University of Southern California Dissertations and Theses

Memory, gender, and rumination in depression: recall of simulated situations with articulated thoughts and the Rivermead behavioral memory test

(USC Thesis Other)

Memory, gender, and rumination in depression: recall of simulated situations with articulated thoughts and the Rivermead behavioral memory test

PDF

Download a page range

Download transcript

Copy asset link

Request this asset

Transcript (if available)

Content

MEMORY, GENDER, AND RUMINATION IN DEPRESSION: RECALL
OF SIMULATED SITUATIONS WITH ARTICULATED THOUGHTS
AND THE RIVERMEAD BEHAVIORAL MEMORY TEST

by

Kean Jia Jiann Hsu
____________________________________________________________________

A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements of the Degree
MASTER OF ARTS
(PSYCHOLOGY)

May 2009

Copyright 2009 Kean Jia Jiann Hsu

ii
ACKNOWLEDGEMENTS
I would like to sincerely thank the members of my committee: Dr. Davison, Dr.
Knight, and Dr. Walsh for their dedicated support, encouragement, guidance, and helpful
input throughout this project.
I would also like to think my dedicated team of research assistants and my study
coordinator, Phil Ehret, for their energy and effort in helping me complete this study.

iii
TABLE OF CONTENTS
Acknowledgements ii

List of Tables v

Abstract vi

Chapter 1: Introduction 1
Rumination 11

Chapter 2: Methods 14
Overview 14
Participants 15
ATSS Phase 15
Assessment Packet 17
Rivermead Behavioral Memory Test 19

Chapter 3: Results 21
Sample Characteristics 21
Recall Coding 22
Correlations Between Independent Variables and Covariates 24
Correlations Between Dependent Measures 25
Primary Aim Association Between Depressed/Non-Depressed
Individuals and Memory 27
Secondary Aim: Associations Between Depression Severity,
Rumination and Performance on Memory Measures 29
Secondary Aim: Associations Between Gender, Depression
Severity, Rumination, and Performance on Memory Measures 29
Statistical Power 30

Discussion 31

Conclusions 40

References 41

Appendix A: ATSS Scenarios 48
Appendix B: State Rumination Questionnaire 50
Appendix C: CES-D Scale 52
Appendix D: Rumination Responses Scale 54

iv
Appendix E: Negative Mood Regulation Scale 56
Appendix F: Background Demographics Questionnaire 59

v
LIST OF TABLES
Table 1: Complete Sample Characteristics 22
Table 2: Correlation Between Sample Characteristics and Memory
Measure Scores 23
Table 3: Subject Demographics (Female vs. Male 24
Table 4: Subject Demographics (Non-Depressed vs. Depressed 24
Table 5: Inter-Rater Reliability for Transcript Coding of Details 25
Table 6: Correlation Between Independent Variables and Covariates 26
Table 7: Correlation Between Dependent Variables 28
Table 8: Results of Canonical Regression for Depression Severity
and Rumination on Recall 30
Table 9: Results of Canonical Regression for Depression Severity,
Rumination, and Sex on ATSS Recall and RBMT Performance 30

vi
ABSTRACT
Although research on depression and memory has been varied, examining
depression related to impairment of recall as well as facilitated recall of negative
information, few studies have sought to examine both phenomena in the same
experimental framework.
In this study, we used an Articulated Thoughts in Simulated Situations (ATSS)
paradigm as a vehicle for testing recall in order to investigate what factors may play a
role in the relationship between depression and memory. ATSS scenarios of different
valences were presented to 67 subjects for response and subsequent recall along with a
memory battery and other questionnaires. Depressed individuals displayed no
differences in recall on the variety of memory measures compared to non-depressed
participants. These findings add to the body of mixed results regarding how depression
affects memory, highlighting the need for more fine-grained examination of potential
moderators of the relationship between depression and memory.

1
Chapter 1: INTRODUCTION

The burden of mental disorders belies a need for extensive and sustained
research to understand the mechanisms behind mental disorders and how to
successfully prevent and treat them. In particular, depression is a serious and
significant burden in a variety of ways: affecting a substantial number of people within
their lifetime, increasing risk of suicide, and creating an economic burden on the
person as well as those around them (Davidson et al., 2002). By gaining a better
understanding of precisely how memory might be affected by depression, we can
theorize how cognitions might be influenced by this altered pattern of recall. For
example, general impairments in memory could result in reduced self-efficacy and
reinforcement of a negative self-image, similar to the results suggesting that socially
anxious individuals have poorer memory for aspects of the social environment (such
as interpersonal information; Bond & Omar, 1990; Hope, Heimberg, & Klein, 1990,
Kimble & Zehr, 1982). Mood congruent memory could lead to more negative
attributional styles and Beckian biases (negative thoughts about the self, world, and
the future) through increased recall of negatively valenced information and/or
decreased recall of positively valenced information, particularly concerning oneself. If
memory was altered in both ways in a depressed individual, these changes could lead
to more prolonged and severe bouts of depression compared to individuals with only
one type of alteration in recall. In addition, by exploring the relationship between
depression and memory, we can improve our knowledge of depressive

2
symptomatology and how depression might be manifested. In particular, there could
be a gender difference in depression manifestation, with alterations in memory
(including increased recall of negatively-valenced information or a general deficiency
in memory) as one difference in symptomatology. While some studies have suggested
gender differences in the clinical presentation of depression (Bennett, Ambrosini,
Kudes, Metz, & Rabinovich, 2005; Gorman, 2006), others found no such differences
(Bogner & Gallo, 2004; Hildebrandt, Stage, & Kragh-Soerensen, 2003; Young,
Scheftner, Fawcett, & Klerman, 1990). However, none of these studies to our
knowledge examined memory within the context of gender differences in depression
symptomatology.
Mood congruent memory has been studied as an intersection between mood
and memory. Mood congruent memory refers to when subjects are in a particular
mood state, material of that valence or mood is more easily recalled. Although the
majority of research on mood congruent memory compares depressed or dysphoric
subjects to non-depressed/dysphoric subjects, a few studies have examined this
phenomenon in normal populations. A study by Forgas & Moylan (1987) found that
responses to questions of judgment relating to politics, the future, responsibility and
guilt, and quality of life were all significantly influenced by the affective quality of a
film just seen (happy, sad or aggressive). In an analysis of normal subjects over three
studies, Mayer, McCormick, & Strong (1995) found strong evidence for mood
congruent memory. Bower, Gilligan & Monteiro (1981) found that subjects better

3
identified and had better recall of characters in a story with the same mood as the
subject.
To address findings that exhibited mood-incongruent memory, Rusting &
DeHart (2000) tested the memory of undergraduate students in a series of studies that
involved negative mood induction followed by a mood-regulation strategy task and
then a memory task. To conceptually replicate the findings over different procedures,
the investigators used different forms of mood induction (induction through short
vignettes or idiographic (personal memory) recall of a very unhappy time in his/her
life) in the different studies as well as different forms of memory testing (free recall or
autobiographical memory recall). In addition to these tasks, Rusting & DeHart
included a measure assessing how much subjects regulated their mood as a personality
variable. They suggested that the instances of mood-incongruent memory were related
to the level of mood regulation an individual utilizes.
They found that when subjects used a positive reappraisal mood-regulation
strategy, they showed a mood-incongruency effect for memory (recalling more
positive words than negative words after a negative mood induction). Similarly, when
subjects used a continued negative focus mood-regulation strategy, they showed a
mood congruency effect. As predicted, subjects who rated higher on the negative
mood regulation scale had higher levels of mood incongruency than subjects with low
levels of negative mood regulation, especially on the continued negative focus mood-
regulation strategy condition in the studies. These findings further support the notion

4
of mood congruent memory and help provide a possible reason for discrepant studies
in the literature.
Fiedler, Nickel, Muehlfriede, and Unkelbach (2001) elaborated on the research
into mood congruent memory by using signal detection theory to test if mood
congruent memory was a genuine memory phenomenon or whether it was a response
bias. Subjects listened to a series of stimulus verbs then received a positive, negative,
or neutral mood induction by use of emotional films. Subsequently participants were
tested on the stimulus verbs by discriminating them from semantically matched
distractor verbs. By comparing the correct number of hits to “false alarms” (when a
subject indicated a distracter verb had been given previously), signal detection theory
could determine whether mood congruent memory was directly related to memory (hit
rate exceeding false alarm rate for mood-congruent conditions) or was a form of
response bias (high rates of both hits and false alarms in the mood-congruent
condition). The study found strong support for mood congruent memory as a genuine
phenomenon of memory rather than as a form of response bias.
Depression is an exceedingly common disorder with a 17% lifetime prevalence
rate (higher than any other individual DSM disorder) and an annual prevalence rate
(the percentage of people experiencing depression within the span of a year) of 10%
(Kessler et al., 1994). Major depression is also deadly, as people with depression are
11 times more likely to attempt suicide (Davila & Daley, 2000). Furthermore,
depression is burdensome, with an estimated economic burden in 2000 of 83.1 billion

5
dollars between direct treatment costs, suicide-related costs, and workplace costs
(Greenberg et al., 2003). These points highlight the significant impact of depression on
daily life for many people, including those without the disorder, and the need to gain a
better understanding of depression in order to more effectively prevent and treat it.
Unfortunately, depression is a complicated disorder with multiple suspected
etiologies and consequently a number of different theoretical approaches to
understanding it. These different approaches range from developmental theories such
as temperament vulnerabilities, to neurobiological approaches that examine brain
structures and neurochemistry, to cognitive and behavior approaches that consider
negative biases, diathesis-stress, and learned helplessness (Davidson et al., 2002).
Although each approach has empirical support for understanding depression, there has
been no integrative model of depression that incorporates all of the findings to provide
a complete picture of the disorder. To further complicate our understanding of
depression, there is a strong sex-difference in depression prevalence that arises during
adolescence (Nolen-Hoeksema, 1987). The female-to-male ratio for depression is 2:1,
classified both by diagnosis and those with a severe level of symptoms. The sex
difference in prevalence of depression also has multiple etiological theories, most of
which fail to fully account for the empirical findings. The presence of rumination, put
forth by Susan Nolen-Hoeksema, has been one of the more accepted theories to
explain the sex differences seen between men and women in depression. Rumination
is the process of thinking about how sad/apathetic/tired one feels, wondering about the

