Running Head: MEMORIAL BIAS AS PREDICTOR OF DEPRESSIVE SYMPTOMS
Relation of Depressive Symptoms to Mood-Congruent Memorial Bias in Young
Children: A Longitudinal Study
Kristel Thomassin
Thesis completed in partial fulfillment of the requirements of the Honors Program in
Psychological Sciences
Under the direction of Professor David A. Cole
Vanderbilt University
April 2007
Memorial Bias
2
Abstract
The current study examines whether children show evidence of adult-like
depressive cognitive schemas and when such schemas emerge. Mood-congruent
cognitive schemas have been strongly associated with adult depression (Ingram, 1984;
Ingram et al., 1998). Findings suggest that a processing bias emerges in early childhood
and adolescence (Neshat-Doost et al., 1998; Taylor & Ingram, 1999). The current study
extends the current literature of mood-congruent memorial bias to 5- and 6-year old
children. Controlling for prior depressive symptoms, results indicated that both biased
recall and recognition are significant predictors of depressive symptoms from wave 2 to 3
but not from wave 1 to 2. Our results have narrowed the age range at which we first see
evidence of biased memory and depressive symptoms.
Memorial Bias
3
Relation of Depressive Symptoms to Mood-Congruent Memorial Bias in Young
Children: A Longitudinal Study
Recent research on depression has focused on the underlying mechanisms in an
attempt to address potential risk factors for the development of depressive symptoms.
Derivations of Beck’s (1976) cognitive model of depression have provided a strong
foundation for such investigations. According to Beck (1976), depression can be
characterized by a distorted information processing in which views of the self, world, and
future are negatively biased. Correspondingly, depression in adults is characterized by
negative cognitive schemas and biases that form a cognitive vulnerability to developing
depression. Research on the relationship between affect and cognition derives primarily
from Bower’s (1981) Network Theory of Affect. According to this theory, affective states
influence cognitions through their effect on cognitive processes such as memory. As a
result, affect-consistent information processing is enhanced at both the encoding and
retrieving levels.
In keeping with these models, Ingram has examined the relation of moodcongruent cognitive biases to depressive symptoms (Ingram, 1984; Ingram et al., 1998).
Scher, Ingram, and Segal (2005) argued that cognitive are triggered by the negative mood
associated with naturally occurring negative life events. Laboratory-based mood
inductions provide a useful method to invoke a milder form of a mood that would be
created by a stressful event. Individual differences in the strength of mood-activated
depressive schemas constitute a preexisting cognitive diathesis for the development
depressive symptoms (Segal & Shaw, 1986).
Memorial Bias
4
Support for the relation between such cognitive distortions and depression in
adults is robust. Matt, Vasquez, and Campbell (1992) conducted a meta-analysis of the
published research on mood-congruent recall in normal nondepressed, subclinically
depressed, clinically depressed, experimentally-induced depressed, and experimentallyinduced elated individuals. As hypothesized, nondepressed individuals showed biased
recall in favor of positive stimuli. The pattern of recall for subclinically depressed
persons was not biased. These individuals recalled a more balanced number of positive
and negative stimuli. This pattern of results for nondepressed and subclinically depressed
individuals provides support for the depressive realism phenomenon, which states that
depressed individuals are more realistic in their view of the world whereas nondepressed
individuals tend to show a positive bias (Alloy & Abramson, 1988; Greenberg et al.,
1988; Matt et al., 1992). In comparison to non-depressed and subclinically depressed
individuals, individuals whose depression was severe enough to warrant a diagnosis
showed biased recall in factor of negative stimuli.
Investigators have attempted to apply adult models of cognitive distortion and
bias to younger children (Kendall et al., 1990; Murray et al., 2001; Neshat-Doost, 1998;
Whitman & Leitenberg, 1990). When applying any adult cognitive model to a child
population, it is critical to consider developmental differences that may influence the
development and very nature of depression in children and adults. Although some
investigators acknowledge this fact (Cicchetti & Schneider-Rosen, 1986; Rutter, 1986),
others tend to minimize these differences (Whitman & Leitenberg, 1990). Even if some
level of continuity exists between youth and adult models of cognitive distortions despite
important cognitive developmental differences, it remains essential to consider these
Memorial Bias
5
differences and not simply rely on adult models when examining mood-congruent
memorial biases in children. The development of new developmentally appropriate childbased cognitive models is necessary to more adequately characterize the relation of
cognitive distortions to depressive symptoms.
Overall, findings from the relevant literature on biased memory in children is
inconclusive, and the role of memorial biases as a cognitive vulnerability to developing
depressive symptoms has not yet been entirely explained. Neshat-Doost et al. (1988)
investigated whether there is a memorial bias for clinically depressed children and
adolescents between the ages of 10 and 17. They hypothesized that when compared to
nondepressed individuals, clinically depressed participants would show a negative bias in
recall. The investigators presented the participants with 60 words and asked them to write
down as many words as they could remember. Results supported their hypothesis that
depressed children would show a bias in recall in favor of negative trait adjectives, and
this bias was stronger in older, depressed children. These findings show evidence of a
negative mood-congruent memorial bias in depressed adolescents.
