Download Cognitive-Behavioral Treatment for Chronic Nightmares in Trauma-Exposed Persons: Assessing Physiological

Cognitive-Behavioral Treatment for Chronic Nightmares
in Trauma-Exposed Persons: Assessing Physiological
Reactions to Nightmare-Related Fear
m
Jamie L. Rhudy, Joanne L. Davis, Amy E. Williams,
Klanci M. McCabe, Emily J. Bartley,
Patricia M. Byrd, and Kristi E. Pruiksma
Department of Psychology, The University of Tulsa
Cognitive-behavioral treatments (CBTs) that target nightmares are
efficacious for ameliorating self-reported sleep problems and psychological distress. However, it is important to determine whether these
treatments influence objective markers of nightmare-related fear,
because fear and concomitant physiological responses could promote
nightmare chronicity and sleep disturbance. This randomized,
controlled study (N 5 40) assessed physiological (skin conductance,
heart rate, facial electromyogram) and subjective (displeasure, fear,
anger, sadness, arousal) reactions to personally relevant nightmare
imagery intended to evoke nightmare-related fear. Physiological
assessments were conducted at pretreatment as well as 1-week,
3-months, and 6-months posttreatment. Results of mixed effects
analysis of variance models suggested treatment reduced physiological and subjective reactions to nightmare imagery, gains that were
generally maintained at the 6-month follow-up. Potential implications are discussed. & 2010 Wiley Periodicals, Inc. J Clin Psychol 66:
1–18, 2010.
Keywords: psychophysiology; emotion; nightmares; treatment
outcome; cognitive-behavioral therapy
Frequent nightmares are associated with chronic distress (e.g., Kilpatrick et al., 1998;
Schreuder, Kleijn, & Rooijmans, 2000) and poor, long-term functioning (e.g.,
Harvey & Bryant, 1998), but they may also contribute to the initiation and/or
maintenance of posttraumatic stress disorder (PTSD) in trauma-exposed individuals
(Neylan et al., 1998; Ross, Ball, Sullivan, & Caroff, 1989). Despite the pervasive
negative impact of nightmares, they can be particularly resistant to interventions that
Correspondence concerning this article should be addressed to: Joanne L. Davis, The University of Tulsa,
Department of Psychology, 800 South Tucker Drive, Tulsa, OK 74104; e-mail: [email protected]
JOURNAL OF CLINICAL PSYCHOLOGY, Vol. 66(4), 1--18 (2010)
& 2010 Wiley Periodicals, Inc.
Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/jclp.20656
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Journal of Clinical Psychology, April 2010
broadly target PTSD symptomatology (e.g., Clark et al., 1999; Forbes, Creamer, &
Biddle, 2001). However, cognitive-behavioral treatments (CBTs) that specifically
target nightmares appear to be more efficacious, showing improvements in subjective
sleep quality and reductions in the severity and frequency of idiopathic and traumarelated nightmares (e.g., Davis & Wright, 2007; Krakow et al., 2001). We find it
interesting that these interventions also improve symptoms of PTSD and depression,
although these are not specifically targeted in treatment (e.g., Davis & Wright;
Krakow et al., 2001).
From a theoretical standpoint, it may be important to assess objective indicators
of nightmare-related fear and negative affect as an outcome of nightmare treatments,
because fear may promote and maintain nightmare chronicity. For example, Levin
and Nielsen (2007) have argued that posttraumatic nightmares (and even distressing
non-posttraumatic nightmares) reflect a failure of fear extinction processes that
would normally occur during dreaming—processes that are mediated by a putative
neural circuit involving the amygdala, medial prefrontal cortex, anterior cingulate
cortex, and hypothalamus. In Levin and Nielsen’s conceptualization, nightmares are
pathological versions of fear memory networks that are highly resistant to extinction
(Foa & Kozak, 1986; Lang, 1979) and lead to responses such as avoidance,
physiological reactivity, and affective distress. Successful amelioration of nightmares
requires the extinction of the fear memory network, breaking linkages among (a) the
nightmare content, (b) physiological, verbal, and behavioral responses of fear, and
(c) the meaning associated with these responses (Foa & Kozak, 1986; Lang, 1979;
Levin & Nielsen, 2007). Following Levin and Nielsen’s line of reasoning, successful
nightmare treatments should reduce objective measures of nightmare-related fear.
One experimental paradigm that can be used to assess physiological reactions to
nightmare-related fear is script-driven imagery. In most script-driven imagery
experiments, participants are exposed to a personally relevant fear script and asked
to imagine it as vividly as possible while physiological reactions are assessed (e.g.,
heart rate [HR], skin conductance [SC], facial electromyogram [EMG]). This method
of fear elicitation has been used extensively in individuals with PTSD and other
anxiety disorders with results indicating a marked increase in physiologicalemotional reactions to the personal fear imagery (e.g., Cuthbert et al., 2003;
Lindauer et al., 2006; Orr, 1997). As further validation, imaging research employing
the script-driven imagery paradigm have found it can activate neural circuitry
involved with fear and negative emotions (e.g., amygdala, anterior cingulated; e.g.,
Etkin & Wager, 2007; Lanius et al., 2007; Lindauer et al., 2004; Shin et al., 2004),
and treatment outcome studies have found that physiological responses to scriptdriven fear are reduced by successful interventions (e.g., Lindauer et al., 2006;
Shalev, Orr, & Pitman, 1992).
