Couples’ neuroendocrine activity in response to family conflict discussions: the role of self-reported anger and previous marital aggression

PDF

Download

Open document

Flip pages

Summarize

Download a page range

Download transcript

Copy asset link

Request this asset

Transcript (if available)

Content COUPLES’ NEUROENDOCRINE ACTIVITY IN RESPONSE TO FAMILY
CONFLICT DISCUSSIONS: THE ROLE OF SELF-REPORTED ANGER AND
PREVIOUS MARITAL AGGRESSION

by
Aubrey Joy Rodriguez

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

August 2010

Copyright 2010 Aubrey Joy Rodriguez

ii
Table of Contents
List of Tables iii
List of Figures iv
Abstract v
Chapter 1: Background and Significance 1
Marital Quality and Health 1
Marital Quality and Physiological Reactivity 2
Self-Reported Emotional Arousal and Physiological Reactivity 3
Spouse-Reported Emotional Arousal and Physiological Reactivity 5
Marital Aggression and Physiological Reactivity 6
The Present Study 7

Chapter 2: Experimental Design and Methods 8
Participants 9
Procedures 11
Cortisol Measures 12
Questionnaire Measures

Chapter 3: Results 15
Chapter 4: Discussion 34
Sex Differences in Physiological Reactivity 35
The Role of Marital Aggression in Physiological Reactivity 39
Limitations 40
Summary 41
References 42
iii

List of Tables
Table 1: Descriptive Statistics for Cortisol, Marital Aggression, 15
and Discussion Anger
Table 2: Nonparametric Correlations Among Marital Aggression, 17
Husbands’ and Wives’ Anger, and Husbands’ and Wives’ Cortisol

Table 3: Husbands’ and Wives’ Means, by Own Self-Reported Anger, 19
on Cortisol Measures and ANOVA Summary

Table 4: Husbands’ and Wives’ Means, by Partner’s Self-Reported Anger, 21
on Cortisol Measures and ANOVA Summary

Table 5: Couples’ Marital Aggression Moderating the Relation Between 27
Own Anger and Cortisol Levels Using HLM

Table 6: Couples’ Marital Aggression Moderating the Relation Between 30
Partner’s Anger and Cortisol Levels Using HLM
iv
List of Figures

Figure 1: Husbands’ Average Cortisol Curves by Own Anger Group 20

Figure 2: Wives’ Average Cortisol Curves by Own Anger Group 20

Figure 3: Husbands’ Average Cortisol Curves by Wives’ Anger Group 22

Figure 4: Wives’ Average Cortisol Curves by Husbands’ Anger Group 22

Figure 5: The Moderation of the Association Between Husbands’ Anger 28
and Husbands’ Cortisol by Marital Aggression (HLM)

Figure 6: Husbands’ Average Cortisol Curves for Groups 29
Defined by Median Splits on Husbands’ Anger
& Couple Aggression

Figure 7: The Moderation of the Association Between Wives’ Anger 32
and Husbands’ Cortisol by Marital Aggression (HLM)