6
causes of one’s depressive symptoms, and worrying about symptom implications
without doing anything actively constructive to relieve the symptoms or improve on
one’s mood. Ruminative tendencies have been associated with prolonged and more
severe symptoms of depression and more episodes of depression (Nolen-Hoeksema,
2000). The combination of rumination, chronic strain, and low mastery was found by
Nolen-Hoeksema et al. to mediate the gender difference in depressive symptoms,
providing support for rumination’s role in the gender differences in depression.
Changes in memory have been strongly connected to depression as well. A
meta-analysis by Burt, Zembar, & Niederehe (1995) found that depression is
significantly associated with memory impairment. Memory impairment was found in
both recall and recognition tasks, suggesting impairment of explicit and implicit
memory, respectively. The meta-analysis found that in particular there was reduced
memory for positive stimuli. In addition, in tasks requiring increased cognitive effort
depressed subjects exhibited decreased memory abilities compared to non-depressed
subjects. The results imply that depression interferes with cognitive functioning and
can hinder processes important to normal memory function.
Within the context of mood congruent memory, depression has been associated
with mood congruency in a number of different tasks. Mood congruent memory bias
was found in subjects on a cued recall task for a word list, with depressed subjects
(diagnosed with dysthymia or major depression) recalling significantly more
depressed words than control subjects, who recalled more positive words than

7
depressed subjects (Watkins, Mathews, Williamson, & Fuller, 1992). In the same
study, mood congruent memory was not found on the implicit memory task of word
completion. Mood congruent memory bias was found to be specific to information that
was congruent with depression rather than to all negative information (depression
related words and physical threat words). In another study by Direnfeld and Roberts
(2006), naturally dysphoric subjects (scores of 15 or higher on the Beck Depression
Inventory) were found to have a negative bias in an incidental memory task related to
self-descriptive trait adjectives compared to experimentally induced dysphoric and
non-dysphoric subjects, with no group differences on an intentional memory task of
valenced words.
Using prose passages and word lists as the method to assess memory, Sloan
(1998) found that depressed subjects (scores of 10 or higher on the Beck Depression
Inventory) had mood congruent memory for prose passages, recalling more idea units
in negative passages compared to neutral passages, and that control subjects had
“mood congruent memory” for the word list, recalling significantly more neutral
words than negative words. The above results suggest that in some cases, “depressed”
subjects show enhanced memory and recall for negative stimuli compared to controls,
while in other cases, “depressed” subjects merely show decreased memory for positive
stimuli. While both cases fit the notion of mood congruent memory, the latter perhaps
emphasizes the impairment of memory by depression.

8
Memory for faces in the form of facial recognition has also been used as a
method of testing for mood congruent memory and biases in depressed and non-
depressed subjects with only low to moderate success. Gilboa-Schechtman, Erhard-
Weiss, & Jeczemien (2002) showed subjects a set of faces of varying affects (neutral,
angry, happy, or sad) and asked them to indicate whether they would be interested in
meeting the individual in the photo, then tested subjects on a set of pictures and asked
them to indicate whether the faces had been displayed before or not. They found that
subjects with co-morbid depression and anxiety (diagnosed through a structured
clinical interview for the DSM-IV) had enhanced recognition of angry expressions
compared to happy expressions compared to subjects with only anxiety disorders or
normal controls. To a lesser extent, co-morbid subjects also had enhanced recognition
for sad faces compared to happy faces. They also found that men (but not women)
had a significantly better memory for angry expressions compared to sad expressions,
regardless of diagnosis.
Another study by Pine et al. (2004) examined the offspring of parents with
either major depressive disorder, an anxiety disorder, both depression and anxiety, or
no disorder for facial recognition of happy, fearful, or angry faces. Offspring were
administered a semi-structured clinical interview in order to determine the presence of
major depressive disorder. Subjects were asked to rate a set of faces on level of fear
experienced by the subject, width of nose of the person in the picture, and level of
hostility displayed by the person in the picture. Thirty minutes afterwards, subjects

9
were tested on another set of faces that contained both old and new actors, indicating
whether they had previously been displayed or were new. Pine et al. (2004) found that
the youth with a history of depression had decreased memory for fearful faces
compared to youth without a history of depression. Facial memory performance was
not found to relate to parental history. As these studies reveal, mood congruent
memory or a mood congruent bias is only weakly supported for facial recognition.
While Gilboa-Schechtman et al. (2002) found a small association between subjects
with co-morbid depression and anxiety and enhanced recognition for sad faces, the
results generally only indicate a bias for negative stimuli in depressed subjects rather
than a specific bias for items with a depressive association such as indicated in the
tasks using word lists.
While externally focused memory tests have been more varied in
demonstrating mood congruent memory or a mood congruency bias, autobiographical
memory tests have generally been consistent in displaying mood congruent memory
processing. Dysphoric subjects (scoring 9 or above on the self-report version of the
Depression Scale of the Depression Anxiety and Stress Scale) gave more general
responses to positive cues (i.e., less detailed memories) compared to negative or
neutral cues on the Autobiographical Memory Test, suggesting some difficulty in
retrieving positive memories (Popovski & Bates, 2005). The only sex difference found
in the study indicated that dysphoric women gave more general responses to neutral

10
cues than both dysphoric and non-dysphoric men and non-dysphoric women. There
was no demonstrated latency bias in memory recall for any group.
Rottenberg, Hildner, and Gotlib (2006) found that when interviewed about
their happiest and saddest lifetime events, currently depressed subjects displayed less
specific, less emotional memories that were harder to retrieve for their happiest
lifetime events compared to non-depressed subjects, while no differences in
specificity, retrieval difficulty or emotionality were found in their saddest events.
Formerly depressed subjects displayed similar results to non-depressed subjects,
suggesting that remission of symptoms decreases some of the explicit cognitive
dysfunctions associated with depression.
Kuyken, Howell, and Dalgleish (2006) found that adolescents with major
depression (diagnosed through a structured clinical interview) and no reported history
of trauma exhibited an over-general memory bias when given the Autobiographical
Memory Test. Compared to depressed adolescents with a history of trauma, depressed
adolescents without a history of trauma gave more over-general memories. The study
also found that level of trauma (avoidance symptoms) was negatively correlated with
over-generality of memories given in the memory test.
The consistent appearance of mood congruent memory processing in the form
of over-general memory/categoric memory responses for positive cuing and prompts
has been suggested to indicate vulnerability to depression or more depressive
symptoms at a later time point in the presence of high frequencies of stressful life

11
events, even when controlling for depression severity at the initial assessment (Gibbs
& Rude, 2004). Tests of autobiographical memory, whether in the form of an
idiographic interview or through cues given in the Autobiographical Memory Test
generally demonstrate that depressed subjects generate over-general responses to
positive cues and prompts compared to non-depressed controls with no difference in
generality of responses to negative cues. These findings support mood congruency
memory bias in the form of greater difficulty in accessing mood incongruent memory
items.
Rumination
As mentioned previously, gender differences in depression severity/rate have
been suggested to be mediated by rumination (Nolen-Hoeksema et al.,1999).
Rumination, as a construct, is suggested to lead to more severe and longer courses of
depression. However, the previously reviewed literature failed to examine rumination
within the context of their studies on depression and memory. Although the
aforementioned studies failed to indicate or find any significant gender differences in
their results, whether this was a result of a genuine lack of difference between genders
or a potentially neglected area of analysis is uncertain.
Existing research on the effects of rumination and depression on memory has
been sparse. Park, Goodyer, & Teasdale (2004) found that in adolescents with a first
episode of major depressive disorder, experimentally inducing rumination increased
their depressed mood and resulted in more negative categorical (over-general)

12
memories compared to experimentally induced distraction. Experimentally inducing
rumination in community controls or non-depressed psychiatric subjects failed to
increase over-general memories to negative cues, suggesting that rumination interacts
particularly with depression to increase the generality of negative memories. This
interaction is also supported by Watkins & Teasdale (2001), who found that
ruminative thinking may be important in the maintenance of over-general memories in
depressed subjects (classified through a structured clinical interview with the DSM-
III-R). The high analytical thinking condition resulted in more categorical memories
compared to the low analytical thinking condition. Also, high self-focus resulted in
greater levels of despondency compared to low self-focus in subjects. As rumination
combines both analytical thinking and a self-focus, the relationship between
rumination, depression severity, and over-general memory seems more readily
apparent. In addition, Lyubomirsky, Caldwell, & Nolen-Hoeksema (1998) found that
dysphorics (scoring 16 or above on the Beck Depression Inventory) generated the
most negative autobiographical memories, both in amount and level of negativity,
when induced to ruminate, compared to non-dysphorics and dysphorics induced to
distract. The results were consistent whether the memories were generated in free
recall or with general prompts.
Previous studies have suggested that depression can alter memory both through
generalized impairment (as shown on a variety of recall and recognition tasks) and
through mood congruent memory (the improved recall of negative stimuli while in a

13
depressed state). However, no research to our knowledge has sought to examine both
phenomena within the same study. In this study, we would like to examine potential
differences in memory between depressed subjects and non-depressed subjects on a
variety of memory tasks. In particular, we would like to examine how levels of
rumination (thinking about how depressed one feels, wondering about the cause of
their depression, and worrying about symptom implications without doing anything
constructive), depression severity, and gender alter recall on a variety of memory
tasks.