If Levin and Nielsen’s (2007) hypothesis is correct, then assessing physiological
reactions to nightmare-related imagery should provide a method of assessing the
strength of the fear memory network that maintains the nightmares. In a previous
study, we have shown that personal nightmare imagery evokes robust physiological
and negative emotional reactions in trauma-exposed nightmare sufferers, an effect
that is independent of mental health status (PTSD, depressive symptomatology,
dissociation; Rhudy, Davis, Williams, McCabe, & Byrd, 2008). Specifically,
nightmare imagery led to HR acceleration, increased SC (a measure of sympathetic
nervous system activation), and increased tension in facial muscles as assessed from
EMG (indicative of facial displays of negative emotion and fear). Rhudy et al. (2008)
also noted that autonomic responses (HR, SC) evoked by nightmare imagery were
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positively correlated with self-reported sleep problems and health symptoms.
Together, these results suggest the script-driven imagery paradigm is an ideal
method to assess the effects of CBT for nightmares on physiological reactivity to
nightmare-related fear.
The purpose of the present study was to assess the impact of Exposure,
Relaxation, & Rescripting Therapy (ERRT) on physiological and subjective
measures of fear and negative affect (HR, SC, facial EMG) in response to personal,
nightmare-related imagery. ERRT is a brief, three-session treatment that directly
targets nightmares in trauma-exposed persons. A case study (Davis, De Arellano,
Falsetti, & Resnick, 2003), a case series (Davis & Wright, 2005), and a randomized
controlled trial (Davis & Wright, 2007) have previously demonstrated the efficacy of
ERRT on other outcome measures. Specifically, immediate improvements (1 week
posttreatment) were noted in the reported frequency and severity of nightmares,
sleep problems, PTSD symptom frequency and severity, feeling rested upon
wakening, and depression, with treatment gains persisting to the 6-month followup (e.g., only 16% reporting a nightmare in the previous week; Davis & Wright). To
date, no study has examined the influence of treatment for nightmares on objective
measures of nightmare-related fear. However, given the positive effects ERRT has
on other outcome measures, we predicted it would reduce physiological and
subjective emotional reactions to nightmare imagery and that treatment gains would
persist for at least 6 months.
Methods
Participants
Participants were eligible to participate if they were Z18 years old, had previous
trauma exposure, and nightmares Z1 time/week for the previous 3 months.
Exclusion criteria included psychosis, mental retardation, suicidality/parasuicidal
behaviors, or current drug/alcohol dependence. Participants were asked to refrain
from consuming alcohol, nicotine, or caffeine 24 hours before physiological
assessments. Figure 1 depicts the recruitment flowchart and final participant
numbers. Of the 40 participants randomized to the study, most were female (73.2%),
married (42.9%), and employed full time (46.3%). Ages ranged from 21 to 63 years
(M 5 38 yrs, SD 5 12). Trauma exposure comprised the following items (participants
could list more than one): serious accident (63.4%), natural disaster (34.1%),
diagnosed with serious illness (19.5%), sexual assault/rape (53.7%), attacked with
weapon (53.7%), attacked without weapon (43.9%), serious injury/physical damage
(31.7%), threat of death/serious injury (48.8%), and witnessed others seriously
injured or violently killed (41.5%). Written informed consent was obtained from all
participants after a complete description of the study was provided.
Cognitive Behavioral Treatment for Nightmares: Exposure, Relaxation, and
Rescripting Therapy (ERRT)
For a thorough description of ERRT, see Davis and Wright (2007). ERRT was
administered 2 hours a week for three weeks. Session 1 included psychoeducation
(about trauma, PTSD, nightmares, and sleep hygiene) and training in progressive
muscle relaxation (PMR). Homework included practicing PMR, changing one’s
sleep habit, and monitoring nightmares and psychological symptoms. Session 2
included review of homework and instructions for exposure and rescripting.
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Figure 1. Flowchart of participant recruitment and final participant numbers.
Exposure included writing out the nightmares, reading it aloud, and identifying
relevant themes (McCann, Sakheim, & Abrahamson, 1988; Resick & Schnicke,
1993). Participants were instructed to rescript their nightmare any way they wanted
but were encouraged to use the themes (e.g., increase sense of power if nightmare
theme was powerlessness) in writing and read aloud the rescripted nightmare.
Session 2 ended with diaphragmatic breathing and homework (visualize rescripted
dream, PMR, change another sleep habit, practice breathing, monitor symptoms).
Session 3 included homework review, discussion of rescripting process, and problemsolving difficulties.
Questionnaires
For the present study, several questionnaires were administered to assess demographic
information and to determine whether there were group differences (completers vs.
noncompleters) on important psychological and sleep-related variables.
A self-report demographic questionnaire was used to obtain information about
age, marital status, educational achievement, ethnicity, vocational status, and
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household income. The symptom endorsement method of scoring the ClinicianAdministered PTSD scale (CAPS; Blake et al., 1990) was used to determine current
and lifetime PTSD diagnoses. This method has adequate sensitivity and specificity
rates (Weathers, Ruscio, & Keane, 1999) and good reliability (Blake et al.; Weathers
et al.). The Modified PTSD Symptom Scale Self Report (MPSS-R-SR; Resnick,
Best, Kilpatrick, Freedy, & Falsetti, 1993) assessed the frequency and severity of 17
PTSD symptoms (Falsetti, Resnick, Resick, & Kilpatrick, 1993; Wright, Davis,
Inness, & Stem, 2003). The Beck Depression Inventory-2 (BDI-2; Beck, Steer, &
Brown, 1996) was used to assess depressive symptomatology. The Pittsburgh Sleep
Quality Index (PSQI; Buysse, Reynolds, Monk, Berman, & Kupfer, 1989) was used
to assess sleep problems and quality for the 1-month before the assessment (Buysse
et al.). A global sleep quality score was obtained by summing seven component
scores (subjective sleep quality, sleep latency, sleep duration, habitual sleep
efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction).