Figure 8: Husbands’ Average Cortisol Curves for Groups 33
Defined by Median Splits on Wives’ Anger
& Couple Aggression
v
Abstract
This study investigated whether wives’ and husbands’ hypothalamic-pituitary-
adrenocorticol (HPA) axis activity, as measured through cortisol, is associated with their
own and their partner’s anger during a family conflict discussion, and whether previous
marital conflict alters the HPA axis response. Fifty-six middle-aged couples provided 4
saliva samples: immediately following a relaxation task, immediately following a
conflict discussion, 10 minutes post-discussion, and 20 minutes post-discussion. The
spouses also reported on anger they experienced during the conflict discussion and
frequency of marital aggression during the past year. Husbands reporting high anger
showed greater overall cortisol activity than husbands reporting no anger. Wives
reporting high anger did not show similar cortisol activity. Previous marital conflict
interacted with discussion-specific anger. There is evidence of a trend such that husbands
with low anger and low previous aggression did not show the same post-discussion
cortisol increase as did husbands with previous aggression or with current anger. The
implications of these findings for relational functioning and health are discussed in light
of the commonality of family conflict as an everyday stressor.
1
Background and Significance
Marital Quality and Health
Married individuals generally reap considerable health and relational benefits
from their relationship status (Johnson, Backlund, Sorlie, & Loveless, 2000); however, a
disssatisfying marital relationship can increase the risk of negative outcomes (Graham,
Christian, & Kiecolt-Glaser, 2006). Some of the observed effects of poor marital quality
include diminished immune functioning, poorer mental health, and cardiovascular disease
(Kiecolt-Glaser et al., 1993; Whisman, 1999; Coyne, Rohrbaugh, Shoham, et al., 2001).
The relationship between marriage and physical and mental health outcomes is evidently
complex, and low-quality marriages seem to not only fail to provide the typical health
benefits of marriage, but may themselves be sources of physical and psychological strain
(Burman & Margolin, 1992; Whitson & El-Sheikh, 2003; Hetherington, 1993). The
exact mechanisms by which “poor” marriages contribute to negative outcomes for
individuals are only beginning to be examined and understood. One hypothesized
mechanism by which the stress of marriage enters the body is through neuroendocrine
stress-response systems such as the hypothalamic-pituitary-adrenocortical (HPA) axis.
Because the HPA axis is responsive to anger (al’Absi, Bongard, & Lovallo, 2000), anger
toward a marital partner might elicit HPA axis responses. In the present study, we use
family conflict discussions as a way to examine the association between anger and short-
term HPA activity in husbands and wives. We also examine whether marital aggression
experienced over the past year changes HPA activity in response to this common
everyday stressor.
2
Marital Conflict and Physiological Reactivity
Studies that involve marital conflict interactions in laboratories show bidirectional
relationships between marital quality/satisfaction and various indices of physiological
activity, such that couples who report lower marital satisfaction show enhanced
physiological reactivity during conflict (Kiecolt-Glaser et al., 1997) and that high levels
of observed reactivity to an in-lab conflict discussion predict declines in marital
satisfaction over time (Gottman & Levenson, 1985; Kiecolt-Glaser et al., 2003). These
findings indicate that couples’ physiological reactivity to conflict is related to the quality
of their marriages, and suggests that this quantifiable response to discrete marital events
(i.e., conflict) may explain some of the relationship between marital quality and the
bodily regulatory and response processes.
The hypothalamic-pituitary-adrenocortical (HPA) axis is one of the biological
systems implicated in the human body’s response to stress; it is the slower hormonal
response which accompanies the faster action of sympathetic nervous system. When
confronted with a stressor, the HPA axis stimulates the release of adrenocorticotropin
hormone (ACTH), which in turn stimulates production of cortisol by the adrenal cortex.
Cortisol increases conversion of stored fat and the release of glucose to provide energy
necessary for “fight-or-flight” responses, and is also strongly linked to immune
functioning (Loving, Heffner, & Kiecolt-Glaser, 2006). In healthy individuals, cortisol
shows a diurnal pattern with a peak shortly after awakening and a decline throughout the
day (Lovallo & Thomas, 2000); in response to acute stressors, the system shows an
increase in cortisol occurring 5-20 minutes after stressor onset (Kirschbaum &
3
Hellhammer, 1994). Although there is considerable variability in cortisol functioning
across individuals (Smyth, Ockenfels, Gorin et al., 1997), deviations from the normal
diurnal pattern (Lauc, Zvonar, Vuksic-Mihaljevic, & Flogel, 2004; Spiegel & Giese-
Davis, 2003) and the acute response pattern (Michaud, Matheson, Kelly, & Anisman,
2008) have been linked to chronic stress and health outcomes.
In reviews of physiological responses to laboratory marital conflict tasks, Kiecolt-
Glaser and colleagues (Kiecolt-Glaser & Newton, 2001; Robles & Kiecolt-Glaser, 2003)
concluded that marital disagreements are reliably linked to changes in endocrine
functioning. Kiecolt-Glaser and colleagues have examined endocrine responses to
discrete behaviors of husbands and wives during laboratory-based conflict discussions,
and have found relationships between negative and hostile behaviors and increased
output of cortisol (Malarkey, Kiecolt-Glaser, Pearl, & Glaser, 1994; Heffner et al., 2006).
In studies with both newly-weds (Kiecolt-Glaser, et al., 1993) and older adults (Kiecolt-
Glaser et al., 1997), wives’ physiological changes during conflict discussions are more
persistent and more closely linked to observed conflict behaviors. The present study
examines spouses’ endocrine activity in middle adulthood and in the context of a family
discussion with a child present. In addition, the present study examines the association
between self-reported anger and endocrine responses.
Self-Reported Emotional Arousal and Physiological Reactivity
Studies based primarily on diurnal patterns of HPA activity show links between
subjective distress, mood, and negative affect and indices of HPA axis function (e.g.,
Pollard, Ungpakorn, Harrison, & Parkes, 1996; Saxbe & Repetti, 2010; Saxbe, Repetti, &
4
Nishina, 2008). A recent meta-analysis (Miller, Chen, & Zhou, 2007) found evidence that
higher subjective ratings of chronic distress were linked to changes in diurnal HPA
functioning, including lower morning cortisol, higher afternoon/evening cortisol, and
higher daily cortisol output. More nuanced support for effects of emotion on diurnal
cortisol responses is found in experience sampling studies that assess momentary
fluctuations in mood and cortisol across the day (incorporating both tonic diurnal patterns
and acute phasic responses). These studies (e.g., Adam, 2005; Jacobs, Myin-Germeys,
Derom, Delespaul, van Os, & Nicolson, 2007) find that momentary experiences of
negative emotions are associated with increases in cortisol relative to the expected diurnal
slope. Among these investigations, there is evidence that the association between
negative emotion and increased cortisol secretion is stronger for men (Adam, 2005).
In contrast to findings on diurnal patterns of cortisol, the link between the
psychological experience of distress and physiological reactivity to acute stressors is not
uniformly supported in the literature. A meta-analysis of studies involving acute
stressors (Dickerson & Kemeny, 2004) failed to find evidence of a link between general
ratings of psychological distress (including perceived stress, negative affect, and arousal)
and cortisol reactivity. Researchers found that neither subjective reports of distress nor of
negative affect were associated with cortisol reactivity. More generally, subjective
ratings of psychological distress can be discordant with physiological reactivity data,
particularly for women (Levenson, Carstensen, & Gottman, 1994; Collins &
Frankenhauser, 1978).
5
Evidence for specific emotional responses and cortisol reactivity in acute stress
paradigms is more promising than for global measure of emotional distress. Denson,
Spanovic, and Miller’s (2009) meta-analysis of laboratory mood- and stress-induction
studies provides support for the integrated specificity model (Ax, 1953; Dickerson,
Gruenewald, & Kemeny, 2004), which suggests that specific emotions (e.g., anger,
sadness, fear) are coupled with specific physiological response profiles. Based on this
model, specific emotions are more likely to be linked to cortisol reactivity than are the
global dimensions of emotion (e.g., valence) often assessed in self-report subjective
distress measures because such measures collapse across multiple distinct emotions that
may exert opposite effects on the HPA response system. In support of this model, anger,
and related negative, high arousal emotions (e.g., hostility) have been consistently related
to increased cortisol secretion (Suarez, Kuhn, Schanberg, Williams, & Zimmerman,
1998; al’Absi, Bongard, & Lovallo, 2000). In light of the importance of emotion-
specificity, the present study focuses on spouses’ reports of anger-related emotions and
HPA activity.
Spouse-Reported Emotional Arousal and Physiological Reactivity
Marital conflict interactions differ from other acute stress paradigms in that
spouses may be influenced not only by their own subjective experience, but also by that
of the partner. The transmission or crossover of negative emotion and distress between
spouses is a prominent finding in the marital literature, with negative emotions more
readily transmitted between spouses than positive emotions (Chan & Margolin, 1994;
Larson & Almeida, 1999; Song, Foo, & Uy, 2008; Saxbe & Repetti, 2010). According to
6
Westman et al. (2008), emotional transmission reflects several mechanisms: empathy
with the partner, shared experience of stress, and (indirectly) through negative behaviors
that result from (or communicate) a spouse’s negative mood. Thus, emotional
transmission may be particularly likely among marital partners who have years of
experience observing and responding to one’s another’s emotional states. In the present
study, we examine the transmission of emotional affect to the partner’s physiological
arousal, that is, whether one partner’s self-reported anger is associated with the other’s
HPA activity.
Marital Aggression and Physiological Reactivity
A couple’s history with previous marital aggression may alter the way a couple
approaches and responds to later conflict discussions, although it is not necessarily clear
whether a couple would become sensitized or desensitized to future conflict. The data
thus far examining marital aggression and physiological reactivity in laboratory conflict
discussions suggest that husbands who have been maritally aggressive report more
physiological arousal during conflict discussions (Margolin, 1988) and, for the most part,
show increased heart rate reactivity (Gottman, Jacobson, Rushe, & Shortt, 1995). Wives
in relationships with domestic violence, compared to those in non-aggressive marriages,
also show greater heart rate reactivity (Jacobson et al, 1994). These data thus suggest
that previous aggression in marriage tends to sensitize spouses to later marital conflict but
this question has not been assessed in terms of HPA axis activity. The present study
further examines this question by exploring the impact of a couple’s previous marital
aggression as a context for the association between anger and cortisol activity. Although
it is possible that previous marital aggression will be associated with an increase in
7
cortisol as an index of stress, it also is possible that, over time, repeated exposure to
marital aggression is associated with a downregulation or attenuated cortisol response
(Fries et al., 2005). The present study thus examines previous marital aggression as a
context for stress responses in family conflict discussion stress.
The Present Study
The present study builds on the existing literature by examining middle-aged
couples’ cortisol reactivity in the context of a triadic family discussion with their young
teenage child. Based on the assumption that a conflict-based discussion is not anger
provoking in all participants, the first objective of the study is to examine whether self-
reported anger is associated with HPA activity. Based on previous studies showing a link
between observed hostility and HPA activity, it is hypothesized that spouses who report
experiencing higher anger during the discussion will exhibit higher cortisol activity.
Second, the study examines the possibility that transmission of the partner’s anger will
also affect HPA activity. It is hypothesized that spouses whose partners report
experiencing higher anger during the discussion will exhibit higher cortisol activity.
Third, because of the changing nature of HPA response upon repeated exposure to stress,
this study examines the role of couples’ previous marital aggression. We hypothesize
that previous marital aggression will be associated with dysregulation in anticipated link
between anger and cortisol activity but, because of the complicated nature HPA activity
to repeated stress, leave open the possibility for either hypocortisol or hypercortisol
response.
8
Chapter 2: Experimental Design and Methods
Participants
This study is based on data from the fourth wave of a longitudinal study
that examines the effects of family conflict upon the emotional, psychological, and
physiological functioning and development of the family members. Families from the
greater Los Angeles community initially volunteered for the study in response to
newspaper ads, fliers, and referrals from other participants and were asked to participate
if they met the following criteria: had lived together for the past 3 years, had a co-resident
child between 9-10 years of age, and were able to complete the study measures in English
at the time of study enrollment. The present research utilizes data collected from the
subset of 59 couples who attended the 4
th
laboratory meeting and who provided saliva
samples. However not all data from these couples could be used. Due to participants’
ages, we scrutinized the Saliva Questionnaire for medications and chronic health
conditions that might affect cortisol concentrations (Granger, Hibel, Fortunato, &
Kapelewski, 2009; Bruehl, Wolf, & Convit, 2009). In 3 couples, neither partner provided
usable cortisol data. Among these spouses, one husband was diabetic, two husbands had
cortisol that was systematically elevated (i.e., all cortisol samples > +3 SD from mean),
one wife reported having worked through the previous night (which disrupted her cortisol
pattern), one wife was pregnant, and one wife was using a hydrocortisone cream. In
addition, four individual husbands and four individual wives reported having a health
condition or taking a medication (e.g., steroids) linked to systematic differences in
salivary cortisol. Among husbands, two reported diabetes, one was taking anti-rejection
(i.e., immunosuppressant) medications following organ transplant, and one used a
9
cortisone inhaler less than 2 hours prior to saliva samples collection. Among wives, one
reported diabetes, two reported taking antidepressant medication, and one reported using
cortisone cream. We also excluded one additional wife, who had systematically elevated
(> +3 SD from the mean) cortisol at all sampling points. Thus, 47 couples provided
complete self-report and cortisol data. Because we retained individual spouses’ cortisol
data, 56 couples provided self-report data and at least one spouse’s cortisol data for the
current analyses.
In our sample of 56 couples, wives’ and husbands’ mean ages were 45.0 (SD =
5.2, range = 33.8-54.5) and 47.0 (SD = 6.2, range = 35.3-61.8), respectively. Wives’
mean education level was 14.3 years (SD = 2.1, range = 11-20) and husbands’ mean
education was 14.3 years (SD = 2.5, range = 8-20). Based on spouses’ individual reports
of race and ethnicity, 25.0% of the couples self- identified as Caucasian (Non-
Hispanic/Latino), 19.6% as Hispanic/Latino, 14.3% as African American, 12.5% as
Asian/Pacific Islander, and 28.6% as multiple ethnicities for the couple. The mean
family income was $72,275 (SD = $38,951; range = $0 - $165,000) and 25% of families
reported an income below $50,000. Couples had been married or cohabiting for 18.2
years, on average (SD = 5.1; range = 7-30) and participated in this study with their child
(mean age = 15.2, SD = 0.8).
Procedures
When participants arrived at the laboratory for the wave 4 visit, research
assistants conducted informed consent procedures and family members completed
questionnaires, including the Saliva Questionnaire. To establish a baseline for cortisol
reactivity, couples participated in a relaxation induction, which involved watching a 10-
10
minute video with calming images and music in a dimly lit room. Following this
relaxation period, participants allowed saliva to passively drip down a straw into a vial
for five minutes. Next, in preparation for the family conflict discussion, each member of
the family individually completed a questionnaire on which he or she rated the presence
of conflict with other participating family members about various issues of family life
and the degree to which conflict about this issue upset him or her. Experimenters then
conducted private individual priming interviews with each family member, in which each
participant provided details about the topics he or she identified as most conflictual and
upsetting and prepared the family member to communicate his/her views on each issue.
The experimenters conferred to identify the three topics that were most conflictual for all
family members, and these topics were used to guide the subsequent 15-minute family
discussion. Families were instructed to begin discussing the most conflictual topic and to
attempt to ensure that each family member had the chance to communicate his or her
point of view; families were also encouraged to discuss the problem as they normally
would at home (See Gordis, Margolin, Spies, Susman & Granger, 2010 for further
details).
At the end of the discussion, each participant provided a second saliva sample and
completed the Post-Discussion Questionnaire to describe his or her reactions to the
discussion. Additional saliva samples were collected at 10- and 20- min after the end of
the conflict discussion, while participants quietly filled out questionnaires in private
rooms. The Domestic Conflict Index was completed after the fourth saliva sample.

