathology-focused endeavor because it has explored
and identified correlates and predictors of disordered rather than
adaptive eating. It has been argued that psychologists also need to
consider adaptive behaviors that contribute to and maintain overall
psychological health (Seligman & Csikszentmihalyi, 2000). Some
psychologists have addressed adaptive eating behaviors when ex-
ploring unrestrained eating (e.g., Kahan, Polivy, & Herman, 2003;
Polivy & Herman, 1999) and the eating disorder continuum (e.g.,
Mintz & Betz, 1988; Tylka & Subich, 1999, 2004); however, they
have defined these behaviors as the absence of eating disorder
symptoms. Professionals within other disciplines (e.g., dietetics)
have discussed adaptive eating, but it usually is presented in the
form of behavioral guidelines for the intake of certain food groups
rather than an exploration of its correlates and predictors, and it is
often kept separate from the literature on clinical eating disorders
(Ogden, 2003). As a result, the study of eating behaviors is
disjointed, and much remains unknown about positive eating
behaviors.
Instruments assessing eating behaviors have mirrored this focus
on pathology. It is true that low levels and asymptomatic rank on
such measures as the Eating Attitudes Test–26 (EAT-26; Garner,
Olmsted, Bohr, & Garfinkel, 1982), the Eating Disorder
Inventory–3 (Garner, 2004), and the Questionnaire for Eating
Disorder Diagnoses (Mintz, O’Halloran, Mulholland, & Schnei-
der, 1997) are indicators of adaptive eating because they reflect the
absence of characteristics associated with clinical eating disorders
(e.g., preoccupation with food, binge eating, dietary restriction).
Yet, some scholars (e.g., Tribole & Resch, 1995) have argued that
adaptive eating is more than just the absence of these characteris-
tics because different internal cues are used to determine when,
what, and how much to eat. Individuals who eat adaptively often
use physiological hunger and satiety cues to guide their eating
behaviors, whereas individuals with clinical eating disorders often
use emotional cues to guide their eating behaviors. Also, individ-
uals may not display eating disorder symptomatology per se but
may not eat adaptively (e.g., by habitually eating in the absence of
hunger but not an amount large enough to be considered a binge or
by eating everything on the plate with no regard to satiety level).
Thus, adaptive eating may be negatively related to but not solely
defined by the absence of eating disorder symptoms. In order to
understand this construct more comprehensively, measures of
adaptive eating need to be developed. Use of these measures can
raise awareness about potential variables that can serve as buffers
to developing disordered eating behaviors. The purpose of the
present study, then, was to develop and assess the psychometric
properties of such a measure.
Although there could be several facets of adaptive eating, the
current study focuses on describing and measuring intuitive eating
(i.e., eating based on physiological hunger and satiety cues rather
than external and emotional cues; Tribole & Resch, 1995). Several
psychologists (e.g., Carper, Fisher, & Birch, 2000; Fedoroff, Po-
livy, & Herman, 1997; Polivy & Herman, 1987, 1992) and nutri-
tionists (e.g., Tribole & Resch, 1995) have argued that this style of
eating is adaptive because it is associated with a strong connection
with, understanding of, and response to internal physiological
needs pertaining to hunger and satiety as well as low preoccupa-
tion with food. These scholars have identified three central features
of intuitive eating: (a) unconditional permission to eat when hun-
gry and what food is desired, (b) eating for physical rather than
emotional reasons, and (c) reliance on internal hunger and satiety
cues to determine when and how much to eat. These components
Correspondence concerning this article should be addressed to Tracy L.
Tylka, Department of Psychology, Ohio State University, 1465 Mt. Vernon
Avenue, Marion, OH 43302. E-mail: tylka.2@osu.edu
Journal of Counseling Psychology Copyright 2006 by the American Psychological Association
2006, Vol. 53, No. 2, 226–240 0022-0167/06/$12.00 DOI: 10.1037/0022-0167.53.2.226
226
are interrelated, and the presence of each is necessary to reflect
intuitive eating (Tribole & Resch, 1995). A detailed discussion of
each feature, including why it is considered adaptive, is presented
next.
Unconditional Permission to Eat (When Hungry and What
Food Is Desired)
Unconditional permission to eat reflects a readiness to eat in
response to internal physiological hunger signals and the food that
is desired at the moment (Tribole & Resch, 1995). Individuals who
engage in this eating strategy do not try to ignore their hunger
signals, nor do they classify food into acceptable and nonaccept-
able categories and attempt to avoid food in the latter category.
Laboratory experiments have revealed that these individuals eat
more food after a period of not eating or after eating a small
amount of food rather than after eating a large amount of food
(Herman & Polivy, 1988; Woody, Costanzo, Leifer, & Conger,
1981). Therefore, their eating is controlled by their hunger and
satiety signals, unlike those who allow themselves to eat but have
no control over their eating (e.g., individuals who engage in binge
eating).
People who place conditions on when, how much, and what
foods they can eat (i.e., by restricting the timing, amount, and type
of food eaten according to some external standard) increase their
likelihood of feeling deprived and preoccupied with food (Polivy
& Herman, 1999; Tribole & Resch, 1995). When men who had no
prior preoccupation with food were placed on a greatly reduced
calorie diet for 6 months, many became extremely preoccupied
with food and engaged in binge eating that persisted even after the
diet was terminated (Keys, Brozek, Henschel, Mickelsen, & Tay-
lor, 1950). Children whose parents restricted their food intake were
more likely to eat in the absence of hunger and had higher body
mass than children whose parents did not substantially restrict their
food intake (Faith, Scanlon, Birch, Francis, & Sherry, 2004).
Laboratory experiments have revealed that restrained eaters over-
indulge in food as a result of perceiving that dietary rules have
been broken or that they have eaten a forbidden food (Herman &
Polivy, 1988; Woody et al., 1981). In addition, people engaging in
dietary restraint are more likely to allow visual and olfactory cues
of foods to guide their food intake than are people who do not
restrict their eating (Fedoroff et al., 1997). Because dietary re-
straint further increases food preoccupation (Keys et al., 1950;
Polivy & Herman, 1999), people who restrict their food intake
actually may eat more than people who give themselves uncondi-
tional permission to eat.
Eating for Physical Rather Than Emotional Reasons
People who eat intuitively use food to satisfy a physical hunger
drive and not to cope with their emotional fluctuations and/or
distress (Tribole & Resch, 1995). A boundary model has been
proposed that explores the connection between eating behavior and
emotions (Herman & Polivy, 1983). Individuals who do not diet
have two boundaries corresponding to hunger and satiety. When
hungry, they will eat so as to escape the hunger zone and will stop
eating when indifferent or slightly sated. Research has shown that
individuals who do not diet often eat less when they are anxious or
stressed than when they are calm, perhaps because of the appetite-
suppressing sympathomimetic effects of these emotions (Herman,
Polivy, Lank, & Heatherton, 1987). However, the behavior of
individuals who restrict their eating is largely under the control of
a third and unnatural diet boundary (Herman & Polivy, 1983).
When the diet boundary is breached, eating often becomes disin-
hibited and in defiance of the hunger and satiety boundaries.
Emotional agitation frequently disrupts the diet boundary because
people who restrain their eating increase their food intake when
they experience negative affect (Costanzo, Reichmann, Friedman,
& Musante, 2001; Herman et al., 1987).
Reliance on Internal Hunger and Satiety Cues to
Determine When and How Much to Eat
People who engage in intuitive eating are both aware of their
internal hunger and satiety signals and trust these signals to guide
their eating behavior (Carper et al., 2000; Tribole & Resch, 1995).
Awareness of inner experiences is a central aspect to well-being
(Rogers, 1964). This awareness is inborn; with development, how-
ever, some people substitute external rules (e.g., proscribing when,
what, and how much to eat) for inner experience as they internalize
societal messages that dieting will lead to favorable outcomes.
Laboratory experiments have revealed that young children have an
internal mechanism that helps them fairly accurately regulate food
intake; even though their intake at each meal was highly variable,
their total daily energy intake was relatively constant (e.g., a
high-calorie meal was followed by a low-calorie meal; Birch,
Johnson, Andresen, Petersen, & Schulte, 1991).
Many caregivers observe children’s variable eating behaviors,
conclude that children cannot adequately regulate food intake, and
adopt coercive strategies to exert control over children’s eating
behaviors (Birch et al., 1991). These strategies are counterproduc-
tive because they replace innate internal hunger and satiety signals
with external rules and lead to a disconnection from internal
experience and innate ability to regulate food intake. In fact, this
type of pressure in child feeding is associated with the emergence
of dietary restraint, weight gain, eating in the absence of hunger,
and eating in response to emotions (e.g., sadness or boredom) and
situational factors (e.g., the mere presence of food) among young
girls (Birch & Fisher, 2000; Birch, Fisher, & Davison, 2003;
Carper et al., 2000).
To date, an instrument has not been developed that assesses
these key components of intuitive eating. In four studies, the
current investigation reports the development of such a measure,
the Intuitive Eating Scale (IES), and its preliminary psychometric
examination with college women.