Scores ranged from 0 to 21 (higher scores 5 poorer sleep quality). Additionally, the
Pittsburgh Sleep Quality Index Addendum for PTSD (PSQI-A; Germain, Hall,
Krakow, Shear, & Buysse, 2005) was used to assess PTSD-related sleep/nighttime
behaviors. Scores can range from 0 to 21 with higher scores reflecting greater sleep
problems. A computer version of the Self-Assessment Manikin (SAM; Bradley &
Lang, 1994) was used to assess subjective valence/pleasure (unpleasant–pleasant) and
arousal (calm–excited) in response to nightmare imagery (Rhudy, Williams,
McCabe, Nguyen, & Rambo, 2005). For this study, the valence/pleasure scale was
reverse scored to assess displeasure. Scores ranged between 1 and 9 for each
dimension (higher scores 5 greater displeasure or arousal). Additionally, participants were asked to rate their subjective fear, anger, and sadness in response to the
imagery using 21-point Likert-type scales (0 5 Not at all, 20 5 Extremely).
Emotional Scripts for Script-Driven Imagery
Experimenters constructed a personal nightmare script for each participant from
content assessed by the Nightmare Content Interview, a structured interview
developed for the present study. The Nightmare Content Interview asked
participants to report on their most recurrent, or most recent (if a single recurring
nightmare was not available), nightmare. General instructions asked them to ‘‘briefly
describe your recurrent nightmare,’’ and then follow-up questions probed for
cognitive, somatic, and sensory details of the nightmare. In addition, nonpersonal
scripts (fear 5 public speaking, neutral 5 sitting on a lawn chair, pleasant 5 lying on
beach, action 5 riding a bicycle) were obtained from other researchers using scriptdriven imagery (Peter Lang, personal communication; Scott Orr, personal
communication) and used as control stimuli. All personal and nonpersonal scripts
were approximately 100 words long, written in second person, and recorded onto the
computer by a female experimenter in a slow-paced voice (length530-s). Thus, the
computer presented all scripts and the order of scripts was randomized both withinand between-subjects.
We have previously demonstrated the validity of script-driven imagery for evoking
nightmare-related fear and negative emotions (Rhudy et al., 2008). Specifically, in 28
participants, nightmare imagery was shown to evoke significant displeasure (SAM
valence ratings reversed scored) and arousal (Ms 5 8.28 and 7.61, respectively).
Moreover, variability in these reactions was small (SEMs 5 0.25 and 0.38,
respectively), suggesting that despite the nightmare scripts being different for each
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Table 1
Means and Standard Errors for Subjective Emotional Reactions to Nightmare Imagery,
Separated by Treatment (N 5 18) and Waitlist Control (N 5 21) Groups and Assessment
Period
Baseline
Rating scale
SAM displeasure (1–9)
Fear (1–20)
Anger (1–20)
Sadness (1–20)
SAM arousal (1–9)
Treatment
Control
Treatment
Control
Treatment
Control
Treatment
Control
Treatment
Control
Posttreatment/baseline #2
Mean
SEM
Mean
SEM
8.33
8.43
16.67
15.95
9.28
10.48
12.89
12.90
8.00
7.76
0.30
0.27
1.21
1.12
1.74
1.61
1.58
1.46
0.38
0.35
6.60
8.57
7.36
14.72
7.55
10.33
6.68
12.27
5.93
7.27
0.34
0.30
1.39
1.23
1.82
1.66
1.74
1.55
0.45
0.39
Note: SEM 5 standard error of the mean; SAM 5 Self-Assessment Manikin.
Indicates the Bonferroni adjusted mean comparison between baseline and posttreatment was significant
at po0.05.
participant, they were consistently distressing. Data from the current study also
support the validity of using script-driven imagery to evoke nightmare-related fear
(see Table 1).
We have also shown that reactions to nightmare imagery correlate with other
treatment outcome variables (Rhudy et al., 2008). For example, HR reactivity was
associated with global sleep problems (as assessed by the Pittsburgh Sleep Quality
Index; r 5 0.55), reported hours slept per night (r 5 0.59), subjective panic upon
waking (r 5 0.58), reported health symptoms (as assessed by the Pennebaker
Inventory of Limbic Languidness; r 5 0.54), and minutes taken to fall asleep
(r 5 0.41). SC reactivity was associated with minutes taken to fall asleep (r 5 0.50),
hours slept per night (r 5 0.40), and panic upon awakening (r 5 0.63). Displeasure
reactions were associated with PTSD-related sleep behaviors (r 5 0.46) and
corrugator EMG reactions were associated with minutes taken to fall asleep
(r 5 0.41). Together, these data provide external validity for the use of the scriptdriven imagery to assess treatment outcome.
