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Factors affecting postpartum depression severity

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Title:
Factors affecting postpartum depression severity the role of sleep disturbance and marital distress
Creator:
Lillis, Teresa A
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Language:
English
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x, 41 leaves : ; 28 cm

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Subjects / Keywords:
Postpartum depression ( lcsh )
Sleep disorders ( lcsh )
Spouses ( lcsh )
Distress (Psychology) ( lcsh )
Distress (Psychology) ( fast )
Postpartum depression ( fast )
Sleep disorders ( fast )
Spouses ( fast )
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bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

Notes

Bibliography:
Includes bibliographical references (leaves 27-37).
General Note:
Department of Psychology
Statement of Responsibility:
by Teresa A. Lillis.

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|University of Colorado Denver
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|Auraria Library
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All applicable rights reserved by the source institution and holding location.
Resource Identifier:
656365729 ( OCLC )
ocn656365729
Classification:
LD1193.L645 2010m L54 ( lcc )

Full Text
FACTORS AFFECTING POSTPARTUM DEPRESSION SEVERITY:
THE ROLE OF SLEEP DISTURBANCE AND MARITAL DISTRESS
by
Teresa A. Lillis
B.A., Gonzaga University, 2007
A thesis submitted to the
University of Colorado Denver
in partial fulfillment
of the requirements for the degree of
Master of Arts
Clinical Psychology
2010


This thesis for the Masters of Arts
degree by
Teresa A. Lillis
has been approved
by
Peter Kaplan
Elizabeth Allen
AUrc<\ ^ %o(Q
Date


Lillis, Teresa, A. (Master of Arts, Clinical Psychology).
Factors Affecting Postpartum Depression Severity: The Role of Sleep
Disturbance and Marital Distress.
Thesis directed by Associate Professor Peter Kaplan, Ph.D.
ABSTRACT
Postpartum depression (PPD) is the most common problem women
experience in the postpartum period. Despite the dire physiological and
psychological consequences PPD can cause for both mother and baby, it often
goes undiagnosed or undetected. Accordingly, screening for PPD and isolating
symptoms that contribute to a robust presentation of the disorder are of particular
importance. The current study examined Sleep Disturbance and Marital Distress
as predictors of depression symptom level severity based on depression screens in
the postpartum period. Additionally, this study investigated how mothers who
were diagnosed with depression differed in terms of diagnostic severity on the
basis of these variables.
Both Sleep Disturbance and Martial Distress significantly predicted
greater depression symptom level severity on the Postpartum Disorder Screening
Scale (PDSS) and Beck Depression Inventory-11 (BDI-I1). Mothers who had a
diagnosis of depression did not differ significantly in terms of Diagnostic Severity
based on Sleep Disturbance or Marital Distress.


This study contributes to the existing literature on Sleep Disturbance and
Marital Distress as predictors of depression in the postpartum period. Although
the women in this sample who were diagnosed with depression did not differ
significantly based on these variables, future research could replicate this study
with a larger sample size in order to determine how Sleep Disturbance and
Marital distress affect women who have already been diagnosed with depression.
This abstract accurately represents the content of the candidates thesis. I
recommend its publication.
Signed
Peter Kaplan.


DEDICATION PAGE
I would like to dedicate my thesis to my parents, Sharon and Pat Lillis, and my
brother and sisters, Joe, Erin and Kate Lillis. Their extraordinary support and
unwavering interest in my scholarly activity has sustained the success I have
achieved thus far and has motivated me to continue on my academic journey
through psychology.
I would also like to dedicate my thesis to the mothers I worked with at The
Postpartum Depression Intervention Program at The Childrens Hospital of
Denver. Their bravery in and willingness to share their stories has not only
informed this research, but has also motivated me to continue studying PPD in my
professional career in hopes of better preventing, detecting and treating this
disorder.


ACKNOWLEDGMENT
I would like to thank Dr. Kaplan for his continued guidance over the past year
with this project in addition to his eagerness to allow me access to his data and
support in pursuing my questions through his study. I would also like to extend
my appreciation to Dr. Elizabeth Allen and Dr. Jennifer Elamed-Adams for their
support, lending of expertise and thoughtful suggestions across the completion of
my thesis. Finally, I would like to thank Dr. Jennifer Paul and Dr. Brian Stafford
for the opportunity to work in the Postpartum Depression Intervention Program at
The Childrens Hospital of Denver over the past year; their willingness to take me
on as a therapist for the program allowed me unparalleled access to my population
of interest and provided me with an informed perspective for this research.