Similarly, Whitman and Leitenberg (1990) investigated the relation between
memorial bias and depressive mood in 52 fourth-, fifth-, and sixth-grade students. They
presented the participants with a word association task and provided each participant with
artificial feedback on whether their association was “correct” or “incorrect” (Whitman &
Leitenberg. 1990). Research assistants also asked children to recall which association
they had made correctly. The investigators hypothesized that all children would show
differential recall of information. Depressed children would overestimate the amount of
negative feedback and underestimate positive feedback, and nondepressed children would
Memorial Bias
6
underestimate the amount of negative feedback and overestimate the amount of positive
feedback. Although their findings revealed no difference between the depressed and
nondepressed participants in the recall of negative feedback, they did find a difference in
the recall of positive feedback. Nondepressed children recalled more positive events than
their depressed counterparts (Whitman & Leitenberg, 1990). These findings support
evidence of mood-congruent memorial bias in nondepressed children, but they fail to
support a negative bias in recall in depressed children.
These inconsistencies may be explained partly by methodological limitations
(Kendall et al., 1990). For example, some studies have relied on parents’ ratings of
children’s depressive symptoms (Fuhrman & Kendall, 1986). The parent questionaires
rely on second party observations of perceptible symptoms and therefore do not paint a
full picture of an individual’s depressive symptoms. A second limitation is the use of
word lists to assess distorted cognitions. Word lists are often developmentally
inappropriate in their content and structure, relying on advanced levels of cognitive
processing. Perhaps more reliable findings will require the use of more developmentally
appropriate and meaningful stimuli to test for cognitive distortions and biased processing
(Murray et al., 2001). Both of these limitations can be inadequate in measuring children’s
depressive symptoms and distorted processing. The present study attempts to resolve the
first issue by using a self-report measure of depressive symptoms. To address the second
limitation, this study utilized a children’s story instead of mere word lists, thus presenting
the children with a more engaging stimulus.
Do children show evidence of adult-like depressive cognitive schemas, and if so,
when do such schemas emerge? Cole and colleagues found evidence of a relation
Memorial Bias
7
between mood-congruent cognitive bias and depression in 8- to 12-year old children
(Cole & Jordan, 1995; Prieto, Cole, & Tageson, 1992). Furthermore, findings suggest that
the onset of processing biases occurs in childhood and adolescence (Neshat-Doost et al.,
1998; Taylor & Ingram, 1999). Much less research on depression in preschool age
children has been conducted, and existing studies with children in this age group have yet
to include an assessment of mood-congruent memorial bias. To our knowledge, no
findings have conclusively shown mood-congruent memorial biases relating to
depressive symptoms for children younger that 8-years-old. The current study therefore
extends the investigation of mood-congruent memorial bias to 5- and 6-year old children.
Evidence for cognitive distortions in childhood and early adolescence is
inconsistent and evidence for such distortions in the preschool years is lacking. Murray et
al. (2001) suggest that this lack of evidence stems from the fact that such negative
schemas are latent and require an induced mood in order to be activated and expressed.
The investigators base their hypothesis on similar findings in the adult literature. They
further comment that negative self-distortions in preschool children may be more
dependent on induced mood than in older children. Several studies have provided
significant results to support this hypothesis (Taylor & Ingram, 1999; Kelvin, Goodyer,
Teasdale, & Brechin 1999). In light of these findings, and in keeping with Ingram’s work,
we decided to use a negative mood induction prior to assessing cognitive distortions in
young children.
The current study examines whether there is evidence for a mood-congruent
memorial bias in young children, and whether this bias favors positive or negative
stimuli. To avoid the problematic use of meaningless stimuli, the present study presents
Memorial Bias
8
the participants with a children’s story about one child’s day. As Murray et al. (2001)
explain, the use of the story, a more engaging stimulus, will allow for the spontaneous
appearance of cognitions. Our study attempts to examine both recall and recognition in
order to narrow down the level at which processing is affected. In comparison to recall,
recognition requires fewer processes since what is being remembered is present. Recall,
on the other hand, requires more processes with respect to retrieval. By examining moodcongruent memorial biases in kindergarten to second grade children, which is a younger
age group than previously studied, the current study will help to identify when the
relation between depressive schemas and mood in children first evolve. Essentially, this
research attempts to examine the developmental origins of cognitive processes that may
predispose later clinical depression.