Prior analyses on physiological-emotional reactions to imagery at baseline
suggested only the personally-relevant, nightmare script produced robust physiological responses (Rhudy et al., 2008). Of the nonpersonal scripts, the fear script led to
the largest change in SC (0.28 DmS), corrugator EMG (1.22 DmV), and lateralis
frontalis EMG (0.25 DmV), and the action script led to the largest change in HR
(2.56 Dbpm). When these reactions are compared with the personally relevant,
nightmare imagery (see Fig. 2), it is clear that reactions to nonpersonal scripts
were much smaller. Therefore, to avoid floor effects (i.e., it would be difficult
to observe reliable decreases in such small reactions), only reactions to the
nightmare script were used to assess treatment response in the present study.
However, preliminary analyses that examined the influence of treatment on
physiological reactions to the fear script (the nonpersonal script that evoked the
most consistent responses) found that treatment did not alter those reactions
(Davis et al., 2008).
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Figure 2. Physiological reactions to nightmare imagery separated by group (treatment vs. waitlist) and time
(baseline vs. 1-week posttreatment). Posttreatment data for the control group are values following a wait
period equivalent to the length of treatment. Graphs on the left are facial electromyographic (EMG) reactions
(corrugator 5 left eyebrow muscle, lateralis frontalis 5 left forehead muscle), whereas graphs on the right are
autonomic responses (heart rate [HR]; skin conductance [SC]). Error bars are standard error of the mean
(SEM). Indicates significant Bonferroni adjusted mean comparison of baseline to posttreatment ( po0.05).
Apparatus and Physiological Recording
Participants sat alone in a sound attenuated chamber while being monitored from an
adjoining room by video camera. A PC with dual 17’’ flat panel monitors and A/D board
(National Instruments, PCI-6036E) presented scripts and SAM questionnaires, as well as
acquired and stored physiological data. One monitor was used by the experimenter to
track physiological signals, whereas the participant used the other monitor to complete
the SAM. Signals were sampled at 250 Hz and collected/filtered using a Model 15LT
Bipolar Amplifier (Grass Technologies, West Warwick, RI) with Quad AC (15A54) and
Dual DC (15A12) modules. SC was measured using an adaptor (Grass, Model SCA1)
for the 15A12, and electrodes filled with isotonic paste (EC33, Grass) were placed on the
distal volar surface of the nondominant index and middle fingers. Miniature electrodes to
measure corrugator electromyogram (EMG) and lateralis frontalis EMG were placed
according to the recommendations of Fridlund and Cacioppo (1986) on the left-side of
the face. Electrodes for electrocardiogram (ECG) were placed on the forearms to assess
heart rate (HR). Facial EMG and ECG electrodes were applied by degreasing the skin,
slightly abrading the skin using NuPrep gel (r10 KO), and filling the electrodes with
EC60 gel (Grass). Facial EMG activity was used as a physiologic measure of negative
affect (e.g., Orr et al., 1998), because the corrugator pulls the eyebrow down into a frown
and the lateralis frontalis raises the outer eyebrow as in displays of fear. HR and SC were
used to assess autonomic reactivity, with SC being primarily driven by the sympathetic
nervous system (Dawson, Schell, & Filion, 2000).
Procedure
All procedures were approved by the University of Tulsa ethics review board. At an
initial laboratory visit, eligible participants were assessed on psychological variables
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(demographics, PTSD symptom severity, depressive symptoms, nightmare characteristics, and sleep problems), and a structured interview (Nightmare Content
Interview) assessed details of their nightmares to generate a personal nightmare
script. Then, participants were randomly assigned to treatment or a waitlist control
group. In a subsequent laboratory visit (referred to as ‘‘baseline assessment’’ from
here forward), participants were seated in a recliner, instrumented for facial EMG,
SC, and ECG, and then sat quietly during a 5-minute habituation period after the
experimenter left the room. Computer-presented instructions guided the participant
through a 3-minute diaphragmatic breathing exercise. During script-driven imagery,
emotionally charged scripts were presented in random order (randomized withinsubjects and between-subjects) and participants were instructed to ‘‘imagine it as if it
were happening to you.’’ Physiological reactivity to imagery was derived from
2-minute epochs (30-s baseline, 30-s computer-presented script, 30-s imagery, 30-s
recovery). After each 2-minute epoch, the participants rated their subjective
reactions to the imagery using the Self-Assessment Manikin and emotion descriptors
(i.e., fear, anger, sadness), and then the heart rate was monitored until it returned to
prescript levels (generally 1–2 min). Although several scripts were presented to evoke
emotional imagery, this study focused only on physiological reactions to personal
nightmare scripts. Reactivity to script-driven imagery was assessed again 1 week
after Exposure, Relaxation, and Rescripting Therapy or an equivalent waiting
period for the control group. At that time, control participants were offered
treatment. Reactivity to script-driven imagery was assessed again in all participants
at 3-months and 6-months posttreatment. To minimize experimenter bias,
experimenters that conducted physiological assessments were blinded to participants’ group assignments. Participants received a $20 gift card for each completed
assessment period.
Physiological Data Reduction
ECG was converted offline to heart rate (HR) in beats per minute (BPM). The raw
signals for HR, SC, and facial EMG were visually inspected for artifacts in five s
bins. Bins that did not contain artifacts were then averaged into 30-s phases
(baseline, script, imagery, recovery). Physiological reactivity due to script-driven
imagery was defined as the average change in the raw physiological signals during
the 30-s imagery phase minus the average activity during the 30-s baseline phase.