TABLE OF CONTENTS
TABLES...............................................................x
CHAPTER
1. INTRODUCTION................................................1
Postpartum Depression (PPD).............................2
Sleep Disturbance in PPD................................3
Dyadic Adjustment During the Transition to Parenthood...5
Screening for PPD.......................................7
Rational For Current Study..............................9
2. METHOD....................................................11
Participants...........................................11
Procedure..............................................12
Measures...............................................12
Postpartum Depression Screening Scale (PDSS).....12
Beck Depression Inventory-II (BDI-II)............14
Dyadic Adjustment Scale (DAS-7)..................15
SCID DSM-IV-TR Diagnoses.........................16
Analyses...............................................16
3. RESULTS...................................................19
viii
Multiple Regressions
19


MANOVA
.20
4. DISCUSSION...........................................22
Limitations........................................24
Summary............................................25
REFERENCES....................................................27
IX


LIST OF TABLES
Table
1.1 Intercorrelation Between Scores of Depression and Scores of Sleep
Disturbance and Marital Distress.........................................38
1.2 Stepwise Multiple Regression of Sleep Disturbance and Marital Distress
Predicting Depression Symptom Level Severity on the PDSS.................39
1.3 Stepwise Multiple Regression of Sleep Disturbance and Marital Distress
Predicting Depression Symptom Level Severity on the BDI-II...............40
1.4 MANOVA Means and Standard Deviations for Diagnostic Severity on the
basis of Sleep Disturbance and Marital Distress..........................41
x


CHAPTER 1
INTRODUCTION
The birth of a child is often a joyous time for new mothers. However, for
those whole develop postpartum depression (PPD), it can be a particularly dark and
nightmarish experience (Runquist, 2007). PPD is the most common postpartum
problem, occurring in roughly 10- 15% of childbearing women worldwide (Sword,
Busser, Ganann, McMillan, & Swinton, 2008; Beck & Gable, 2002; OHara & Swain,
1996) and in an estimated half-million American women (Beck & Gable, 2001;
Wisner, Parry, & Piontek, 2002). The physical and psychological stress from labor,
delivery and the new demands of motherhood increase the likelihood of a mother
experiencing a depressive episode (Cox et al., 1993; Runquist, 2007b). Although PPD
often has dire psychological and physical consequences for the mother, it also imbues
developmental risks on her infant, specifically in the areas of cognitive, social and
emotional development (Sohr-Preston & Scaramella, 2006; Kim, Hur, Kim, Oh, &
Shin, 2008).
Despite being considered a major public health concern, PPD frequently goes
undiagnosed or undetected (Hanusa, Scholle, Haskett, Spadaro, & Wisner, 2008) and
many women suffer the effects of the disorder in silence, shameful of their violated
expectations of motherhood as a joyous time (Jolley, Elmore, & Barnard, 2009).
Accordingly, adequate screening is of particular importance (Beck & Gable, 2005;
1


Rychnovsky, 2006; Hanna, Jarman, & Savage, 2004; Hanusa et al.).
Postpartum Depression (PPD)
PPD is distinguished from the baby blues that roughly 50- 70% of mothers
report experiencing (Andrews-Fiske, 1999). The baby blues are characterized by a
mildly depressed mood that develops between the first and fourth postpartum day,
often as a result of the flux in hormone levels (Gonidakis, Rabavilas, Varsou,
Kreatsas, & Christodoulou, 2007) and typically dissipates within the first two weeks.
PPD, on the other hand, is characterized by a more severely depressed mood,
including irritability, crying spells, fatigue, sleep disturbance, anxiety, poor
concentration and loss of sense of self (Silverman et al., 2007). These symptoms can
manifest as early as two weeks and as late as one year, but usually peak between the
sixth and twelfth postpartum week (Posmontier, 2008). The Diagnostic and Statistical
Manual for Mental Disorders (APA, 2000) diagnostic criteria for PPD are the same as
for a major depressive episode, but are limited to occurring between the first and
twelfth month postpartum period and are coded with a modifier for postpartum onset.
Although the precise etiology of PPD is unclear, specific risk factors have
been identified, as have been variables that can exacerbate and lengthen the disorder.
The most salient risk factor for PPD is a history of depression (Hobfol, Ritter,
Hilsizer, Cameron, & Lavin, 1995). Other factors implicated in the etiology of the
disorder include a lack of social support (OHara & Swain, 1996; Simpson, Rholes,
Campbell, Tran & Wilson, 2003; Gottman, Driver, & Tabares, 2002), stresses due to
2


infant care, recent stressful life events, and lower socioeconomic status, age and
general health (Beck, 1996). Two factors that have received substantial support in
previous literature as both predictors of and variables that maintain PPD are sleep
disturbance (Karraker & Young, 2007; Ross, Murray, & Steiner, 2005; Runquist,
2007) and marital distress (Boyce & Hickey, 2005; Beck, 2001; OHara, 1996). These
factors are particularly noteworthy as they tax the puerperal womans already limited
resources thereby rendering her more vulnerable to developing PPD and/or
aggravating existing symptamalogy.
Sleep Disturbance in PPD
In the general population, sleeping difficulties are associated with depression,
being both a precursor as well as a negative prognostic factor for the disease
(Dorheim, Bondevik, Eberhand-Gran, Bjorvatn, 2009). Frequent sleep disruption and
sleep restriction have been reliably linked with depression across several studies
(Roman, Hagewoud, Luiten, & Meerlo, 2006; Chang, Ford, Mead, Cooper-Patrick, &
Klag, 1997) and depressed individuals frequently report sleep disorders, such as
insomnia (Field, Diego, Hernandez-Reif, Figueriedo, Schanberg, & Kuhn, 2007).
Studies have shown that sleep loss leads to mood deterioration in healthy individuals
(Scott, McNaughton, & Polman, 2006) and that both circadian phase and total
wakefulness can powerfully influence subjective mood ratings (Totterdell, Reynolds,
Parkinson, & Briner, 1994). Moreover, under laboratory-controlled conditions,
3