11
Cortisol Measures
Saliva samples were frozen and shipped in dry ice to Salimetrics, LLC to be
assayed for concentrations of free salivary cortisol, an index of HPA axis activity. Each
saliva sample was assayed twice to establish reliability of measurement r (434) = .99,
p<.0001; the mean of these two values was used for all analyses. Analyses were repeated
if any pair of results from a single sample differed by more than seven percent. 3 out of a
total of 412 cortisol concentrations above four ug/dL were dropped and 4 cortisol
samples were winsorized to 3 SDs above the mean to minimize the impact of outliers, as
recommended by Granger et al. (2006). We used regression imputation to generate
values for missing data points for AUC calculations and analyses.
To test the various dimensions of cortisol data reflected in our hypotheses, we
measured HPA activity several ways: 1) raw increase, 2) total output across time, and 3)
linear trajectory, and 4) the four individual cortisol samples. First, raw increase in
cortisol concentrations, calculated as the difference between baseline and peak,
measured the absolute magnitude of reactivity. Second, following Pruessner and
colleagues (Pruessner, Kirschbaum, Meinlschmid, & Hellhammer, 2003), we calculated
Area Under the Curve with respect to Ground (AUC
G
) and Area Under the Curve with
respect to Increase (AUC
I
) to evaluate cortisol output over the time. AUC
G
calculates the
area under the cortisol concentration curve, taking into account the time elapsed between
measurements (i.e., the ground of the reactivity graph), and AUC
I
, focuses on reactivity
by substracting the baseline (i.e., time 1) cortisol concentration from subsequent
measurements. These AUC measurements account more fully for the nonlinearity of the
12
cortisol trajectory due to recovery. Third, we examined linear trajectory through
hierarchical linear analyses to estimate intercepts and linear slopes for the cortisol curves
over time based on the four individual cortisol samples – baseline, immediately post-
discussion, 10 minutes post discussion, and 20 minutes post-discussion.
Questionnaire Measures
Saliva Questionnaire – Participants completed a 20-item Saliva Questionnaire
prior to relaxation procedures to assess information about factors that are likely to
influence salivary cortisol concentrations, such as medication use, waking time, and
recent consumption of food, caffeine, and alcohol.
Self-Reported Anger – Immediately following the discussion, each participant
completed the Discussion Follow-Up Questionnaire, designed to assess the subjective
experience of the participant during the family conflict discussion. Participants rated the
extent to which they experienced specific emotions during the discussion on a 5-point
Likert-type scale from 0 (None) to 4 (A lot). A measure of self-reported anger was
constructed from the sum of the following 5 emotions: angry, frustrated, upset, tense, and
irritated. We used regression imputation to generate values for 7 missing data points (out
of 560 data points or 1.3%). Cronbach’s alphas for the anger measure suggest
considerable consistency in ratings of the five emotions: α = .85 for husbands, and α =
.93 for wives. Anger scores ranged from 0 to 17; 29% of wives and 25% of husbands
reported a total score of 0.
Marital Aggression – Husbands and wives completed the Domestic Conflict
Index (DCI; Margolin, Burman, John, & O’Brien, 2000), a 61-item questionnaire
13
containing items assessing the frequency of physical and emotional aggression as well as
general conflict behaviors within the past year (including many items from the Conflict
Tactics Scale -2 [CTS-2]; Straus, Hamby, Boney-McCoy, & Sugarman, 1996). Each
partner reported on his or her own behaviors and those of the spouse. For each behavior
listed, the participant indicated the frequency of the behavior over the course of the past
year, using the following frequency categories: zero per year (0), once yearly (1), 2-5
times per year (2), 6-12 times per year (3), 2-4 times per month (4), and more than once
per week (5).
The current study assessed the emotionally/psychologically aggressive (13 items)
and physically aggressive (15 items) behaviors on the DCI. Examples of emotional
aggression items include “insulted or shamed your spouse in front of others”, “tried to
prevent your spouse from seeing/talking to family or friends”, and “frightened your
spouse.” Physical aggression items include “pushed, grabbed, or shoved your spouse”,
and “choked or strangled your spouse.” Husbands’ and wives’ physical and
emotional/psychological aggression were correlated at .56 and thus were combined to
yield a single score for marital aggression for each couple. To use both partners’ reports,
item level comparisons between the two reporters were used to identify the maximum
reported score; maximum scores are used to counter individuals’ tendencies to
underreport undesirable conflict behavior (Arias & Beach, 1987). For these participants,
Cronbach’s alpha for the marital aggression scale was .84. Aggression scores were
winsorized to three standard deviations above the mean to minimize the influence of
outliers. Couple aggression scores, calculated as the sum of husband and wife aggression,
14
ranged from 0 to 35.08 (mean = 6.7; median = 3.0). 74.6% of couples reported at least
some physical or psychological aggression within the past year.
15
Chapter 3: Results
Table 1 presents descriptive data on all study variables and identifies differences
between wives and husbands based on t-test analyses. Husbands had significantly higher
mean cortisol concentration than wives at the third sampling point (10 minutes post-
discussion), t (101) = -2.46, p < .05, and a marginally higher cortisol concentration at the
fourth sampling point (20 minutes post-discussion), t (101) = -1.89, p = .06. Husbands
also had marginally higher raw increases than wives, t (101) = -1.72, p = .09. Husbands
and wives did not significantly differ in their self-reported anger, AUC
G
, AUC
I
, or
cortisol concentrations at baseline or immediately post-discussion.
Table 1. Descriptive Statistics for Cortisol, Marital Aggression, and Discussion Anger

N Mean
Standard
Deviation
Minimum Maximum
Marital Aggression 56 6.29 8.40 0.00 35.08
Wives
Discussion Anger 56 4.21 4.90 0.00 17.00
AUC
G
51 253.84 127.03 73.59 598.71
AUC
I
51 6.10 86.81 -174.51 309.74
Raw Increase 51 0.015 0.04 -.061 .114
Raw cortisol sample 1 51 .068 .037 .014 .178
Raw cortisol sample 2 51 .068 .040 .010 .191
Raw cortisol sample 3 51 .069 .035 .001 .159
Raw cortisol sample 4 51 .071 .040 .003 .177
Husbands
Discussion Anger 56 3.46 3.49 0.00 14.00
AUC
G
52 292.56 150.20 85.00 647.43
AUC
I
52 21.90 116.29 -368.31 367.35
Raw Increase 52 .032 0.06 -.067 .228
16
Table 1, Continued
Note. Values for raw cortisol are reported in ug/dL.
Table 2 presents intercorrelations among marital aggression, husbands’ and
wives’ anger, and cortisol concentrations and cortisol reactivity measures, adjusting all
analyses involving cortisol for time of sampling. Wives’ and husbands’ anger were
significantly correlated. Husbands’ anger and husbands’ cortisol AUC
G
were
significantly correlated. Neither husbands nor wives’ anger was significantly correlated
with previous marital aggression. We found marginal to significant correlations between
husbands’ and wives’ cortisol levels for each post-discussion sample (cortisol 2, 3 and 4)
but not at baseline. These correlations provide evidence for co-regulation of the acute
stress response within couples. Not surprisingly, we found significant within-spouse
correlations among the four cortisol samples for husbands and wives.
To evaluate the hypothesis that anger would be associated with cortisol activity,
we split self-reported anger values into three groups: no anger, some anger, and high
anger. Specifically, 16 wives and 14 husbands reported no anger. Then a median split
was performed on the non-zero values to create some (21 wives and 23 husbands, mean
anger = 2.35; range = 0.56-4.00) and high anger groups (19 wives and 19 husbands, mean
anger = 8.84; range = 4.28-17.00).

N Mean
Standard
Deviation
Minimum Maximum
Raw cortisol sample 1 52 .073 .042 .007 .214
Raw cortisol sample 2 52 .075 .045 .005 .211
Raw cortisol sample 3 52 .095 .065 .025 .342
Raw cortisol sample 4 52 .087 .047 .021 .243
17
Table 2. Nonparametric Correlations Among Marital Aggression, Husbands’ and Wives’ Anger, and Husbands’ and Wives’
Cortisol
17

--
Note. ** p < .01, * p < .05,

p < .10. Partial correlations are presented among husbands’ and wives’ cortisol variables, controlling for sampling time. For each
analysis controlling for sampling time, n = 44. For analyses across spouses that do not adjust for sampling time, n = 47. For analyses within spouse, n = 52
for husbands and n = 51 for wives.