14
Chapter 2: Methods
Overview
In this study an Articulated Thoughts in Simulated Situations (ATSS)
paradigm was utilized. The paradigm presented subjects with an audio-taped scenario
in portions of roughly 15 seconds (which the subjects are instructed to immerse
themselves in, taking on the role of the main character in the scenario) and asked them
to verbalize their thoughts for 30 seconds after each portion. In addition to assessing
cognition, ATSS was also used as a vehicle for testing memory. Three scenarios were
presented, of positive, negative, and neutral valence. Each scenario had a number of
embedded details, with total number of details (19) balanced across all three valences.
After each scenario was presented in its entirety and the subject had completed their
last of six verbal responses, a state measure of rumination was given. Upon
completion of the measure, subjects were asked to verbalize all the details they are
able to recall from the simulated situation they had just responded to. Recall of ATSS
scenarios yielded four scores, including a recall score for each scenario valence as
well as a total recall score for the three scenarios combined. Subjects were also given a
standardized memory battery, the Rivermead Behavioral Memory Test (RBMT) to
give a general assessment of memory. In addition, subjects received an assessment
packet containing a variety of questionnaires assessing rumination, depression
severity, and negative mood regulation, among other things.

15
Participants
Subjects were recruited through an online USC psychology study subject pool,
Experimerix ™. A total of 101 participants were recruited into and participated in this
study. Of those 101 participants, 7 subjects had audio equipment malfunctions where
all audio data on the subject were unable to be recovered or used. Another 27 subjects
failed to recall at least two of the three ATSS scenarios. Consequently, there were a
total of 67 participants who had a viable set of data for data analysis. Subjects were
excluded from the study if they were below the age of 18 or if they were not fluent in
English.
ATSS Phase
Depressive cognitions were assessed through the use of the Articulated
Thoughts in Simulated Situations (ATSS) paradigm. The paradigm presents subjects
with an audio-taped scenario in portions (which the subjects are instructed to immerse
themselves in, taking on the role of the main character in the scenario) and asked to
verbalize their thoughts for 30 seconds after each portion. The paradigm has shown to
be effective in obtaining online measures of cognitive style and processing, and has
been used successfully in detecting differences in negative thought processes
(“Beckian” biases) between clinically depressed psychiatric subjects and non-
depressed psychiatric controls (White, Davison, Haaga, & White, 1992). The
paradigm has been shown to have good face validity, construct validity, discriminant
validity, and inter-rater reliability (for a review, see Davison, Vogel, & Coffman,

16
1997). Utilizing task-based measures of depressive schemata is important in
supplementing questionnaires as task-based measures have been found to be more
effective in detecting negative thinking than questionnaires (Rude, Covich, Jarrold,
Hedlund, & Zentner, 2001). By using ATSS to assess depressive cognitions, we were
able use the paradigm as an alternative to the CES-D scale in order to measure
depression severity.
ATSS was also used as a vehicle for testing memory. Three scenarios were
presented, of positive, negative, and neutral valence. Each scenario had a number of
embedded details, with total number of details (19) balanced across all three valences.
After each scenario was presented in its entirety and the subject had completed their
last of six verbal responses, a state measure of rumination was given. Upon
completion of the measure, subjects were asked to verbalize all the details they were
able to recall from the simulated situation they had just responded to. Recall of ATSS
scenarios yielded seven scores, including a recall score for each scenario valence, a
recall score for number of details recalled of a particular valence, and a total recall
score for the three scenarios combined.
After each ATSS scenario but before the recall component of ATSS, subjects
completed a self-evaluation questionnaire composed of nine items regarding
ruminative reactions. Subjects were directed to answer each question with an
indication of their agreement for each statement “right now, at this moment,” in order
to draw upon current feelings of rumination. Similar to a visual analogue scale used

17
for pain or anxiety, responses were in the form of a vertical line marked through a
horizontal 8 cm. line spanning from “Definitely agree” to “Definitely disagree.” The
distance between the “Definitely agree” end of the line and the response line was
averaged over the entire questionnaire for a single state score of rumination. This
instrument is in the process of being validated by Sharmin Ghaznavi under Susan
Nolen-Hoeksema (Y. Levin, personal communication, January 27, 2007). This state
measure of rumination was compared with the Ruminative Responses Scale (RRS; see
below) in order to determine the convergent validity of the measure (as higher scores
on the RRS should be associated with a general increase in state rumination scores).
Internal consistency (coefficient alpha) was also calculated as another form of
instrumental validation.
Assessment Packet
Depression severity was assessed by the Center for Epidemiologic Studies
Depression (CES-D) scale (Radloff, 1977). The CES-D is a 20-item self-report
measure that provides a variety of statements relating to depressive symptoms.
Subjects are asked to rate the frequency of each symptom statement over the past
week on a 4-point scale ranging from less than 1 day to 5 to 7 days. Scores of 16 or
higher are generally suggested as cut-off scores indicating clinical depression
(Comstock & Helsing, 1976). The CES-D scale was derived from portions of the
Minnesota Multiphasic Personality Inventory depression scale, Beck Depression
Inventory, Gardner Symptom Checklist, Raskin Self-Report Depression Scale, and

18
Zung Depression Scale (Beck, Ward, Mendelson, Mock, & Erbaugh, 1961; Dahlstrom
& Welsh, 1960; Gardner, 1968; Raskin, Chulterbrandt, Reating, & McKeon, 1970;
Zung, 1965). As a likely result, the CES-D scale correlates well with other measures
of depression severity (Weissman, Sholomskas, Pottenger, Prusoff, & Locke, 1977).
The CES-D also discriminates depression effectively from other psychiatric
populations and displays changes in response to effective treatment (Husaini, Neff,
Harrington, Hughes, & Stone, 1980; Weissman et al., 1977). The CES-D shows good
internal consistency, good construct validity, and reliability across different ethnic
groups (Radloff, 1977; Roberts, 1980; Weissman et al., 1977).
Ruminative was also assessed through the used of the Ruminative Responses
Scale (Nolen-Hoeksema & Morrow, 1991). The Ruminative Responses Scale is a 22-
item measure designed to assess the tendency to ruminate in response to expressions
and symptoms of negative emotion. The items are trait measures of rumination with
responses ranging on a 4-point scale, from 1 (never or almost never) to 4 (always or
almost always) regarding whether the subject tends to respond ruminatively to
depressed moods. The test shows good construct validity and test-retest reliability, as
well as high levels of internal consistency (Nolen-Hoeksema & Davis, 1999). The
measure also discriminates between constructs such as extraversion and neuroticism
and demonstrates convergent and predictive validity (Butler & Nolen-Hoeksema,
1994; Just & Alloy, 1997). In addition, we administered the Negative Mood
Regulation Scale, a 30-item measure seeking to assess generalized expectancies of

19
negative mood regulation (Catanzaro & Mearns, 1990). Items are scored on a 5-point
scale, from 1(strong disagreement) to 5 (strong agreement), with 16 negative items
that are scored in reverse fashion. Internal consistency, test-retest reliability, and
discriminate validity from social desirability and locus of control have all been
demonstrated previously (Catanzaro & Mearns, 1990). Before taking the Rivermead
Behavioral Memory Test, subjects responded to the state rumination questionnaire (as
mentioned in the above section).
Rivermead Behavioral Memory Test
Memory was assessed through the Rivermead Behavioral Memory Test
(RBMT), an 11-component test that unlike “traditional” laboratory measures of
memory seeks to test everyday memory function. Each component is comprised of an
analogue of commonplace tasks that an individual might need to accomplish in the
course of a day. The components include: (a) remembering a name; (b) remembering a
hidden object; (c) remembering an appointment; (d) picture recognition; (e)
remembering a newspaper article or short story (immediate and delayed recall); (f)
face recognition; (g) remembering a new route (immediate); (h) remembering a new
route (delayed); (i)) delivering a message; (j) orientation; and (k) date. RBMT
performance represented by profile score is correlated -0.75 with number of observed
memory lapses, with reliability for the profile score at 0.85 (Wilson, Cockburn,
Baddeley, & Hiorns, 1989). Perhaps more importantly, this memory measure has
demonstrated the ability to reflect differences between normal controls and subjects

20
with remitted major depression, with normal controls performing significantly better
than remitted depressed subjects, unlike a number of traditional memory tests. The
RBMT may be more sensitive to minor deficits in memory compared to traditional
lab-based memory tests by requiring the integration of a number of different memory
abilities (Fennig, Mottes, Ricter-Leven, Treves, & Levkovitz., 2002).

21
Chapter 3: Results
Sample Characteristics
The sample consisted of 57 females and 10 males. The average age of the
sample was 20.28 years of age (SD = 1.25). The sample was 40.3% Caucasian, 37.3%
Asian, 7.5 % Black, 7.5% Hispanic, and 7.4 % other. The average depression severity
of the sample was 13.99 (SD = 8.90). Complete sample information is included in
Table 1. The correlations between sample characteristics and scores on the memory
measures are also presented in Table 2).
In order to examine subject group equality (i.e. between females and males and
between depressed and non-depressed individuals), the sample was separated into
groups and analyses of variance (ANOVAs) were run to determine whether there were
any significant differences between groups. Analyses revealed that there were no
significant differences between females and males on any of the demographic
information or independent variables (i.e., depression severity, rumination or negative
mood regulation; see Table 3 for specific figures). There were also no significant
differences between non-depressed and depressed subjects on any of the independent
variables (aside from depression severity) or any of the variables relating to
demographics (Table 4).