Study 1: Exploratory Factor Analysis and Construct
Validity
In Study 1, the IES items were developed. Once a scale is
developed, it is imperative to explore its factor structure and
determine whether it yields reliable and valid scores (Walsh &
Betz, 2001). Also, it is essential to determine whether the scale’s
items are internally consistent and whether the scale is strongly
related to other scales that measure similar and related constructs
in order to establish its integrity (Walsh & Betz, 2001). Several
hypotheses were generated. First, a three-factor structure corre-
227
INTUITIVE EATING SCALE
sponding to the central aspects of intuitive eating was expected to
emerge in the exploratory factor analysis. Second, scores on the
total IES and the emergent factor subscales were expected to
demonstrate evidence of internal consistency reliability. Third,
because intuitive eating is conceptualized as adaptive eating (Tri-
bole & Resch, 1995) and eating disorder symptomatology is con-
ceptualized as maladaptive eating (Garner, 1991), the IES was
expected to be related in a negative direction to eating disorder
symptomatology. Fourth, it has been asserted (e.g., Tribole &
Resch, 1995) that significant others can foster intuitive eating in
women by accepting their body size and by not pressuring them to
become thinner; as a result, women are more likely to refrain from
internalizing the thin-ideal prototype advocated by society, accept
their bodies, be aware of and attend to their internal hunger and
satiety signals, and eat in response to these signals. Indeed, it has
been found that women who do not restrict their food intake report
lower pressure for thinness, body dissatisfaction, and internaliza-
tion of the thin-ideal image than do women who restrict their food
intake (Mills, Polivy, Herman, & Tiggemann, 2002). Given the
above theory and research, the IES was hypothesized to be nega-
tively related to body dissatisfaction, poor interoceptive aware-
ness, pressure for thinness, and internalization of the thin-ideal
stereotype.
Method
Participants and procedure. Women enrolled in introductory psychol-
ogy courses volunteered to participate though the psychology department’s
organized research program. The study was described as an investigation of
the relation between eating habits, body attitudes, and personality charac-
teristics. After women were guaranteed anonymity and their informed
consent was obtained, they completed the questionnaires in a classroom
used as a research lab. The measures were counterbalanced to control for
order effects. Participants received credit that was applied toward their
class grade.
Responses from 5 women who did not complete at least 90% of any
given measure were not entered into the data set. The final data set included
responses from 391 women from a large Midwestern university who
ranged in age from 17 to 61 years (M20.85, SD 6.21). Women
identified as Caucasian American (87.7%), Asian American (3.8%), mul-
tiracial (3.4%), African American (3.1%), Native American (2.8%), and
Latina (0.5%). One woman (0.3%) did not indicate her ethnicity. Over half
of the women were freshmen (64.7%); of the remaining women, 15.3%
were sophomores, 8.2% were juniors, 9.0% were seniors, 0.8% were
postbaccalaureate students, 0.5% were graduate students, and 1.3% did not
specify their college rank. Participants described themselves as middle
class (50.6%), upper middle class (30.7%), working class (15.3%), and
upper class (2.3%). One percent did not report a socioeconomic
identification.
Measures. Twenty-eight items were designed to assess the following
key aspects of intuitive eating: (a) unconditional permission to eat when
hungry and what food is desired at the moment (12 items), (b) eating for
physical rather than emotional reasons (9 items), and (c) reliance on
internal hunger and satiety cues to determine when and how much to eat (7
items). Items were written until it was determined that the group of items
comprehensively and adequately reflected the central characteristics of
each of the three aspects of intuitive eating. To formulate the items, I used
information gathered from extant theoretical and empirical literature dis-
cussing intuitive eating, unrestrained eating, and how to promote adaptive
eating (e.g., Carper et al., 2000; Mills et al., 2002; Polivy & Herman, 1992;
Tribole & Resch, 1995). The response format for the IES is a 5-point
Likert-type scale (i.e., 1 strongly disagree,2disagree,3neutral,
4agree,5strongly agree). Higher scores indicate higher levels of
intuitive eating.
Following initial item generation, several steps were taken to ensure the
integrity of each item. One doctoral student in an American Psychological
Association-accredited counseling psychology program and two under-
graduate senior honors students provided feedback regarding the content,
clarity, and parsimony of each item. A counseling psychologist and a
nutrition consultant also were consulted to ensure that the items accurately
reflected the content domain. A majority of these evaluators agreed that all
items should be retained; however, three items were reworded for clarifi-
cation. No new items were proposed.
In addition to the IES, the following measures were given to the
participants. These scales typically have been used in research to assess
their respective constructs (Tylka & Subich, 2004).
The EAT-26 (Garner et al., 1982) was used to assess eating disorder
symptomatology. Each of its 26 items (e.g., “I am terrified about being
overweight”) is rated on a scale ranging from 1 (never)to6(always).
Although Garner et al. recommended that the responses never, rarely, and
sometimes receive a score of 0 and that the responses often, very often, and
always receive scores of 1, 2, and 3, respectively, participants’ total scores
were equal to the average of the coded responses to prevent range restric-
tion. Other researchers (e.g., Mazzeo, 1999; Tylka & Subich, 2004) also
have used this continuous scoring method with nonclinical samples of
college women. Items were averaged to obtain a total score; higher scores
indicate greater eating disorder symptomatology. Among college women,
a coefficient alpha of .91 and a 3-week test–retest reliability estimate of .80
for its scores have been reported (Mazzeo, 1999). For the present study,
alpha was .91 for its scores. The EAT-26 has been shown to be related to
the Drive for Thinness subscale (r.84) and to the Bulimia subscale (r
.55) of the Eating Disorder Inventory–2 (EDI-2; Garner, 1991) among
college women, supporting its convergent validity (Brookings & Wilson,
1994).
The Body Dissatisfaction (BD) and Interoceptive Awareness (IA) sub-
scales of the EDI-2 (Garner, 1991) were used to measure their respective
constructs. For the purposes of this study, only these two subscales of the
EDI-2 were administered. The BD subscale contains 9 items that measure
dissatisfaction with overall body size and the belief that parts of the body
are too large, whereas the IA subscale contains 10 items that assess poor
awareness of internal body states, such as emotions, hunger, and satiety.
Items are rated on a scale ranging from 1 (never true of me)to6(always
true of me). Although Garner (1991) recommended that the item responses
never true of me, seldom true of me, and sometimes true of me receive a
score of 0 and the responses often true of me, very often true of me, and
always true of me receive scores of 1, 2, and 3, respectively, the coded
responses were averaged to prevent range restriction. Other researchers
(e.g., Tylka & Subich, 2004) also have used this scoring method with
college women. Higher subscale scores are indicative of greater body
dissatisfaction and poorer interoceptive awareness, respectively. Among
college women, alphas of .91 for BD subscale scores and .78 for IA
subscale scores have been reported (Brookings & Wilson, 1994). For the
present study, alphas were .93 for BD and .86 for IA subscale scores. Over
a 3-week period, test–retest reliability estimates have been found to be .97
for BD and .85 for IA subscale scores among college women (Wear &
Pratz, 1987). Also, BD scores were related to body preoccupation (r
.83), and IA scores were related to difficulty identifying feelings (r.78)
among college women, supporting the convergent validity for these two
subscales (Tylka & Subich, 2004).
The Perceived Sociocultural Pressures Scale (Stice, Ziemba, Margolis,
& Flick, 1996) was used to determine the women’s reported pressure for
thinness from significant others (i.e., family, friends, and partners) and the
media. It contains eight items (e.g., “I’ve felt pressure from my family to
lose weight”) that are each rated along a scale ranging from 1 (strongly
228 TYLKA
disagree)to5(strongly agree) and are averaged to obtain a total score.
Higher scores reflect greater perceived pressure to be thin. Among high
school and college women, alpha for the Perceived Sociocultural Pressures
Scale scores was .87, its stability of its scores over a 2-week period was
.93, and it was related (r.51) to retrospective reports of pressure to lose
weight during childhood (Stice et al., 1996). For the present study, alpha
was .88 for its scores.
The Internalization subscale of the Sociocultural Attitudes Toward Ap-
pearance Questionnaire (Heinberg, Thompson, & Stormer, 1995) was used
to assess the extent to which the women believed that the thin-ideal societal
stereotype is the ideal body type. It contains eight items (e.g., “Photographs
of thin women make me wish that I were thin”) that are each rated along
a scale ranging from 1 (completely disagree)to5(completely agree) and
are averaged to obtain a total subscale score. Higher subscale scores
indicate greater internalization of the thin-ideal stereotype. Among college
women, alpha was .88 for its scores, and its unidimensionality was upheld
(Heinberg et al., 1995). This subscale was related (r.64) to college
women’s perceptions of ideal body type (Tylka & Subich, 2004). For the
present study, alpha was .90 for its scores.
Results and Discussion
Data first were examined to ensure that the variables’ distribu-
tions would not violate statistical assumptions of the planned
analyses; no substantial violations were uncovered. Further, the
sample size exceeded the number of cases needed for a
participants-to-parameter ratio of 5–10:1, which is required to
accurately estimate the factor structure of a scale (Bentler, 1990).
Means, standard deviations, and intercorrelations of the measures
are included in Table 1.