Using a variety of measures of memory including recall and recognition, we
expected to see evidence of a negative mood-congruent memorial bias in both incidental
recall and recognition paradigms. We further posited that this memorial bias would in
turn serve as a cognitive vulnerability to the development of depressive symptoms. In
fact, we hypothesized that a bias in memory would be a significant predictor of
depressive symptoms.
Methods
This study is part of a larger, longitudinal investigation of the developmental
origins of depressive cognitions in children. Participants were recruited at the start of the
2003-2004 academic year. Participants were in kindergarten at the beginning of the study
and participated in three waves of data collection (with one year separating adjacent
Memorial Bias
9
waves). Thus we collected data in kindergarten, first grade, and second grade. Parents
and students actively provided their consent for participation in the study.
Participants
Participating children consisted of a single cohort of elementary school students
recruited from two public schools from predominantly lower and working class
neighborhoods in a mid-sized southern city. Not all participants were available for every
wave of data collection. Each year we lost participants, primarily due to their moving out
of the school district. Therefore, we recruited new participants at the end of each wave to
offset this attrition. Initially, in wave I, 97 students participated in the study. Of these, 29
withdrew before the start of wave II, and 34 new students joined. Before the third wave,
41 students withdrew and 21 new students joined. Essentially, 31.6% of the initial
participants dropped from the investigation prior to the last wave. To offset the effects of
attrition, we redistributed consent forms to parents to recruit more students.
Approximately 22% of the participants in the total sample (n = 158) were added to the
study after wave I. Three participants’ data were eventually dropped because of
equipment malfunction. With attrition and re-sampling, the sample sizes for waves 1, 2,
and 3 were 97, 102, and 91, respectively. In comparison to those that completed the
studies, there were no significant differences between those that attritted and joined.
Over all waves, the sample was 48% male and 52% female. The average age of
the children was 5.4 years (SD = 0.56), 6.6 (SD = 0.59), and 7.4 (SD = 0.56) for waves 1,
2, and 3, respectively. The sample was racially diverse, including students who were
African American (60.9%), Caucasian (34.1%), Hispanic (2.5%), and multiethnic (2.5%).
The number of children living in participants’ homes ranged from 1 to 7, with a mean of
Memorial Bias 10
2.45 (SD = 1.2). Approximately 30% of the children had at least one parent who was
currently or previously divorced. Parent education levels ranged from 8th grade or lower
to some education after bachelor’s degree, with the majority of parents reporting they had
completed high school or passed the high school equivalency test. Annual family income
ranged from less that $10,000 to $120,000 (Mdn = $20,000).
Measures
Self-report measure of depressive symptom. The Children's Depression Inventory
(CDI; Kovacs, 1981, 1982) is a widely used 27-item self-report instrument that assesses
cognitive, affective, and behavioral symptoms of depression in children. Each item
consists of three statements graded in order of increasing severity from 0 to 2. Children
select one sentence from each group that best describes themselves for the past two
weeks (e.g., 0 = “I am sad once in a while,” 1 = “I am sad many times,” 2 = “I am sad all
the time”). In the current study, we treated this measure as an interview. A research
assistant read each item and participants answered either verbally or by pointing to their
response. Total scores range from 0 to 54 with total scores of 19 or greater considered to
be indicative of significant levels of depressive symptoms (Kendall et al., 1990). In
nonclinic populations, the measure has relatively high levels of internal consistency, testretest reliability, predictive, convergent, and construct validity (Blumberg & Izard, 1986;
Carey, Faulstich, Gresham, Ruggiero, & Enyart, 1987; Kazdin, French, & Unis, 1983;
Lobovits & Handal, 1985; Mattison, Handford, Kales, Goodman, & McLaughlin, 1990;
Saylor, Finch, Spirito, & Bennett, 1984; Smucker, Craighead, Craighead, & Green,
1986). In the current study, the suicide item was dropped due to concerns by school
administration. This 26-item questionnaire has shown a high degree of internal
Memorial Bias 11
consistency in previous research (Cronbach's alpha = .89: Cole & Jordan, 1994).
Cronbach’s alpha for the CDI in the current study was .77 for wave I, .85 for wave II, and
.90 for wave III.
Priming story/task. Prior to the memory task, the researcher first presented the
participant with a story, which was intended to induce negative affect. The components
of the priming story were quite similar for all waves, although the details differed each
year. For the first wave, the kindergarteners were told a story of a child of the same
gender and age as themselves whose puppy had run away. Then, the character’s parents
told them that they would all be moving somewhere far away and cold, and that they had
to say goodbye to all her friends and had to start a new school next year. For the second
wave, the story was about a child who had broken a leg and could not play his/her
favorite sport anymore. The participants in the third wave were told a story about a child
who had his birthday party canceled because they had been bad and their mom was angry
at them. The child in the story had to return all the presents and clean the house instead.
To personalize the story, participants were asked if anything similar had ever happened to
them, and they were allowed to elaborate.
Memory task. The memory task for this study tested the participants’ uncued and
cued recall of events in a story. The story was created by the researchers especially for
this study. An illustrated picture book described the activities of an elementary-age and
gender-neutral child named Ollie. The events of the story are categorized into 3 types:
positive, negative, and neutral. Different stories were created each year in order to avoid
any effects of previous exposure. Each story contained the same number of positive and
negative events. During the first wave, the participants were told a story about Ollie’s
Memorial Bias 12
school day. In the second wave, participants were told a story about Ollie’s Saturday at
home. In the third wave, the participants were told a story about Ollie’s class fieldtrip to
the zoo. During each story, Ollie experienced 13 positive events (e.g., Ollie got an ice
cream cone), 13 negative events (e.g., Ollie got bit by a mosquito), and 10 neutral events
(e.g., They saw elephants). Researchers administered the task individually to each
participant by reading the story out loud while the child looked at the illustrated booklet.
The priming story as well as the memory task was videotaped.
Coding of uncued recall. After reading the story, the researcher removed the
illustrated booklet and asked the participants what they remembered from Ollie’s day.
Each event was recorded at the time of the data collection. The researcher asked on two
different occasions if the child could remember anything else. At a later date, trained
research assistants reviewed the videotapes and coded each event on a scale of 1 to 3 (1 =
negative, 2 = neutral, 3 = positive). Any fabricated response (i.e. a recalled event that
was not in the story) was also noted and rated. In an effort to note the quick and effortless
recall of each participant, the researcher recorded the first three events the child
spontaneously recalled. Inter-rater reliability correlation were examined for 30% of the
tapes and were found to be .90 for positive events, .85 for neutral events, and .95 for
negative events.
Coding of cued recall. When the participant could no longer freely recall any
additional events from the story, the research assistant showed the child the illustrations.
The research assistant walked the participants through the story page-by-page asking the
children what they remembered from each illustration. These responses were noted as
cued recall or recognition. At a later date, these items were rated (negative, neutral, or
Memorial Bias 13
positive) as well as any fabricated responses. Inter-rater reliability based on 30% was .90
for positive events, .85 for neutral events, and .95 for negative events.
Derived measures. Several measures were computed in order to assess memorial
bias. For our recall paradigm, we constructed a difference score (DIFREC) to represent
biased recall (i.e., the number of positive items minus the number of negative items
recalled). With respect to the first three items recalled, we computed a ratio (RANEG),
which represented the proportion of the first three items recalled that were of negative
valence. Lastly, we constructed a difference score (DIFREG) to represent biased
recognition (i.e., the number of positive items recognized minus the number of negative
items recognized).
Procedure
Graduate and advanced undergraduate research assistants received extensive
training on proper experimental procedures and were tested on expected criteria prior to
their first data collection. Data were collected at the child’s school during the
nonacademic portion of their regular school day. The current study involves measures
from a larger battery administered to participants during a one-hour session. This subset
of measures took approximately 30 minutes to administer. Upon arrival, research
assistants retrieved the participants from their classrooms one at a time. After these
measures, the video camera was set up to record the remainder of the session. Research
assistants told the priming story and presented the participants with the memory task. For
their participation, children were given decorative pencils, stickers, and candy.
Results
Preliminary Analyses
Memorial Bias 14
Descriptive statistics for the study measures are shown in Table 1. The mean
scores for the CDI at each wave were elevated in comparison to scores in previous
research with nonreferred school samples (Cole et al., 1998; Cole, Hoffman, Tram, &
Maxwell, 2000). This may have been due to the fact that we read the CDI aloud to these
children, possibly reducing their tendency to slip into either a nay-saying or a social
desirability response set. It could also be because of the urban, high-poverty environment.
As expected, participant scores on the recognition measures were considerably higher
than scores on the recall measures. Intercorrelations between the memory measures and
self-report measures of depressive symptoms are provided in Table 2.
Recall Performance
We conducted a series of linear regression analyses to investigate whether biased
memory is a significant predictor of later depressive symptoms. In the first regression, we
used a difference score (DIFREC) to represent biased recall. Thus, a positive difference
score indicates a positive recall bias whereas a negative difference score indicates a
negative recall bias. We regressed CDI scores at one wave onto DIFREC at a prior wave,
while controlling for prior CDI scores (see Table 3). Results revealed that DIFREC at
wave 1 significantly predicted CDI score at wave 3 while controlling for CDI scores at
wave 1. These results were significant in the expected direction. A positive memorial
bias at wave 1 predicted lower scores on the CDI at wave 3. We found the same pattern
of results between wave 2 and wave 3 with positive memorial bias in wave 2 predicting
CDI scores in wave 3. The regression of wave 2 CDI onto wave 1 DIFREC, however,
was not significant, after controlling for wave 1 CDI scores.
Memorial Bias 15
In the second set of regressions, we focused on the first three items recalled.
Specifically, we constructed a negative ratio measure (RANEG), which represented the
ratio of the first three recalled items that were of negative valence. Again, we regressed
CDI scores onto prior RANEG scores, while controlling for prior CDI scores (see Table
4). Results revealed that RANEG at wave 2 significantly predicted CDI scores at wave 3,
controlling for CDI at wave 2. This result was in the expected direction such that a more
negative memorial bias was associated with higher scores on the CDI at wave 3. RANEG
scores at wave 1, however, did not significantly predict CDI scores at either wave 2 or 3.
Recognition Performance
We also conducted linear regression analyses in order to examine whether biased
recognition is a significant predictor of later depressive symptoms. Similar to the
difference in recall analyses, we used a difference score (DIFREG) to represent biased
recognition. We regressed CDI scores at each wave onto DIFREG at the prior wave,
controlling for prior CDI scores (see Table 5). Results revealed that DIFREG at wave 2
significantly predicted CDI score at wave 3. These results were significant in the
expected direction with a positive memorial bias predicting lower scores on the CDI.
DIFREG scores at wave 1 did not significantly predict CDI scores at either wave 2 or 3.
Discussion
Four major results derived from this study. First, results indicated a significant
relation between biased recall and depressive symptoms. Essentially, a positive bias in
recall was a significant predictor of lower depressive symptoms. Second, a negative bias
with respect to the first three items recalled was a significant predictor of higher
depressive symptoms one year later. Third, a positive bias in recognition was also a
Memorial Bias 16
significant predictor of lower depressive symptoms one year later. Lastly, a longitudinal
relation between depressive symptoms and biased memory was evident between waves 2
and 3 (i.e, 1st and 2nd grade) of our study but not between in waves 1 and 2 (i.e.,
kindergarten and 1st grade). Each of these findings is discussed more completely below.
The results of the recall portion of the memory task showed that participants who
exhibited a positive bias in recall in kindergarten and first grade reported lower selfreported depressive symptoms in second grade. This supports the previous finding that
children’s positively biased recall distinguishes depressed from nondepressed individuals
(Taylor & Ingram, 1999; Whitman & Leitenberg, 1990). Findings suggest that there is
evidence of negative mood-congruent memorial bias, and that this bias is a preexisting
vulnerability to developing depressive symptoms one and two years later.
Next, similar to the results of previous studies (Neshat-Doost, 1998), we found a
negative bias in recall. More specifically, first graders’ negatively biased recall of the
first three items predicted higher self-reported depressive symptoms in second grade. In
order to make sure that automatic and spontaneous recall would be assessed, we noted the
first three items that each participant spontaneously recalled. We posited that this would
assess the participants’ free recall before their use of various memorial strategies. The
significance of our results reinforces the aforementioned findings with the recall measure.
Results were not significant from kindergarten to 2nd grade as they were in the recall
measure.
Looking at the recognition portion of the memory task, we found that positively
biased recognition in the first grade predicted lower levels of self-reported depressive
symptoms in second grade. These findings suggest that distortions in memory processing
Memorial Bias 17
also occur at the encoding level. In comparison to biased recall, however, biased
recognition in kindergarten was not a significant predictor of depressive symptoms in
second grade. Our findings suggest that biased recognition is also a significant cognitive
vulnerability to developing depressive symptoms one year later.
According to the Network Theory of Affect (Bower, 1981), the processing of
information in accordance with affective mood is enhanced at both the encoding and
retrieving levels. The significant results with respect to our incidental recall paradigm
does not isolate a certain level of processing. Adding the recognition paradigm suggests
that encoding cannot be ruled out and is likely affected by mood. Furthermore, retrieval
cannot be simply ruled out thus warranting further examination.
With respect to our main hypothesis, the significance of recall and recognition as
predictors of depressive symptoms is present from wave 2 to 3 but not from wave 1 to 2.
These results suggest that memory-related cognitive distortions arise as significant
predictors of depressive symptoms prior to the age of 8 in children in first and second
grade but not in kindergartens. These are noteworthy findings for two reasons: first, our
findings show the existence of mood-congruent memorial bias in much younger children
than those previously studied. Second, results of our study have narrowed the age range
at which we first see evidence of biased memory and depressive symptoms. Our findings
show that the relation between mood-congruent memorial bias and depressive symptoms
could arise in children as young as 6.
Various shortcomings in the current study suggest avenues for future research.
First, due to developmental limitations, young children have more difficulty with selfreflection (Murray et al., 2001). Children this young may have difficulty appropriately
Memorial Bias 18
reporting depressive symptoms, especially if it requires reporting on the previous two
weeks as does the CDI. Furthermore, children tend to focus on the here and now and may
have a somewhat limited capacity for reporting past symptoms. The current study
attempted to minimize this limitation by reading each CDI item to individual participants,
but this does not address the issue of whether or not the participants comprehend the task.
Perhaps the self-report measure of depressive symptoms should be administered in an
unstructured interview format in order to yield a more accurate measure of depressive
symptoms. Secondly, as Murray et al. comment, memorial biases may only be evident
when a low mood is induced. With this in mind, it is important to note the implications of
using a mood induction. The efficacy of our priming story in inducing such a mood is not
clear. The story was constructed to fit all participants and was not geared towards each
child. This universal story might be a problem when considering that it is necessary to
activate negative schemas. Perhaps the priming story would be more effective if it were
modified for each participant. Furthermore, the valence of each event in the story was
determined by our investigators and therefore might not be perceived in the same manner
by our participants. Lastly, the current study focused on nonreferred children taken from
local schools. As a result, the application of these results to clinic-referred youth with
clinically diagnosed depression in unclear. Perhaps our current results would be amplified
in a clinical population. Further research should therefore examine the application of our
results to a clinically depressed sample. Taken together, however, our findings are
consistent with a causal relation between negative mood-congruent memorial biases and
depressive symptoms.
Memorial Bias 19
Table 1
Means and Standard Deviations for Memory Measures and Self-Report Measure of
Depressive Symptoms for Each Wave
Measure
N
Mean
Std.
Deviation
Minimum
Maximum
Wave 1
CDI
95
11.91
6.77
0.00
28.00
Total Recall
93
8.46
5.50
0.00
25.00
Total Recognition
93
19.85
5.56
5.00
33.00
Diff in Recall
91
-0.08
0.34
-1.00
0.67
Diff in Recognition
93
0.06
0.11
-0.40
0.38
Negative Ratio
89
0.55
0.40
0.00
1.00
Wave 2
CDI
101
15.70
10.98
0.00
41.00
Total Recall
100
9.43
5.30
0.00
25.00
Total Recognition
100
20.87
4.92
9.00
33.00
Diff in Recall
98
-0.13
0.29
-1.00
0.50
Diff in Recognition
100
0.02
0.11
-0.40
0.33
Negative Ratio
97
0.50
0.39
0.00
1.00
Wave 3
CDI
90
10.20
7.39
0.00
34.32
Total Recall
87
8.78
4.71
0.00
21.00
Total Recognition
87
20.85
4.58
9.00
34.00
Diff in Recall
86
-0.33
0.22
-1.00
0.00
Diff in Recognition
87
-0.28
0.11
-0.59
0.00
Negative Ratio
87
0.44
0.40
0.00
1.00
Note. CDI = Children’s Depression Inventory. Diff in Recall = the difference between the
number of positive items recalled and the number of negative items recalled. Diff in
Recognition = the difference between number of positive items recognized and the
number of negative items recognized. Negative Ratio = the proportion of the first three
items recalled that were of negative valence.
Memorial Bias 20
Table 2
Intercorrelations between Memory Measures and Self-Report Measures of Depressive Symptoms
Measure
1
2
3
4
5
6
7
8
9
10
11
12
Wave I
1. DIFREC
1
2. RANEG
-.250*
1
3. DIFREG
.086
-.042
1
4. CDI
.016
.034
.116
1
5. DIFREC
.096
-.122
-.083
.015
1
6. RANEG
.037
.014
.124
.073
-.461**
1
7. DIFREG
.495**
-.333**
.297*
.069
.116
-.084
1
.021
-.155
.128
.297*
-.125
.188
.025
1
9. DIFREC
.251
-.165
-.052
.158
.072
.212
-.051
.064
1
10. RANEG
.095
.074
-.113
-.146
-.086
-.053
.071
-.095
-.527**
1
11. DIFREG
.231
-.122
.237
.206
.140
-.017
.192
.158
.263*
-.195
1
-.296*
.227
-.081
.460**
-.339**
.359**
-.346**
.306*
-.035
-.028
.034
Wave II
8. CDI
Wave III
12. CDI
1
Note. ** p< .01; * p< .05 CDI = Children’s Depressive Inventory; DIFREC = difference in recall; RANEG = ratio of negative items
out of the three first remembered; DIFREG = difference in recognition.
Memorial Bias 21
Table 3
Longitudinal Regressions of CDI onto Biased Recall (difference between positive and
negative items recalled) controlling for prior CDI.
Predictors
B
SE
Beta
t
sig.
3.22
0.002
DV = CDI at Wave 2
Intercept
9.02
2.80
CDI at wave 1
0.50
0.20
0.30
2.45
0.017
Difference of items recalled
at wave 1
-0.68
3.52
-0.02
-0.19
0.847
1.68
0.100
DV = CDI at Wave 3
Intercept
2.95
1.75
CDI at wave 1
0.39
0.12
0.41
3.18
0.003
Difference of items recalled
at wave 1
-5.51
2.22
-0.32
-2.49
0.017
4.29
0.000
DV = CDI at Wave 3
Intercept
5.44
1.27
CDI at wave 2
0.18
0.07
0.31
2.62
0.011
Difference of items recalled
at wave 2
-6.77
2.59
-0.31
-2.62
0.011
Note. CDI = Children’s Depression Inventory. Diff in Recall = the difference between the
number of positive items recalled and the number of negative items recalled. Diff in
Recognition = the difference between number of positive items recognized and the
number of negative items recognized. Negative Ratio = the proportion of the first three
items recalled that were of negative valence.
Memorial Bias 22
Table 4
Longitudinal Regressions of CDI onto Ratio of Negative Items Recalled out of the Total
of First Three Items Recalled controlling for prior CDI.
Predictors
B
SE
Beta
t
sig.
3.60
0.001
DV = CDI at Wave 2
Intercept
11.88
3.33
CDI at wave 1
0.45
0.20
0.28
2.28
0.026
Ratio of negative items
recalled at wave 1
-4.77
3.23
-0.18
-1.48
0.145
0.37
0.714
DV = CDI at Wave 3
Intercept
0.94
2.56
CDI at wave 1
0.48
0.15
0.43
3.11
0.003
Ratio of negative items
recalled at wave 1
3.37
2.53
0.18
1.33
0.190
2.80
0.007
DV = CDI at Wave 3
Intercept
4.12
1.47
CDI at wave 2
0.14
0.07
0.25
2.03
0.047
Ratio of negative items
recalled at wave 2
4.93
2.19
0.28
2.25
0.028
Note. CDI = Children’s Depression Inventory. Diff in Recall = the difference between the
number of positive items recalled and the number of negative items recalled. Diff in
Recognition = the difference between number of positive items recognized and the
number of negative items recognized. Negative Ratio = the proportion of the first three
items recalled that were of negative valence.
Memorial Bias 23
Table 5
Longitudinal Regressions of CDI onto Biased Recognition (difference between positive
and negative items recognized) Controlling for Prior CDI.
Predictors
B
SE
Beta
t
sig.
3.48
0.001
DV = CDI at Wave 2
Intercept
9.33
2.68
CDI at wave 1
0.45
0.20
0.29
2.30
0.025
Difference of items
recognized at wave 1
3.95
11.51
0.04
0.34
0.733
1.62
0.113
DV = CDI at Wave 3
Intercept
3.11
1.92
CDI at wave 1
0.51
0.14
0.49
3.71
0.001
Difference of items
recognized at wave 1
-9.49
7.49
-0.17
-1.27
0.212
4.80
0.000
DV = CDI at Wave 3
Intercept
6.51
1.36
CDI at wave 2
0.20
0.07
0.32
2.87
0.006
-21.61
6.70
-.36
-3.22
0.002
Difference of items
recognized at wave 2
Note. CDI = Children’s Depression Inventory. Diff in Recall = the difference between the
number of positive items recalled and the number of negative items recalled. Diff in
Recognition = the difference between number of positive items recognized and the
number of negative items recognized. Negative Ratio = the proportion of the first three
items recalled that were of negative valence.
Memorial Bias 24
References
Alloy, L.B., & Abramson, L.Y. (1988). Depressive realism: Four theoretical perspectives.
Cognitive processes in depression. New York: Guilford.
Beck, A.T. (1976). Cognitive therapy and the emotional disorders. Madison, CT:
International Universities Press.
Blumberg, S.H. & Izard, C.E. (1988). Discriminating patterns of emotions in 10- and
11 yr-old children's anxiety and depression. Journal of Personality and Social
Psychology, 51 (4), 852-857.
Bower, G.H. (1981). Mood and Memory. American Psychologist, 36, 129-148.
Carey, M.P., Faulstich, M.E., Gresham, F.M., & Ruggiero, L. (1987). Children's
Depression Inventory: Construct and discriminant validity across clinical and
nonreferred (control) populations. Journal of Consulting and Clinical Psychology,
55 (5), 755-761.
Cicchetti, D., & Schneider-Rosen, K. (1986). An organizational approach to childhood
depression. In M. Rutter, C.E. Izard, & P.B. Read (Eds.), Depression in young
people: Clinical and developmental perspectives. (pp. 71-134). New York:
Guilford.
Cole, D.A. & Jordan, A.E. (1995). Competence and memory: integrating psychosocial
and cognitive correlates of child depression. Child Development, 66, 459-473.
Cole, D. A., Martin, J. M., Peeke, L. G., Seroczynski, A. D., Hoffman, K. (1998). Are
cognitive errors of underestimation predictive of reflective of depressive
symptoms in children: A longitudinal study. Journal of Abnormal Psychology,
107, 481-496.
Memorial Bias 25
Cole, D. A., Hoffman, K., Tram, M., Maxwell, S. E. (2000). Structural differences in
parent and child reports of children’s symptoms of depression and anxiety.
Psychological Assessment, 12, 174-185.
Fuhrman, M.J. & Kendall, P.C. (1986). Cognitive tempo and behavioral adjustment in
children. Cognitive Therapy and Research, 10, 45-50.
Goodman, S.H., & Gotlib, I.H. (1999). Risk for psychopathology in the children of
depressed mothers: A developmental model for understanding mechanisms of
transmission. Psychological Review, 106, 58-490.
Gotlib, I.H., & Hammen, C.L. (1992). Psychological aspects of depression: toward a
cognitive-interpersonal integration. New York: John Wiley & Sons.
Greenberg, M.S., Vasquez, C., & Alloy, L.B. (1988). Depression versus anxiety:
Differences in self- and other-schemata. In L. B. Alloy (Ed.), Cognitive processes
in depression (pp. 109-142). New York: Guilford
Ingram, R. (1984). Towards an information processing analysis of depression. Cognitive
Therapy and Research, 8, 443–478.
Ingram, R., Miranda, J., & Segal, Z.V. (1998). Cognitive vulnerability to depression.
NewYork: Guilford.
Kazdin, A.E., French, N.H., & Unis, A.S. (1983). Child, mother, and father evaluations
of depression in psychiatric inpatient children. Journal of Abnormal Child
Psychology, 11 (2), 167-180.
Kelvin, R.G., Goodyer, I.M., Teasdale, J.D., & Brechin, D. (1999). Latent negative self
schema and high emotionality in well adolescents at risk for psychopathology.
Journal of Abnormal Child Psychology, 40, 959-968.
Memorial Bias 26
Kendall, P.C., Stark, K.D., Adam, T. (1990). Cognitive deficit or cognitive distortion in
childhood depression. Journal of Abnormal Child Psychology, 18, 255-270.
Lobovits, D.A. & Handal, P.J. (1985). Childhood depression: Prevalence using DSM-III
criteria and validity of parent and child depression scales. Journal of Pediatric
Psychology, 10 (1), 45-54.
Matt, G.E., Vazquez, C., & Campbell, K. (1992). Mood-congruent recall of affectively
toned stimuli: a meta-analytic review. Clinical Psychology Review, 12, 227-255.
Mattison, R.E., Handford, H.A, Kales, H.C., & Goodman, A.L. (1990). Four-year
predictive value of the Children's Depression Inventory. Psychological
Assessment, 2 (2), 169-174.
Murray, L., Woolgar, M., & Cooper, P. (2001). Cognitive vulnerability to depression in
5-year-old children of depressed mothers. Journal of Child Psychology and
Psychiatry 42, 891-899.
Neshat-Doost, H.T., Taghavi, M.R., Moradi, A.R., Yule, W., & Dalgleish, T. (1998).
Memory for emotional trait adjectives in clinically depressed youth. Journal of
Abnormal Psychology, 107, 642-650.
Prieto, S.L., Cole, D.A., & Tageson, C.W. (1992). Depressive self-schemas in clinic and
nonclinic children. Cognitive Therapy and Research, 16, 521-534.
Rutter, M. (1986). The developmental psychopathology of depression : Issues and
perspectives. In M. Rutter, C.E. Izard, & P.B. Read (Eds.), Depression in young
people: Clinical and developmental perspectives. (pp. 3-30). New York: Guilford.
Saylor, C.F., Finch, A.J., Spririto, A., & Bennett, B. (1984). The Children's Depression
Memorial Bias 27
Inventory: A systematic evaluation of psychometric properties. Journal of
Consulting and Clinical Psychology, 52 (6), 955-967.
Scher, C. D., Ingram, R. E., & Segal, Z. V. (2005). Cognitive reactivity and vulnerability:
Empirical evaluation of construct activation and cognitive diatheses in unipolar
depression. Clinical Psychology Review, 25, 487-510.
Segal, Z. V., & Shaw, B. F. (1986). Cognition in depression: A reappraisal of Coyne and
Gotlib’s Critique. Cognitive Therapy and Research, 10, 671-694.
Smucker, M.R., Craighead, W.E., Craighead, L.W., & Green, B.J. (1986). Normative and
reliability data for the Children's Depression Inventory. Journal of Abnormal
Child Psychology, 14 (1), 25-39.
Taylor, L. & Ingram, R.E. (1999). Cognitive reactivity and depressotypic information
processing in children of depressed mothers. Journal of Abnormal Psychology,
108, 202-210.
Whitman, P.B. & Leitenberg, H. (1990). Negatively biased recall in children with selfreported symptoms of depression. Journal of Abnormal Child Psychology, 18,
15-27.