22
Table 1. Complete Sample Characteristics

Variable

Sex (%) Female/Male 85.07/14.93
Race (%) Caucasian 40.30
Asian-American 37.31
Black 7.46
Hispanic 7.46
Other 7.47

Age Mean/sd 20.28/1.25

Rumination (RRS score) Mean/sd 49.27/12.11
Negative Mood
Regulation (NMR score)
Mean/sd 107.15/21.17
Depression Severity Mean/sd 13.99/8.90

Antidepressant Use Yes/No 1/66

Recall Coding
Coding of transcripts for recall of details from the ATSS scenarios was split
between three coders. The pool of subjects/transcripts was split into three separate
blocks as well, with each coder taking two of the blocks. As a result, each transcript
block had two coders whose reliability was determined by calculating the Pearson’s
product-moment correlation between their scores for each scenario over the entire
block. Inter-rater reliability ranged from 0.788 to 0.961, suggest a moderate to high
range of reliability between coders (see Table 5 for specific Pearson’s correlations),
indicating reliable scoring of the transcripts for each of the subjects.

23
Table 2. Correlation Between Sample Characteristics and Memory Measure Scores

Note: * p < 0.05, ** p < 0.01, *** p < 0.001.
Abbreviations:
a
deprsv = CES-D score,
b
yearsed = Years of Education,
c
RRS =
Ruminative Responses Scale score,
d
NMR = Negative Mood Regulation score,
e
e
e
antidepr = Whether there was use of an anti-depressant,
f
negdet1= Number of
negative ATSS details recalled,
g
neudet1 = Number of neutral ATSS details
recalled,
h
posdet1 = Number of positive ATSS details recalled,
i
totdet1 = Number of
total ATSS details recalled,
j
rbmt = RiverMead Behavioral Memory Test,
k
negrum =
State Rumination score preceding Negative ATSS Scenario recall,
l
neurum = State
Rumination score preceding Neutral ATSS Scenario recall,
m
posrum = State
Rumination score preceding Positive ATSS Scenario recall,
n
rbtmrum = State
Rumination score preceding RiverMead Behavioral Memory Test

24
Table 3. Subject Demographics (Female vs. Male)

Variable Mean Std. Dev. F-value p-value
Depression
Severity
(CES-D)
14.67/10.1 9.31/4.61 2.29 0.1354
Age 20.28/20.3 1.32/0.82 0.00 0.9646
Rumination
(RRS)
49.05/50.5 12.26/11.73 0.12 0.7301
Negative Mood
Regulation
(NMR)
106.07/113.3 18.77/32.32 0.99 0.3229

Note: Values for Female subjects are listed first.

Table 4. Subject Demographics (Non-depressed vs. Depressed)

Variable Mean Std. Dev. F-value p-value
Depression
Severity (CES-
D)
9.25/25.26 3.76/8.11 118.54 <0.0001
Age 20.1/20.74 1.12/1.48 3.61 0.062
Rumination
(RRS)
48.40/51.47 11.38/13.85 0.88 0.3521
Negative Mood
Regulation
(NMR)
107.63/105.95 18.98/26.47 0.08 0.7725
Sex 39F|9M / 18F|1M -- 1.95 0.1675

Note: Values for Non-Depressed subjects are listed first.
Depressed subjects = CES-D ≥ 16.
Correlations Between Independent Variables and Covariates
A few noteworthy correlations were found between independent variables and
covariates. Trait rumination (i.e. scores on the RRS) was significantly associated

25
Table 5. Inter-rater Reliability for Transcript Coding of Details

Block Raters Inter-rater reliability
(Pearson’s r)
A Rater 1
Rater 3
0.961
B Rater 1
Rater 2
0.788
C Rater 2
Rater 3
0.944

(negatively) with degree of negative mood regulation (r = -0.4078, p < 0.01),
providing an element of construct validity for the NMR questionnaire and scale. Years
of education and age were positively correlated (r = 0.808, p < 0.0001), as expected.
Depression severity was positively correlated with trait rumination scores (r = 0.271, p
< 0.05) and negatively correlated with degree of negative mood regulation (r = -0.30,
p < 0.05), again in expected directions. In addition, depression was positively
correlated with both years of education (r =0.265, p < 0.05) and age (r =0.349,
< 0.01). Further information on correlations between the independent variables and
covariates is listed in Table 6.
Correlations Between Dependent Measures
The recall of different valenced ATSS scenario details was highly correlated
with one another, ranging from r = 0.049 to r = 0.97 (all p < 0.0001). The strong but
variable correlations between the ATSS detail recall scores suggests that the recall of
ATSS scenarios measures a particular type of memory that is related to one another

26
Table 6. Correlation Between Independent Variables and Covariates

Note: * p < 0.05, ** p < 0.01, *** p < 0.001.
Abbreviations:
a
deprsv = CES-D score,
b
yearsed = Years of Education,
c
RRS =
Ruminative Responses Scale score,
d
NMR = Negative Mood Regulation score,
e
Antidepr = Whether there was use of an anti-depressant

but still has variation in how much information is recalled (i.e. measuring memory but
touching upon different aspects of recall, like recall for negative, positive, and neutral
information). Relatedly, the ATSS recall scores were not correlated with the RBMT

27
raw score, suggesting a potential difference in how memory was measured in this
study. Similar to the ATSS valenced detail recall, the state rumination measures were
all correlated with one another (ranging from r = 0.60 to r = 0.77, p < 0.0001). This
pattern of correlations again suggests measuring a particular construct (i.e.,
rumination) but differing in how it is measured (i.e., at different time points, yielding
state scores of rumination). Further information on correlations between the dependent
variables is listed in Table 7.
Primary Aim: Association Between Depressed/Non-Depressed Individuals and
Memory

The first set of analyses was conducted on the data to determine whether there
was an association between being depressed (i.e., CES-D score greater than or equal to
16) and changes in memory performance on the various memory measures. As there
was an association between the dependent variables (i.e., some of the dependent
measures were correlated with one another), we conducted a Multivariate Analysis of
Variance (MANOVA) in order to test whether there was an association, using the
number of negative, neutral, and positive details recalled from all three ATSS
scenarios, as well as the RBMT raw score, as outcome variables. The MANOVA
revealed that there was no significant association between being depressed and how an
individual performed across the memory measures (F (4,57) = 0.20, p = 0.93.96).

28
Table 7. Correlation Between Dependent Variables

Note: * p<0.05, ** p<0.01, *** p<0.001
Abbreviations:
a
negdet1= Number of negative ATSS details recalled,
b
neudet1 =
Number of neutral ATSS details recalled,
c
posdet1 = Number of positive ATSS
details recalled,
d
totdet1 = Number of total ATSS details recalled,
e
rbmt =
RiverMead Behavioral Memory Test,
f
negrum = State Rumination score preceding
Negative ATSS Scenario recall,
g
neurum = State Rumination score preceding Neutral
ATSS Scenario recall,
h
posrum = State Rumination score preceding Positive ATSS
Scenario recall,
i
rbtmrum = State Rumination score preceding RiverMead Behavioral
Memory Test

29
Secondary Aim: Associations Between Depression Severity, Numination, and
Performance on Memory Measures

In order to examine this aim canonical regression was used, which allows for
the accounting of correlations between the dependent variables. Depression severity
and trait rumination were used as the independent variables, with age, years of
education, and ethnicity serving as covariates, and used to predict performance on the
RBMT and recall of negative, neutral and positive ATSS details. Canonical regression
suggests that there was one canonical variable significantly associated with
performance on the various memory measures (see Table 8 for complete results).
However, further examination of this canonical variable suggested that this variable
was primarily associated with age and years of education attained, rather than
depression severity or rumination. The third canonical variable was the first of the
variables to display any association to either depression severity or rumination.
Secondary Aim: Associations Between Gender, Depression Severity, Rumination, and
Performance on Memory Measures

Again, canonical regression was used in order to account for the correlation
between dependent variables. Sex was included along with depression severity and
trait rumination as independent variables, with age, years of education, and ethnicity
serving as covariates to predict performance on the RBMT as well as recall of
negative, neutral and positive ATSS details. Canonical regression yielded no
significant canonical variable that was predictive of performance on the various
memory measures (see Table 9 for details).

30
Table 8. Results of Canonical Regression for Depression Severity and Rumination on
Recall

Canonical
Variable
Associated
Variables
Eigenvalue Approx. F-
value
p-value
1 (+) yearsed, (-)
age
0.2608 1.64 0.0471*
2 (+) age, (-)
yearsed, (-) rrs
0.2131 1.61 0.0958
3 (-) age, (-) rrs 0.1383 1.34 0.2455
4 (+) deprsv 0.01116 0.32 0.7243

Note: (+) denotes a positive association with the variable, (-) denotes a negative
association with the variable.

Table 9. Results of Canonical Regression for Depression Deverity, Rumination, and
Sex on ATSS Recall and RBMT Performance

Canonical
Variable
Associated
Variables
Eigenvalue Approx. F-
value
p-value
1 (+) sex, (+) age 0.2867 1.51 0.0673
2 (+) yearsed 0.2607 1.45 0.1331
3 (-) age 0.1429 1.05 0.4071
4 (-) sex 0.0157 0.29 0.8344

Note: (+) denotes a positive association with the variable, (-) denotes a negative
association with the variable.