Data Analysis
Preliminary analyses. Preliminary analyses were conducted to determine whether
interpretations of treatment outcomes for the controlled portion of this study
(i.e., baseline assessment and posttreatment/baseline 2; see Fig. 1) may have been
confounded by attrition. To do so, chi-square analyses (for nominal variables) and
independent samples t-tests (for interval or ratio scale variables) were used to compare
those who completed assessments 1 and 2 with those who did not on relevant study
variables assessed at baseline (demographics, sleep quality, psychological symptoms,
physiological-emotional reactivity).
Analysis of treatment response. First, to assess treatment response relative to the
control group, a 2 (Time: baseline assessment vs. posttreatment/baseline ]2) 2
(Group: treatment vs. waitlist) mixed effects ANOVA was conducted separately for
each physiological (corrugator EMG, lateralis frontalis EMG, HR, SCR) or
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subjective (SAM displeasure, SAM arousal, fear, anger, sadness) outcome using the
SPSS 14.02 MIXED procedure. Participant ID number was used as the grouping
variable, and the error structure of repeated measures was modeled as AR1. A major
advantage of the MIXED procedure is that cases with incomplete or missing data
are not dropped from the analysis. Thus, participants who dropped out are still
included in the analyses. However, for comparison, a second set of analyses were
conducted that carried the last value forward to replace missing data to see whether
this altered the conclusions.
To determine the magnitude of the treatment effects for the comparison to waitlist
controls, first the change over time for the treatment group was defined as folows:
Cohen’s dtreatment 5 (posttreatment mean baseline mean)/pooled standard deviation. Then, change over time for the control group was defined as follows: Cohen’s
dcontrol 5 (baseline assessment 2 mean baseline assessment ]1 mean)/pooled
standard deviation. The treatment effect size was defined as Cohen’s dtreatment–
Cohen’s dcontrol. Cohen (1988) provides guidelines for interpreting d (small 5 0.20,
medium5 0.50, large 5 0.80).
In the second set of analyses, the participants in the waitlist control group who
completed the treatment were combined with the immediate treatment group to
determine the long-term benefits of treatment (i.e., treatment response at 3-month
and 6-month follow-up). These analyses were conducted with mixed effects analysis
of variances (ANOVAs) that included only the effect of time as a nominal variable
with four levels (pretreatment, posttreatment, 3-month, and 6-month). Again, a
second set of comparison analyses were conducted after carrying the last value
forward to replace missing data.
For all MIXED ANOVAs, significant effects were followed up using Bonferroni
corrected mean comparisons to control for family-wise error rate (reported p values
are the probability of Type I error after Bonferroni corrections were made). In the
SPSS MIXED procedure, degrees of freedom for the denominator of F tests are
estimated using Satterthwaite approximation and are, therefore, reported with
decimals.
Hypotheses
For the analyses that compared active treatment to the waitlist control, it was
predicted that ERRT would decrease physiological and subjective reactivity to
nightmare imagery. Therefore, significant Group Time interactions were expected,
such that the simple effect of time should be significant for participants randomized
to treatment but not the control group. For analyses of the long-term treatment
response in all participants (including control participants after being provided
treatment), it was predicted that posttreatment gains would be maintained at
3-month and 6-month follow-up periods.
Results
Preliminary Analyses
Data from 1 of the 40 participants was lost due to equipment problems. Participants
who completed baseline assessment and posttreatment/baseline 2 (completers,
n 5 30) did not differ on any relevant variables from those who did not complete
both assessments (noncompleters, n 5 9), except noncompleters reacted with less
subjective arousal to the nightmare imagery (Table 2). Thus, it does not appear that
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Table 2
Comparison of Completers and Noncompleters on Psychological, Sleep, and Baseline
Physiological-Emotional Reactivity Variables
Psychological symptoms
Depression symptoms (BDI-2)
PTSD symptom frequency (MPSS-R)
PTSD symptom severity (MPSS-R)
% Current PTSD diagnosis (CAPS)
% Lifetime PTSD diagnosis (CAPS)
Sleep problems
Global sleep quality (PSQI)
PTSD-related sleep problems (PSQI-A)
Baseline physiological-emotional reactions
Corrugator EMG (DmV)
Lateralis frontalis EMG (DmV)
Heart rate (Dbpm)
Skin conductance level (DmS)
SAM displeasure rating (1–9)
SAM arousal rating (1–9)
Fear rating (0–20)
Anger rating (0–20)
Sadness rating (0–20)
Completers (n 5 30)
Noncompleters (n 5 9)
Mean or %
SD
Mean or %
SD
19.57
20.14
24.43
27%
57%
10.89
10.19
14.36
22.89
22.75
27.00
33%
33%
14.36
16.26
18.47
.75
.43
.42
.15
1.51
.46
.68
.66
.70
.22
12.86
9.23
4.70
4.50
12.43
10.67
5.19
5.79
.22
.78
.83
.44
8.41
1.24
6.36
0.99
8.53
8.10
15.93
9.70
12.43
9.55
3.27
7.05
1.09
0.82
1.27
4.92
7.06
6.64
2.69
1.28
2.76
0.74
7.75
6.88
17.13
9.50
13.75
4.79
3.63
5.69
0.82
1.75
2.03
3.64
8.11
7.72
1.63
.03
1.33
.60
1.22
2.13
.64
.07
.48
.11
.98
.19
.55
.26
.04
.52
.95
.63
t or w2 p value
Note: BDI-2 5 Beck Depression Inventory, 2nd edition; PTSD 5 posttraumatic stress disorder; MPSSR 5 Modified PTSD Symptom Scale Self Report; CAPS 5 Clinician-Administered PTSD Scale;
PSQI 5 Pittsburgh Sleep Quality Index; EMG 5 electromyogram; SAM 5 Self-Assessment Manikin.
attrition confounded analyses that compared the treatment group with waitlist
controls.