manipulating the duration and timing of sleep episodes was found to significantly
alter self-reported mood (Wood & Magnello, 1992).
Disturbed sleep is a common occurrence in the lives of new parents (Karraker
& Young, 2007; Ross, Murray, & Steiner, 2005; Runquist, 2007) and adjusting to
both the absence of sleep and any kind of a sleep routine with a new infant can be
truly exhausting (Meltzer & Mindell, 2007). Indeed, the estimated wake time
percentages for mothers increase by roughly 20% during the first six weeks
postpartum (Horiuchi & Nishihara, 1999) and newborns that have multiple night
awakenings have been found to render more sleep deprivation, sleep fragmentation
and overall fatigue in new mothers (Stremler, Hordnett, Lee, MacMillan, Mill, &
Ongcangco, 2006). Yet beyond the task of tending to their infants night awakenings,
mothers in the postpartum period also experience decreases estrogen and
progesterone, which modulate circadian rhythm and amplitude further disrupting
sleep (Posmontier, 2008; Parry et al., 2008).
Therefore, it is not surprising that a negative mood state has been related to
increased wake time at night for first time mothers (Dorheiem et ah, 2009; Wolfson,
Crowley, Anwer, & Bassett, 2003; Meltzer & Mindell, 2007). The sleep disturbance
most mothers experience is both a risk factor for and a symptom of PPD (Andrews-
Fiske, 1999; Runquist, 2007). In fact, one study found that mothers who experienced
more sleep disturbances were almost four times as likely to be depressed (Huang,
Carter, & Guo, 2004). Some previous research has likened the experience of sleep
4


deprivation to that of PPD, such that chronic sleep deprivation in new mothers
produces symptamology very similar to PPD symptamology (Armstrong, Van
Haeringen, Dadds, & Cash, 1998). Yet, it is not just sleep deprivation that exacerbates
PPD symptamology, but deficits in sleep quality as well (Posmontier, 2008; Bozoky
& Corwin, 2002). It has been found that postpartum women experience poorer sleep
quality, less total sleep time, longer sleep latency (more time to fall asleep), less sleep
efficiency (time asleep vs. time in bed), less REM sleep and more wake after sleep
onset (WASO) (Posmontier).
Dyadic Adjustment During the Transition to Parenthood
One function of close relationships is to act as a buffer against the impact of
negative life events and to help facilitate smooth transitions during developmental
changes across the lifespan (Figueiredo, Field, Diego, Flemandez-Reif, Deeds, &
Ascencio, 2008). Yet a robust decline in marital satisfaction has been reliably
documented in previous literature during a period of considerable change: the
transition to parenthood (Doss, Rhoades, Stanley, & Markman, 2009; Cowan &
Cowan, 2000; Shapiro, Gottman, & Carrere, 2000). This decline is especially
precipitous for women as they have been found to report earlier and greater marital
dissatisfaction than men (Shapiro et al.; Gottman et al., 2002). Many studies link this
decline to the changing roles and responsibilities of new parents (Goyal, Gay & Lee,
2009), while others highlight the decrease in communication, increase in conflict,
feelings of ambivalence (Figueiredo et al.), decline in sexual intimacy (Kung, 2000)
5


and difficult infant temperament and sleeping patterns (Meijer & van den Wittenboer,
2007) . Research has also documented that decreases in dyadic-focused time and
positive experiences relevant to the dyad may additionally contribute to poor dyadic
adjustment (MacDermid, Hutson, & McHale, 1990).
Marital dissatisfaction itself has been documented as a consequence of PPD
(Hock, Schirtzinger, Lutz, & Widaman, 1995) as depressed women are more likely to
report marital dysfunction than non-depressed women (Roux, Anderson, & Roan,
2002). However, marital distress has also been found to be a risk factor for the
development of PPD (Boyce & Hickey, 2005; Beck, 2001; OHara, 1996) and
remains relatively stable even after the woman has recovered from her depression
(Stein et al., 1991, as cited in Roux et ah). Moreover, women with a history of
depression are more likely to have a relapse after the birth of a child if they are
dissatisfied with their partner (Misri, Kostaras, Fox, & Kostaras, 2000). Alternatively,
partner support and dyadic adjustment have been found to be relatively stable
protecting factors for depression vulnerability and promote more ease during the
transition to parenthood (Burke, 2003; Coyne & Benazon, 2001; Figueiredo et ah,
2008) . Additionally, husband-expressed fondness and admiration and awareness for
new mothers have been documented to lead to increases in marital satisfaction during
the transition to parenthood (Shapiro, Gottman & Carrere, 2000).
6


Screening for PPD
Despite the reported high incidence of PPD, many women suffering the
devastating effects of the disorder continue to be missed by their health professionals
(Hanna, Jarman, & Savage, 2003), and diagnoses and treatment of PPD have been
found to be at best, infrequent, and at worst, non-existent, within medical settings
(Goodman, 2004). In addition to the stigma that many mothers fear incurring if they
report their depressive feelings after giving birth, or a lack of awareness as to why
they are feeling distressed (Hanna et al.), mothers may also not report their PPD
symptamology due to low energy and lack of motivation- two hallmark symptoms of
PPD (OHara et ah, 2000). This is particularly troubling given the adverse effects
PPD can have not only on the mothers wellbeing, but also her infants (Forman,
OHara, Stuart, Gorman, Larsen, & Coy, 2007; Preston & Sohr-Scaramella, 2006).
Furthermore, without treatment, long-term physical and mental sequelae can increase
with the duration of the disorder (Hanusa et ah, 2008). Thus, early detection and
proper screening of PPD are of utmost importance as they facilitate more rapid access
to treatment (Georgiopoulos, 2001).
Though measures of depression, such as the Beck Depression Inventory-II
(Beck, Steer, & Brown, 1996) have been validated for and used to detect PPD (Beck,
1995, 1998, as cited in Beck & Gable, 2005), specific measures that exist for
assessing PPD symptamology generally provide more accurate detection (Bennett,
Einarson, Taddio, Koren, & Einarson, 2004). The Edinburgh Postnatal Depression
7


Scale (EPDS) is the most widely used scale for detecting PPD (Cox, Holden, &
Sagovsky, 1987). This 10-item self report scale assesses for PPD based on the
following dimensions of depression: inability to laugh, inability to look forward to
enjoyable things, blaming oneself unnecessarily, being anxious or worried, scared or
panicky, inability to cope, difficulty sleeping, being sad or miserable, frequent crying,
and thoughts of harming oneself (Cox et al.). It has 87% sensitivity, 78% specificity
and a 73% positive predictive value (Cox et al.; Rowley, 2002). However, the EPDS
is somewhat limited in that it does not assess PPD severity (Hanna, Scholle, &
Haskett, 2003).
The Postpartum Depression Screening Scale (PDSS) developed by Beck and
Gale (2000) also seeks to detect PPD symptamology, but does so through a longer
and more comprehensive scale. The PDSS is comprised of 35 items assessing 7
dimensions of distress and impairment related to PPD: Sleeping/Eating Disturbances,
Anxiety/Insecurity, Emotional Lability, Cognitive Impairment, Loss of Self,
Guilt/Shame, and Contemplating Harming Oneself (Beck & Gable, 2000). PDSS item
content was generated from discussions with women about their experience of PPD
from the authors first qualitative study on PPD (Beck, 1992, 1993, 1996; as cited in,
Beck & Gable, 2005). The authors reported the sensitivity and specificity of the
PDSS to detect a MDD to be comparable with that of the Structured Clinical
Interview for DSM-IV Axis I Disorders (Hanusa et al., 2008), in addition to noting
that is was more accurate in finding major and minor depression at 12-weeks
8


postpartum than both the BDI-II and EPDS (Beck and Gable, 2001). Medical
professionals and researchers alike frequently choose the PDSS because it is better
able to capture the multidimensional components of PPD than other measures
(Rychnovsky, 2006).
Rational for Current Study
Although previous research suggests that both sleep disturbance and marital
distress can influence the development and maintenance of PPD, examining these
relationships with respect to a specific screen of PPD, the PDSS (Beck & Gable,
2002) in addition to a general measure of depression, the BDI-II, has not be done.
Furthermore, examining how women with a diagnosis of depression differ in terms of
Sleep Disturbance and Marital Distress will better capture how these variables present
on the basis of diagnostic severity. Accordingly, the specific aims of this study are
twofold: (1) to determine whether greater Sleep Disturbance and Marital Distress
predict greater Symptom Level Severity (more self-reported symptoms) measured by
the PDSS and BDI-II (2) to determine whether mothers classified as depressed using
the DSM-IV criteria differ significantly in terms of Sleep Disturbance and Marital
distress based on categories of Diagnostic Severity (Mild, Moderate, Severe). My
hypotheses are as follows:
HI: Both Sleep Disruption and Marital Distress will predict greater Symptom
Level Severity measured by the PDSS and the BDI-II.
9


H2: Mothers classified as depressed using the DSM-IV criteria will differ
significantly in terms of Sleep Disturbance and Marital Distress based on the three
categories of Diagnostic Severity (Mild, Moderate, Severe).
10


CHAPTER 2
METHODS
Participants
As part of cross-sectional study to assess the effect of maternal depression on
infant learning during the first year postpartum, a community sample of 106 mothers
and infants were recruited to participate through advertisements in Colorado Parent
magazine and fliers distributed at Head Start Programs and Montessori Centers. Only
mothers with infants between the age of 3.5 and 6 months were eligible for the study.
Mothers had an average age of 29.81 (SD = 5.12, range 18- 40) and the
average age of the infants was 4.5 months (SD = 23 days, range 95- 199 days).
Approximately two-thirds of the mothers were married (75.5%) with just under half
reporting having only one child (44.3%). Just over half of the women identified
themselves as Caucasian (52.8%), with the remaining 29% as Latin/Hispanic, 9.3% as
African-American and 8.4% as Other (including Asian American, Native American,
and other). Roughly a third of the women (32.7%) reported starting college, but not
finishing, yet under half of reported having obtained a college degree (44.9%) with
15% acknowledging the completion of a Masters degree. Roughly 40% of mothers
earned a combined annual household income of greater than $50,000 with
approximately a quarter (24.6%) earning between $31,000 and $50, 000.
11


Procedure
Mothers interested in participating in the study first spoke with the study
coordinator and, after being informed of the details of the study, were given the
option to come the Infant Learning Lab at the University of Colorado Denver
Downtown Campus for a 2-hour visit. After inclusion criteria had been met, eligible
mothers were provided with a series of questionnaires to fill out, were interviewed,
and were asked to provide speech samples. Eligible infants participated in one 5-
minute test in which taped segments of parental speech signal for the infant as a slide
of a smiling face appears on a projection screen in front of the infant. Mothers were
paid $50 for each session in which they participated, whether or not they, or their
infant, completed the session. This study was fully approved by the University of
Colorado Denvers Downtown Campus Human Subjects Review Committee (HRSC).
Measures
Postpartum Depression Screening Scale (PDSS')
The PDSS (Beck & Gable, 2002) is comprised of 35 items assessing 7
dimensions of distress and impairment related to PPD; each dimension represents a
sub-scale of the total measure with five items respective to each scale that the mother
can endorse on a Likert scale (1, strongly disagree- 5, strongly agree). Total scores on
the PDSS can range from 35- 175 and breakdown into one of three interpretive
outcomes: cutoff scores for a normal postpartum adjustment are anything 59 or
below, significant symptoms of PPD reflect scores between 60 and 79, and a positive
12


screen for PPD results from scores 80 and above (Beck & Gable). The PDSS also has
a 7-item short form which is primarily used to distinguish women at more of an
elevated risk for PPD; examinees with scores above 14 on the short form are give the
remaining 28 items for symptom and severity exploration (Hanusa et al, 2008).
The content validity of the PDSS is based empirical literature, expert
reviewers and focus groups (Beck and Gable, 2001). Validity and reliability were
established from a sample of 525 women and confirmatory factor analysis and item
response theory techniques provided additional support for 7 sub-scales (Hanna et al,
2004; Beck & Gable). For the 7 dimensions, alpha internal consistency reliabilities
ranged from .83- 94 (Beck and Gable) and the total scale reliability garnered was .97
(Beck & Gable, 2002).
Scores for assessing Sleep Disruption in this study were generated by isolating
three items on the PDSS pertaining to sleep and totaling those item scores for each
individual. The scores for this Sleep Disruption variable could range from 3- 15 with
scores of 9 or above denoting the presence of sleep disruption. Cutoff scores for the
Sleep Disruption variable were generated by modeling cutoff scores from the
Sleep/Eating Disturbances sub-scale of the PDSS. Sleep Disruption scores were
subtracted from the total overall score of the PDSS for each participant. The average
sleep disruption score for the sample was 8.52 (SD = 3.78, range 3- 15).
Scores for assessing PDSS Symptom Level Severity in this study were
generated from the PDSS total overall score (with sleep item values subtracted). The
13


average total overall score was 69 (SD 24.98, range 32- 133). Participants overall
scores were further categorized into the three interpretive outcome categories for the
PDSS: 37% of women were categorized as having normal adjustment, 24% as having
significant symptoms of PPD and 34% as having a positive screen for PPD.
Beck Depression Inventory II (BDI-I1)
The Beck Depression Inventory (BDI-II; Beck, Steer & Brown, 1996)
assesses 21 symptoms of depression relative to the DSM-IV diagnostic criteria.
Symptoms include sadness, pessimism, past failure, loss of pleasure, guilty feelings,
punishment feelings, self-dislike, self-criticalness, suicidal thoughts or wishes, crying,
loss of interest, indecisiveness, changes in sleeping pattern, irritability, changes in
appetite, tiredness or fatigue, loss of interest in sex, agitation, worthlessness, and
concentration difficulty. Symptoms are measured on a 4 point scale with range of 0 -
3. Cutoff scores for the BDI-II are any scores 13 and above denoting the presence of
depression and scores 12 or below denoting an absence of depression.
Psychometrics of the BDI-II were generated from a sample of 500 psychiatric
outpatients (alpha = .92) and a sample of 120 college students (alpha = .93) (Beck,
Steer, & Brown, 1996). Dozois, Dobson, and Ahnberg (1998) examined the
sensitivity and specificity of the BDI-II in a sample of 1,022 college students and
found .81 and .92, respectively. Despite the ubiquity of the measure, the BDI-II is not
as readily used to assess PPD due to the overlap in symptoms of depression with
symptoms of being a new mother (Huffman, Lamour, Bryan, & Pederson, 1990).
14


Scores for assessing BDI-II Symptom Level Severity were taken from the
BDI-II total score. The average total BDI-II score for the sample was 13.86 (SD =
8.78, range 0- 38). Additionally, the majority of the sample was not classified as
depressed, based on the BDI-II cutoff scores; 56% of the women garnered a score of
12 or less while 43% had a score of 13 or more.
Dyadic Adjustment Scale 7 (DAS-7)
The DAS-7 was adapted from Spaniers (1976) 32-item DAS, which provides
a multidimensional view of marriage based on four sub-scales: Dyadic Consensus,
Satisfaction, Cohesion and Affective Express. The full DAS is currently the most
widely used scale to assess marital functioning (Glenn, 1990; Touliatos, Perlmutter,
& Straus, 1990, as cited in Hunsely, et al., 2001). A short form of the DAS, the DAS-
7, was created by extracting three items pertaining to dyadic consensus, three items
pertaining to dyadic cohesion and one item assessing global dyadic satisfaction
(Sharpley & Cross, 1982). The DAS-7 has demonstrated alpha reliability estimates in
the .76 range, inter-item correlations ranging from .34 to .71, and criterion validity
such that the scale was able to distinguish married, separated and divorced
participants (Hunsely et al.). The DAS-7 also demonstrated considerable construct
validity (a=.82) with other measures of relationship satisfaction. Hunsely et al.
suggested cutoff scores for the DAS-7 as anything below 19 being categorized as
distressed and anything above a 26 as non-distressed. Scores for assessing Marital
15


Distress in this study were generated from the DAS-7 total score. The average DAS-7
total score for the sample was 24 (SD = 7, range 0- 36).
SCID DSM-IV Diagnoses
In order to determine diagnoses of depression, women were administered a
Structured Clinical Interview for DSM-IV Diagnoses (SCID; Diagnostic and
Statistical Manual of the American Psychiatric Association, 2000). This was the only
method available to make valid clinical diagnoses for the study. The SCID is
comprised of 5 sections which provide information on: A: Mood Episodes; B:
Psychotic and associated symptoms; C: Differential Diagnosis of Psychotic
Disorders; D: Mood Disorders; E: Alcohol and other substance use disorders; F:
anxiety and other disorders. SCID interviews were conducted by M.A.-level clinical
psychologists and trained Research Assistants from the University of Colorado
Denver. From the sample of 106 women, 13 were diagnosed as depressed (12% of
sample). In terms of severity of depression levels, four women were classified as
having mild depression (5 of 9 DSM-IV criteria symptoms), 3 as having moderate
depression (7 of 9 DSM-IV criteria symptoms) and 6 as having severe depression (9
of 9 DSM-IV criteria symptoms).
Analyses
The following analyses were conducted using SPSS 16.0. In order to first
determine whether subsequent effects could be due to influences of demographic
variables, a preliminary bivariate correlation was conducted between mothers age,
16


income, ethnicity, and education with the impendent variables Sleep Disruption and
Marital Distress. Additionally, a preliminary multivariate analysis of variance
(MANOVA) was conducted in order to determine whether mothers with differing
levels of Diagnostic Severity differed significantly on the basis of the aforementioned
demographic variables.
Second, in order to determine whether a relationship between Sleep
Disruption and PDSS Symptom Level Severity and Marital Distress and PDSS
Symptom Level Severity and BDI-II Symptom Level Severity existed, a second
bivariate correlation was conducted.
Following these correlations, three main analyses were conducted. The first
was a multiple linear regression. Two continuous independent variables were entered
in a stepwise manner: (1), Sleep Disturbance was measured by isolating and
combining the items from the PDSS questions pertaining to sleep from the
Sleep/Eating Disturbances sub-scale; (2) Marital Distress was measured by the DAS-
7 total scores. The analysis was then repeated with Marital Distress entered first and
Sleep Disturbance second to determine whether independent effects existed. The
continuous dependent variable, PDSS Symptom Level Severity, was measured by the
total scores from the PDSS (with the PDSS sleep item values subtracted).
The second analysis conducted was a multiple linear regression. The same
continuous independent variables were entered in identical fashion from the above-
17


mentioned analysis. The continuous dependent variable, BDI-II Symptom Level
Severity, was measured by the total scores from the BDI-II.
All assumptions for parametric tests and diagnostics for a multiple regression
were met for all independent variables and 80% power and a medium-to-large effect
were achieved through adequate sample size and number of predictor variables (Miles
and Shelvin, 2001).
The third analysis conducted was a MANOVA. The fixed factor was the
categorical variable of Diagnostic Severity (Mild, Moderate, Severe) from the DSM-
IV depression diagnosis. The dependent continuous variables were the
aforementioned Sleep Disturbance variable (measured from the sleep items on the
PDSS) and Marital Distress variable (measured from the DAS-7 totals scores).
Due to the fact that only a small subgroup of our sample had a diagnosis of
depression (N = 13), there was not enough power to detect an effect. Therefore, the
purpose of this analysis was purely descriptive in nature.
18


CHAPTER 3
RESULTS
Preliminary Correlations and MANOVA
The preliminary bivariate correlations indicated no significant relationships
between independent variables Sleep Disturbance and Marital Distress and
demographic variables of mothers age, income, ethnicity and education (all ps >
05). Additionally, the preliminary MANOVA revealed no significant differences
across all Diagnostic Severity categories on the basis of the aforementioned
demographic variables (all ps> .05).
There was a significant positive relationship between Sleep Disruption and
PDSS Symptom Level Severity, r = .578, p (one-tailed) < .01 and a significant
negative relationship between Marital Distress and PDSS Symptom Level Severity, r
= -.25, p (one tailed) < .01. There was also a significant positive relationship between
Sleep Disruption and BDI-II Symptom Level Severity, r = .558,p (one tailed) < .01
and a significant negative relationship between Marital Distress and BDI-II Symptom
Level Severity, r = -.474, p (one tailed) < .01 (Refer to Table 1.1 for complete
correlation matrix).
Multiple Regression Analyses
Stepwise multiple hierarchical regression analysis revealed that both Sleep
Disturbance and Marital Distress significantly predicted PDSS Symptom Level
19


Severity, F(3, 103) = 31.29,/? < .01. Additionally each independent variable was
found to contribute significant independent effects after switching the order of the
entry into the regression: Sleep Disturbance, F(3, 103) = 48.49,/? < .01 and Marital
Distress, F(3, 103) = 16.71 ,/? < .01 (Refer to Table 1.2 for Regression statistics with
Sleep Disturbance in Step 1). When Sleep Disturbance was entered first, it accounted
for roughly 32% of the variance while Marital Distress accounted for 6%. When
Marital Distress was entered first, it accounted for 13% of the variance while Sleep
Disturbance accounted 25%.
The second stepwise hierarchical regression analysis revealed that both Sleep
Disturbance and Marital Distress significantly predicted BDI-II Symptom Level
Severity F(3, 103) = 36.07,/? < .01. Each independent variable contributed significant
independent effects: Sleep Disturbance, F(3, 103) = 44.59,/? < .01 and Marital
Distress, F(3, 103) = 27.15,/? < .01 (Refer to Table 1.3 for Regression results with
Sleep Disturbance entered in Step 1). When Sleep Disturbance was entered first, it
accounted for 31% of the variance while Marital Distress accounted for 11%. When
Marital Distress was entered first, it accounted for 20% of the variance while Sleep
Disturbance accounted for 21%.
MANOVA
A MANOVA was conducted to investigate how women with different levels
of Diagnostic Severity differed based on the dependent continuous variables of Sleep
Disruption and Marital Distress. A non-significant overall difference was found
20


[Wilks A = .971, F(2, 13) = .066,p > .05], Refer to Table 1.4 for MANOVA means
and standard deviations.
21


CHAPTER 4
DISCUSSION
The overarching goal of this study was to investigate what contributions Sleep
Disruption and Marital Distress may have on PPD severity. Previous research has
implicated both of these constructs in the development and maintenance of PPD
(Karraker & Young, 2007; Ross, Murray, & Steiner, 2005; Runquist, 2007; Boyce &
Hickey, 2005; Beck, 2001; OHara, 1996), but they have not been explored with
respect to a specific screen of PPD: the PDSS in addition to a general measure of
depression: the BDI-II. Furthermore, examining how women with differently levels
of Diagnostic Severity differ based on Sleep Disturbance and Marital Distress
illuminates how these factors present in the diagnosis of depression versus a screen
for depression. Accordingly, this study sought to examine these variables as both
predictors of PPD and illuminators of group differences based on the DSM-IV
Diagnostic Severity categories for depression.
As predicted in HI, both Sleep Disruption and Marital Distress significantly
predicted greater PDSS and BDI-II Symptom Level Severity. Although both variables
were significant predictors, Sleep Disruption accounted for more variance than did
Marital Distress in both the PDSS and BDI-II analyses. This is not surprising given
that the majority of women in the sample were satisfied with their current relationship
(50.5%). Furthermore, because the PDSS intends to capture the unique sleep
22


disruption that many postpartum women experience through their sleep items, there
may have been additional endorsing of items that may not have panned out on other
measures of sleep (for instance, the Pittsburgh Sleep Quality Index; (PSQI) Buysse,
Reynolds, Monk, Berman, & Kupfer, 1989). However, this result could also be
interpreted as a strength of the PDSS because the PDSS may in fact have succeeded
in capturing the unique sleep disruption of postpartum women. Additionally, because
the BDI-II contains items pertaining to fatigue and sleep disruption that were not
removed from the total score, women who reported sleeping difficulties on the PDSS
likely also reported them on the BDI-II.
The second hypothesis was not supported as it was found that women with
different levels of Diagnostic Severity did not differ significantly based on Sleep
Disturbance and Marital Distress. While this result is not in accordance with what the
current literature suggests about the relative contributions of greater sleep disturbance
and more marital strife in worsening PPD severity (Huang, Carter, & Cash, 1998;
Boyce & Hickey, 2005), it is also not necessarily surprising given the small sub-
sample of women who had a diagnosis of depression (N = 13). Importantly, the three
Diagnostic Severity Categories did not differ across demographic variables of age,
ethnicity, income or education, which supports existing literature suggesting that
depression can affect all women of all races, intelligences and SES (OHara, 2009).
23


Limitations
This study is not without its limitations. The first limitation is that the study is
cross-sectional and, thus, only provides a snapshot of how sleep disruption and
marital distress can affect PPD severity. Importantly, with cross-sectional data, it is
not possible to determine whether this sample of women was experiencing PPD
symptoms before they experienced sleep disruption and marital distress. Thus, an
additional limitation of this study is the lack of determining causality from the
variables.
Another limitation of the study is the sample size and associated issues of
generalizability. This relatively small sample of 106 women, while representative of
Denver county demographics (according to the most recent Census data), may not
fully represent the broad range of women who experience PPD symptamology.
Although a substantial number of the women in the sample were categorized as
experiencing significant symptoms of PPD or having a positive screen for PPD, it is
not known whether these rates would increase or decrease with a larger and even
more diverse sample.
Finally, self-selection issues could have tainted the data garnered from this
study. Women who participated in this study could have been seeking consultation or
treatment for their PPD. Hence, data from women who might be experiencing PPD
symptoms, but are not actively seeking consultation or treatment for it, might have
differed in their presentation of PPD. Additionally, although the study sought
24


participants who were healthy and had no symptoms of PPD, the fliers noted that
researchers were especially interested in mothers with depression. Again, this could
have contributed to an oversampling of women with PPD and under sampling of
women without PPD or those who are experiencing PPD symptoms but choosing not
to seek consultation or treatment for it.
Summary
A host of factors have been implicated in the development and maintenance of
PPD, yet the role of sleep disruption and marital distress have not be examined with
respect to specific screens of PPD: the PDSS, in conjunction with a general screen of
depression: the BDI-II. By investigating the role of sleep disruption and marital
distress in PPD through the PDSS and BDI-II, early detection and prevention of PPD
through the use of the PDSS and BDI-II may increase and become more accurate.
Additionally, examining how these women who already have diagnoses of depression
differ on the basis of these factors will lead to a better understanding of what can
aggravate and making an existing diagnosis of depression more severe.
As predicted, both increases Sleep Disruption and Marital Distress
significantly contributed to increases in scores on the PDSS and BDI-II. However,
women who were diagnosed with depression did not differ in terms of Diagnostic
Severity based on Sleep Disruption and Marital Distress. Thus, for medical
professional using the PDSS and BDI-II as a screen for PPD, additional attention
should be given to the womans sleep score and questions should be asked about the
25


womans social support network, especially her partner. For women with a diagnosis
of depression, clinicians and medical professionals should still pay attention to her
sleep habits and social support networks, but assess other factors that may be
contributing to varying levels of diagnostic severity.
Future research could expand upon this study by correlating different
measures of sleep and marital functioning with the PDSS or BDI-II and investigating
the relationships between sleep quality/quantity and marital functioning
longitudinally with the PDSS and BDI-II. Additionally, examining sleep disruption
and marital distress within a larger population of puerperal women diagnosed with
depression may better illuminate the relative contributions of each variable to
diagnostic severity. Ultimately, isolating and identifying factors which contribute to
PPD severity will allow for better detection and prevention of the disorder which will
then hopefully improve the livelihood, health and well-being of new mothers and
their babies.
26


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37


TABLES
Table 1.1: Intercorrelation Between Scores of Depression and Scores of Sleep
Disturbance and Marital Distress
Measure & Score 1. 2. 3. 4.
1. BDI-II Total Score - .558** .816** .474**
2. PDSS Sleep Score .558** - .578** .274**
3. PDSS Total Score .816** .578** - -382**
4. DAS-7 Total Score ..474** -.274** _ 382** -
** p < .01 (one-tailed)
38


Table 1.2: Stepwise Multiple Regression of Sleep Disturbance and Marital Distress
Predicting Depression Symptom Level Severity on the PDSS.
B SEB P P
Step 1
Constant 37.19 5.07
PDSS Sleep Score 3.79 .54 .58* * <.01
Step 2
Constant 62.26 9.39
PDSS Sleep Score 3.36 .53 .51* * <.01
DAS-7 TotalScore -.90 .29 -.26 * <.01
Note R7 = .33 for Step 1; AR2 = .39 for Step 2 (ps < .01)
39


Table 1.3: Stepwise Multiple Regression of Sleep Disturbance and Marital Distress
Predicting Depression Symptom Level Severity on the BDI-II.
B SEB P P
Step 1 Constant 3.04 1.81
PDSS Sleep Score 1.30 .20 .56* * <.01
Step 2 Constant 15.17 3.22
PDSS Sleep Score 1.10 .18 .47* * <.01
DAS-7 Total Score -.45 .10 -.35* *<.01
Note R2 = .31 for Step 1; A R2 = .43 for Step 2 {ps < .01)
40


Table 1.4: MANOVA Means and Standard Deviations for Diagnostic Severity on the basis of Sleep Disturbance and Marital Distress
Diagnostic Severity Category Mean PDSS Sleep Score (SD) Mean DAS-7 Total Score (SD)
Mild 10.50 24.25
(3.87) (5.85)
Moderate 11.67 22.00
(5.77) (12.12)
Severe 11.00 22.33
(3.69) (4.13)
41