Statistical Power
Power analysis was conducted through the use of G*Power (for a review, see
Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (in press); Erdfelder, E., Faul, F. &
Buchner, A., 1996).
Aim 1. To calculate a priori power (i.e., the required sample size needed to
detect an established effect size given the alpha and power), the group means and

31
standard deviations from the 2002 Fennig et al. article regarding differences in RBMT
performance between remitted depressed subjects and control subjects were used.
Consequently, an estimated effect size of 1.15 was used for calculating power on the
MANOVA. This study would have needed 22 subjects per group to detect an effect
size of 1.15 with 95% power and using an a = 0.05. A sensitivity power analysis was
also conducted to see what range of effect sizes should have been able to be detected
with the sample sizes seen in this study. Assuming α = 0.05 with 95% power, the
study should have been able to detect effect sizes of f
2
= 1.279.
Aim 2. A separate sensitivity power analysis was conducted in order to
determine what effect sizes would be detected when utilizing depression severity and
trait rumination as independent variables and age, years of education, and ethnicity as
covariates in canonical regression. Assuming a = 0.05 with 95% power, the study
should have been able to detect effect sizes of f
2
=0.323 with 67 total subjects.
Aim 3. A similar sensitivity power analysis was conducted in order to
determine what effect sizes would be detected when utilizing depression severity and
trait rumination as independent variables and age, years of education, and ethnicity as
covariates in canonical regression. Assuming α = 0.05 with 95% power, the study
should have been able to detect effect sizes of f
2
= 0.345 with 67 total subjects. .
Discussion
Previous studies have found that depression results in a general impairment of
memory, both in terms of recall and recognition (Burt, Zembar, Niederehe, 1995).

32
Depressed individuals have a harder time recalling information across a variety of
contexts with the differences displaying a moderate effect size (d = 0.56; Burt et al.,
1995). However, not all forms of memory are impaired. Numerous other studies have
found that depression can facilitate memory, particularly for negative information.
These findings of memory facilitation have been found across a number of different
settings, including life events, stories, pictures, and even autobiographical memory
(Direnfeld & Roberts, 2006; Sloan, 1998; Watkins et al., 1992). Factors such as
depression severity and gender have been considered as specific potential influences
upon how memory is altered in the presence of depression.
Rumination, believed to be a maintaining factor for episodes of depression and
critically related to the gender difference in prevalence of depression, has also been
examined for its influence upon autobiographical memory, but not for general or
valenced recall or recognition. While little research has been done to directly examine
this varying relationship between depression and memory, particularly with regards to
mechanistic explanations and theory, this study sought to add more to the general
understanding of what factors play a role in this relationship by using a variety of
memory tasks in order to examine recall of valenced and non-valenced information by
depressed and non-depressed individuals.
The results of this present study suggest that there is no significant difference
between depressed and non-depressed individuals with regards to memory, both for
valenced and non-valenced measures. Depressed individuals performed no worse than

33
non-depressed individuals in recalling information from the Articulated Thoughts in
Simulated Situations (ATSS) paradigm nor did they perform worse in completing the
Rivermead Behavioral Memory Test (RBMT). While depression severity and trait
rumination were shown to be associated with changes in performance on the memory
measures, further examination revealed that these changes were more associated with
differences in age and years of education than depression severity or trait rumination.
Gender was also demonstrated to not be associated with changes in memory
performance. These null findings may be interpreted in a number of different ways.
The most basic interpretation is that our study did not have enough power to
accurately assess the influence of a variety of factors on the relationship between
depression and memory. With the number of outcome measures used in our study and
using group sizes of about 20 each (given that our smallest group, depressed, had only
19 individuals), our study would only have been capable of detecting large effect sizes
(f
2
=.1.279) with alpha set at α = 0.05 and 95% power. As mentioned previously, a
meta-analysis of 99 studies done by Burt et al. (1995) revealed that the effect size of
the association between depression and memory was moderate (d = 0.56), suggesting
that our study was too under-powered to detect a relationship between the presence of
depression and memory, preventing us from properly examining any associations.
While our sample size of sixty seven should have been sensitive enough to detect
effect sizes in the range of f
2
= 0.323 to f
2
= 0.345, there were likely other problems
with our sample.

34
Another potential issue is that the sample recruited for this study was not truly
suffering from major depression. Even though a number of the individuals in the
sample exceeded the clinical cut-off score of 16 normally used by clinicians to
indicate a diagnosis of major depression, this does not necessarily mean that these
individuals had major depression. Previous studies have suggested that in the absence
of major depression the CES-D measures nonspecific psychological distress
(Dohrenwend, Shrout, Egri, & Mendelsohn, 1980; Schonfeld, 1990). Even for
individuals without depression in this study, scores often fell into a range that would
exceed the clinical cut-off score (M = 13.03, SD = 11.03).
This would provide an alternate explanation for the elevated scores found, and
seem consistent with the observations of the investigator, who did not observe many
overt displays of depressed mood or psychomotor retardation during the course of the
study that might be consistent with elevated scores on the CES-D and a consequent
diagnosis of major depression. Given that the subject sample was composed of
students from a university, it is unlikely that many of the students were suffering from
severe episodes of depression and yet still functioning at a high enough level to
complete a full-time university course load, and much more likely that the students
were displaying distress from being faced with a rigorous academic schedule and
requirements. Without a formal diagnostic interview like the Structured Clinical
Interview for the DSM-IV (SCID), it is impossible to determine to what extent the
subjects actually met criteria for major depression.

35
Another interpretation is that the measures used during the course of this study
may not have been adequate to appropriately examine the relationships of interest. As
mentioned before, the CES-D might not have been the best measure of depression
severity and symptomatology; the Hamilton Depression Rating Scale or the Beck
Depression Inventory may have been better suited for assessing depression.
In addition, the use of the newly-developed state rumination questionnaire may
have been premature as it has not been fully developed and normed as a state measure
of rumination, and is still in the process of being refined. The state rumination scores,
aside from the ruminative scores for the negative scenario recall, were not
significantly associated with the trait rumination scores derived from the RRS.
The memory measures themselves displayed some evidence of being
inadequate; specifically the negative and positive scenarios seemed to display little
variance in terms of the amount of information recalled during the course of the study
(the mean number of negative details recalled was 6.182, with a standard deviation of
2.64, with the mean number of positive details recalled at 3.354 with a standard
deviation of 2.33). This lack of variance makes it more difficult to find differences
between populations, including depressed and non-depressed subject populations. The
scenarios might not have been designed as effectively as possible to elicit recall of
information from the scenarios as only a small number of details might be salient from
each individual scenario.

36
Recalling scenarios is also a novel form of memory testing in this literature, as
it is not the same as recall of prose passages necessarily (considering the personal
involvement component derived from reacting and articulating thoughts about the
scenarios after each portion) nor is it the same as autobiographical memory recall (as
even though the scenarios are intended to be interpreted as happening to the person
right at that moment in time, the subjects are not actually experiencing the situations in
person with all components of sensory information present).
In addition, even though the Rivermead Behavioral Memory Test has
previously been able to demonstrate memory differences between remitted depressed
subjects drawn from a clinic setting and non-depressed individuals, it may not be able
to differentiate between non-depressed and mildly depressed subjects (Fennig et al.,
2002). Thus, while the RBMT may be suited for some depressed populations, using it
in a university setting, where it is unlikely that the investigators will encounter many
students experiencing (currently or previously) severe bouts of depression, may be
inappropriate if intended to distinguish between the two subject groups.
In contrast to the previous interpretations that allude to the idea that we were
not able to properly examine the relationship between depression and memory,
another possibility is that there is no relationship between depression and memory in
the context of this novel form of memory testing. Depression may impact more basic
forms of recall in the form of prose passages and word lists, as well as idiographic
memories like autobiographical memories, but not involved and potentially complex

37
memories like those derived from going through the ATSS paradigm. This is an
unlikely interpretation given that this form of short term recall is not critically unique
or distinct from other basic forms of memory (despite the differences outlined above)
and should have no distinct reason for having a different relationship.
A more general interpretation is that there is no relationship between
depression and memory at all. Again, this is an unlikely interpretation given the
findings of the meta-analysis by Burt et al. (1995) as well as recent research by
Hamilton and Gotlib (2008). Hamilton and Gotlib were able to demonstrate mood
congruent memory in a sample of 14 depressed and 12 non-depressed individuals.
More critically, however, they were able to utilize fMRI to demonstrate that the
depressed individuals had increased right amygdala activity (as well as increased
connectivity with the hippocampus and caudate-putamen) compared to non-depressed
individuals in response to negative stimuli, but not neutral or positive stimuli. In
addition, the degree of right amygdala activity was correlated with depression severity.
These findings suggest that mood congruent memory has specific biological
mechanisms rooted in right amygdala connectivity and activity, and that this activity is
related to depression severity. Consequently, studies that fail to find any indications of
mood congruent memory may not be engaging the biological mechanism outlined by
Hamilton and Gotlib, perhaps either due to weak stimuli or poor subject samples
among other issues.