Analysis of Treatment Response: Comparisons to the Waitlist Control Group
Physiological outcomes. Figure 2 illustrates these data. The Group Time
interaction was significant for the following: corrugator EMG, F(1, 35.34) 5 4.93,
p 5 0.03; lateralis frontalis EMG, F(1, 31.46) 5 5.17, p 5 0.03; HR, F(1, 34.32) 5 5.51,
p 5 0.03; and SC, F(1, 36.20) 5 6.16, p 5 0.02. Bonferroni comparisons that
decomposed the interactions indicated that all physiological reactions to nightmare
imagery were lower at posttreatment than baseline for the treatment group (all
psr0.013), but physiological reactions of the control group did not change over time
(all ps40.40). Cohen’s d treatment effect sizes were large: corrugator EMG 5 1.13;
lateralis frontalis EMG 5 0.89; HR 5 0.93; and SC 5 0.99. Together, these results
suggest physiological reactivity to nightmare imagery was significantly reduced by CBT.
Analyses of physiological outcomes that used the last value carried forward
method to handle missing data resulted in the exact same conclusions. The
Group Time interaction was significant for all physiological measures (all
psr.046), and the baseline versus posttreatment comparison was significant for
the treatment group (all psr0.01), but no change over time was noted in the control
group (all ps40.40).
Subjective outcomes. Table 1 presents means and standard errors for subjective
outcomes. The Group Time interaction was significant for the following: SAM
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displeasure ratings, F(1, 30.68) 5 13.36, p 5 0.001; fear ratings, F(1, 36.49) 5 16.22,
po0.001; sadness ratings, F(1, 31.85) 5 8.34, p 5 0.007; and SAM arousal ratings,
F(1, 31.77) 5 4.84, p 5 0.04. Bonferroni comparisons that decomposed the
interactions indicated that ratings of displeasure, fear, sadness, and arousal were
lower at posttreatment compared to baseline for the treatment group (all psr0.001),
but subjective reactions of the control group did not change over time (all ps40.31).
Although mean levels of anger were lower at posttreatment than baseline in the
treatment group, no significant effects were found for anger ratings (all ps40.17).
Cohen’s d treatment effect sizes were small to large: SAM displeasure 5 1.24;
fear 5 1.20; anger 5 0.46; sadness 5 0.90; SAM arousal 5 0.68. Together, these
analyses suggest that, except for anger, negative emotional reactions to nightmare
imagery were reduced but only in the treatment group.
Analyses of subjective outcomes that used the last value carried forward method
to handle missing data resulted in the same conclusions, except that the
Group Time interaction for arousal ratings was not significant ( p 5 0.06).
However, for displeasure, fear, and sadness ratings, the Group Time interaction
was significant (all psr0.012) and the baseline versus posttreatment comparison was
significant for the treatment group (all psr0.001), but there was no change over time
in the control group (all ps40.37). Like the analysis with missing data, anger ratings
were not affected by treatment (Group Time interaction: p 5 0.30).
Analysis of Treatment Response: Follow-up Analyses
For follow-up analyses, the assessment period most proximal to treatment delivery
was used as time 1 (baseline assessment for the treatment group, baseline assessment
2 for the control group; see Fig. 1). Four participants in the control group dropped
out before baseline assessment 2, which resulted in available data from 35
participants for these analyses.
Physiological outcomes. Figure 3 presents these data. The main effect of time was
significant for the following: corrugator EMG, F(3, 66.67) 5 5.35, p 5 0.002; lateralis
frontalis EMG, F(3, 45.31) 5 3.88, p 5 0.02; HR, F(3, 65.83) 5 6.07, p 5 0.001; and
SC, F(3, 50.36) 5 10.71, po0.001. Bonferroni tests for corrugator EMG and SC
reactivity suggested mean comparisons were significant for baseline versus
posttreatment ( pr0.006), baseline versus 3-month ( pr0.02) and baseline versus
6-month follow-up ( pr0.03). But, tests that compared means at posttreatment,
3-month, and 6-month assessments were all nonsignificant (all ps40.99) for
corrugator EMG and SC reactivity. Lateralis frontalis reactivity was lower during
posttreatment than baseline ( p 5 0.006), but all other Bonferroni comparisons were
nonsignificant (all ps40.12). HR reactivity decreased from baseline to posttreatment
( p 5 0.002) and 6-month follow-up ( p 5 0.01), but all other comparisons were
nonsignificant (all ps40.18). Together, these analyses suggested corrugator EMG
and SC showed consistent long-term maintenance, whereas reductions in HR
reactivity were maintained only at 6-month follow-up, and reductions in lateralis
frontalis EMG were not maintained at 3-month or 6-month follow-up. Analyses of
physiological outcomes that used the last value carried forward method to handle
missing data resulted in the exact same conclusions.