Exploratory factor analysis. SPSS Version 13.0 was used to
conduct the exploratory factor analysis and all other statistical
analyses reported in this article, except for the confirmatory factor
analysis reported in Study 2. The significance of Bartlett’s test of
sphericity,
2
(300, N391) 4,329.63, p.001, and the size
of the Kaiser–Meyer–Olkin measure of sampling adequacy (.89)
revealed that the set of IES items had adequate common variance
for factor analysis (Tabachnick & Fidell, 1996). To evaluate the
structure of the IES, I used a common factor analysis with prin-
cipal axis factoring and direct oblimin rotation. I chose this type of
rotation because I expected the factors to be correlated. The delta
weight was specified to be zero; this value permits a moderate
correlation between the factors. The number of factors was deter-
mined by factor eigenvalues above 1.0 and a noticeable change in
the slopes within the scree plot (Tabachnick & Fidell, 1996). The
rotated factor matrix was examined to pinpoint items that loaded
on these factors. Criteria for factor loadings included item values
greater than or equal to .40 on the primary factor and values less
than or equal to .30 on other factors. Although a common guideline
is to interpret loadings of .32 or higher (Tabachnick & Fidell,
1996), the minimum loading cutoff was set at .40 in order to
maximize confidence in the factors derived from the solution.
Six factors had eigenvalues greater than 1.0. Initial eigenvalues
and percentage of variance accounted for by each of these factors
were 7.14 and 27.45% for Factor 1, 3.64 and 14.00% for Factor 2,
1.83 and 7.04% for Factor 3, 1.40 and 4.98% for Factor 4, 1.27 and
4.54% for Factor 5, and 1.05 and 3.76% for Factor 6. Together,
they accounted for 61.77% of the variance. After inspecting the
scree plot, I observed a notable difference in the slopes of the first
three factors from those of subsequent factors. Therefore, the
factor solution of only these three factors was examined.
Three items that had either factor loadings less than .40 or
cross-loadings greater than or equal to .30 were eliminated. This
procedure resulted in 25 items, with Factor 1 containing 11 items,
Factor 2 containing 8 items and Factor 3 containing 6 items. Next,
these 25 items were factor analyzed with a principal-axis factor
analysis, three factors, and a direct oblimin rotation (
0). All
items loaded greater than .40 on their respective factor and less
than .30 on any other factor. This three-factor solution accounted
for 49.84% of the variance of the data. As expected, all items
loaded on the intuitive eating factor for which they were written.
Table 2 demonstrates these factor loadings.
The first factor (eigenvalue 7.02) accounted for 28.08% of
the variance; its factor loadings ranged from .45 to .81. This
factor and subscale was labeled Unconditional Permission to
Eat. The second factor (eigenvalue 3.61) accounted for
14.44% of the variance; its factor loadings ranged from .41 to
.79. This factor and subscale was labeled Eating for Physical
Table 1
Means, Standard Deviations, and Correlations Among the Measures of Study 1 (N 391)
Measure MSD 123456789
1. IES: Total 3.36 0.56 .84** .70** .62** .66** .53** .46** .52** .47**
2. IES: Unconditional Permission 3.41 0.82 .84** .27** .29** .72** .44** .31** .41** .41**
3. IES: Eating for Physical Reasons 3.13 0.78 .72** .29** .41** .23** .31** .41** .37** .29**
4. IES: Reliance on Hunger/Satiety Cues 3.59 0.53 .62** .32** .43**
5. Eating Attitudes Test-26 2.41 0.68 .69** .76** .24** .27** —
6. EDI-2: Body Dissatisfaction 3.88 1.24 .56** .48** .33** .35** .54**
7. EDI-2: Interoceptive Awareness 2.56 0.73 .49** .36** .39** .28** .53** .38**
8. PSPS: Pressure for Thinness 2.30 0.90 .55** .46** .37** .28** .53** .59** .45**
9. SATAQ: Internalization 3.39 0.95 .50** .44** .31** .23** .58** .57** .36** .47**
Note. Values below the diagonal are for the 25-item Intuitive Eating Scale (IES) (M3.36, SD 0.56), the 11-item Unconditional Permission to Eat
subscale (M3.41, SD 0.82), and the 8-item Eating for Physical Reasons subscale (M3.13, SD 0.78); values above the diagonal are for the revised
21-item IES (
.88; M3.31, SD 0.58), the 9-item Unconditional Permission to Eat subscale (
.89; M3.36, SD 0.87), and the 6-item Eating
for Physical Reasons subscale (
.86; M2.96, SD 0.85). EDI-2 Eating Disorder Inventory—2; PSPS Perceived Sociocultural Pressures Scale;
SATAQ Sociocultural Attitudes Toward Appearance Questionnaire.
** p.001.
229
INTUITIVE EATING SCALE
Rather Than Emotional Reasons. The third factor (eigenvalue
1.83) accounted for 7.32% of the variance; its factor loadings
ranged from .41 to .58. This factor and subscale was labeled
Reliance on Internal Hunger/Satiety Cues.
Internal consistency reliability evidence for the IES. The in-
ternal consistency reliabilities (alphas) for scores on the total IES
and subscales were .89 for the total 25-item IES, .89 for the
Unconditional Permission to Eat subscale, .86 for the Eating for
Physical Rather Than Emotional Reasons subscale, and .72 for the
Reliance on Internal Hunger/Satiety Cues subscale. For each sub-
scale, corrected item-total correlations were all above .30.
Validity evidence for the IES. Correlations between the IES
and the other study measures are presented in Table 1 below the
diagonal. Correlations around .10 were considered small or negli-
gible, correlations around .30 were considered moderate, and cor-
relations at or above .50 were considered large (Cohen, 1992;
Walsh & Betz, 2001). However, it should be noted that correlation
coefficients do not reflect the practical significance of a relation-
ship (Rosenthal, 1990); thus, it is important to consider this fact
when interpreting the strengths of these coefficients. First, the
hypothesis that the IES was related in a negative direction to eating
disorder symptomatology was explored. As expected, the total IES
and the Unconditional Permission to Eat subscale were strongly
related in a negative direction to eating disorder symptomatology;
the Eating for Physical Rather Than Emotional Reasons and the
Reliance on Internal Hunger/Satiety Cues subscales were slightly
to moderately related in a negative direction to eating disorder
symptomatology.
Second, the hypothesis that the IES would be negatively related
to body dissatisfaction, poor interoceptive awareness, pressure for
thinness, and internalization of the thin-ideal stereotype was in-
vestigated. As predicted, the total IES was strongly related in a
negative direction to these variables. For the IES subscales, Un-
conditional Permission to Eat was moderately to strongly related in
a negative direction to these variables, Eating for Physical Rather
Than Emotional Reasons was moderately related in a negative
direction to these variables, and Reliance on Internal Hunger/
Satiety Cues was slightly to moderately related in a negative
direction to these variables. Collectively, these findings provide
initial support for the IES’s construct validity.
Table 2
Item Factor Loadings and Corrected Item-Total Correlations for Each Intuitive Eating Scale
Factor Obtained From Analyzing the Data of Study 1 (N 391)
Factor and item
Factor
Item-total: r123
Factor 1: Unconditional Permission to Eat (
.89)
1. I try to avoid certain foods... .70 .11 .05 .61
4. If I am craving a certain food... .45 .21 .07 .37
5. I follow eating rules... .65 .08 .06 .62
13. I try to ignore... .51 .06 .18 .53
14. I get mad at myself... .79 .13 .04 .77
19. I have forbidden foods... .65 .02 .05 .63
23. I feel guilty... .81 .15 .02 .79
25. I think of a certain food... .75 .01 .12 .67
26. I don’t trust myself... .55 .28 .02 .59
27. I don’t keep certain foods... .71 .28 .03 .72
28. I use caffeine... .45 .11 .09 .48
Factor 2: Eating for Physical Rather Than Emotional Reasons (
.86)
2. I stop eating... .13 .58 .09 .54
3. I find myself eating when I’m emotional... .17 .66 .03 .62
8. I find myself eating when I am bored... .11 .68 .03 .60
9. I eat everything on my plate... .05 .41 .14 .42
15. I find myself eating when I am lonely... .11 .67 .07 .68
21. I use food to help me soothe... .07 .79 .05 .72
22. I find myself eating when I am stressed... .13 .78 .02 .73
24. I find myself still eating... .05 .57 .09 .58
Factor 3: Reliance on Internal Hunger/Satiety Cues (
.72)
11. I can tell when I’m slightly full. .02 .07 .55 .37
12. I can tell when I’m slightly hungry. .01 .11 .57 .36
16. I trust my body to tell me when... .01 .22 .51 .57
17. I trust my body to tell me what... .01 .14 .41 .41
18. I trust my body to tell me how much... .09 .28 .49 .58
20. When I’m eating... .02 .04 .58 .43
230 TYLKA
Study 2: Confirmatory Factor Analysis and Additional
Construct Validity
It is recommended that a scale’s factor structure be analyzed
with confirmatory factor analysis in order to determine the overall
fit of the data to the scale model and whether items load on their
hypothesized latent factor(s) (Tabachnick & Fidell, 1996). Further-
more, when latent factors are expected to be related and connected
to a higher order factor, as in the IES’s structure, confirmatory
factor analysis allows for the estimation of the relationships be-
tween the latent factors and the determination of whether the latent
factors load on a higher order factor. Therefore, via a second-order
confirmatory factor analysis, it was hypothesized that the IES’s
items would load on their respective latent factors, that the latent
factors would be related, that the latent factors would load on a
higher order intuitive eating factor, and that the overall model
would provide an acceptable fit to the data.