16

--
.73**
15

--
.63**
.73**
14

--
.59**
.48**
.28

13

--
.24
.34*
.20
.25

12

--
.74**
.23
.41**
.27

.22
11

--
.66**
.64**
.36*
.54**
.34*
.29*
10

--
.40*
.34*
.37*
.18
.24
.24
.31*
9

--
.13
-.03
.10
.04
-.56**
.18
.28

.58**
8

--
.02
-.25

.41**
.77**
.63**
.13
.23
.05
.01
7

--
.00
.90**
.10
.09
.08
.00
-.50**
.30*
.31*
.55**
6

--
.00
.81**
-.09
-.48**
.56**
.54**
.44**
.21
.30*
.13
.04
5

--
.24
.19
.19
.09
.19
.44**
.36*
.25

.61**
.80**
.72**
.62**
4

--
.50**
.28

.16
.41**
.13
.62**
.83**
.78**
.69**
.21
.40**
.30*
.26

3

--
-.05
-.08
.15
.07
.22
.08
-.10
-.09
.01
-.01
-.19
-.06
-.16
.00
2

--
.40**
.40**
.09
.13
.18
.13
.19
.21
.20
.36*
.24

-.20
.02
.01
.03
1
--
.20
.15
-.10
.00
.11
.02
.08
.08
-.22
-.21
.06
-.11
-.10
-.05
.08
.04

1. Aggression
2. H Anger
3. W Anger
4. H AUCg
5. W AUCg
6. HAUCi
7. W AUCi
8. H Raw Inc
9. W Raw Inc
10. H cortisol 1
11. H cortisol 2
12. H cortisol 3
13. H cortisol 4
14. W cortisol 1
15. W cortisol 2
16. W cortisol 3
17. W cortisol 4
18
Table 3 presents the means, SDs and results for 2 (spouse) x 3 (anger group)
mixed effects ANOVAs, with spouse as a fixed factor, and anger group as a random
factor. A significant interaction between spouse x anger group was found for cortisol
AUCg

and for the saliva sample at 10 min post-discussion. Based on post-hoc
comparisons, AUCg for husbands with high anger was significantly higher than for
husbands with no anger, t (27) = -3.44, p < .01, for husbands with some anger, t (37) = -
2.26, p = .03, and for wives with no anger, t (29) = -2.16, p = .04, some anger, t (33) = -
3.33, p < .01, and high anger, t (31) = -2.62, p = .01. Relatedly, husbands with high anger
had higher cortisol at 10-min post-discussion than wives with high anger, t (31) = -2.90, p
< .01, and wives with some anger, t (33) = -2.65, p = .01, and marginally higher cortisol
at 10-min post-discussion than wives with no anger, t (29) = 1.99, p = .06, husbands with
no anger, t (27) = -1.74, p = .09, and husbands with some anger, t (37) = -1.88, p = .07.
No significant main effects were found for spouse or for anger group on any of the
cortisol variables examined. For wives, however, there are no significant differences
between the anger groups on cortisol reactivity as indexed by AUCg

(Figures 1 and 2 are
presented for closer inspection of the cortisol data at each of the time points for the
husbands and wives in the 3 anger groups).
Table 4 presents a parallel set of 2 x 3 ANOVAs investigating the emotion
transmission hypothesis involving the association between cortisol activity and the
partner’s reported anger. Figures 3 and 4 are presented for visual inspection of these data.
In the analyses, the only significant finding is the main effect for husbands versus wives
19
Table 3. Husbands’ and Wives’ Means, by Own Self-Reported Anger, on Cortisol Measures and ANOVA Summary

F-statistic
Spouse X
Anger Group
(df = 2, 97)
3.54*
0.11
0.43
2.85

1.34
3.23*
0.97
Note.

p < .10, * p < .05, ** p <.01;
a
means differ at p = .04,
b
means differ at p < .01,
c
means differ at p = .01,
d
means differ at p < .01,
e
means
differ at p = .03,
f
means differ at p = .06,
g
means differ at p = .01,
h
means differ at p < .01,
i
means differ at p = .09,
j
means differ at p = .07

Anger
Group (df
= 2, 97)
0.83
10.84

0.75
0.73
0.30
0.33
0.06
Spouse (df
= 1, 97)
0.49
3.90
7.01
0.20
0.42
1.91
3.98
Husband Means (SD)
By Own Anger Group
High Anger
(n = 16)
381.35
a,b,c,d,e

(140.17)
5.57
(147.79)
.036
(.075)
.096
(.046)
.087
(.043)
.124
f,g,h,I,j

(.089)
.098
(.042)
Some
Anger
(n = 23)
273.77
e

(150.19)
39.11
(103.78)
.031
(.047)
.062
(.037)
.075
(.050)
.085
j

(.047)
.080
(.043)
No Anger
(n = 13)
216.51
d

(111.86)
11.56
(96.92)
.030
(.061)
.065
(.039)
.060
(.034)
.076
i

(.061)
.086
(.060)
Wife Means (SD)
By Own Anger Group
High
Anger
(n = 17)
256.67
c

(133.07)
2.60
(96.79)
.010
(.032)
.065
(.038)
.063
(.030)
.062
h

(.032)
.064
(.025)
Some
Anger
(n = 19)
234.61
b

(120.50)
26.97
(87.70)
.026
(.048)
.062
(.037)
.070
(.046)
.070
g

(.031)
.075
(.050)
No Anger
(n = 15)
274.90
a

(133.16)
-16.36
(71.93)
.007
(.038)
.079
(.035)
.071
(.042)
.077
f

(.042)
.073
(.040)
Cortisol
Measure
AUCg
AUCi
Raw increase
Baseline
Sample
Post-
discussion
Sample
Post+10
minutes
Post+20
minutes
20
Figure 1. Husbands’ Average Cortisol Curves by Own Anger Group

Figure 2. Wives’ Average Cortisol Curves by Own Anger Group
21
Table 4. Husbands’ and Wives’ Means, by Partner’s Self-Reported Anger, on Cortisol Measures and ANOVA Summary

F-statistic
Spouse X
Anger Group
(df = 2, 97)
0.37
0.62
0.12
0.26
0.92
0.44
0.59
Note.

p < .10, * p < .05, ** p <.01

Anger
Group (df
= 2, 97)
0.68
1.68
16.11

4.61
0.28
0.10
0.13
Spouse (df
= 1, 97)
4.95
0.94
19.69*
1.31
0.73
11.51

5.44
Husband Means (SD)
By Wives’ Anger Group
High Anger
(n = 19)
283.40
(146.15)
26.40
(.98.54)
.043
(.064)
.065
(.034)
.066
(.040)
.094
(.075)
.082
(.042)
Some
Anger
(n = 20)
309.52
(160.18)
23.59
(144.74)
.029
(.057)
.081
(.047)
.086
(.053)
.100
(.059)
.091
(.047)
No Anger
(n = 13)
279.86
(149.77)
12.73
(98.07)
.022
(.058)
.073
(.047)
.072
(.035)
.087
(.060)
.089
(.057)
Wife Means (SD)
By Husbands’ Anger Group
High
Anger
(n = 18)
275.97
(152.59)
40.73
(104.87)
.030
(.046)
.060
(.033)
.072
(.045)
.074
(.043)
.075
(.047)
Some
Anger
(n = 19)
247.67
(135.69)
-13.23
(70.65)
.006
(.034)
.070
(.042)
.065
(.045)
.063
(.029)
.063
(.038)
No Anger
(n = 14)
233.74
(70.38)
-12.18
(71.61)
.009
(.038)
.076
(.034)
.066
(.024)
.073
(.032)
.075
(.032)
Cortisol
Measure
AUCg
AUCi
Raw increase
Baseline
Sample
Post-
discussion
Sample
Post+10
minutes
Post+20
minutes
22
Figure 3. Husbands’ Average Cortisol Curves by Wives’ Anger Group

Figure 4. Wives’ Average Cortisol Curves by Husbands’ Anger Group
23
on raw increase, which does not contribute information about husbands’ cortisol in
relation to wives’ anger. This main effect coincides with the previously reported
significant finding that husbands, compared to wives, exhibited higher cortisol at 10-min
post-discussion.
We used Hierarchical Linear Modeling (HLM) version 6.01 (Raudenbush, Bryk,
Cheong, & Congdon, 2004) to test the hypothesis that previous aggression would
moderate the effect of anger and cortisol reactivity. HLM is optimal for these analyses
because it can calculate intercepts and slopes for cortisol even in the presence of missing
data, and it does not require equal numbers of observations (i.e., cortisol samples) per
person or identical spacing between observations (i.e., sampling times; Hrushka, Kohrt,
& Worthman, 2005). For HLM analyses, cortisol concentrations for each sampling point
were natural log transformed to correct for positive skew.
In order to account for statistical interdependence between husbands and wives,
the data were modeled at the dyadic level. Husbands’ and wives’ data were entered on
separate lines in the datafile and paired through the use of couple-level IDs. In each
model constructed, separate intercept terms were calculated for husbands and wives
through the use of dummy variables. To aid in interpretation, participant’s anger scores
and couple marital aggression scores were standardized in SPSS prior to being utilized in
HLM; these values thus represent standard deviations from the grand mean. All HLM
results reported represent the final estimation of fixed effects, with robust standard errors.
In all HLM models described, logged cortisol was used as the outcome variable
and separate intercept and slope terms were estimated for husbands and wives. The
24
Level 1 equation models the effects of within-person variables on each individual’s
cortisol trajectory, while the Level 2 equation models the effects of between-person
variables on the parameters in the Level 1 equation.
The first model was constructed to evaluate the moderation of the relationship
between each individual’s own self-reported anger and cortisol reactivity (i.e., the HLM
slope term) by previous marital aggression within the couple. A parallel model was run
examining the interaction between spouse-reported anger and marital aggression. The
Level 1 equation for the model included intercepts for both husband and wife, and control
variables for time, in hours, since collection of the baseline sample for both husbands and
wives. The complete Level 1 equation for these models was
Y
ij
= π0
i
HUSB + π0
i
WIFE +π1
i
HTIME
ij
+ π1
i
WTIME
ij
+ ε
ij

in which Y
ij
is the cortisol level for individual i at sampling occasion j; HUSB and WIFE
are dummy variables that represent husbands’ and wives’ data, with 0
i
representing
spouses’ respective intercepts for the model; H refers to husband and W to wife; the
TIME variable is the time elapsed since the baseline sample, in hours, for the sampling
occasion; and ε
ij
represents the within-couple error.
The Level 2 equations, an example of which is presented below, model the effects
of between-person variables on the parameters (i.e., intercept and slope) of the Level 1
model. Time since awakening, in hours, was computed by subtracting the participant’s
reported awakening time on the day of the laboratory visit from the time the baseline
saliva sample was collected. Time since awakening was modeled at Level 2 in order to
control for the effect of the normal diurnal cortisol slope; values for this variable were
25
centered by subtracting the lowest time since waking in the sample from each data point.
Oral birth control medications were controlled for in Level 2 models, as previous
research (e.g., Kirschbaum, Kudielka, Gaab, Schommer, & Hellhammer, 1999) has
documented their effects on both baseline levels of cortisol and cortisol reactivity. In
addition, sample dilution was controlled for in the Level 2 equations due to a procedural
error (i.e., 9 couples were allowed or encouraged to drink water during the cortisol
sampling period, and had potentially diluted cortisol concentrations). Dilution of samples
was included as a predictor of the intercept for both husbands and wives; oral
contraceptive use was included as a predictor of intercept and slope for wives. Finally,
the between-person variables of interest – the individual’s self-reported anger, the
couple’s previous marital aggression, and the interaction between these variables – were
added to the equations predicting intercept and slope. For example, the Level 2 equation
below defines the influence of the interaction between wives’ self-reported anger and
couple aggression, on wives’ cortisol intercept (π0
i
)