Subjective outcomes. Table 3 presents these data. The main effect of time was
significant for the following: SAM displeasure ratings, F(3, 55.81) 5 5.35, po0.001;
fear ratings, F(3, 50.40) 5 18.04, po0.001; anger ratings, F(3, 46.63) 5 5.76,
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Figure 3. Long-term effects of cognitive-behavioral treatment for nightmares on physiological reactions
to nightmare imagery. Data depicted are from all participants, including those randomized to delayed
treatment (waitlist control group). Graphs on the left are facial electromyographic (EMG) reactions
(corrugator 5 left eyebrow muscle, lateralis frontalis 5 left forehead muscle), whereas graphs on the right
are autonomic responses (heart rate [HR]; skin conductance, SC). Error bars are standard error of the
mean (SEM). Indicates significant Bonferroni adjusted mean comparison to baseline ( po0.05).
Table 3
Subjective Reactions to Nightmare Imagery for Follow-Up Analyses (N 5 35)
Baseline
Outcome variable
SAM displeasure (1–9)
Fear (1–20)
Anger (1–20)
Sadness (1–20)
SAM arousal (1–9)
Mean
8.49
15.63
10.09
12.49
7.66
Posttreatment
SEM
Mean
0.31
0.98
1.21
1.12
0.32
6.69
8.48
7.90
6.97
6.02
3-month follow-up
SEM
Mean
0.35
1.12
1.29
1.23
0.37
6.87
6.95
5.76
6.87
5.70
6-month follow-up
SEM
Mean
SEM
0.37
1.19
1.35
1.31
0.39
7.23
6.44
5.74
7.70
5.73
0.40
1.31
1.43
1.42
0.42
Note: SEM 5 Standard error of the mean; SAM 5 Self-Assessment Manikin.
Indicates statistically significant comparison to baseline based on Bonferroni adjusted tests ( po0.05).
p 5 0.002; sadness ratings, F(3, 52.62) 5 9.61, po0.001; and arousal ratings,
F(3, 64.72) 5 9.53, po0.001. Bonferroni tests for displeasure, fear, sadness, and
arousal ratings suggested the mean comparisons were significant for baseline versus
posttreatment (all psr0.001), baseline versus 3-month (all psr0.001), and baseline
versus 6-month follow-up (all psr0.039). But, tests that compared means at
posttreatment, 3-month, and 6-month assessments were nonsignificant (all ps40.99)
for displeasure, fear, sadness, and arousal ratings. Anger ratings did not decrease
from baseline to posttreatment ( p 5 0.14), but they did decrease from baseline to
3-month ( p 5 0.002) and 6-month follow-up ( p 5 0.009), despite the fact that anger
ratings at posttreatment, 3-month, and 6-month assessments were all statistically
equivalent (all ps40.22). Together, these analyses suggest reductions in displeasure,
fear, sadness, and arousal ratings were maintained at 3- month and 6-month
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13
assessments. However, reductions in anger were not noted at posttreatment, only at
3-month and 6-month follow-ups. Analyses of subjective outcomes that used the last
value carried forward method to handle missing data resulted in the exact same
results.
Discussion
This study assessed the influence of a CBT (ERRT) for chronic nightmares on
physiological and subjective responses to nightmare-related imagery. Physiological
reactions to nightmare imagery (corrugator EMG, lateralis frontalis EMG, HR, SC)
were reduced following treatment, relative to pretreatment baseline. This effect was
not noted after an equivalent wait period in persons randomized to the control
group, which suggests reductions in physiological reactivity noted in the treatment
group are not due to habituation or exposure to the nightmare script. Important,
treatment effect sizes for reductions in physiological reactivity were large (Cohen’s
d 5 0.89 [lateralis frontalis] to 1.13 [corrugator]), even after removing any effect due
to changes over time in the control group. Moreover, follow-up analyses that
included all participants after being treated indicated reductions in corrugator and
SC were maintained 3-months and 6-months posttreatment. We found it interesting
that HR reactivity to nightmare imagery, while reduced at posttreatment, was not
maintained at the 3-month assessment. However, a significant reduction in HR was
noted at the 6-month follow-up relative to pretreatment. Although it is unclear at
this time why HR gains may be more variable, it does underscore the importance of
measuring follow-up beyond 3-months posttreatment. Treatment gains in lateralis
frontalis EMG were not maintained at the 3-month or 6-month assessments.
Although more data are needed to explain this observation, it may stem from a floor
effect that made significant reductions in lateralis frontalis hard to detect, because
lateralis frontalis reactivity at baseline was relatively small (e.g., o2 DmV compared
with48 DmV in corrugator EMG at baseline; Fig. 2).
Treatment-related changes in subjective reactions were also noted. Displeasure,
fear, sadness, and arousal ratings of nightmare imagery were decreased following
treatment, an effect that was not observed in the control group after an equivalent
wait period. However, anger was not significantly decreased at the 1-week
posttreatment assessment. Effect sizes for treatment-related changes in subjective
reactions were generally large (Cohen’s d 5 0.90 [sadness] to 1.24 [displeasure]),
although effect sizes for arousal (d 5 .68) and anger (d 5 .46) were smaller. Followup analyses on all participants suggested treatment gains in subjective reactions were
maintained at 3-month and 6-month assessments, with anger ratings only showing a
significant reduction at the 3-month and 6-month assessments but not 1-week
posttreatment. This suggests nightmare-related anger may persist for some time after
treatment is over, and it may reflect a consequence of nightmare alleviation (rather
than a precursor), given that the number of nightmares experienced per week is an
outcome that also showed a delayed response to treatment in the current study
(Davis et al., 2009).