Determining whether the IES would yield additional construct
validity evidence was also an aim of this study. It has been asserted
that intuitive eating is associated with psychological well-being
(Tribole & Resch, 1995). Specifically, dieting is associated with
(a) decreased self-esteem among women because it encourages
them to equate their self-worth with their body size (Fredrickson &
Roberts, 1997) and (b) feelings of deprivation and negative affect
that can decrease satisfaction with life and optimism (Polivy &
Herman, 1999). It has been proposed that because they are not
experiencing dieting-instigated negative affect, people with intui-
tive eating have higher self-esteem, satisfaction with life, opti-
mism, and use of adaptive coping strategies (Tribole & Resch,
1995). Given the above theory and research, it is hypothesized that
IES scores would be related in a positive direction to self-esteem,
optimism, proactive coping (i.e., efforts to develop resources that
lead to challenging goals and personal growth; Greenglass,
Schwarzer, & Taubert, 1999), and satisfaction with life. Last, IES
scores should not be related to response style. Therefore, it was
hypothesized that the IES would yield nonsignificant relations to
impression management, a biased form of responding that reflects
the tendency to give inflated self-descriptions to an audience.
Method
Participants and procedure. Participants read a description of the
study and enrolled via the psychology department Web site. The study was
described as an investigation of the relationships between eating habits,
personality characteristics, and response styles. After participants signed
the informed consent form and were guaranteed anonymity, they com-
pleted the measures, which were counterbalanced, in a classroom used as
a research laboratory. They received course credit for their involvement.
Responses from 7 women who did not answer 90% or more of any given
measure were not included in the data set. The final data set included
responses from 476 women from general psychology classes at a large
Midwestern university. Participants ranged in age from 17 to 50 (M
19.70, SD 4.50), and most (86.2%) identified as Caucasian American,
followed in frequency by Asian American (5.3%), African American
(3.9%), Latina (2.1%), and multiracial (2.4%). A large majority of the
participants were freshmen (72.6%); of the remaining participants, 14.6%
were sophomores, 4.6% were juniors, 7.7% were seniors, and 2 participants
(0.4%) did not indicate their college rank. Many women described them-
selves as upper middle class (47.9%) and middle class (41.6%), whereas
fewer women endorsed working-class (7.6%) and upper class (1.9%)
labels.
Measures. The 25-item IES, discussed in Study 1, was used in Study
2. Internal reliability (coefficient alpha) for the total IES was .87, internal
reliability for the Unconditional Permission to Eat subscale was .88,
internal reliability for the Eating for Physical Rather Than Emotional
Reasons subscale was .86, and internal reliability for the Reliance on
Internal Hunger/Satiety Cues subscale was .76.
In addition to the IES, the following scales were given to participants.
These scales frequently have been used to assess their respective constructs
(e.g., Lopez & Snyder, 2003; Paulhus, 1994).
Self-esteem was assessed by the Rosenberg Self-Esteem Scale (Rosen-
berg, 1965). It contains 10 items (e.g., “I feel that I have a number of good
qualities”) rated on a 4-point scale ranging from 1 (strongly disagree)to4
(strongly agree). Items are averaged, and higher scores reflect greater
self-esteem. Among college women, an alpha of .93 has been reported for
its scores (Tylka & Subich, 2004). For college students, the stability of its
scores over a 2-week period was .85, and it was related (r.59) to another
measure of self-esteem (Robinson & Shaver, 1973). For the present study,
alpha was .90 for its scores.
The Life Orientation Test—Revised (Scheier, Carver, & Bridges, 1994)
contains six items (e.g., “In uncertain times, I usually expect the best”) that
assess generalized optimism and four filler items that are rated on a 4-point
scale ranging from 1 (strongly disagree)to4(strongly agree). In order to
obtain a total score, the six nonfiller items are averaged; higher scores
indicate a greater optimistic life orientation. Among a sample of college
students, the internal consistency reliability for its scores was .82, and it
was related to self-esteem (r.54), self-mastery (r.55), trait anxiety (r
⫽⫺.59), and neuroticism (r⫽⫺.50), supporting its construct validity
(Scheier et al., 1994). For the present study, alpha was .86 for its scores.
The Proactive Coping subscale from the Proactive Coping Inventory
(Greenglass et al., 1999) was used to assess women’s tendency to engage
in proactive coping. It contains 14 items (e.g., “I always try to find a way
to work around obstacles; nothing really stops me”) rated on a 5-point scale
ranging from 1 (strongly disagree)to5(strongly agree). Items are aver-
aged; higher scores reflect greater use of proactive coping. Among Cana-
dian college students, an alpha of .85 for its scores has been reported, and
evidence for its construct validity was garnered because it was related to
proactive attitudes (r.70) and generalized self-efficacy (r.70)
(Greenglass et al., 1999). For the present study, alpha was .89 for its scores.
The Satisfaction With Life Scale (Diener, Emmons, Larsen, & Griffin,
1985) was used to assess women’s global life satisfaction. Its five items
(e.g., “In most ways my life is close to ideal”) are rated along a 7-point
scale ranging from 1 (strongly disagree)to7(strongly agree). Items are
averaged to obtain a total score; higher scores indicate greater satisfaction
with life. Among college students, alpha was .87 for its scores, the stability
of its scores over a 2-month period was .82, and it was related to positive
affect (r.50) and self-esteem (r.54), supporting its construct validity
(Diener et al., 1985). For the present study, alpha was .91 for its scores.
The Impression Management subscale of the Balanced Inventory of
Desirable Responding Version 6 (Paulhus, 1994) assesses the tendency to
present inflated self-descriptions to others. Its 20 items (e.g., “I never
swear”) are rated on a 5-point scale ranging from 1 (not at all true of me)
to5(very true of me) and averaged. Higher scores indicate greater impres-
sion management. Among college students, alpha was .86 for its scores,
and the stability of its scores over a 5-week period was .77 (Paulhus, 1994).
For the present study, alpha was .77 for its scores.
Results and Discussion
The sample was large enough to perform confirmatory factor
analysis on the IES items (Bentler, 1990) in that 59 parameters
231
INTUITIVE EATING SCALE
were estimated. First, data were examined to ensure that the IES
items’ distributions were in accordance with the statistical assump-
tions of confirmatory factor analysis. No substantial violation was
indicated within the data; therefore, no items were transformed.
Mplus Version 2.12 (Muthe´n & Muthe´n, 2001) with maximum
likelihood estimation was used to perform the confirmatory factor
analysis. The 25 IES items served as indicators of their respective
first-order latent factor (i.e., Unconditional Permission to Eat,
Eating for Physical Rather Than Emotional Reasons, Reliance on
Internal Hunger/Satiety Cues). Relations between the three hy-
pothesized latent factors were estimated, and a second-order (i.e.,
Intuitive Eating) latent factor was estimated from the first-order
factors. The adequacy of fit was determined by the four indices
calculated by Mplus and recommended by Hu and Bentler (1999):
the comparative fit index (CFI), the Tucker–Lewis Index (TLI)—
also known as the nonnormed fit index—the standardized root-
mean-square residual (SRMR), and the root-mean-square error of
approximation (RMSEA). The fit statistics ranged from poor (i.e.,
CFI .83, TLI .81) to fair (RMSEA .09, SRMR .09) as
determined by criteria for model fit adequacy (Browne & Cudeck,
1993; Hu & Bentler, 1999). Contrary to hypotheses, this model did
not provide a good overall fit to the data.
Consequently, factor loadings for this model were evaluated to
determine whether certain items did not load strongly on their
hypothesized latent factor and whether the deletion of such items
would enhance the fit of the model to the data. Other researchers
(e.g., Phillips, Szymanski, Ozegovic, & Briggs-Phillips, 2004)
have discarded items that load below .45 on their hypothesized
factor; thus, I decided to delete four items (Items 9, 13, 24, and 28)
that loaded at .37, .44, .44, and .42, respectively, on their hypoth-
esized latent factor. A second confirmatory factor analysis then
was conducted with the remaining 21 items as indicators of their
respective first-order latent factor. Similar to the first model,
relations between the first-order factors were estimated, and a
second-order intuitive eating latent factor was estimated from the
first-order factors. This revised model provided an adequate fit to
the data (Browne & Cudeck, 1993; Hu & Bentler, 1999) because
all fit statistics were acceptable (i.e., CFI .91, TLI .90,
RMSEA .08, SRMR .07). Figure 1 displays the item and
factor loadings from this analysis. All items loaded significantly on
their respective first-order latent factors, and each first-order factor
loaded significantly on the second-order intuitive eating factor;
thus, the hypothesized latent factors are internally consistent and
exist empirically. The first-order factors were moderately related
to one another. Consequently, the remaining analyses were con-
ducted by using this 21-item version of the IES, which is presented
in Appendix A.
Validity evidence for the IES. First, the hypothesis that the IES
would be related in a positive direction to self-esteem, optimism,
proactive coping, and satisfaction with life was explored. As
predicted, IES total scores were moderately to strongly related to
self-esteem and satisfaction with life and moderately related to
optimism and proactive coping. The Unconditional Permission to
Eat subscale was moderately related to self-esteem and satisfaction
with life; however, it was only negligibly related to optimism and
unrelated to proactive coping. The Eating for Physical Rather Than
Emotional Reasons subscale was moderately to strongly related to
self-esteem and moderately related to optimism, proactive coping,
and satisfaction with life. Last, the Reliance on Internal Hunger/
Satiety Cues was moderately to strongly related to satisfaction
with life and was moderately related to self-esteem, optimism, and
proactive coping. As demonstrated in Table 3, all relationships
were in a positive direction, indicating that higher IES scores are
associated with higher levels of psychological health. Collectively,
these findings lend additional support for the IES’s construct
validity.
Last, the hypothesis that intuitive eating would be either unre-
lated or negligibly related to impression management was ex-
plored. As expected, this hypothesis was supported because im-
pression management was not related to the total IES, the
Unconditional Permission to Eat subscale, or the Eating for Phys-
ical Rather Than Emotional Reasons subscale. It was only negli-
gibly related to the Reliance on Internal Hunger/Satiety Cues
subscale. Table 3 presents these relationships.
Internal consistency reliability evidence for the revised IES
scores. Alphas were recalculated for the total IES and the first
two subscales, which were affected by the deletion of the four IES
items. Alphas were .85 for the total IES scores, .87 for the
Unconditional Permission to Eat subscale scores, and .85 for the
Eating for Physical Rather Than Emotional Reasons subscale
scores.
Reanalyzing the data of Study 1 by using the revised 21-item
IES. For Study 1, the IES’s means, standard deviations, alpha
levels, and intercorrelations with the other Study 1 measures were
recalculated by using the 21-item version. This information is
presented in Table 1. As indicated, similar values were obtained
for the 21-item version.
Study 3: The Relation of the IES to Body Mass:
Additional Construct Validity
Because intuitive eaters allow their internal hunger cues to guide
their food intake and follow their internal satiety cues to determine
when to stop eating, they are more likely to weigh an amount that
is ideal for their body type (Polivy & Herman, 1992; Tribole &
Resch, 1995). Conversely, approximately 95% of those who diet
and lose weight will regain the weight within a few years, and
many of these individuals will gain more weight than they origi-
nally lost (Heatherton, Mahamedi, Striepe, Field, & Keel, 1997).
Dieting also has been associated with increased food preoccupa-
tion, binge eating, and eating in the absence of hunger (Birch et al.,
2003; Keys et al., 1950; Polivy & Herman, 1999). Indeed, indi-
viduals who do not diet were found to be less likely to eat in
response to emotional fluctuations and situational factors (e.g.,
visual and olfactory food cues) than those who diet (Carper et al.,
2000; Fedoroff et al., 1997; Kahan et al., 2003). Overall, these
findings indicate that individuals who eat intuitively are less likely
to engage in behaviors that may lead to weight gain (e.g., eating in
the absence of hunger, eating in response to emotional fluctuations
and situational factors, binge eating) than people who diet. Even
though some average and below average weight women may
practice restrained eating without engaging in these behaviors,
women who eat intuitively should have, on average, lower body
mass than those who restrain their eating, because dieting is an
ineffective means of weight loss for most individuals (Heatherton
232 TYLKA
et al., 1997). Therefore, it was hypothesized that IES scores would
be related in a negative direction to women’s body mass; body
mass index (BMI) was examined in lieu of weight because it
controls for height.
Method
Participants and procedure. Participants were enrolled in introductory
psychology courses and learned about the study through the psychology
department’s organized research program. They were informed that the
study was an investigation of their eating habits. Participants were in-
formed that their responses would remain anonymous. After providing
their consent, participants completed the survey in a classroom used as a
research lab. They received credit that was applied toward their class grade.
Responses from 3 women who did not answer at least 90% of the IES or
did not report their weight or height were not included in the data set.
Responses from 199 women (Mage 18.92 years, SD 3.25, range
17–55) from a large Midwestern university were entered into the data set.
Women identified as Caucasian American (75.4%), African American
(13.1%), Asian American (4.0%), Latina (2.0%), international (3.5%),
multiracial (1.5%), and Native American (0.5%). Most participants were
freshmen (77.4%), whereas 16.6% were sophomores, 3.5% were juniors,
1.0% were seniors, and 1.5% did not report their college rank. Most women
described themselves as middle class (43.7%) and upper middle class
(33.2%); fewer women described themselves as working class (8.0%) and
upper class (4.0%).
Measures. The 21-item IES was used. Participants also were asked to
report their current weight and height; this information was garnered to
estimate participants’ BMI. Because college women’s actual BMI has been
found to be highly correlated with the BMI calculated from their self-
ratings of weight and height (r.98, p.001; Tylka & Subich, 1999),
I decided to assess only self-ratings of these variables. The average BMI
for the current sample was 23.50 (SD 3.90; range 17.47–34.94); this
average score is within the normal range (i.e., 22–25) recommended for
women (Kuczmarski & Flegal, 2000). Average IES scores were 3.09
(SD 0.57) for the total IES, 3.08 (SD 0.88) for the Unconditional
Figure 1. Factor loadings of the Intuitive Eating Scale (IES) garnered via second-order confirmatory factor
analysis of the revised 21-item IES data of Study 2 (N476). *p.01.
233
INTUITIVE EATING SCALE
Permission to Eat subscale, 2.65 (SD 0.88) for the Eating for Physical
Rather Than Emotional Reasons subscale, and 3.56 (SD 0.63) for the
Reliance on Internal Hunger/Satiety Cues subscale. Alphas were .85 for the
total IES scores, .87 for the Unconditional Permission to Eat subscale
scores, .85 for the Eating for Physical Rather Than Emotional Reasons
subscale scores, and .78 for the Reliance on Internal Hunger/Satiety Cues
subscale scores.
Results and Discussion
As hypothesized, IES scores were negatively related to BMI.
The relationships between BMI and IES scores were –.28 ( p
.001) for the total IES, –.21 for the Unconditional Permission to
Eat subscale ( p.01), –.17 for the Eating for Physical Rather
Than Emotional Reasons subscale ( p.05), and –.20 for the
Reliance on Internal Hunger/Satiety Cues subscale ( p.01).
These relationships are slight to moderate in size and are consistent
with theory and research (e.g., Kahan et al., 2003; Tribole &
Resch, 1995) suggesting that listening to body signals in deter-
mining what, when, and how much to eat is associated with lower
body mass. These findings support the construct validity of the IES
because they are consistent with the tenets of intuitive eating.
Study 4: Test–Retest Reliability Estimates
When investigating the psychometric properties of a scale that
claims to measure a stable construct, it is important to examine
whether the scale yields consistent scores over a given time period
(Walsh & Betz, 2001). Because intuitive eating has been proposed
to be fairly consistent over time (Tribole & Resch, 1995), it was
hypothesized that the total IES and subscale scores would be stable
over a 3-week period, which would support the test–retest reliabil-
ity of its scores.
Method
Women at the regional campus were recruited via verbal announcements
of the experiment given in their psychology classes, and women at the main
campus learned of the study through the psychology department’s orga-
nized research program. They were informed that the study was an inves-
tigation of their eating habits. For each administration, participants were
instructed to write a code consisting of the first two letters of their mother’s
maiden name and the last two digits of their house or apartment number on
their questionnaire. This code permitted the matching of their initial and
follow-up responses. After participants were assured of the anonymity of
their responses and provided their consent, they completed the IES in a
classroom used as a research lab. They completed the IES for the second
time exactly 3 weeks later and received extra credit that was applied toward
their grade.
Responses from 17 women who did not complete at least 90% of the IES
during the first and second administration (16 of these women did not
complete the IES at the second administration) were not entered into the
data set. The final data set included responses from 194 women (mean
age 22.07 years, SD 7.38, range 17–55) enrolled in general and
upper level psychology classes at a regional campus (n67) and the main
campus (n127) of a large Midwestern university. Women identified as
Caucasian American (94.3%), multiracial (2.6%), African American
(2.1%), Latina (0.5%), and Native American (0.5%). Most participants
were freshmen (54.1%), whereas 15.5% were sophomores, 9.8% were
juniors, 19.1% were seniors, and 3 participants (1.5%) did not report their
college rank. Many women described themselves as middle class (60.8%);
fewer women endorsed upper middle class (21.1%), working-class
(17.5%), and upper class (0.5%) labels.
For the first and second administration, respectively, mean scores and
alphas were 3.41 (SD .53;
.86) and 3.43 (SD .54;
.89) for
the total IES, 3.50 (SD .82;
.89) and 3.49 (SD .80;
.91) for
the Unconditional Permission to Eat subscale, 3.03 (SD .85;
.87)
and 3.01 (SD .84;
.89) for the Eating for Physical Rather Than
Emotional Reasons subscale, and 3.67 (SD .53;
.72) and 3.74 (SD
.51;
.78) for the Reliance on Internal Hunger/Satiety Cues subscale.
Mean IES total and subscale scores did not differ between the regional and
main campus settings, nor did they differ between general psychology and
upper level psychology students (all ps.05).
Results and Discussion
As hypothesized, the stability of the IES over a 3-week period
was supported. The relationship between the first and second
administration was .90 for the total IES, .88 for the Unconditional
Permission to Eat subscale, .88 for the Eating for Physical Rather
Than Emotional Reasons subscale, and .74 for the Reliance on
Internal Hunger/Satiety Cues subscale (all ps.001).
Table 3
Means, Standard Deviations, and Correlations Among the Measures of Study 2 (N 476)
Measures MSD 123456789
1. IES 3.24 0.54
2. IES: Unconditional Permission 3.19 0.83 .81**
3. IES: Eating for Physical Reasons 2.91 0.82 .66** .18**
4. IES: Reliance on Hunger/Satiety Cues 2.72 0.41 .60** .24** .33**
5. Rosenberg Self-Esteem Scale 3.21 0.50 .44** .28** .36** .35**
6. LOT–R (Optimism) 2.90 0.50 .29** .14* .24** .31** .73**
7. PCI: Proactive Coping 3.77 0.52 .29** .10 .27** .34** .63** .67**
8. Satisfaction With Life Scale 5.08 1.14 .41** .26** .26** .38** .68** .61** .54**
9. BIDR-6: Impression Management 2.82 0.51 .12 .07 .06 .16** .21** .15** .18** .10 —
Note. The IES is based on the 21-item scale, Unconditional Permission to Eat is based on the 9-item subscale, and Eating for Physical Reasons is based
on the 6-item subscale. IES Intuitive Eating Scale; LOT–R Life Orientation Test—Revised; PCI Proactive Coping Inventory; BIDR-6 Balanced
Inventory of Desirable Responding— 6.
*p.01. ** p.001.
234 TYLKA
General Discussion
Intuitive eating is characterized by eating according to internal
hunger and satiety signals; it is not akin to binge eating, where
individuals allow themselves to eat but cannot control their eating.
In four studies, the development of a measure of intuitive eating
(the IES) was discussed, its factor structure was investigated, and
reliability and validity evidence for its scores was garnered among
college women. An exploration of the IES’s factor structure in
Study 1 revealed that its 25 items formed three conceptually
meaningful factors, which accounted for approximately 50% of its
variance. However, findings from a second-order confirmatory
factor analysis conducted in Study 2 suggested that 4 of these
original IES items did not load strongly on their respective latent
factors and were subsequently deleted from the scale. The resultant
21-item scale provided a good fit to the data and consequently was
used to obtain the findings presented in this discussion. The first
factor–subscale, Unconditional Permission to Eat, consisted of 9
items that assessed the willingness to eat when physiologically
hungry and what food is desired at the moment. The second
factor–subscale, Eating for Physical Rather Than Emotional Rea-
sons, consisted of 6 items that reflected the tendency to eat to
satisfy an internal hunger drive rather than to cope with emotional
fluctuations and/or distress. The third factor–subscale, Reliance on
Internal Hunger/Satiety Cues, contained 6 items that reflected the
degree of awareness of internal hunger and satiety signals and the
ability of these signals to guide eating behavior.
The second-order confirmatory factor analysis further revealed
that the hypothesized latent factors (formed from the subscale
items) were moderately related to one another and loaded on a
higher order latent factor. These findings provide empirical sup-
port for the assertion that IES factors are theoretically distinct
albeit related components of the broader intuitive eating construct.
Moreover, the total IES and its subscale scores were found to be
internally consistent in all studies and stable over a 3-week period
in Study 4.
This study also obtained construct validity evidence for the total
IES and its subscales. Claims made by scholars (e.g., Costanzo et
al., 2001; Mills et al., 2002; Polivy & Herman, 1999; Tribole &
Resch, 1995) that intuitive eating should be negatively related to
eating disorder symptomatology, body dissatisfaction, poor intero-
ceptive awareness, pressure for thinness, and internalization of the
thin-ideal stereotype were supported in the present study because
Study 1 demonstrated that the total IES and the IES subscales were
negatively related to these variables. Consistent with theory and
research on intuitive eating behaviors (e.g., Costanzo et al., 2001;
Polivy & Herman, 1999; Tribole & Resch, 1995), Study 2 revealed
that IES total and subscale scores were positively related to mea-
sures of self-esteem, optimism, proactive coping, and satisfaction
with life (with the exception of the nonsignificant relation between
Unconditional Permission to Eat and proactive coping), further
supporting the IES’s connection to psychological well-being.
Study 3 found that IES total and subscale scores were negatively
related to BMI, which upholds the connection documented be-
tween dieting and elevated weight (Birch et al., 2003; Carper et al.,
2000; Heatherton et al., 1997). In addition, the IES total and
subscale scores were either not related or negligibly related to an
impression management response style, which supports the dis-
criminant validity of the IES.
The findings that women with higher levels of intuitive eating
are more satisfied with their bodies and perceive less pressure to be
thin may be explained, at least in part, by the negative association
between IES scores and body mass (i.e., they more closely resem-
ble the societal thin-ideal body type). Yet, these women were more
likely to reject the societal stereotype that thinness is their ideal
body type, indicating that they are less likely to base their self-
worth on being thin.
Furthermore, women scoring higher on the Eating for Physical
Rather Than Emotional Reasons subscale may not use food to cope
with their emotional distress because they experience less of this
distress, whereas women who score lower on this subscale may
experience more emotional distress and eat as a coping, albeit
maladaptive, strategy. However, women scoring higher on this
subscale also scored higher on proactive coping, indicating that
they reported using more constructive strategies to deal with their
emotional distress.
Collectively, these findings support the IES and the adaptive
properties of intuitive eating. Given that the IES is relatively brief
and easy to administer and score, it would be useful for both
researchers and clinicians who work with women in a variety of
venues. The total IES and subscale mean values, standard devia-
tions, and skewness and kurtosis values were calculated for the
total sample of women (N1,260) and for the various ethnic
groups, with the data collapsed across all four studies. These
values are presented in Appendix B.
Limitations and Future Research
Most of the participants in the present study were young-adult,
Caucasian, middle- to upper middle-class first-year psychology
students. It is important to determine whether the IES yields
reliable and valid scores with other samples of women (e.g.,
community women or women of color). Also, future research
endeavors could be aimed at demonstrating whether its psycho-
metric properties are upheld with men. Scores on the IES may be
similar for women and men because both women and men are
socialized to adopt an external orientation to food intake: whereas
women are socialized to lose weight, men are socialized to gain
muscle mass (Vartanian, Giant, & Passino, 2001). Men may in-
ternalize the cultural pressure to restrict their eating to high-protein
foods and eat these foods when they are not hungry in order to gain
weight, which will negatively impact their IES scores.
Another limitation is that many of the first and second subscale
items were worded in the direction of maladaptive eating (e.g., “I
find myself eating when I am stressed out, even when I’m not
physically hungry”) and then reverse scored. Reverse scoring these
negative items may not yield the most valid possible measure of
the converse construct. Amending many of these items in the
direction of adaptive eating (e.g., “I am able to cope with my stress
without turning to food for comfort”) and determining the psycho-
metric properties of this revised scale is recommended.
The present study’s exclusive use of self-report methodology
also is somewhat limiting because it relies on participants’
accurate reporting of their current level of functioning. In
235
INTUITIVE EATING SCALE
particular, participants in Study 3 could have either distorted
their weight and height or not known and estimated this infor-
mation. Furthermore, women’s perceptions of their eating hab-
its may or may not be an accurate portrayal of reality. Thus,
another avenue for research could be to determine whether
self-reported eating practices on the IES are strongly correlated
with actual eating behaviors.
Research could focus on determining the best way to help
individuals who have developed an external orientation to food
intake (e.g., those who chronically diet) work toward eating ac-
cording to their internal hunger and satiety signals. These individ-
uals’ internal signals have been weakened as a result of being
ignored, numbed, and replaced with external cues as to when,
what, and how much to eat; consequently, these individuals may
be unable to tell when they are hungry or sated (Birch & Fisher,
2000; Garner, 1991). Because hunger and satiety signals are often
ambiguous, these individuals may interpret their emotional distress
as cues that they are physiologically hungry (Costanzo et al.,
2001).
The IES was related to eating disorder symptomatology, yet the
strength of this relation indicated that there was not a complete
overlap among these constructs (i.e., they shared 43.6% of the
variance). This finding provides preliminary support for the
uniqueness of intuitive eating, suggesting that it is negatively
related to, but more than the mere absence of, eating disorder
symptomatology. Nevertheless, it remains to be determined
whether intuitive eating predicts unique variance in psychological
health variables (e.g., self-esteem, subjective well-being) above
and beyond the variance accounted for by eating disorder
symptomatology.