π0
i
= γ20 + γ21(Diluted) + γ22(BCpill) + γ23(WifeWAKE) + γ24(WifeANG)
γ25(CoupleAGG) +γ26(WifeANG X CoupleAGG) + u2
i,

where π0
i
is predicted by γ20, a constant term representing the mean cortisol value across
wives from the Level 1 model; γ21, dilution of samples due to drinking water during the
procedures (coded as 0 or 1); γ22, oral contraceptive use, scored dichotomously (0 or 1);
γ23, time elapsed between wives’ waking and collection of wives’ baseline saliva sample;
γ24, wives’ self-reported anger during the discussion; γ25, the couples’ previous year
26
marital aggression; γ26, the interaction between wives’ anger and couples’ aggression;
and u2
i
, the between-couple error term.
The following Level 2 equation defines the model for determining the influence
of wives’ self-reported anger on wives’ cortisol slope (π1
i
)
(π1
i
) = γ30 + γ31(BCpill) + γ32(WifeWAKE) + γ33(WifeANG) +γ34(CoupleAGG)
+γ35(WifeANG X CoupleAGG) + u3
i ,

where π1
i
is predicted by γ30, a constant term representing the average cortisol slope
across wives from the Level 1 model; γ31, oral contraceptive use, scored dichotomously
(0 or 1); γ32, time elapsed between wives’ waking and collection of wives’ baseline
saliva sample; γ33, wives’ self-reported anger during the discussion; γ34, the couples’
previous year marital aggression; γ35, the interaction between wives’ anger and couples’
aggression; and u3
i
, the between-couple error term.
Table 5 presents the results of the HLM model evaluating the interaction between
the individual’s self-reported anger and the level of previous aggression within the couple
as a statistical predictor of cortisol intercept and slope. The interaction between
husbands’ anger and previous marital aggression was significantly associated with
husbands’ cortisol slope, indicating that marital aggression moderated the association
between husbands’ anger and husbands’ cortisol reactivity. Husbands’ anger, previous
marital aggression, and their interaction were not associated with husbands’ cortisol at
baseline (i.e., intercept). The HLM graph displaying this interaction is presented in
Figure 5. In this model, the main effect associating husbands’ anger and husbands’
27
cortisol reactivity (i.e., slope) approached significance (p = .07). There was no significant
association between any of the predictors (wives’ anger, marital aggression, or the
interaction term) and wives’ cortisol intercept or slope.
Table 5. Couples’ Marital Aggression Moderating the Relation Between Own Anger and
Cortisol Levels Using HLM
Fixed Effect N
Coefficient
(SE) t ratio
Husbands
Level 1 Intercept 52 -2.86 (.10) -27.43**
Level 2 effect of dilution on intercept 52 -.42 (.17) -2.48*
Level 2 effect of time since waking 52 -.64 (1.38) -0.47
Level 2 effect of husband anger (ANG) on
intercept
52 .06 (.04) 1.50
Level 2 effect of couple aggression (AGG) on
intercept
52 -.01 (.02) -0.60
Level 2 effect of husband ANG x couple AGG 52 -.002 (.003) -0.69
Level 1 Slope of sample time 53 .27 (.09) 2.97*
Level 2 effect of time since waking 53 1.08 (1.40) 0.77
Level 2 effect of husband ANG 53 -.06 (.03) -1.85

Level 2 effect of couple AGG 53 -.01 (.02) -0.41
Level 2 effect of husband ANG x couple AGG 53 .005 (.002) 2.17*
Wives
Level 1 Intercept 51 -2.82 (.08) -37.00**
Level 2 effect of dilution on intercept 51 .10 (.19) 0.52
Level 2 effect of birth control pill on intercept 51 .31 (.19) 1.61
Level 2 effect of time since waking 51 2.08 (1.11) 1.87

Level 2 effect of wife ANG 51 -.01 (.02) -0.79
Level 2 effect of couple AGG on intercept 51 -.005 (.01) -0.40
Level 2 effect of wife ANG x couple AGG 51 .001 (.001) 0.98

28
Table 5, Continued
Fixed Effect N
Coefficient
(SE) t ratio
Level 1 Slope of sample time 52 -.04 (.09) -0.39
Level 2 effect of BCpill 52 -.40 (.35) -1.17
Level 2 effect of time since waking 52 -2.87 (1.39) -2.07*
Level 2 effect of wife ANG 52 .01 (.02) 0.38
Level 2 effect of couple AGG 52 -.01 (.01) -0.82
Level 2 effect of wife ANG x couple AGG 52 .001 (.001) -0.42
Note.

p < .10, * p < .05, ** p <.01
Figure 5. The Moderation of the Association Between Husbands’ Anger and Husbands’
Cortisol by Marital Aggression (HLM)

29
To examine the interaction between anger and marital aggression, median splits
were performed on the self-reported anger and marital aggression variables to create four
groups: low anger and low aggression, low anger and high aggression, high anger and
low aggression, and high anger and high aggression. The mean cortisol curve for each of
these groups was then plotted (Figure 6). Based on this graph, the interaction effect
appears to be driven by the difference between the slope of the low anger, low aggression
group and the other three groups. Specifically, among husbands who reported lower than
average anger and had experienced lower than average marital aggression, the mean
cortisol curve shows a small and gradual increase in cortisol from baseline through 20
minutes post-discussion. The average cortisol trajectories for the three remaining groups
Figure 6. Husbands’ Average Cortisol Curves for Groups Defined by Median Splits on
Husbands’ Anger & Couple Aggression

30
(i.e., low anger and high aggression, high anger and low aggression, and high anger and
high aggression) demonstrated a more marked increase in cortisol between the sample
taken immediately post-discussion and the sample taken ten minutes later. These groups
also showed a decline in cortisol from the third (10 minutes post-discussion) to fourth (20
minutes post discussion) samples.
A parallel HLM model was constructed to evaluate whether previous marital
aggression moderated the relation between partner-reported anger and cortisol reactivity
(Table 6). The interaction between wives’ anger and previous marital aggression was
significantly associated with husbands’ cortisol slope (p < .05). The HLM graph
displaying this interaction is presented in Figure 7. For husbands, there were no main
effects for wives’ anger or previous marital aggression on cortisol baseline or reactivity.
For wives, neither previous marital aggression nor the interaction between husbands’
anger and marital aggression was associated with baseline cortisol or reactivity.
However, husbands’ anger was associated with lower baseline cortisol and increased
cortisol reactivity among wives (ps < .05).
Table 6. Couples’ Marital Aggression Moderating the Relation Between Partner’s Anger
and Cortisol Levels Using HLM
Fixed Effect N
Coefficient
(SE) t ratio
Husbands
Level 1 Intercept 52 -2.84 (.10) -28.20**
Level 2 effect of dilution on intercept 52 -.47 (.17) -2.70*
Level 2 effect of time since waking 52 -.66 (1.32) -0.50
Level 2 effect of wife anger (ANG) on
intercept
52 .00 (.02) 0.02

31
Table 6, Continued
Fixed Effect N
Coefficient
(SE) t ratio
Level 2 effect of couple aggression (AGG) on
intercept
52 .004 (.011) -0.39
Level 2 effect of wife ANG x couple AGG 52 -.003 (.002) -1.43
Level 1 Slope of sample time 53 .24 (.09) 2.58*
Level 2 effect of time since waking 53 .64 (1.41) 0.45
Level 2 effect of wife ANG 53 -.01 (.02) -0.62
Level 2 effect of couple AGG 53 -.01 (.01) -0.80
Level 2 effect of wife ANG x couple AGG 53 .004 (.002) 2.15*
Wives
Level 1 Intercept 51 -2.82 (.07) -38.60**
Level 2 effect of dilution on intercept 51 .05 (.20) 0.27
Level 2 effect of birth control pill on intercept 51 .37 (.20) 1.85

Level 2 effect of time since waking 51 2.06 (1.08) 1.91

Level 2 effect of husband ANG 51 -.05 (.02) -2.17*
Level 2 effect of couple AGG on intercept 51 -.001 (.010) -0.09
Level 2 effect of husband ANG x couple
AGG
51 .001 (.001) 0.77
Level 1 Slope of sample time 52 -.04 (.09) -0.43
Level 2 effect of BCpill 52 -.48 (.37) -1.30
Level 2 effect of time since waking 52 -2.87 (1.36) -2.11*
Level 2 effect of husband ANG 52 .05 (.02) 2.20*
Level 2 effect of couple AGG 52 .005 (.011) 0.44
Level 2 effect of husband ANG x couple
AGG
52 -.002 (.002) -1.26
Note.

p < .10, * p < .05, ** p <.01

32
Figure 7. The Moderation of the Association Between Wives’ Anger and Husbands’
Cortisol by Marital Aggression (HLM)

Again, mean cortisol curves for groups created by median splits of the spouses’
anger and couple aggression variables were plotted to examine the interaction effect
(Figure 8). These cortisol curves were similar to those representing husbands’ own
anger and marital aggression groups; the low anger and low aggression group showed a
smaller positive slope than the other three groups, indicating less reactivity.

33

Figure 8. Husbands’ Average Cortisol Curves for Groups Defined by Median Splits on
Wives’Anger & Couple Aggression

34
Chapter 4: Discussion
The results of the current study provide partial evidence that spouses’ reported
anger during a conflict discussion is linked to their neuroendocrine reactivity, but this
holds primarily for husbands, not wives. Evidence from this middle-aged sample of
volunteers from the community suggests that husbands’ cortisol responses to a family
conflict discussion are positively linked to their own self-reported anger. Further, the
current study is one of the first to suggest that shared experiences in couples’ relationship
histories, namely, previous marital aggression, creates an altered context for the conflict
discussion such that husbands are physiologically more reactive when they have
experienced previous marital aggression. Though the data are preliminary, husbands who
do not have history of marital aggression, and who experienced lower than average anger
in the discussion, show a small but steady increase in cortisol across the 3 post-discussion
cortisol samples. By contrast, husbands who either experienced higher anger in the
discussion or had more marital aggression in the previous year showed marked cortisol
reactivity to the discussion. The data do not support the hypothesis that emotional
transmission across spouses relates to cortisol activity.
Our hypothesis that individuals who reported more anger in the conflict
discussion would display greater reactivity held only for husbands, not wives.
Specifically, husbands in the high anger group had a significantly higher AUC
G
value
than husbands in the no anger group and had higher AUC
G
than wives in the no anger,
some anger, and high anger groups. AUC
G
reflects these husbands’ higher cortisol
reactivity overall, capturing a combination of higher initial (i.e., baseline) cortisol output
35
and higher reactivity. Husbands’ also exhibited higher cortisol at 10 minutes post-
discussion, the most likely time for discussion related stress to peak. Although we need
to view these findings as preliminary, based on the small sample size, there is evidence
that husbands’ reported anger in family discussions is related to heightened cortisol
output.
Sex Differences in Physiological Reactivity
These findings raise some important considerations about the role of sex in
emotional and physiological reactivity generally, and in response to family conflict
discussions. Men generally have demonstrated greater reactivity to most individually-
focused laboratory stress tasks such as those involving giving speeches, performing
mental arithmetic, or viewing distressing film clips; in fact, salivary cortisol response
magnitudes in men have been found to be approximately double the response magnitudes
of women (see Kudielka & Kirschbaum, 2005 for a review of sex differences in HPA
reactivity to acute stressors). In addition, men have also shown a cortisol response linked
to mere anticipation of a stressful task; women did not show this response (Kirschbaum,
Wust, & Hellhammer, 1992).
In addition, self-reported affect or emotion seems to be more reliably linked to
men’s physiological responses generally and within the context of marital conflict. As
mentioned previously, using experience sampling methods, men’s negative affect was
found to be more strongly linked to cortisol reactivity than was women’s negative affect
(Adam, 2005). Levenson, Carstensen, and Gottman (1994) provided evidence that,
although men and women both report negative emotions in response to marital conflict,
36
only men’s affective reports are linked with physiological responses, in this case, somatic
activity and cardiovascular measures. This might suggest that men possess a greater
attunement to or awareness of their physiological arousal or that physiological cues play
a more significant role in the way that men label their anger. Husbands who have been
physically aggressive to their wives report high physiological arousal during marital
conflict discussions (Margolin, 1988). In laboratory studies (Harver, Katkin, & Bloch,
1993; Koltyn, O'Connor, & Morgan, 1991; Fairclough & Goodwin, 2007), men have
shown greater awareness of their bodily states (e.g., changes in heart rate) than women,
but in naturalistic settings, women are equally accurate at reporting their internal states
(see Pennebaker & Roberts, 1992 for a review). Pennebaker & Roberts’s (1992)
suggested that men may base inferences of affective states on physiological arousal,
whereas women may attend to situational and contextual cues when determining their
affective states.
Our lack of findings for women should be interpreted somewhat cautiously.
Recent investigations of acute stressor paradigms such as the Trier Social Stress Task
(TSST) suggest that women may show greater variability in their reactivity due to
hormonal influences such as menstrual cycle phase and the use of oral contraceptives.
Women in the luteal phase of the menstrual cycle show similar reactivity to men, while
women in the follicular phase and those taking oral contraceptives show decreased
reactivity (Kirschbaum, Kudielka, Gaab, Schommer, & Hellhammer, 1999). It is thus
possible that no clear pattern emerged for women in this study due to variability related
to hormonal status (e.g., due to menstrual phase, menopause, or use of contraceptives).
37
Moreover, previous studies employing marital conflict interactions as a stressor
have found a different sex pattern than what we found. That is, women are more likely
than men to demonstrate enhanced neuroendocrine reactivity to marital conflict (Kiecolt-
Glaser & Newton, 2001). In addition, behaviors of both spouses within marital
discussions have been more consistently linked to women’s cortisol reactivity than men’s
(e.g., Kiecolt-Glaser et al., 1996, Robles, Shaffer, Malarkey, & Kiecolt-Glaser, 2006).
However, some research suggests that women might be more active in initiating
discussion or requesting change in marital conflict discussions and may thus be exerting
more cognitive and emotional effort, which might increase their physiological responses
(Newton & Sanford, 2003). Other theories have suggested that spouses with lower power
or influence within the relationship show greater physiological reactivity to relationship
stress (Loving et al., 2004). Finally, the threat to communality that occurs within marital
conflict discussions has been hypothesized to increase responses among women, as
contrasted with threats to agency or achievement, which are present in task such as the
Trier Social Stres Task (e.g., Smith, Gallo, Goble, Ngu, & Stark, 1998).
That increased neuroendocrine reactivity to family conflict discussions was
exhibited by husbands, but not wives in our sample, raises questions about the meaning
of this task for couples. The presence of the child made the discussion simultaneously a
parenting task, a co-parenting task, and a marital conflict task. Our procedures
specifically elicited topics that were currently conflictual for the entire family, such that
when child concerns were discussed, there was often disagreement within the couple
about how to address the concern. It is possible, however, that women are more
38
accustomed to conflict in the ‘family’ realm or with the child present, and that these
discussions thus are more stressful for men. It is also possible that those husbands who
anticipated that the task would be challenging or potentially anger-provoking were
emotionally and/or physiologically primed for the task. Indeed, the nature of the findings
linking husbands’ anger to their cortisol suggests that baseline cortisol played a role in
this relation. As noted above, the anticipation of stress has been related to increased
cortisol reactivity, specifically for men (Kirschbaum et al., 1992).
This study examined a here-to-fore untested hypothesis that one partner’s anger
would have direct effect on the other partner’s neuroendocrine reactivity. Our data do
not support this direct effect but do not rule out an indirect effect, particularly in light of
the correlation between spouses’ anger. That is, one spouse’s anger might spill over to
the other’s anger, which is then associated with heightened cortisol. Adequate testing
this indirect effect would require more nuanced examination of the sequencing of these
events, e.g., anger leading to anger. Moreover, the correlation between spouses’ post-
discussion cortisol levels raises questions of some physiological co-regulation although
again, an explanation of this requires better a more detailed examination of changes in
affect and cortisol. The possibility that the transmission of anger between spouses might
lead to increased cortisol reactivity was also evaluated. We found a trend within our
analyses to support this hypothesis, namely that individuals whose partners reported high
anger showed marginally significantly greater raw increases in cortisol than individuals
whose partners reported no or some anger.