38
One last possible interpretation is that there was a third variable that was not
assessed and might have affected the overall relationship between depression and
memory. This third variable could have been critically related to the mechanistic
process behind how depression affects memory and been reduced or lacking over the
course of this study, resulting in the lack of results. One possible candidate for this
third variable is attention or concentration. As attention to stimuli is an important
requisite of the memory encoding process, if subjects were not fully attentive to the
scenarios or behavioral memory test, then performance was very likely to be impaired
or altered. This could have washed out the effects of depression upon memory and
accounted for the lack of significant findings.
Given the current state of literature regarding how depression can affect
memory both in a general context and with regards to specific valenced contexts,
attention may be a critical variable to consider in general. Attention may theoretically
drive the differences seen in the memory literature; depressed individuals may have an
attentional bias in information that makes it difficult to shift focus away from negative
information. If depressed individuals are unable to shift focus away from negative
information, any sort of positive or neutrally valenced information is much more likely
to be forgotten or not encoded, resulting in poor recall. This inability to shift focus
away from negative information would consequently yield facilitated recall for
negative information due to the additional attention devoted to negative stimuli. This
attentional bias has been empirically examined and validated through the use of the

39
emotional Stroop task, with studies suggesting that depressed individuals have a more
difficult time shifting their attention away from negative information compared to
positive or neutral information and compared to healthy controls (Dudley, O’Brien,
Barnett, McGuckin, & Britton, 2002; Koster, De, Goeleven, Franck, & Crombez,
2005; Mitterschiffthaler et al., 2008; Williams Mathews, & MacLeod et al., 1996).
Further study of how attentional processes might drive differences in memory is a
primary direction worth future investigation.
One final important direction worth further investigation is the clinical
significance of mood congruent memory. While there has been some suggestion
regarding the clinical implications of mood congruent memory and it serving as a
potential diathesis in the cognitive diathesis-stress theory (e.g., Ramel et al., 2007), the
implications have not been aggressively pursued further in the form of sustained and
systematic longitudinal study. Ramel et al. found that individuals who had remitted
from their episode of major depression still displayed evidence of mood congruent
memory (only during an induced sad mood) that was not seen in the non-depressed
controls. Ramel and colleagues concluded that the results were consistent with the
cognitive diathesis-stress model of depression but were unable to supply further
assertions. It is unclear whether mood congruent memory is a precursor or result of
major depression. Often studies that examine individuals who are “at risk” for
depression utilize individuals who have previously experienced an episode of
depression and consequently are more likely to develop another episode. This

40
experimental methodology renders null any chance for examining the temporal
relationship of mood congruent memory and depression. If mood congruent memory
is indeed a diathesis for the development of depression, perhaps future interventions
could target mood congruent memory as a risk factor.
Conclusions
The results of this study suggest that depression and memory are not
associated. In particular, depression severity, gender, and rumination did little to
predict how depression could possibly affect memory. However, given the limitations
of this study, particularly with regards to power and a possibly non-depressed
“depressed” sample, as well as the current state of the literature, these findings are
more inconclusive than indicative of how depression is not associated with memory
performance.

41
References

Beck, A. T., Ward, C. H., Mendelson, M., Mock, J. E., & Erbaugh, J. K. (1961). An
inventory for measuring depression. Archives of General Psychiatry, 4, 561-
571.

Bennett, D. S., Ambrosini, P. J., Kudes, D., Metz, C., & Rabinovich, H. (2005)
Gender differences in adolescent depression: Do symptoms differ for boys and
girls? Journal of Affective Disorders, 89, 35-44

Bogner, H. R., & Gallo, J. J. (2004). Are higher rates of depression in women
accounted for by differential symptom reporting? Social Psychiatry and
Psychiatric Epidemiology, 39, 126-132.

Bond, C. F., & Omar, A. S. (1990) Social anxiety, state dependence and the next-in-
line effect. Journal of Experimental Social Psychology, 26, 185-198

Bower, G. H., Gilligan, S. G., & Monteiro, K. P. (1981). Selectivity learning caused
by affective states. Journal of Experimental Psychology: General, 110, 451-
473.

Burt, D. B., Zembar, M. J., & Niederehe, G. (1995). Depression and memory
impairment: A meta-analysis of the association, its pattern, and specificity.
Psychological Bulletin, 117(2): 285-305

Butler, L. D., & Nolen-Hoeksema, S. (1994). Gender differences in responses to
depressed mood in a college sample. Sex Roles, 30(5-6), 331-346.

Catanzaro, S. J., & Mearns, J. (1990). Measuring generalized expectancies for
negative mood regulation: Initial scale development and implications. Journal
of Personality Assessment, 54 (3&4), 546-563.

Comstock, G. W., & Helsing, K. J. (1976). Symptoms of depression in two
communities. Psychological Medicine, 6, 551-564.

Dahlstrom, W. G., & Welsh, G. S. (1960). An MMPI Handbook. Minneapolis:
University of Minnesota Press, 1960.

Davidson, R. J., Lewis, D. A., Alloy, L. B., Amaral, D. G., Bush, G., Cohen, J. D.,
Drevets, W. C., Farah, M. J., Kagan, J., McClelland, J. L., Nolen-Hoeksema,
S., & Peterson, B. S. (2002). Neural and behavioral substrates of mood and
mood regulation. Biological Psychiatry, 52, 478-502.

42
Davila, J., & Daley, S. E. (2000). Studying interpersonal factors in suicide:
Perspectives from depression research. In: T. E. Joiner & M. D. Rudd (Eds),
Suicide science: Expanding the boundaries. Boston: Kluwer Academic.

Davison, G. C., Vogel, R. S., & Coffman, S. G. (1997). Think-aloud approaches to
cognitive assessment and the articulated thoughts in simulated situations
paradigm. Journal of Consulting and Clinical Psychology, 65(6), 950-958.

Direnfeld, D. M., & Roberts, J. E. (2006). Mood congruent memory in dysphoria: The
roles of state affect and cognitive style. Behaviour Research and Therapy, 44,
1275-1285.

Dohrenwend, B. P., Shrout, P. E., Egri, G., & Mendelsohn, M. D. (1980). Non-
specific psychological distress and other dimensions of psychopathology:
Measures for use in the general population. Archives of General Psychiatry,
37, 1229-1236.

Dudley, R, O’Brien, J., Barnett, N., McGuckin, L., & Britton, P. (2002)
Distinguishing depression from dementia in later life: A pilot study employing
the emotional stroop task. International Journal of Geriatric Psychology, 17:
48-53.

Erdfelder, E., Faul, F., & Buchner, A. (1996) GPOWER: A general power analysis
program. Behavior Research Methods, Instruments, & Computers, 28, 1-11.

Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (in press). G*Power 3: A flexible
statistical power analysis for the social, behavioral, and biomedical sciences.
Behavior Research Methods, Instruments, and Computers.

Fennig, S. Mottes, A., Ricter-Levin, G., Treves, I., & Levkovitz, Y. (2002). Everyday
memory and laboratory memory tests: general function predictors in
schizophrenia and remitted depression. Journal of Nervous & Mental Disease,
190(10), 677-682.

Fiedler, K., Nickel, S., Muehlfriedel, T., & Unkelbach, C. (2001). Is mood congruency
an effect of genuine memory or response bias? Journal of Experimental Social
Psychology, 37, 201-214.

Forgas, J. P., & Moylan, S. (1987). After the movies: Transient mood and social
judgments. Personality and Social Psychology Bulletin, 13, 167-177.

43
Gardner, E. A. (1968). Development of a symptom checklist for the measurement of
depression in a population. Unpublished manuscript (cited in: Ensel, 1986),
Gibbs, B. R., & Rude, S. S. (2004). Overgeneral autobiographical memory as
depression vulnerability. Cognitive Therapy and Research, 28(4), 511-526.

Gibbs, B. R., & Rude, S. S. (2004). Overgeneral autobiographical memory as
depression vulnerability. Cognitive Therapy and Research, 28(4), 511-526.

Gilboa-Schechtman, E., Erhard-Weiss, D., Jeczemien, P. (2002). Interpersonal deficits
meet cognitive biases: memory for facial expressions in depressed and anxious
men and women. Psychiatry Research, 113, 279-293.

Gorman, J. M. (2006) Gender differences in depression and response to psychotropic
medication. Gender Medicine, 3(2), 93-109.

Greenberg, P. E., Kessler, R. C., Birnbaum, H. G., Leong, S. A., Lowe, S. W.,
Berglund, P. A., & Corey-Lisle, P. K. (2003). The economic burden of
depression in the United States: How did it change between 1990 and 2000?
Journal of Clinical Psychiatry, 64(12), 1465-1475.

Hamilton, J. P., & Gotlib, I. H. (2008). Neural substrates of increased memory
sensitivity for negative stimuli in major depression. Biological Psychiatry, 63,
1155-1162.

Hildebrandt, M. G., Stage, K. B., & Kragh-Soerensen, P. (2003) Gender differences in
severity, symptomatology, and distribution of melancholia in major depression.
Psychopathology, 36, 204-212.

Hope, D. A., Heimberg, R. G., & Klein, J. R. (1990) Social anxiety and the recall of
interpersonal information. Journal of Cognitive Psychotherapy: An
International Quarterly, 4, 189-199.

Husaini, B. A., Neff, J. A., Harrington, J. B., Hughes, M. D., & Stone, R. H. (1980).
Depression in rural communities: Validating the CES-D scale. Journal of
Community Psychology, 8, 20-27.

Just, N., & Alloy, L. B. (1997). The response styles theory of depression: tests and an
extension of the theory. Journal of Abnormal Psychology, 106(2), 221-229.

44
Kessler, R. C., McGonagle, K. A., Zhao, S., Nelson, C. B., Hughes, M., Eshleman, S.,
Wittchen, H. U., & Kendler, K. S. (1994). Lifetime and 12-month prevalence
of DSM-III-R psychiatric disorders in the United States. Results from the
National Comorbidity Survey. Archives of General Psychology, 54, 54-59.

Kimble, C. E., & Zehr, H. D. (1982). Self-consciousness, information load, self-
presentation, and memory in a social situation. Journal of Social Psychology,
118, 39-46.

Koster, E. H., De, R. R., Goeleven, E., Franck, E., & Crombez, G. (2005). Mood-
congruent attention bias in dysphoria: maintained attention to and impaired
disengagement from negative information. Emotion, 5, 446-455

Kuyken, W., Howell, R., & Dalgleish, T. (2006). Overgeneral autobiographical
memory in depressed adolescents with, versus without, a reported history of
trauma. Journal of Abnormal Psychology, 115(3), 387-396.