Together, these results suggest CBT of nightmares results in significant reductions
of physiological and subjective reactions to nightmare-related imagery. To our
knowledge, this is the first study to demonstrate beneficial effects on objective
measures of fear. These findings add to the growing body of literature, suggesting
psychological treatments for chronic nightmares can be effective. For example,
uncontrolled (Forbes, Phelps, & McHugh, 2001; Forbes et al., 2003) and controlled
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(Davis & Wright, 2007; Krakow et al., 2001, 2000; Krakow, Kellner, Pathak, &
Lambert, 1995) studies have found that brief CBT is effective in reducing not only
subjective reports of nightmare frequency and severity but also symptoms of
psychological distress not directly targeted (e.g., posttraumatic stress symptoms,
depression). These conclusions were further supported by analyses from the current
randomized, controlled trial (reported elsewhere) that indicated ERRT led to
improvements on several variables related to sleep and psychological functioning
(e.g., nightmare frequency, nightmare severity, hours slept, sleep quality, depression
symptoms, panic symptoms upon waking, PTSD symptom frequency), improvements
that were maintained at follow-up (Davis et al., in preparation; Davis et al., 2008).
This study demonstrated that thinking about nightmare-related content elicited
significant facial muscle tension, HR acceleration, and sympathetic nervous system
activation (i.e., skin conductance) prior to treatment. Such responses are likely to
reflect the activation of a pathological fear network that could promote nightmare
maintenance and sleep disturbance (Foa & Kozak, 1986; Lang, 1979; Levin &
Nielsen, 2007). Although not addressed in the current study, it is tempting to
hypothesize that heightened physiological reactivity elicited by nightmare-related
thoughts at bedtime would interfere with getting to sleep, sleep quality, and
returning to sleep after awakening. Consistent with this, research from another
laboratory suggests increased HR leads to longer sleep onset latency (Bonnet &
Arand, 2005), and our research group has shown that HR and SC evoked by
nightmare imagery are associated with self-reported global sleep problems, time
taken to fall asleep, hours slept per night (negative correlation), and the degree of
panic upon awakening from a nightmare (Rhudy et al., 2008). To address this issue
further, Davis and colleagues (in preparation) analyzed data from the current trial to
determine whether physiological reactivity to nightmare imagery was associated with
treatment-related changes in sleep disturbance and psychological functioning. They
found that persons with higher HR reactivity to nightmare imagery at pretreatment
baseline demonstrated greater treatment gains in sleep quality, hours slept per night,
and depressive symptoms, and that treatment-related decreases in HR reactivity
were associated with improvements in sleep quality and depressive symptoms. Thus,
there appears to be some overlap between improvements in physiological reactions
and traditional outcome measures.
But, physiological reactions may also provide unique and important information
not assessed by other variables. For example, frequent or chronic activation of the
fear network by nightmares and nightmare-related thoughts could increase stress
and allostatic load, the long-term consequences of which could put nightmare
sufferers at risk for cardiovascular or other metabolic diseases (Blanchard, 1990;
Boscarino & Chang, 1999; McEwen, 1998). Thus, to the degree that physiological
reactivity to nightmare imagery assesses activation of the fear network, physiological
reactivity may index risk for future health problems. In line with this notion,
preliminary data from our laboratory found that HR acceleration evoked by
nightmare imagery is positively correlated with self-reported physical symptoms
(Rhudy et al., 2008). Although additional longitudinal studies assessing objective
health-related outcomes are needed to draw firm conclusions regarding the direction
of these effects, the results from the present study suggest that psychological
interventions could improve physical health, sleep, and psychological distress by
reducing physiological reactivity associated with nightmare-related cognitions. These
results also underscore the importance of evaluating both subjective and
physiological outcomes in clinical trials of nightmare treatments.
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15
The present study had limitations that should be noted. First, the relatively small
sample size and the fact that participants were treatment seeking may limit the
generalizability of the results. Although it is important to replicate these findings in a
different, more diverse sample, the small sample does not appear to pose a problem
for Type II error, because treatment-related effect sizes were generally large. Thus,
the sample size provided adequate statistical power. Second, although the dropout
rate of 21% (from baseline to 1-week posttreatment) is not unusual for psychological
treatments, it may suggest these participants may have been more symptomatic.
Nevertheless, analyses indicated that noncompleters did not differ from those that
completed the study, with the exception that noncompleters reported less subjective
arousal to the nightmare imagery. Although this may suggest they were functioning
somewhat better than completers, it may also indicate greater psychological
avoidance. And finally, our procedures did not have a way to control for
physiological-emotional reactivity due to the personal relevance of the nightmare
script. However, physiological responses to the nightmare imagery did not change
over time for the waitlist control group, but they did change for the treatment group.
This pattern of results would not be expected if the physiological reactivity were due
solely to personal relevance. Nonetheless, to overcome this last problem, we
recommend that future studies include a control script that is personally relevant but
nightmare-irrelevant.
Despite these limitations, the current study suggests CBT (ERRT) may reduce
physiological-emotional arousal to nightmare imagery, an effect that could have
long-term positive implications for physical and psychological health. Future
research is needed to determine the relationship between reductions in physiologicalemotional reactivity and other objective (e.g., polysomnogram, medical utilization)
and subjective (e.g., sleep diaries) indicators of treatment outcome.
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