39
The Role of Marital Aggression in Physiological Reactivity
Finally, we found support among husbands for our hypothesis that previous
marital aggression would moderate the relation between own and spouse’s anger and
cortisol reactivity. Husbands who reported lower than average anger, and had
experienced lower than average marital aggression showed the least immediate reactivity
to the conflict discussion. They did, however, show a slow but steady positive incline in
cortisol activity. Perhaps this discussion was not a strong stressor but was somewhat
arousing, especially since the general cortisol response at this time of day would be a
decline. The data also show that the presence of high levels of anger, marital aggression,
or both is linked to a nonlinear inverted-U pattern of steeper increasing slopes and
declining slopes in HPA response to family conflict discussions among husbands. This
finding is compelling because it suggests that previous marital aggression may alter the
meaning or tone of family conflict discussions. Previous research has suggested that
aggression within the marital relationship is related to affectively compromised
interactions with children for both husbands and wives (Margolin, Gordis, & Oliver,
2004). The current study suggests that one potential mechanism for this relation is that
previous marital aggression may increase husbands’ physiological reactivity to family
conflict discussions. In the marital interaction literature, increases in physiological
arousal – and potentially emotional arousal – among husbands has been associated with
behavioral withdrawal from conflict (Gottman & Levenson, 1988), which may
compromise the quality of family relationships.
40
Furthermore, if previous marital aggression sensitizes men to react
physiologically to family conflicts, which are a recurrent feature of family life while
children are living with their parents, this may lead to repeated hits on the HPA system.
Repeated activation of the HPA stress response is one of the mechanisms hypothesized to
result in systemic down-regulation of the HPA axis, with potentially serious
consequences for mental and physical health (Robles & Kiecolt-Glaser, 2003). Thus, to
the extent that marital aggression sensitizes the HPA response in husbands such that this
system will be activated in the face of a ubiquitous source of stress (i.e., family conflict),
marital aggression may function as a mechanism through which poor marital quality
increases risk for negative health outcomes.
Limitations
There are several limitations of this study that warrant mention. First, the results
of study may be affected by our sample size, particularly given the amount of variability
that characterizes cortisol data. Lack of power may have reduced our significance in
some analyses. Second, our results may be affected by our selection of task. Because
adolescent youth can play an important role in marital conflicts (Feinberg, Kan, &
Hetherington, 2007), we chose to use a family discussion and not segregate the couple
system from the rest of the family. It would be informative, however, to replicate this
design with couple-only discussion. Third, it would useful to know to what extent the
discussions elicited here reflect discussions that take place at home and whether what we
found here is a frequent or infrequent event for spouses. Fourth, this study focuses only
on anger as the emotion of interest. Given the likely importance of other emotions,
41
particularly fear and sadness in couples with marital aggression (Gordis, Margolin, &
Vickerman, 2005; Beach, Kim, Cercone-Keeney, Gupta, Arias, & Brody, 2004), future
studies should include additional emotional dimensions. Finally, the current study
incorporated no measures of spouses’ actual behaviors during the discussion. Given that
wives’ physiological reactivity has been uniquely linked to observed behaviors within
marital discussions (Kiecolt-Glaser et al., 1996, Robles et al., 2006), another future
direction would be to examine cortisol activity in connection with observed behaviors.
Summary
The current study provides preliminary evidence to link emotion experienced
during family conflict to couples’ patterns of neuroendocrine reactivity. Husbands who
self-reported high anger showed greater neuroendocrine reactivity to a conflict discussion
task. These findings demonstrate the importance of considering couples’ affective
reactions during conflict as potentially indicating or influencing physiological
functioning. In addition, this study provides preliminary evidence to support marital
aggression as a potential mechanism linking poor marital quality to poor health among
husbands. This underscores the importance of understanding contextual and historical
relationship issues when examining couples’ reactivity to stress.
42
References
Adam, E.K. (2005). Momentary emotion and cortisol levels in the everyday lives of
working parents. In B. Schneider & L.J. Waite (Eds.), Being together, working apart:
Dual-career families and the work-life balance, (pp. 105-133). New York: Cambridge
University Press.

al’Absi, M., Bongard, S. & Lovallo, W.R. (2000). Adrenocorticotropin responses to
interpersonal stress: effects of overt anger expression style and defensiveness.
International Journal of Psychophysiology, 37, 257-265.

Arias, I. & Beach, S.R.H. (1987). Validity of self-reports of marital violence. Journal of
Family Violence, 2, 139-149.

Ax, A.F. (1953). The physiological differentiation between fear and anger in humans.
Psychosomatic Medicine, 15, 433-442.

Beach, S.R.H., Kim, S., Cercone-Keeney, J., Gupta, M., Arias, I., & Brody, G.H. (2004).
Physical aggression and depressive symptoms: Gender asymmetry in effects? Journal of
Social and Personal Relationships, 21, 341-360.

Bruehl, H., Wolf, O.T., & Convit, A. (2009). A blunted cortisol awakening response and
hippocampal atrophy in type 2 diabetes mellitus. Psychoneuroendocrinology, 34, 815-
821.

Burman, B., & Margolin, G. (1992). Analysis of the association between marital
relationships and health problems: an interactional perspective. Psychological Bulletin,
112, 39-63.

Chan, C., & Margolin, G. (1994). The relationship between dual-earner couples’ daily
work mood and home affect. Journal of Social and Personal Relationships, 11, 573–586.

Collins, A., & Frankenhaeuser, M. (1978). Stress responses in male and female
engineering students. Journal of Human Stress, 4, 43-48.

Coyne, S.E., Rohrbaugh, M.J., Shoham, V., Cranford, J.A., Nicklas, J.M., & Sonnega, J.
(2001). Prognostic importance of marital quality for survival of congestive heart failure.
American Journal of Cardiology, 88, 526-2001.

Denson, T.F., Spanovic, M. & Miller, N. (2009). Cognitive Appraisals and Emotions
Predict Cortisol and Immune Responses: A meta-analysis of acute laboratory social
stressors and emotion inductions. Psychological Bulletin, 135, 823-853.

43
Dickerson, S. S., Gruenewald, T. L., &Kemeny, M. E. (2004). When the social self is
threatened: Shame, physiology, and health. Journal of Personality, 72, 1191–1216.

Dickerson, S.S. & Kemeny, M.E. (2004). Acute stressors and cortisol responses: A
theoretical integration and synthesis of laboratory research. Psychological Bulletin, 130,
355-391.

Fairclough, S.H. & Goodwin, L. (2007). The effect of psychological stress and relaxation
on interoceptive accuracy: Implications for symptom perception. Journal of
Psychosomatic Research, 62, 289-295.

Feinberg, M.E., Kan, M.L., & Hetherington, E.M. (2007). The longitudinal influence of
coparenting conflict on parental negativity and adolescent maladjustment. Journal of
Marriage and Family, 69, 687-702.

Fries, E., Hesse, J., Hellhammer, J., & Hellhammer, D.H. (2005). A new view on
hypocortisolism. Psychoneuroendicrinology, 30, 1010-1016.

Gordis, E.B., Margolin, G., & Vickerman, K.A. (2005). Communication and frightening
behavior among couples with past and recent histories of physical marital aggression.
American Journal of Community Psychology, 36, 177-191.

Gottman, J.M., Jacobson, N.S., Rushe, R.H., & Shortt, J.W. (1995). The relationship
between heart rate reactivity, emotionally aggressive behavior, and general violence in
batterers. Journal of Family Psychology, 9, 227-248.

Gottman, J.M., & Levenson, R.W. (1985). A valid procedure for obtaining self-report of
affect in marital interaction. Journal of Consulting and Clinical Psychology, 53, 151-160.

Graham, J.E., Christian, L.M., & Kiecolt-Glaser, J.K. (2006). Marriage, health, and
immune function. In S.R.H. Beach, M.Z. Wamboldt, N.J. Kaslow, R.E. Heyman, M.B.
First et.al. (Eds.) Relational Processes and DSM-V: Neuroscience, assessment,
prevention, and treatment. (pp. 61-76). Washington, DC: American Psychiatric
Association.

Granger, D.A., Hibel, L.C., Fortunato, C.K., & Kapelewski, C.H. (2009). Medication
effects on salivary cortisol: Tactics and strategy to minimize impact in behavioral and
developmental science. Psychoneuroendocrinology, 34, 1437-1448.

Granger, D.A., Kivlighan, K.T., Blair, C., El-Sheikh, M., Mize, J., Lisonbee, J.A. &
Buckhalt, J.A. (2006). Integrating the measurement of salivary α-amylase into studies of
child health, development, and social relationships. Journal of Social and Personal
Relationships, 23(2), 267-290.
44
Harver, A., Katkin, E. S. & Bloch, E. (1993). Signal-detection outcomes on heartbeat and
respiratory resistance detection tasks in male and female subjects. Psychophysiology, 30,
223-230.

Heffner, K.L., Loving, T.J., Kiecolt-Glaser, J.K., Himawan, L.K., Glaser, R. & Malarkey,
W.B. (2006). Older spouses’ cortisol responses to marital conflict: Associations with
demand/withdraw communication patterns. Journal of Behavioral Medicine, 29, 317-
325.

Hetherington, E. M. (1993). An overview of the Virginia Longitudinal Study of Divorce
and Remarriage with a focus on early adolescence. Journal of Family Psychology, 7, 39 –
56.

Hrushka, D., Kohrt, B., & Worthman, C. A. (2005). Estimating between- and within-
individual variation in cortisol using multilevel models. Psychoneuroendrocrinology, 30,
698 –714.

Jacobs, N., Myin-Germeys, I., Derom, C., Delespaul, P., van Os, J. & Nicolson, N.A.
(2007). A momentary assessment study of the relationship between affective and
adrenocortical stress responses in daily life. Biological Psychology, 74, 60-66.

Jacobson N.S., Gottman J.M., Waltz J., et al. (1994). Affect, verbal, content, and
psychophysiology in the arguments of couples with a violent husband. Journal of
Consulting and Clinical Psychology, 62, 982-988,

Johnson, N.J., Backlund, E., Sorlie, P.D., & Loveless, C.A. (2000). Marital status and
mortality: the National Longitudinal Mortality Study. Annals of Epidemiology, 10, 224-
238.

Kiecolt-Glaser, J.K., Bane, C., Glaser, R., & Malarkey, W.B. (2003). Love, marriage, and
divorce: Newlywed’s hormones foreshadow relationship changes. Journal of Consulting
and Clinical Psychology, 71, 176-188.

Kiecolt-Glaser, J.K., Glaser, R., Cacioppo, J.T., MacCallum, R.C., et al. (1997). Marital
conflict in older adults: Endocrinological and immunological correlates. Psychosomatic
Medicine, 59, 339-349.

Kiecolt-Glaser, J.K., Malarkey, W.B., Chee, M., Newton, T., Cacioppo, J.T., Mao, H., &
Glaser, R. (1993). Negative behavior during marital conflict is associated with
immunological down-regulation. Psychosomatic Medicine, 55, 395-409.

Kiecolt-Glaser, J.K. & Newton, T.L. (2001). Marriage and health: His and hers.
Psychological Bulletin, 127, 472-503.
45
Kiecolt-Glaser, J.K., Newton, T., Cacioppo, J.T., MacCallum, R.C., Glaser, R. &
Malarkey, W.B. (1996). Marital conflict and endocrine function: Are men really more
physiologically affected than women? Journal of Consulting and Clinical Psychology,
64, 324-332.

Kirschbaum, C., & Hellhammer, D.H. (1994). Salivary cortisol in psychoneuroendocrine
research: recent developments and applications. Psychoneuroendocrinology, 19, 313–
333.