Lyubomirsky, S., Caldwell, N. D., & Nolen-Hoeksema, S. (1998). Effects of
ruminative and distracting responses to depressed mood on retrieval of
autobiographical memories. Journal of Personality and Social Psychology,
75(1), 166-177.

Mayer, J. D., McCormick, L. J., & Strong, S. E. (1995). Mood-congruent memory and
natural mood: New evidence. Personality and Social Psychology Bulletin, 21,
736-746.

Mitterschiffthaler, M. T., Williams, S. C. R., Walsh, N. D., Cleare, A. J., Donaldson,
C., Scott, J., & Fu, C. H. Y. (2008) Neural basis of the emotional stroop
interference effect in major depression. Psychological Medicine, 38, 247-256.

Nolen-Hoeksema, S. (1987). Sex differences in unipolar depression: Evidence and
theory. Psychological Bulletin, 101(2), 259-282.

Nolen-Hoeksema, S. (2000). The role of rumination in depressive disorders and mixed
anxiety/depressive symptoms. Journal of Abnormal Psychology, 109, 504-511.

Nolen-Hoeksema, S., & Davis, C. G. (1999). “Thanks for sharing that”: ruminators
and their social support networks. Journal of Personality and Social
Psychology, 77(4), 801-814.

45
Nolen-Hoeksema, S., Larson, J., & Grayson, C. (1999). Explaining the gender
difference in depressive symptoms. Journal of Personality and Social
Psychology, 77(5), 1061-1072.

Nolen-Hoeksema, S., & Morrow, J. (1991). A prospective study of depression and
posttraumatic stress symptoms after a natural disaster: The 1989 Loma Prieta
earthquake. Journal of Personality and Social Psychology, 61, 115-121.

Park, R. J., Goodyer, I. M., & Teasdale, J. D. (2004). Effects of induced rumination
and distraction on mood and overgeneral autobiographical memory in
adolescent major depressive disorder and controls. Journal of Child
Psychology and Psychiatry, 45(5), 996-1006.

Pine, D. S., Lissek, S., Klein, R. G., Mannuzza, S., Moulton III, J. L., Guardino, M., &
Woldehawariat, G. (2004). Face-memory and emotion: associations with major
depression in children and adolescents. Journal of Child Psychology and
Psychiatry, 45(7), 1199-1208.

Popovski, M., & Bates, G. W. (2005). Autobiographical memory and dysphoria: The
effect of mood, gender, and cue type on generality and latency. North
American Journal of Psychology, 7(3), 505-518.

Radloff, L. S. (1977). The CES-D scale: A self-report depression scale for research in
the general population. Applied Psychological Measurement, 1, 385-401.

Ramel, W., Goldin, P. R., Eyler, L. T., Brown, G. G., Gotlib, I. H., & McQuaid, J. R.
(2007). Amygdala activity and mood-congruent memory in individuals at risk
for depressive relapse. Biological Psychiatry, 61, 231-239.

Raskin, A., Chulterbrandt, J. S., Reating, N., & McKeon, J. (1970). Replication of
factors in psychopathology in interview, ward behavior, and self report ratings
of hospital depressives. Journal of Nervous and Mental Disease, 198, 87-96.

Roberts, R. E. (1980). Reliability of the CES-D scale in different ethnic contexts.
Psychiatry Research, 2, 125-134.

Rottenberg, J., Hildner, J. C., & Gotlib, I. H. (2006). Idiographic autobiographical
memories in major depressive disorder. Cognition and Emotion, 20(1), 114-
128.

46
Rude, S. S., Covich, J., Jarrold, W., Hedlund, S., & Zentner, M. (2001). Detecting
depressive schemata in vulnerable individuals: questionnaires versus
laboratory tasks. Cognitive Therapy and Research, 25 (1), 103-116.

Rusting, C. L., & DeHart, T. (2000). Retrieving positive memories to regulate
negative mood: Consequences for mood congruent memory. Journal of
Personality and Social Psychology, 78(4), 737-752.

Schonfeld, I. S. (1990) Psychological distress in a sample of teachers. The Journal of
Psychology, 124 (3): 321-338.

Sloan, L. L. (1998). Processing Strategies and recall performance for narrative
passages and word lists of negative and neutral affective valence in depression
(Doctoral dissertation, University of North Dakota, 1990). Dissertation
Abstracts International, 59, 1387.

Watkins, E., Teasdale, J. D. (2001). Rumination and overgeneral memory in
depression: effects of self-focus and analytic thinking. Journal of Abnormal
Psychology, 110, 353-357.

Watkins, P. C., Mathews, A., Williamson, D. A., & Fuller, R. D. (1992). Mood-
congruent memory in depression: Emotional priming or elaboration? Journal
of Abnormal Psychology, 101(3), 581-586.

Weissman, M. M., Sholomskas, D., Pottenger, M., Prusoff, B. A., & Locke, B. Z.
(1977). Assessing depressive symptoms in five psychiatric populations: A
validation study. American Journal of Epidemiology, 106(3), 203-214.

White, J., Davison, G. C., Haaga, D. A. F., & White, K. (1992) Cognitive bias in the
articulated thoughts of depressed and nondepressed psychiatric patients.
Journal of Nervous and Mental Disease, 180(2), 77-81.

Williams, J. M. G., Mathews, A., & MacLeod, C. (1996). The emotional stroop task
and psychopathology. Psychological Bulletin, 120 (1): 3-24.

Wilson, B., Cockburn, J., Baddeley, A., & Hiorns, R. (1989). The development and
validation of a test battery for detecting and monitoring everyday memory
problems. Journal of Clinical and Experimental Neuropsychology, 11(6), 855-
870.

47
Young, M. A., Scheftner, W. A., Fawcett, J., & Klerman, G. L. (1990) Gender
differences in the clinical features of unipolar major depressive disorder.
Journal of Nervous and Mental Disease, 178(3), 200-203.

Zung, W. W. K. A. (1965). A self rating depression scale. Archives of General
Psychiatry, 12, 63-70.

48
APPENDIX A
ATSS SCENARIOS (WITH OUTLINED DETAILS AND SCORING
RUBRIC)
Negative:
1. Too bad about that [get-together you had planned (N2)] [outdoors (N1)] at
[City Park (N2)]. You put in [a lot of time and effort (N1)] the whole thing. {6}
2. The [rain really ruined it (-1)]. Especially since [most people were already
there when the rain started (-1)]. {2}
3. All the [food people had brought was ruined (-2)]. I felt really bad, I [ruined
my good jacket in the rain (-1)] too. And [Mary caught a cold (-1)]. {4}
4. You didn’t look too happy sitting there in the rain, [trying over and over to
start the fire (-2)]. {2}
5. [Walking all the way across the park back to the parking lot (N1)] in the rain
was really rough. It looked like [people really wanted to get out of there (-1)].
{2}
6. I guess the [weather report was wrong (N1)] about it [clearing and being a
sunny day (N2)]. Pretty bad luck, I’d say. {3}

Positive:
1. You know, it was really lucky [you were over at my house (N1)] when [my
basement got flooded (-1)]. I thought I’d only see you for a second since you
were [dropping off(+1)] those [three books(N1)] [for me(+1)]. {5}
2. I don’t know what I would have done without you. I really [needed you to help
me figure out what to do(+1)]. Thanks for [helping me move(+1)] those [set of
boxes(N1)] too. {3}
3. I’m really glad we [managed to fix that without it becoming more of a
mess(+1)]. The [plumber said(N1)] it would have taken at least [three hours to
come out(N1)] and [two hundred dollars(N1)] for the job. {4}
4. [Because of your help the basement finished drying out(+1)] just
[yesterday(N1)]. My basement [would have been horrible shape without you
(+1)] there for me. {3}
5. And then [bringing over those sandwiches(N1)] – that really came in handy. I
really [appreciated the lunch (+1)]. {2}
6. I [ran into one of our other friends yesterday and mentioned all this to
him(N2)]. He agreed it was very lucky you were there. {2}

Neutral:
1. Oh hi. I [haven’t seen you in a while(N1)]. How are you? {1}

49
2. Say, did you [hear about my daughter(N1)]? She just [finished that art
course(N1)] she was [taking at the community college(N1)] and they [liked
one of her oil paintings(+1)] so much they’re [putting it in one of the galleries
downtown(N2)]. {6}
3. Of course she’s [pretty happy about it(+1)]. The poor kid needs good news
right now, after [her husband leaving her(-1)] like that [last February(N1)]. She
[still hasn’t been able to find out where he’s gone(-1)]. {4}
4. I don’t know. Kids these days, it seems so hard to understand how they can do
the things they do sometimes. They [were together for five years(N1)] and [he
just up and leaves like that (-1)]. {2}
5. She’s tried to do well for herself in the meantime, [getting a manager
position(N1)] at a [new French restaurant(N2)]. [They’ve gotten really busy
since they’ve opened (N2)]. {4}
6. Well I’ve [got to go meet my husband (N1)]. We should [get together next
weekend (N1)]. It’s been nice talking to you. {2}

Key:
[] – Indicates a specific recall detail
(X#) – Indicates valence (X, with +/-/N corresponding to positive/negative/neutral
detail valences, respectively) and scoring (# of points) for recall detail
{#} – Indicates total number of recall details in the individual scenario component

50
APPENDIX B

STATE RUMINATION QUESTIONNAIRE

ID____________ DATE___________ PRECEDING MEASURE_______________

SELF-EVALUATION QUESTIONNAIRE

INSTRUCTIONS: Each item of this questionnaire is a statement that a person may either
agree with or disagree with. For each item, indicate how much you agree or disagree with
what the item says, right now, that is, at this moment. Please indicate your answer by
marking a vertical line through the horizontal line given below each statement.
1. I am thinking about the physical sensations I feel in my body.
Definitely agree____________________________________Definitely disagree

2. I wonder why I react the way I do.

Definitely agree____________________________________Definitely disagree

3. I am thinking about the possible consequences of the way I feel.

Definitely agree____________________________________Definitely disagree

4. I am thinking about how sad/happy I am feeling.

Definitely agree____________________________________Definitely disagree

5. I am thinking about how awake/tired I feel.

Definitely agree____________________________________Definitely disagree

6. I wonder what I did to deserve how things are going.

Definitely agree____________________________________Definitely disagree

7. I am thinking about a recent situation, wishing it had gone better.

Definitely agree____________________________________Definitely disagree

51

8. I am thinking about why I have problems other people don't have.

Definitely agree____________________________________Definitely disagree

9. I wonder why I don't handle things better.

Definitely agree____________________________________Definitely disagree

52
APPENDIX C

CES-D SCALE

Center for Epidemiologic Studies Depression Scale (CES-D), NIMH

Below is a list of the ways you might have felt or behaved.
Please tell us how often you have felt this way during the past week.