Future studies might also examine whether adaptive environ-
mental influences (e.g., acceptance of body size from significant
others or caregivers’ use of noncoercive feeding strategies) predict
positive body image, which then predicts intuitive eating. This
model could provide insight as to how some women continue to
follow their internal physiological signals within a social milieu
that frequently pressures women to become thinner.
If future research confirms the validity and reliability of the IES
in samples of clients who present with concerns about food or
eating disorder symptoms, the IES may prove to be a valuable
clinical tool. For instance, the IES could be used to assess whether
clients increase adaptive eating behaviors and attitudes as a result
of treatment. In fact, a comprehensive treatment approach for
disordered eating should result in an increase in adaptive charac-
teristics as well as a reduction of maladaptive symptoms. Further-
more, given its attention to adaptive eating, the IES may better
predict relapse prevention than current eating disorder instruments,
such as the EAT-26 or Eating Disorder Inventory–3.
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(Appendixes follow)
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Appendix A
Intuitive Eating Scale (21 Items)
Directions for participants: For each item, please circle the answer that best characterizes your attitudes or behaviors.
1. I try to avoid certain foods high in fat, carbohydrates, or calories.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
2. I stop eating when I feel full (not overstuffed).
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
3. I find myself eating when I’m feeling emotional (e.g., anxious, depressed, sad), even when I’m not
physically hungry.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
4. If I am craving a certain food, I allow myself to have it.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
5. I follow eating rules or dieting plans that dictate what, when, and/or how much to eat.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
6. I find myself eating when I am bored, even when I’m not physically hungry.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
7. I can tell when I’m slightly full.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
8. I can tell when I’m slightly hungry.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
9. I get mad at myself for eating something unhealthy.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
10. I find myself eating when I am lonely, even when I’m not physically hungry.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
11. I trust my body to tell me when to eat.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
12. I trust my body to tell me what to eat.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
13. I trust my body to tell me how much to eat.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
14. I have forbidden foods that I don’t allow myself to eat.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
15. When I’m eating, I can tell when I am getting full.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
238 TYLKA
Appendix A (continued)
16. I use food to help me soothe my negative emotions.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
17. I find myself eating when I am stressed out, even when I’m not physically hungry.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
18. I feel guilty if I eat a certain food that is high in calories, fat, or carbohydrates.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
19. I think of a certain food as “good”or “bad” depending on its nutritional content.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
20. I don’t trust myself around fattening foods.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
21. I don’t keep certain foods in my house/apartment because I think that I may lose control and eat
them.
12345
Strongly Disagree Disagree Neutral Agree Strongly Agree
Scoring Procedure
Total score. Reverse score Items 1, 3, 5, 6, 9, 10, 14, 16, 17, 18, 19, 20, and 21; add these reverse scored items with Items 2, 4, 7, 8, 11, 12, 13, and
15; divide this summed total by 21.
Unconditional Permission to Eat subscale. Reverse score Items 1, 5, 9, 14, 18, 19, 20, and 21; add these reverse scored items with Item 4; divide this
summed total by 9.
Eating for Physical Rather Than Emotional Reasons subscale. Reverse score Items 3, 6, 10, 16, and 17; add these reverse scored items with Item 2;
divide this summed total by 6.
Reliance on Internal Hunger/Satiety Cues subscale. Add together Items 7, 8, 11, 12, 13, and 15; divide this summed total by 6.
Note
Item 1 was Item 1 referenced in the article.
Item 2 was Item 2 referenced in the article.
Item 3 was Item 3 referenced in the article.
Item 4 was Item 4 referenced in the article.
Item 5 was Item 5 referenced in the article.
Item 6 was Item 8 referenced in the article.
Item 7 was Item 11 referenced in the article.
Item 8 was Item 12 referenced in the article.
Item 9 was Item 14 referenced in the article.
Item 10 was Item 15 referenced in the article.
Item 11 was Item 16 referenced in the article.
Item 12 was Item 17 referenced in the article.
Item 13 was Item 18 referenced in the article.
Item 14 was Item 19 referenced in the article.
Item 15 was Item 20 referenced in the article.
Item 16 was Item 21 referenced in the article.
Item 17 was Item 22 referenced in the article.
Item 18 was Item 23 referenced in the article.
Item 19 was Item 25 referenced in the article.
Item 20 was Item 26 referenced in the article.
Item 21 was Item 27 referenced in the article.
Permission to use this measure is not required. However, I do request that you notify me via e-mail if you use the Intuitive Eating Scale in your research.
239
INTUITIVE EATING SCALE
(Appendixes continue)
Received April 19, 2005
Revision received August 31, 2005
Accepted September 1, 2005
Appendix B
Descriptive Information for the IES Collapsed Across All Four Samples
Sample MSDSkewness Kurtosis
All women (N1,259)
a
IES—Total 3.26 0.56 0.01 0.11
IES—Unconditional Permission to Eat 3.27 0.86 0.03 0.63
IES—Eating for Physical Reasons 2.90 0.85 0.14 0.55
IES—Reliance on Hunger/Satiety Cues 3.27 0.66 0.02 0.30
Caucasian American women (n1,087)
IES—Total 3.24 0.55 0.03 0.13
IES—Unconditional Permission to Eat 3.25 0.85 0.02 0.57
IES—Eating for Physical Reasons 2.85 0.84 0.12 0.53
IES—Reliance on Hunger/Satiety Cues 3.27 0.66 0.03 0.27
African American women (n68)
IES—Total 3.49 0.59 0.38 0.38
IES—Unconditional Permission to Eat 3.60 0.91 0.37 0.63
IES—Eating for Physical Reasons 3.24 0.90 0.09 0.88
IES—Reliance on Hunger/Satiety Cues 3.35 0.71 0.39 0.73
Asian American women (n41)
IES—Total 3.33 0.66 0.05 0.43
IES—Unconditional Permission to Eat 3.22 0.84 0.22 0.81
IES—Eating for Physical Reasons 3.17 0.93 0.12 0.77
IES—Reliance on Hunger/Satiety Cues 3.07 0.60 0.13 0.45
Multiracial women (n38)
IES—Total 3.41 0.50 0.01 0.94
IES—Unconditional Permission to Eat 3.38 0.82 0.10 1.08
IES—Eating for Physical Reasons 3.24 0.76 0.23 1.01
IES—Reliance on Hunger/Satiety Cues 3.33 0.57 0.05 0.31
Latin American women (n17)
IES—Total 3.36 0.68 0.19 0.55
IES—Unconditional Permission to Eat 3.27 1.12 0.18 1.23
IES—Eating for Physical Reasons 3.19 1.03 0.51 0.97
IES—Reliance on Hunger/Satiety Cues 3.15 0.76 1.25 1.54
Native American women (n8)
IES—Total 3.40 0.64 0.41 1.03
IES—Unconditional Permission to Eat 3.56 0.81 0.24 0.66
IES—Eating for Physical Reasons 3.17 0.82 0.03 1.39
IES—Reliance on Hunger/Satiety Cues 3.40 0.64 1.06 0.64
Note. IES Intuitive Eating Scale.
a
One woman (Study 1) did not indicate her ethnicity.
240 TYLKA
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... However, before directly targeting negative body image (during, for instance, cognitive-behavior interventions), it is suggested to indirectly reduce its influence by targeting other disordered eating symptoms, such as restrictive eating, overeating episodes, and emotional eating Linardon and Mitchell, 2017). Intuitive eating can be defined as having a strong connection with one's own internal signals of hunger and satiety cues, and consequently eating in response to these signals (Tylka, 2006;Messer et al., 2021). Increasing scientific evidence is pointing to the potential positive role of intuitive eating as a protective factor against several eating disorder symptoms such as disordered eating, binge eating, restrictive eating, and unhealthy weight control behaviors (Dockendorff et al., 2012;Hazzard et al., 2020;Christoph et al., 2021;Linardon et al., 2021;Messer et al., 2021;Sanlier et al., 2021). ...
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Intuitive eating (IE) emphasizes relying on hunger and satiety cues to guide eating, and is associated with positive mental health and health-promoting behaviors. Although parents' own eating patterns often shape those of their children, no known research has explored familial associations of IE. The purpose of this cross-sectional, population-based study was to examine IE concordance between emerging adults and their parents, and whether concordance differed across sociodemographic characteristics and weight perceptions. The analytic sample included 891 emerging adults (M age = 22.0) and their primary parent (M age = 50.4) who participated in the population-based, longitudinal EAT and F-EAT 2010-2018 studies. Parents and emerging adults were grouped into dyads based on IE concordance: (1) neither are intuitive eaters; (2) only the emerging adult is an intuitive eater; (3) only the parent is an intuitive eater; (4) both are intuitive eaters. Dyads differed across socioeconomic status (SES), race/ethnicity, and weight perceptions. Concordant dyads who ate intuitively were more likely to be at higher SES and perceive their weight as "about right" than concordant dyads who did not eat intuitively. Asian emerging adults were most likely to belong to concordant non-intuitive eater dyads. Emerging adults who shared their parent's perception their weight was "overweight" were less likely to be intuitive eaters (even if their parents were). In this sample, sociodemographic characteristics and weight perceptions were related to IE concordance among emerging adults and their parents. Lower SES might be an intergenerational barrier to IE disproportionately impacting communities of color, though longitudinal data are needed. Results also suggest rather than motivating healthful eating, perceiving one's weight as "overweight" could hinder IE. Differences across sociodemographic variables likely intersect in meaningful ways, which is an important future research direction.
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Intuitive eating is an adaptive style of eating that has gained substantial research attention. However, possible predictors and outcomes of intuitive eating are poorly understood, as prospective study designs addressing this are missing. Since theoretical research indicates that positive body image might enhance – and be enhanced by – intuitive eating, the present study tested for possible reciprocal associations between three components of positive body image (body appreciation, functionality appreciation, and body image flexibility) and intuitive eating. Adult women (n = 3039) were invited to complete study measures at baseline (T1), four (T2), and eight month (T3) follow-up. Cross-lagged panel analyses were computed to test for possible reciprocal relationships between intuitive eating and positive body image components. Results showed that intuitive eating and both body appreciation and functionality appreciation were reciprocally related. Higher intuitive eating levels at T1 predicted greater increases in these two positive body image components at T2 (and vice versa). Similarly, higher intuitive eating levels at T2 predicted greater increases in these two positive body image components at T3 (and vice versa). Only unidirectional effects were observed between intuitive eating and body image flexibility: higher intuitive eating levels predicted greater increases in body image flexibility at the subsequent time-point. Findings suggest that intuitive eating and certain components of positive body image might serve to enhance each other over time. Intervention strategies designed to cultivate intuitive eating may also result in concomitant improvements in certain indices of positive body image.
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Objective Parents have an important role in their child’s food routines and eating behaviour and face additional demands when that child is an athlete. Yet little is known about how parents manage providing food for their athletic child, in addition to the wider family, within the context of elite-level youth sport. Methods Semi-structured interviews were conducted with sixteen parents (mothers = 11; fathers = 5) of elite level adolescent swimmers (i.e., competing at UK national level or above; child mean age = 15.4 years) to explore their experiences of family food routines and eating behaviour. Reflexive Thematic Analysis was used to analyse the data. Results Parents outlined the importance of ‘optimal’ fuelling for their athletic child. Parents had an active role in their child’s eating behaviour and shaping their food choices but expressed uncertainty regarding the volume of food their child should consume and concerns regarding their child’s future relationship with food. Meticulous organisational and logistical strategies were employed to meet the extensive food requirements of their adolescent elite swimmer in the face of intensive training schedules. Such schedules also impacted food routines for the wider family (i.e., fewer family mealtimes), and on the quality of parents’ own diets. Conclusion The findings highlight that clearer guidance is needed for parents of elite adolescent swimmers in relation to quantities of food intake and how to support a positive future relationship with food (specifically during any periods of transition in their training or out of the sport). The findings also identify a novel organisational stressor for parents in elite youth sport, in managing and prioritising their own diet. Further research is needed to explore the extent to which parental diet may be impacted by supporting an adolescent athlete.
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BACKGROUND: Intuitive eating is defined by eating response to physiological hunger and satiety cues rather than situational or emotional cues and it has been linked to psychological well-being. The 23-item Intuitive Eating Scale-2 (IES-2) is commonly used to assess the concept of intuitive eating. OBJECTIVE: To develop the Greek version of the IES-2 questionnaire and to test its psychometric qualities. METHODS: Forward and backward translations into Greek and English were completed. Exploratory Factor Analysis (EFA) was applied to understand the underlying factor structure of the IES-2, whilst internal consistency was assessed by Cronbach’s alpha test. The concurrent validity was assessed by evaluating the correlation among the IES-2 and the Eating Attitudes Test-26 Item (EAT-26) questionnaire. RESULTS: A total of 379 adults (mean age = 34 years) participated. EFA gave a three-factor structure with the total variance explained being 54.4% . Cronbach’s alpha was 0.87 for the IES-2 total score, as well as 0.90, 0.84 and 0.70 for the IES-2 subscales. The revised IES-2 total score was significantly correlated with EAT-26 total score (rs = –0.46, p < 0.01) and BMI (rs = –0.46, p < 0.01). CONCLUSION: In this sample, the Greek version of the IES-2 showed good psychometric qualities and can be regarded a helpful tool for examining adult intuitive eating behaviours.
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Overweight and obesity are major public health challenges in China, and increasingly among young people. Valid measures are needed to examine the relationship between eating styles and weight to advance understanding and intervention. Mindful approaches show promise in weight management. This study aimed to investigate the psychometric properties of a Chinese version of Mindful Eating Questionnaire (C-MEQ). Study 1 used a think aloud methodology to examine Chinese young adults' (n = 7) and adolescents’ (n = 10) comprehension of C-MEQ items. Findings informed revision of problematic items before a full validation study (Study 2) of the revised C-MEQ (C-MEQ-R) in a sample of 430 Chinese young adults. In Study 1, both groups misinterpreted ten items as asking about noticing about whether behaviour ever occurred rather than noticing experience, indicating the lack of content validity of the C-MEQ. Ten items were rephrased to emphasise mindful (intentional) noticing in the moment. In Study 2, confirmatory factor analysis revealed an inadequate fit to the original MEQ structure. Exploratory Structural Equation Model of the C-MEQ-R revealed five distinct domains. The C-MEQ-R showed better psychometric properties than the C-MEQ, and significant associations with mindfulness, emotional eating, external eating and BMI in expected directions. However, psychometric limitations including low internal reliability, inadequate coherence of the subscales and limited construct validity were identified. These findings contribute to the progress in the measurement of mindful eating by highlighting the weaknesses of the MEQ. Further research is called to adopt and validate alternative mindful eating measurements to assess mindful eating in Chinese adolescents and young adults.
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Body image is multidimensional and less is known about how the combination of positive and negative body image relates to eating behaviors. We used a person-centered approach to identify profiles of body image and explore the relationship between profile membership, sex, age, race, and current marital status, and eating behaviors in a community sample of adults. We recruited 288 adults 18 and older living in the United States using Prolific Academic. Participants completed an online survey assessing body appreciation, functionality appreciation, body dissatisfaction, weight bias internalization, and adaptive and maladaptive eating behaviors. We used latent profile analysis to identify four distinct body image profiles: appreciation & mild dissatisfaction, functional appreciation & moderate dissatisfaction, strong dissatisfaction, and strong appreciation. Profile membership differed by sex with more women and younger adults in profiles higher in negative body image. The relationships between profiles and eating behaviors differed; the three profiles including negative body image had the lowest adaptive and highest maladaptive eating behaviors. The identification of clinically relevant profiles: (1) confirm positive and negative body image coexist, (2) identify high- and low-risk profiles of body image and eating behavior, and (3) offer preliminary suggestions for screening and tailoring preventive interventions.
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This article offers objectification theory as a framework for understanding the experiential consequences of being female in a culture that sexually objectifies the female body. Objectification theory posits that girls and women are typically acculturated to internalize an observer's perspective as a primary view of their physical selves. This perspective on self can lead to habitual body monitoring, which, in turn, can increase women's opportunities for shame and anxiety, reduce opportunities for peak motivational states, and diminish awareness of internal bodily states. Accumulations of such experiences may help account for an array of mental health risks that disproportionately affect women: unipolar depression, sexual dysfunction, and eating disorders. Objectification theory also illuminates why changes in these mental health risks appear to occur in step with life-course changes in the female body.
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We report on the development and preliminary evaluation of a 10-week group program intended to raise women's consciousness about the costs and side effects of dieting and to provide alternatives to strenuous weight loss efforts. Eighteen female participants were assessed on self-esteem, depression, restraint, and eating pathology measures before the sessions began, at the end of the 10-week program, and (for two of the three groups) 6 months after the sessions ended. Subjects also filled out state self-esteem scales each week. By the end of the program participants had significantly higher self-esteem and lower depression, eating pathology, and restraint. Subjects also reported life-style changes accompanying these psychological improvements. We consider the implications for treating dieting and encouraging 'natural eating.'
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This article reports the development and validation of a scale to measure global life satisfaction, the Satisfaction With Life Scale (SWLS). Among the various components of subjective well-being, the SWLS is narrowly focused to assess global life satisfaction and does not tap related constructs such as positive affect or loneliness. The SWLS is shown to have favorable psychometric properties, including high internal consistency and high temporal reliability. Scores on the SWLS correlate moderately to highly with other measures of subjective well-being, and correlate predictably with specific personality characteristics. It is noted that the SWLS is suited for use with different age groups, and other potential uses of the scale are discussed.
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Susceptibility to appearance-related mass media, interpersonal feedback, and instrumentality were compared as predictors of body satisfaction and shape concerns regarding thinness and muscularity in a sample of 287 undergraduate men and women. Results indicate that both genders experience body dissatisfaction, but along different shape dimensions; susceptibility to appearance-related mass media and negative appearance-related feedback appear to operate in similar ways to affect men's and women's overall body satisfaction. Directions for additional research are discussed.