Kirschbaum, C., Kudielka, B.M., Gaab, J., Schommer, N.C. & Hellhammer, D.H. (1999).
Impact of gender, menstrual cycle phase, and oral contraceptives on the activity of the
hypothalamus-pituitary-adrenal axis. Psychosomatic Medicine, 61, 154-162.

Kirschbaum, C., Wust, S. & Hellhammer, D.H. (1992). Consistent sex differences in
cortisol responses to psychological stress. Psychosomatic Medicine, 54, 648-657.

Koltyn, K. F., O'Connor, P. J. & Morgan, W. P. (1991). Perception of effort in female
and male competitive swimmers. International Journal of Sports Medicine, 12, 427-429.

Kudielka, B.M. & Kirschbaum, C. (2005). Sex differences in HPA axis responses to
stress: A review. Biological Psychology, 69, 113-132.

Larson, R., & Almeida, D. (1999). Emotional transmission in the daily lives of families:
A new paradigm for studying family process. Journal of Marriage and the Family, 61, 5–
20.

Lauc, G., Zvonar, K., Vuksic-Mihaljevic, Z., & Flogel, M. (2004). Post-awakening
changes in salivary cortisol in veterans with and without PTSD. Stress and Health, 20,
99-102.

Levenson, R. W., Carstensen, L. L., & Gottman, J. M. (1994). The influence of age and
gender on affect, physiology, and their interrelations: A study of long-term marriages.
Journal of Personality and Social Psychology, 67, 56–68.

Lovallo, W. R., & Thomas, T. L. (2000). Stress hormones in psychophysiological
research. In J. T. Cacioppo, L. G. Tassinary, & G. G Berntson. (Eds.), Handbook of
Psychophysiology, 2nd ed. (pp. 342-367). New York, NY: Cambridge University Press.

Loving, T.J., Heffner, K.L., & Kiecolt-Glaser, J.K. (2006). Physiology and interpersonal
relationships. In A.L. Vangelisti & D. Perlman (Eds.), The Cambridge handbook of
personal relationships (pp. 385-405). New York: Cambridge University Press.

46
Loving, T.J., Heffner, K.L., Kiecolt-Glaser, J.K., Glaser, R. & Malarkey, W.B. (2004).
Stress hormone changes and marital conflict: Spouses’ relative power makes a difference.
Journal of Marriage and Family, 66, 595-612.

Malarkey, W.B., Kiecolt-Glaser, J.K., Pearl, D., & Glaser, R. (1994). Hostile Behavior
During Marital Conflict Alters Pituitary and Adrenal Hormones. Psychosomatic
Medicine, 56, 41-51.

Margolin, G. (1988). Interpersonal and intrapersonal factors associated with marital
violence. In G.T. Hotaling, D. Finkelhor, J.T. Kirkpatrick, & M.A. Straus, (Eds.), Family
abuse and its consequences: New directions in research. (pp. 203-217). Thousand Oaks,
CA: Sage Publications.

Margolin, G., Burman, B., John, R. S., & O’Brien, M. (2000). The Domestic Conflict
Inventory. Unpublished measure, University of Southern California.

Margolin, G., Gordis, E.B., & Oliver, P.H. (2004). Links between marital and parent-
child interactions: Moderating role of husband-to-wife aggression. Development and
Psychopathology, 16, 753-771.

Michaud, K., Matheson, K., Kelly, O., & Anisman, H. (2008). Impact of stressors in a
natural context on release of cortisol in healthy adult humans: A meta-analysis. Stress,
11, 177-197.

Miller, G. E., Chen, E., & Zhou, E.S. (2007). If it goes up, must it come down? Chronic
stress and the hypothalamic-pituitary-adrenocortical axis in humans. Psychological
Bulletin, 133, 25-45.

Newton, T.L. & Sanford, J.M. (2003). Conflict structure moderates associations between
cardiovascular reactivity and negative marital interaction. Health Psychology, 22, 270-
278.

Pennebaker, J. W, & Roberts, T. A. (1992). Toward a his and hers theory of emotion:
Gender differences in visceral perception. Journal of Social and Clinical Psychology, 11,
199-212.

Pollard, T.M., Ungpakorn, G., Harrison, G.A. & Parkes, K.R. (1996). Epinephrine and
cortisol responses to work: A test of the models of Frankenhaeuser and Karasek. Annals
of Behavioral Medicine, 18, 229-237.

Pruessner, J.C., Kirschbaum, C., Meinlschmid, G., & Hellhammer, D.H. (2003). Two
formulas for computation of the area under the curve represent measures of total hormone
concentration versus time-dependent change. Psychoneuroendocrinology, 28, 916-931.
47
Raudenbush, S. W., Bryk, A. S., Cheong, Y., & Congdon, R. T. (2004). HLM 6:
Hierarchical linear and nonlinear modeling. Lincolnwood, IL: Scientific Software
International.

Robles, T.F. & Kiecolt-Glaser, J.K. (2003). The physiology of marriage: pathways to
health. Physiology and Behavior, 79, 409-416.

Robles, T.F., Shaffer, V.A., Malarkey, W.B. & Kiecolt-Glaser, J.K. (2006). Positive
behaviors during marital conflict: Influences on stress hormones. Journal of Social and
Personal Relationships, 23, 305-325.

Saxbe, D.E., Repetti, R.L., & Nishina, A. (2008). Marital satisfaction, recovery from
work, and diurnal cortisol among men and women. Health Psychology, 27, 15-25.

Saxbe, D.E. & Repetti, R.L. (2010). For better or worse? Coregulation of couples’
cortisol levels and mood states. Journal of Personality and Social Psychology, 98, 92-
103.

Smith, T. W., Gallo, L. C., Goble, L., Ngu, L. Q., & Stark, K. A. (1998). Agency,
communion, and cardiovascular reactivity during marital interaction. Health Psychology,
17, 537–545.

Smyth, J.M., Ockenfels, M.C., Gorin, A.A., Catley, D., Porter, L.S., Kirschbaum, C.,
Hellhammer, D.H., & Stone, A.A. (1997). Individual differences in the diurnal cycle of
cortisol. Psychoneuroendicrinology, 22, 89-105.

Song, Z., Foo, M. & Uy, M.A. (2008). Mood spillover and crossover among dual-earner
couples: A cell phone event sampling study. Journal of Applied Psychology, 93, 443-
452.

Spiegel, D., & Giese-Davis, J. (2003). Depression and cancer: Mechanisms and disease
progression. Biological Psychiatry, 54, 269-282.

Straus, M. A., Hamby, S. L., Boney-McCoy, S., & Sugarman, D. B. (1996). The revised
Conflict Tactics Scales (CTS2): Development and preliminary psychometric data.
Journal of Family Issues, 17, 283-316.

Suarez, E.C., Kuhn, C.M., Schanberg, S.M., Williams, R.B. & Zimmerman, E.A. (1998).
Neuroendocrine, cardiovascular, and emotional responses of hostile men: The role of
interpersonal challenge. Psychosomatic Medicine, 60, 78-88.

Westman, M., Keinan, G., Roziner, I. & Benyamini, Y. (2008). The crossover of
perceived health between spouses. Journal of Occupational Health Psychology, 13, 168-
180.
48
Whisman, M.A. (1999). Marital dissatisfaction and psychiatric disorders: Results from
the National Comorbidity Survey. Journal of Abnormal Psychology, 108, 701-706.

Whitson, S. & El-Sheikh, M. (2003). Marital conflict and health: Processes and
protective factors. Aggression and Violent Behavior, 8, 283-312.

Abstract (if available)

Abstract This study investigated whether wives’ and husbands’ hypothalamic-pituitary-adrenocorticol (HPA) axis activity, as measured through cortisol, is associated with their own and their partner’s anger during a family conflict discussion, and whether previous marital conflict alters the HPA axis response. Fifty-six middle-aged couples provided 4 saliva samples: immediately following a relaxation task, immediately following a conflict discussion, 10 minutes post-discussion, and 20 minutes post-discussion. The spouses also reported on anger they experienced during the conflict discussion and frequency of marital aggression during the past year. Husbands reporting high anger showed greater overall cortisol activity than husbands reporting no anger. Wives reporting high anger did not show similar cortisol activity. Previous marital conflict interacted with discussion-specific anger. There is evidence of a trend such that husbands with low anger and low previous aggression did not show the same post-discussion cortisol increase as did husbands with previous aggression or with current anger. The implications of these findings for relational functioning and health are discussed in light of the commonality of family conflict as an everyday stressor.

Linked assets

University of Southern California Dissertations and Theses

Conceptually similar

PDF

Parents' attunement: relation to adolescent problem behavior and the moderating role of marital conflict

Asset Metadata

Creator Rodriguez, Aubrey Joy (author)

Core Title Couples’ neuroendocrine activity in response to family conflict discussions: the role of self-reported anger and previous marital aggression

School College of Letters, Arts and Sciences

Degree Master of Arts

Degree Program Psychology

Publication Date 07/25/2010

Defense Date 05/11/2010

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

Tag Anger,HPA axis,marital aggression,Marriage,OAI-PMH Harvest,Physiology

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Margolin, Gayla (committee chair), John, Richard S. (committee member), Meyerowitz, Beth E. (committee member)

Creator Email aubreyro@usc.edu,aubrod29@yahoo.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m3217

Unique identifier UC1329212

Identifier etd-Rodriguez-3784 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-348716 (legacy record id),usctheses-m3217 (legacy record id)

Legacy Identifier etd-Rodriguez-3784.pdf

Dmrecord 348716

Document Type Thesis

Rights Rodriguez, Aubrey Joy

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