Rarely or none
of the time
(less than 1
day)
Some or a little
of the time (1-2
days)
Occasionally or
a more
moderate
amount (3-4
days)
Most or all
of the time
(5-7 days)
1. I was bothered by
things that usually
don’t bother me.
   
2. I did not feel like
eating; my appetite was
poor.
   
3. I felt that I could not
shake off the blues
even with the help of
my family or friends.
   
4. I felt I was just as
good as other people.
   
5. I had trouble keeping
my mind on what I was
doing.
   
6. I felt depressed.
   
7. I felt that everything
I did was an effort.
   
8. I felt hopeful about
the future.
   
9. I thought my life had
been a failure.
   
10. I felt fearful.
   
11. My sleep was
restless.
   
12. I was happy.
   
13. I talked less than
usual.
   
14. I felt lonely.
   

53
15. People were
unfriendly.
   
16. I enjoyed life.
   
17. I had crying spells.
   
18. I felt sad.
   
19. I felt that people
disliked me.
   
20. I could not get
“going.”
   

54
APPENDIX D

RUMINATIVE RESPONSES SCALE

 People think and do many different things when they feel sad, blue, or depressed.
 Please indicate if you never, sometimes, often, or always think or do each one when
you feel down, sad, or depressed.
 Please indicate what you generally do, not what you think you should do.

When you feel down, sad, or
depressed, you:
Never Sometimes Often Always
1. Think about how alone you
feel.
   
2. Think “I won’t be able to do
my job if I don’t snap out of this.”
   
3. Think about your feelings of
fatigue and achiness.
   
4. Think about how hard it is to
concentrate.
   
5. Think “What am I doing to
deserve this?”
   
6. Think about how passive and
unmotivated you feel.
   
7. Analyze recent events to try to
understand why you are
depressed.
   
8. Think about how you don’t
seem to feel anything anymore.
   
9. Think “Why can’t I get going?”
   
10. Think “Why do I always react
this way?”
   
11. Go away by yourself and
think about why you feel this
way.
   
12. Write down what you are
thinking and analyze it.
   
13. Think about a recent situation,
wishing it had gone better.
   
14. Think “I won’t be able to
concentrate if I keep feeling this
way.”
   
15. Think “Why do I have
problems other people don’t
have?”
   

55
16. Think “Why can’t I handle
things better?’
   
17. Think about how sad you feel.
   
18. Think about all your
shortcomings, failings, faults, and
mistakes.
   
19. Think about how you don’t
feel up to doing anything.
   
20. Analyze your personality to
try to understand why you are
depressed.
   
21. Go someplace alone to think
about your feelings.
   
22. Think about how angry you
are with yourself.
   

56
APPENDIX E

NEGATIVE MOOD REGULATION SCALE

The Attitude Toward Feelings Scale
This is a questionnaire to find out what people believe they can do about upsetting
emotions and feelings. Please answer the statements by giving as true a picture of your
own beliefs as possible. Of course, there are no right or wrong answers. Remember,
the questionnaire is about what you believe you can do, not about what you actually or
usually do. Be sure to read each item carefully and show your beliefs by marking the
appropriate response.

If you strongly disagree with an item, fill in the bubble under “Strongly disagree.”
Mark the bubble under “Mildly disagree” if you think the item is more generally
untrue than true according to your beliefs. Fill in the bubble under “Agree and
disagree equally” if you feel the item is about equally true and untrue. Fill in the
bubble under “Mildly agree if you think the item is more true than untrue. If you
strongly agree with an item, fill in the space marked “Strongly agree.”

57

When I’m upset, I believe
that…
Strongly
disagree
Mildly
disagree
Agree and
disagree
equally
Mildly
agree
Strongly
agree
1. I can usually find a way to
cheer myself up.
    
2. I can do something to feel
better.
    
3. Wallowing in it is all I can
do.
    
4. I’ll feel okay if I think
about more pleasant times.
    
5. Being with other people
will be a drag.
    
6. I can feel better by treating
myself to something I like.
    
7. I’ll feel better when I
understand why I feel bad.
    
8. I won’t be able to get
myself to do anything about
it.
    
9. I won’t feel much better by
trying to find some good in
the situation.
    
10. It won’t be long before I
calm myself down.
    
11. It will be hard to find
someone who really
understands.
    
12. Telling myself it will
pass will help calm me down.
    
13. Doing something nice for
someone else will cheer me
up.
    
14. I’ll end up feeling really
depressed.
    
15. Planning how I’ll deal
with things will help.
    
16. I can forget about what’s
up upsetting me pretty easily.
    
17. Catching up with my
work will help calm me
down.
    
18. The advice friends give
me won’t help me feel better.
    
19. I won’t be able to enjoy
    

58
the things I usually enjoy.
20. I can find a way to relax.
    
21. Trying to work the
problem out in my head will
only make it seem worse.
    
22. Seeing a movie won’t
help me feel better.
    
23. Going out to dinner with
friends will help.
    
24. I’ll be upset for a long
time.
    
25. I won’t be able to put it
out of my mind.
    
26. I can feel better by doing
something creative.
    
27. I’ll start to feel really
down about myself.
    
28. Thinking that things will
eventually be better won’t
help my feel any better.
    
29. I can find some humor in
the situation and feel better.
    
30. If I’m with a group of
people, I’ll feel “alone in the
crowd.”
    

59

APPENDIX F

BACKGROUND DEMOGRAPHICS QUESTIONNAIRE

Background Demographics Questionnaire
(All information will remain confidential)

1) Age: _____ yrs.

2) Sex: _____ F _____ M

3) Year in USC: _____ First Year
_____ Sophomore
_____ Junior
_____ Senior
_____ Graduate Student

4) Your ethnicity (please check only one choice that you feel is the most appropriate to
you or use “other” to elaborate):
_____ Asian
_____ Black
_____ Hispanic
_____ Indian
_____ Middle-Eastern
_____ White
_____ Other (please
describe):_______________________________________

5) Is English your native language? Yes ______
No (what is your native language?):___________

6) What is the primary language used in your home? -
_____________________________________

60
7) Are you currently taking any anti-depressants (e.g. Paxil, Zoloft, Prozac)?
No_________
Yes (what anti-depressants are you currently taking?)________________

Abstract (if available)

Abstract Although research on depression and memory has been varied, examining depression related to impairment of recall as well as facilitated recall of negative information, few studies have sought to examine both phenomena in the same experimental framework.

Linked assets

University of Southern California Dissertations and Theses

Conceptually similar

PDF

Deficits in selective attention and biases in valenced information processing in depression

PDF

Assessing therapeutic change mechanisms in motivational interviewing using the articulated thoughts in simulated situations paradigm

PDF

In-flight turbulence: an articulated thoughts in simulated situations (ATSS) paradigm investigation of air travelers ' experiences

PDF

Exploring experiences of minority-stress and alcohol use among sexual minorities using articulated thoughts in simulated situations: a proof of concept study

PDF

Personalized normative feedback applied to undergraduates with problem drinking: a comparison with psychoeducation and an examination of cognitive-affective change mechanisms via the articulated ...

PDF

The articulated thoughts of heterosexual male college students in reaction to anti-gay hate speech

PDF

Reacting to the negative consequences of your decisions: an ATSS comparison of cognitive and affective reactions in older versus younger adults

PDF

Age differences in jealousy: an ATSS examination of the role of attributions in the emotional reactions of older and younger adults in relationship-threatening situations

PDF

Aging and emotion regulation in the judgment of facial emotion

PDF

Dementia, co-morbid depressive symptoms, and mortality in older adults: a twin study

Asset Metadata

Creator Hsu, Kean Jia Jiann (author)

Core Title Memory, gender, and rumination in depression: recall of simulated situations with articulated thoughts and the Rivermead behavioral memory test

School College of Letters, Arts and Sciences

Degree Master of Arts

Degree Program Psychology

Publication Date 05/09/2009

Defense Date 09/30/2008

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag ATSS,Depression,memory,mood congruent memory,OAI-PMH Harvest,RBMT,rumination

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Davison, Gerald C. (committee chair), Knight, Bob G. (committee member), Walsh, David A. (committee member)

Creator Email keanhsu@usc.edu,keanjhsu@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m2223

Unique identifier UC1104123

Identifier etd-Hsu-2791 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-236066 (legacy record id),usctheses-m2223 (legacy record id)

Legacy Identifier etd-Hsu-2791.pdf

Dmrecord 236066

Document Type Thesis

Rights Hsu, Kean Jia Jiann

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu