International Journal of Obesity (1999) 23, 231±237
ß 1999 Stockton Press All rights reserved 0307±0565/99 $12.00
http://www.stockton-press.co.uk/ijo
Cognitive appraisals of dietary transgressions
by obese women: Associations with selfreported eating behavior, depression, and
actual weight loss
CF Smith, PM O'Neil and SK Rhodes
Weight Management Center, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston,
South Carolina 29425, USA
OBJECTIVE: To identify three groups of obese people entering weight loss treatment, who have distinctly different
cognitive appraisals of dietary transgressions and to compare these groups on self-report inventories of eating
patterns, dieting, and depression, as well as on treatment completion rates and weight loss.
DESIGN: Retrospective review of clinical records. Using a measure which evaluates eating-related cognitive
appraisals, participants were categorized into one of three cognitive groups (All-or-None, Rationalization, Matterof-Degree).
SUBJECTS: 289 treatment-seeking obese women (age: 40.9 y, body mass index (BMI): 34.7 kg=m2).
MEASUREMENTS: Self-reported eating and dieting behavior (Three-Factor Eating Questionnaire and Eating Behavior
Inventory); depression (Beck Depression Inventory); attendance information and body weight obtained during
treatment.
RESULTS: The cognitive group representing objective thinkers (Matter-of-Degree) reported signi®cantly fewer
problems with overeating and more personal control over eating than did the rigid, dichotomous thinkers (All-orNone). In addition, the Matter-of-Degree (MAT) group endorsed signi®cantly less subjective hunger and fewer
depressive symptoms than the other two cognitive groups. The Rationalization group was more likely to complete
a treatment program than was the All-or-None group, with the MAT group not differing from either. Despite these
®ndings, there were no signi®cant differences among cognitive groups on total weight loss.
CONCLUSIONS: Cognitive appraisals of weight-control lapses appear to be associated with self-reported eating
behavior, depressive symptoms and treatment completion rates, but not with treatment-induced weight loss. The
relationship between long-term weight loss and cognitive appraisals of dieting lapses is yet to be determined. It
appears necessary to assess empirically the validity of assumptions regarding factors associated with treatment
outcome.
Keywords: dietary relapse; cognitive appraisals; eating behavior; weight loss treatment
Introduction
Weight management is a life-long enterprise which
requires behavior change concerning eating. The
relapse prevention model for long-term behavior
change efforts proposes that encountering high-risk
situations and occasional resultant behavioral setbacks
is an expected feature of the change process.1 With
regard to weight control, high risk situations and
subsequent dieting lapses are quite common. Theoretically, lapses may be more common in weight control
than in other addictive disorders, such as alcohol or
nicotine dependence, because one cannot be totally
abstinent from food. Researchers have suggested that
the way in which one reacts to a dietary transgression
greatly affects one's future eating behavior.1 ± 3 Both
Correspondence: Dr Cheryl Smith, Western Psychiatric Institute
and Clinic, 3811 O'Hara Street, Pittsburgh, PA 15213, USA.
Received 6 May 1998; revised 20 August 1998; accepted 21
August 1998
cognitive and behavioral coping strategies have been
found to be effective in preventing a `total' relapse.4,5
Dieters perceive dieting violations in various ways,
ranging from insigni®cant occurrences to catastrophic
events.6 It is believed that overly negative appraisals
of dietary transgressions can lead to guilt and other
negative emotions which may increase the likelihood
of overeating during future high risk situations.1,2
Conversely, objective, quantitative cognitive appraisals of episodes of unplanned eating or overeating,
that neither magnify nor minimize the importance of
an incident, may make subsequent overeating less
likely.1
Evidence supporting this hypothesis is limited and
indirect, but suggestive. Obese binge eaters have more
maladaptive dieting-related attitudes and are more
likely to drop out of treatment than obese nonbinge
eaters.7,8 In an investigation of Marlatt and Gordon's
Abstinence Violation Effect1 in binge eaters, researchers found that cognitive reactions such as all-or-none
thinking (on a diet vs off a diet), internality and guilt,
but not negative affect, were predictors of future binge
Dietary transgressions
C Smith et al
232
eating episodes.2 Furthermore, all-or-none thinking
has been found to be a trigger for the binge-purge
cycle observed in patients with bulimia nervosa.9
It could be hypothesized that obese patients in
weight control programs, who have negative cognitive
appraisals of dieting violations, will lose less weight
and be more likely to drop out of treatment. To our
knowledge, this hypothesis has not been directly
studied. However, a handful of investigations have
examined related cognitive factors within the setting
of weight loss treatment.
Drapkin et al 10 investigated dieters' cognitions in
response to hypothetical high-risk situations and
found that participants who generated more potential
coping responses lost more weight in a behavioral
weight control program. Another study of the Abstinence Violation Effect among patients enrolled in a
very low calorie diet program found that subjects who
made more self-blaming attributions for lapses lost
less weight and spent less time in treatment.11
Eating self-ef®cacy, that is, con®dence in one's
ability to cope effectively with dif®cult food-related
situations, is another cognitive factor related to weight
control. Researchers have found that high scores on a
measure of eating self-ef®cacy predicted weight loss
in individuals who completed behavioral treatment
programs.12 Additionally, an increase in self-ef®cacy
scores over the course of weight loss treatment was
observed in this study. In another investigation of a
similar construct, scores on a measure of weight
control competence were found to be predictors of
weight loss.13
Apart from the above studies, little else is known
about the role of cognitive factors in successful and
unsuccessful weight control. The purpose of the present study was to test the hypothesis that cognitive
appraisals of dieting transgressions predict outcome of
weight loss treatment and are related to eating behavior and affective state. Obese female weight loss
participants were categorized as typifying one of three
distinct patterns of cognitive appraisals: All-or-None
(ALL; dichotomous, `black and white' thinking, perfectionism vs failure), Rationalizing (RAT; retroactively excusing dieting slips) and Matter-of-Degree
(MAT; taking into account the magnitude of the
dieting lapse). It was predicted that participants who
appraise dietary mishaps in a quantitative manner
(MAT) would have better completion rates, achieve
greater weight loss, and report more adaptive eating
patterns compared to the ALL and RAT cognitive
groups.
Methods
Subjects
Clinical records of 615 patients who participated in
either of two comprehensive weight loss treatment
programs between 1984 and 1993, and who had
completed a clinical assessment battery prior to entering a weight control program, were reviewed retrospectively. Of this initial sample, 356 subjects met
inclusion criteria for this study (as described below).
Since there were only 67 male participants (83% of
whom belonged to the MAT cognitive group), their
data were excluded from the analyses. The remaining
female subjects (n ˆ 289) were enrolled in one of two
behavioral weight control programs, a very low calorie diet (VLCD) 30-week program using liquid
supplements (n ˆ 148) or a low calorie diet (LCD)
20-week program utilizing everyday foods (n ˆ 141).
Criteria for entering the treatment programs differed
in that participants wishing to participate in the VLCD
had a body mass index (BMI) > 30. Both treatment
programs emphasized nutrition education, increased
physical activity and behavior change, using a weekly
group format which remained relatively constant over
the period during which data were collected, with the
exception of updating the content when appropriate.
The sample was predominantly Caucasian (93.8%),
and the mean age s.d. of participants was
40.9 12.0 y. Mean age at onset of weight problem
was 19.8 11.9 y. The mean BMI of the sample
before beginning a treatment program was
34.7 7.4 kg=m2. Approximately one half (55%) of
the participants were married.
Measures
Thoughts About Eating Inventory (TAEI).6 The
TAEI describes 10 hypothetical situations during
which a dietary transgression occurs. Table 1 contains
an example of a TAEI item. Following the situation
description, three self-statements which represent distinct cognitive appraisals of the incident are presented.
One choice represents a maladaptive, rigid way of
thinking referred to as All-or-None thinking (ALL).
Another type of appraisal, Rationalization (RAT),
offers an excuse for overeating, thereby denying the
impact of the transgression on weight control efforts.
The third type of cognitive response is indicative of a
Table 1
Item
Example of a Thoughts About Eating Inventory (TAEI)
``You are at a large cocktail party at a friend's house. Everyone is
laughing and having a good time. Your hostess knows that you
have been trying to lose weight and thus avoids asking you to try
the hors d'oeuvres. Your other friends are all eating and
drinking. Though no one presses you to try the food, you
begin snacking and eat and drink throughout the evening.''
The following choices are given:
1. ``I must have gained pounds tonight. Guess I've blown the
diet.'' (All-or-None)
2. ``So I overdid it by a few hundred calories ± I'll start back on
my diet right now!'' (Matter-of-Degree)
3. ``Well, I certainly didn't want to appear rude; I don't get invited
to that many parties.'' (Rationalization)
Dietary transgressions
C Smith et al
more objective appraisal referred to as Matter-ofDegree thinking (MAT), which evaluates the magnitude of the `slip' from an implicitly quantitative
perspective, without overgeneralizing or discounting
the importance of the event in terms of weight
management.6
Respondents are instructed to rank the statements in
order from their most likely response (1) to their least
likely response (3). For purposes of categorizing
subjects in this study, a score for each type of
cognitive appraisal was determined by counting the
number of TAEI items for which that type of appraisal
was rated as number 1. Thus, scores for each type of
cognitive appraisal could range from 0 ± 10.
Although internal consistency for the TAEI was not
reported originally, multivariate analyses have
revealed that none of the 10 items elicited a signi®cantly different response pattern.6 In the current study,
we found the internal consistency of the TAEI to be
adequate (Kuder-Richardson 20, r ˆ 0.70) by scoring
items dichotomously (MAT response ˆ 1 and the
other two responses ˆ 0).
The TAEI was designed to have a high degree of
face validity in that items obviously elicit different
cognitive appraisals. Paine6 reported that obese treatment-seekers endorse signi®cantly more ALL statements than non-obese controls and that nonclinical
obese controls endorsed signi®cantly more MAT
statements than did obese treatment-seekers. Additionally, patients with bulimia nervosa have been
found to score signi®cantly higher on the ALL scale
when compared to non-obese controls.14
Three-Factor Eating Questionnaire (TFEQ).15 The
TFEQ is a factorially derived self-report inventory
containing three factors: Dietary Restraint, Disinhibition and Perceived Hunger. The Dietary Restraint
scale has been reported consistently to measure
restrictive eating.16,17 The Disinhibition scale evaluates the breaking of dietary restraint, as well as selfreported overeating independent of restrained
eating.18 ± 20 The Perceived Hunger factor is purported
to measure subjective hunger.15 Numerous studies
have corroborated the validity and factor structure of
the TFEQ.16,21
Eating Behavior Inventory (EBI).22 The EBI
assesses three aspects of eating from the standpoint
of weight control: Personal Control of Eating, Attention to Weight and Eating, and Use of Stimulus
Control, derived from factor analysis.23 Test-retest
reliability, internal consistency and concurrent validity for this questionnaire have been established.22
Beck Depression Inventory (BDI).24 The BDI was
used to assess depressive symptoms. This measure's
reliability and validity have been established.25 Only
61% of subjects completed the BDI; however, the
administration of this measure varied over the time
period sampled, but was not based on differences in
eating-related cognitions or other participant
characteristics.
Program completion. Program completion was
determined from clinical record and was de®ned as
continued attendance for at least 80% of the treatment
program (16 weeks for the LCD 20 week program
and 24 weeks for the VLCD 30 week program), with
limited absences during the period of attendance.
Weight loss. Weight loss was measured as the difference between initial body weight and last weight
obtained. Weight change was expressed as kg lost,
change in BMI and percentage of body weight lost.
Subject selection
The inclusion criterion for being in one of the cognitive groups was scoring 5 on only one of the TAEI
cognitive style categories, that is, selecting a particular type of statement for at least ®ve out of the 10
items. The reason for this criterion was to ensure that
groups comprised individuals who had a predominant
style of cognitive appraisal of dietary transgressions,
rather than a combination of two or more styles. Of
the 615 initial participants, 356 could be categorized
using this criteria. Males (19%) were removed, leaving 289 women, with 48 categorized as RAT, 50 as
ALL and 191 as MAT. For the RAT group, the mean
number of Rationalization statements endorsed was
6.3 0.2 (r ˆ 5 ± 9). The mean number of All-or-None
statements ranked ®rst for the ALL group was
6.4 0.2 (r ˆ 5 ± 9). Participants in the MAT group,
on average endorsed 7.6 0.1 Matter-of-Degree statements (r ˆ 5 ± 10).
Statistics
Statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS) for
Windows 95 version 7.5.26 Group differences on
descriptive data (age, BMI, age at onset of weight
problem) were examined using a 3 (cognitive
group) 2 (treatment program) multivariate analysis
of variance (MANOVA). Based on the results of this
MANOVA, subsequent analyses were performed
using age at onset of weight problem as a covariate.
Cognitive groups were compared on factor scores of
self-report measures of eating patterns using a MANCOVA. Cognitive group differences on BDI performance were examined with an ANCOVA. Weight
change variables (kg lost, BMI lost, percent body
weight lost) among cognitive groups were compared
within each treatment group separately (LCD and
VLCD) using MANCOVAs. When MANCOVAs
were signi®cant, analyses were followed by univariate
tests and then pairwise comparisons with Bonferroni
correction at the P < 0.003 level of signi®cance.
233
Dietary transgressions
C Smith et al
234
Nonparametric statistics (that is, chi-square) were
used to analyze categorical data. Data are means and
adjusted means s.e.m. unless otherwise speci®ed.
Results
Proportions of participants in each cognitive style
group were not signi®cantly different across the two
treatment programs (X2 ˆ 2.13, P ˆ 0.35). There were
no differences in BMI or age among cognitive groups.
Age at onset of weight problem was signi®cantly later
for the MAT group (21.7 1.1 y) compared to the
ALL group (14.6 1.3 y; P < 0.001), with the RAT
group falling intermediately (18.4 1.5 y). Thus, age
at onset was treated as a covariate in subsequent
analyses.
Participants in the VLCD program had an earlier
onset of weight problem (17.5 1.0 y) than participants in the LCD program (19.8 0.8 y; P < 0.001).
They also had a signi®cantly larger BMI prior to
treatment (38.4 0.6) than participants in the LCD
program (30.5 0.5; P < 0.001). This difference was
expected due to differences in treatment program
criteria; therefore, BMI was not treated as a covariate
in subsequent analyses. There were no signi®cant
differences in age between treatment programs.
Analyses involving self-report measures
The MANCOVA performed on individual factor
scores of the EBI and TFEQ was signi®cant
(Pillias ˆ 0.196, F(12,390) ˆ 3.54, P < 0.001), and
univariate and posthoc comparisons found signi®cant
differences between cognitive groups on three of the
six factors. Speci®cally, the MAT group scored signi®cantly lower on the TFEQ's Disinhibition scale
and signi®cantly higher on the EBI's Personal Control
of Eating factor, than did the ALL group
(P's < 0.003). In addition, MAT participants scored
signi®cantly lower (P < 0.003) on the TFEQ's Perceived Hunger factor compared to both the ALL and
RAT groups. On the BDI, a signi®cant ANCOVA,
Table 2
groups
Scores on self-report measures for three cognitive
TFEQ1: Dietary restraint
TFEQ2: Disinhibition
TFEQ3: Perceived hunger
EBI1: Personal control
EBI2: Attention to weight
EBI3: Stimulus control
BDI
Rationalization
All-orNone
Matter-ofDegree
9.3 0.7a
11.8 0.6ab
8.9 0.6a
20.9 0.8ab
15.4 0.9a
15.3 0.8a
10.9 1.2a
9.1 0.7a
13.2 0.6a
9.0 0.7a
17.9 0.9a
13.4 0.9a
13.7 0.9a
13.9 1.3a
10.1 0.3a
10.6 0.3b
6.2 0.3b
22.5 0.4b
15.0 0.5a
14.9 0.4a
6.0 0.7b
Data are adjusted means s.e.m. from a MANCOVA with age at
onset of weight problem treated as a covariate. Means with the
same superscripts do not differ (P > 0.003). TFEQ ˆ Three-Factor
Eating Questionnaire; EBI ˆ Eating Behavior Inventory;
BDI ˆ Beck Depression Inventory. n ˆ 203 in all cases except for
BDI (n ˆ 176).
Figure 1 Percentage of subjects in the cognitive groups who
completed 80% of either treatment program. The Rationalization (RAT) group differed signi®cantly from the All-or-None (ALL)
and Matter-of-Degree (MAT) groups (P's < 0.05). However, differ-
F(3,133) ˆ 13.3, P < 0.001, followed by pairwise
comparisons, found that the MAT group scored signi®cantly lower than did both the ALL and RAT
groups (P's < 0.003). The RAT and ALL groups did
not differ signi®cantly from each other on any of the
self-report inventories (P's > 0.05). Data are illustrated in Table 2.
Analyses involving treatment outcome variables
Of all participants, 55% completed a treatment program. Overall, completion rates among cognitive
groups were signi®cantly different (X2 ˆ 7.8,
P < 0.05). Pairwise comparisons revealed that more
RAT participants (70%) completed a treatment program, than MAT (55%) and ALL (42%) participants
(P's < 0.05). Figure 1 illustrates these data. With
regard to completion rates within the individual treatment programs, chi-square analyses approached signi®cance for both the LCD (P ˆ 0.06) and VLCD
programs (P ˆ 0.08). Examining each of the treatment
programs separately, visual inspection showed a pattern similar to the overall results with more RAT than
ALL participants completing treatment.
MANCOVAs performed on the weight change
variable (body weight lost, BMI lost and percent
body weight lost), were conducted separately for
each treatment program, due to different program
entry criteria and to known differences in average
weight losses for LCDs and VLCDs.27 Table 3 illustrates these data. No signi®cant differences among
cognitive groups were found for the LCD treatment
program (Pillias ˆ 0.076, F(6,186) ˆ 1.2, P ˆ 0.30).
However, the MANCOVA performed on these
variables in the VLCD program neared signi®cance (Pillias ˆ 0.118, F (6,204) ˆ 2.1, P ˆ 0.052).
Univariate tests and pairwise comparisons revealed
Dietary transgressions
C Smith et al
Table 3
235
Weight loss variables of three cognitive groups for two treatment programs
LCD
n
Weight lost (kg)
BMI lost (kg/m2 )
Body weight lost (%)
VLCD
RAT
ALL
MAT
RAT
ALL
MAT
15
4.1 1.2
1.5 0.4
5.2 1.4
18
5.0 1.1
1.8 0.4
5.4 1.3
65
3.9 0.6
1.4 0.2
4.8 0.7
21
20.8 1.9
7.6 0.7
20.5 1.6
19
15.2 2.0
5.7 0.7
15.5 1.7
67
16.7 1.1
6.1 0.4
15.4 0.9
Data are adjusted means s.e.m. from MANCOVAs with age at onset of weight problem treated as a covariate. There were no
signi®cant differences among cognitive groups in either treatment program (P's > 0.05). Data based on all subjects whether they
completed treatment or not. LCD ˆ low calorie diet; VLCD ˆ very low calorie diet; BMI ˆ body mass index; RAT ˆ Rationalization;
ALL ˆ All-or-None; MAT ˆ Matter-of-Degree.
differences among groups on percent body weight lost
(P ˆ 0.02), indicating that the RAT group lost a
greater percentage of body weight than did the other
two cognitive groups. Differences on the other two
weight variables were not signi®cant (P's > 0.05).
When the sample was limited to program completers
(n ˆ 159), no signi®cant differences between cognitive groups were found for either treatment program
(LCD; Pillias ˆ 0.098, F(6,104) ˆ 0.89, P ˆ 0.50, and
VLCD; Pillias ˆ 0.136, F(6,108) ˆ 1.3, P ˆ 0.26).
Discussion
The current study found that obese women who
appraise dietary lapses objectively are less likely to
break their diet and overeat, and more likely to feel in
control of eating-related situations than obese women
who have rigid and dichotomous appraisals of dietary
transgressions. Additionally, obese women who view
dieting lapses more objectively experience less
reported hunger compared to dieters who either catastrophize or rationalize such dietary mishaps. These
®ndings suggest that there is a relationship between
cognitive reactions to dietary slips and other weightrelated factors, such as decreased overeating,
decreased subjective hunger and increased self-control
during eating. Thus, partial support for this study's
hypothesis was found in that scores obtained by the
MAT participants on cognitive and behavioral measures were indicative of effective weight control.
These results are similar to previous studies of dieters
and binge eaters, that found associations between dietrelated cognitive reactions and eating behavior.2,5
The RAT group was more likely than the ALL
group to complete treatment, with the MAT group
falling intermediately and not differing from either.
This is contrary to the hypothesis that MAT participants would be more likely to complete a program. A
possible explanation for this ®nding is that individuals
who make up excuses for dietary transgressions
(RAT) may have less negative reactions (for example,
guilt) to eating lapses and thus may be more likely to
attend weight control groups, even when they are not
losing weight. Indirect support for this explanation
may be based on the fact that even though more RAT
subjects completed a treatment program, they did not
lose more weight than the other cognitive groups
when analyses were limited to treatment completers.
Despite cognitive group differences on self-report
measures and completion rate, the groups did not
differ on actual weight loss, particularly when analyses were limited to treatment completers. This was
not surprising, given the failure of numerous studies to
®nd reliable psychological predictors of weight loss in
formal programs.28 However, the differences that did
emerge on the self-report measures re¯ected factors
thought to be facilitative of weight loss success, and in
the case of the TFEQ, included scales previously
found to be predictive of treatment outcome. LaPorte
and Stunkard3 found that factor scores on the TFEQ,
particularly on the hunger scale, predicted treatment
adherence and attrition. The current study found
differences among cognitive groups on hunger and
disinhibition, but not on dietary restraint.
One possible reason for the lack of an association
between cognitive group and actual weight loss may
be insuf®cient statistical power. If a larger sample was
used, particularly of treatment completers, such an
association may have been found. The cutoff used as
the inclusion criterion for being in one of the three
cognitive groups (5 out of 10 items) was chosen to
obtain the maximum number of subjects per group,
while ensuring that each participant endorsed one
predominant cognitive style. It is likely that there
would have been more subjects per group if a lower
cutoff was used, although the results would have been
dif®cult to interpret, due to the fact that some of
subjects would have endorsed their `predominant'
cognitive style on fewer than half of the items.
Alternatively, if a higher cutoff was used, the differences between cognitive groups on weight loss may
have been more robust; however, the sample size
would have been smaller, thus compromising statistical power.
Another explanation for the lack of differences in
weight loss is that perhaps cognitive factors play a
more important role in weight loss maintenance. Thus,
the possibility still remains that cognitive appraisals of
dietary transgressions may affect one's long-term
success in maintaining weight loss.1 For example,
Marcus et al 8 found that binge eaters, who differed
Dietary transgressions
C Smith et al
236
signi®cantly from non-binge eaters on a measure of
unrealistic dietary rules, Cognitive Factors Scale,29
did not lose less weight during a 10 week behavioral
weight loss treatment; however, binge eaters regained
signi®cantly more weight at six-month follow-up.
It should be noted that cognitive style as de®ned
here is not necessarily a ®xed trait, particularly among
patients in weight loss programs. It is possible that
over the course of weight loss treatment, eatingrelated cognitive styles were modi®ed, especially
since a component of the weight loss treatment was
to target maladaptive cognitions related to eating and
to encourage MAT thinking. Additionally, investigations of other self-report measures such as the TFEQ
and the EBI (both used in this study) have found
signi®cant changes in scores over the course of weight
loss treatment.23,30 On the other hand, a study of obese
binge eaters found that scores on a measure of eatingrelated cognitions remained stable across a 10 week
behavioral weight control treatment and over a one
year follow-up, indicating the stability of cognitive
style on a measure similar to the TAEI.8 Future
studies aimed at examining the TAEI's test-retest
reliability could help clarify this issue.
There were signi®cant differences among cognitive
groups on the age at onset of weight problem, with
MAT subjects reporting a later age than ALL participants. In fact, ALL participants reported juvenile
onset of weight problem (14.6 y), whereas MAT
subjects' onset occurred in adulthood (21.7 y). Age
at onset of weight problems has been found to be
associated with weight-related cognitive and behavioral measures.31 Additionally, Counts and
Adams32 found that a history of childhood obesity
led normal weight adults to overestimate body size.
Indeed, in the present study, analyses that did not
control for age at onset of weight problem found many
more signi®cant differences among cognitive groups
than did the covariance analyses. Notably, the differences reported here persisted after covariance analyses and were thus not simply spurious re¯ections of
different ages at onset.
Perhaps a more important issue is the possibility
that age at onset of weight problems may in¯uence
cognitive style of appraising dietary transgressions.
Price et al 33 found that the onset of obesity prior to
the age of 10 y signi®cantly increased the risk of
obesity among ®rst degree relatives, suggesting a
possible genetic in¯uence. Given this, it is possible
that certain individuals with a biological predisposition to gain weight may have a greater problem
controlling their weight, and may develop rigid and
pessimistic thoughts concerning dieting, as a result of
experiencing more dieting failures during important
periods of development. Additionally, given that ALL
participants had an earlier age of onset but did not
differ in current age, they had a longer exposure to
weight problems and thus had more time to develop
maladaptive cognitive appraisals of eating-related
situations. Firm conclusions about the nature of this
relationship cannot be made given the correlational
nature of the current data.
Not only did cognitive groups differ on measures of
weight-related cognitions and behaviors, they also
differed on a measure of depression, with the MAT
subjects endorsing signi®cantly fewer depressive
symptoms than RAT and ALL subjects. These results
are similar to previous ®ndings on the TAEI and BDI
with bulimic patients, in which bulimics differed
signi®cantly from controls on both measures, indicating a greater intensity of both depression and negative
cognitions related to eating.14 One interpretation
might be that cognitive style differences are due to
differences in depressive symptoms. Clearly, the ALL
cognitive style resembles well-documented cognitive
features of depression such as dichotomous thinking.34 The explanation for the RAT difference, however, is not apparent. It should be stressed that none of
the cognitive groups' average scores were above the
subclinical range on the BDI.
Generalization of the ®ndings of this study was
limited by subject selection procedures used. First,
only females were studied. Second, a large proportion
of the original participants (42%) were excluded from
the study based on the inclusion criterion of endorsing
primarily one out of three cognitive styles. This was
by design, as we wished in this initial study to focus
on patients who had a clearly predominant cognitive
style. Future studies should include groups of patients
with mixed cognitive styles.
One may argue that the main group differences
primarily re¯ect shared method variance. That is,
groups were delineated based on scores on a selfreport measure and the greatest number of differences
were found on self-report inventories. A few differences were found on completion rates, a behavioral
measure, and none were found on weight loss variables, physiological measures. Future studies should
use multi-trait, multi-method assessment of cognitive
style, such as gathering cognitive and behavioral
coping responses through self-monitoring. In addition,
a laboratory setting could be used to study the effect
of eating-related cognitive appraisals on actual eating
behavior.
Conclusion
Our initial hypotheses shared the overriding assumption that the MAT cognitive style was more adaptive
than the other two cognitive styles. Was this assumption warranted? On the one hand, MAT was associated with less reported disinhibited eating, more
personal control over eating and less subjective
hunger. MAT participants also reported fewer depressive symptoms than the other two cognitive groups.
However, none of this was re¯ected in treatment
outcome as measured by completion rate and actual
Dietary transgressions
C Smith et al
weight loss. Perhaps the most important conclusion is
that there is a need to assess empirically the validity of
assumptions regarding factors associated with treatment outcome. What the present study does demonstrate is that a characteristic response to dieting slips
may re¯ect a constellation of salient weight-related
tendencies. For example, if a person is rigid and
dichotomous in appraisal of a dietary transgression,
then they are also likely to experience increased
hunger and disinhibition, exert less personal control
over eating and be more dysphoric. All of these
factors may be of clinical signi®cance regarding
their associations with weight loss.
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