Trauma symptoms contribute to daily experiential avoidance: Does partner support mitigate risk?

Abstract

Objective:

The present study examined the protective role of partner support in reducing daily experiential avoidance (EA) associated with trauma symptoms in a sample of 154 couples during pregnancy.

Background:

Although psychological distress during pregnancy may hinder the developing bond between parents and infants after birth, high quality intimate partner support has the potential to enhance psychological wellbeing during pregnancy, particularly in the context of trauma. Specifically, partner support might mitigate the impact of trauma symptoms on maladaptive coping strategies such as EA by enabling individuals to safely encounter their distress.

Method:

Participants completed a semi-structured clinical interview of support and a PTSD symptom inventory, followed by home surveys of EA over 14 days. We examined growth trajectories of EA over 14 days using latent trajectory modeling within a dyadic framework.

Results:

Trauma symptom severity was associated with higher levels of EA across the 2 weeks; however, among women, the impact of trauma symptoms on EA was no longer significant when support from a partner was above average quality or higher. Findings also revealed partner effects; to the extent that women reported higher levels of trauma symptoms, their partners had higher levels of EA.

Conclusion:

Findings highlight the protective role of high quality support from intimate partners and suggest that trauma-related interventions targeting partner support processes, especially those implemented during pregnancy, might enhance recovery and prevent further distress and dysfunction among pregnant women experiencing trauma symptoms.

Keywords

Coping dyadic data analysis emotions gender differences pregnancy PTSD social support trauma

Nearly 90% of adults living in the United States will experience at least one traumatic event over their lives (Kilpatrick et al., 2013). Although less than 10% of these individuals will develop posttraumatic stress disorder (PTSD; Kilpatrick et al., 2013), a large proportion will experience clinically significant PTSD symptoms without meeting full diagnostic criteria (i.e., subthreshold PTSD; e.g. McLaughlin et al., 2015). Though definitions vary, subthreshold PTSD is associated with social and family dysfunction (e.g., Gold et al., 2007), sometimes at rates comparable to those meeting full criteria (Zlotnick et al., 2002). Equally troubling, the likelihood of experiencing trauma-related functional impairment is compounded when individuals engage in experiential avoidance (EA), a maladaptive approach for managing trauma symptoms characterized by emotional avoidance and thought suppression (e.g., Hayes et al., 1996; Marx & Sloan, 2005).

One population that may be uniquely impacted by trauma symptoms and related coping is parents expecting the birth of a child. During pregnancy, couples experience elevated risk for both couple discord (Lawrence et al., 2008) and internalizing psychopathology, including depression symptoms (Grekin et al., 2017). Parental mental health symptoms have the potential to impact new members of the family; indeed, a large body of research demonstrates links between parental trauma symptoms and related coping, and maladaptive family processes following childbirth, which can undermine healthy child development (e.g., Leen-Feldner et al., 2013). Such findings have led to calls by researchers and clinicians to recognize the impact of subthreshold PTSD on women and their families (McKenzie-McHarg et al., 2015).

This work highlights the need to identify factors that may buffer the negative sequelae of trauma during pregnancy. Among dual parenting couples, one such factor may be support received from an intimate partner. Families are healthier following the birth of a child to the extent that parents are in high quality intimate relationships during pregnancy (e.g., Stapleton et al., 2012). Conversely, couples reporting lower perceived partner support and higher prenatal relationship discord during pregnancy are at greater risk for concurrent and postpartum maternal psychological distress (e.g., Brock & Lawrence, 2014). Drawing on these findings, the primary goal of the present study is to examine the role of partner support in reducing the impact of trauma symptoms on daily experiential avoidance (EA) among pregnant women and their partners.

Trauma symptoms, experiential avoidance, and partner support as a buffer

Attempts to lessen the burden of trauma exposure on individuals and their families have spurred efforts to identify overarching psychological factors that explain how trauma symptoms ultimately lead to maladaptive outcomes. EA has emerged as a core process that both fosters more severe distress in response to trauma and increases the risk for myriad forms of impairment over time (e.g., Kumpula et al., 2011; Marx & Sloan, 2005). EA is characterized by an inability to tolerate aversive physical sensations, emotions, thoughts, and memories, resulting in specific actions (e.g., substance use, high-risk behaviors) taken to facilitate the avoidance of such experiences (Hayes et al., 1996). EA represents a maladaptive coping strategy that is common among individuals exposed to trauma (e.g., Marx & Sloan, 2005). Notably, although EA overlaps with the avoidance symptom cluster of PTSD, researchers conceptualize EA as a generalized collection of strategies (not necessarily anchored to particular traumatic events), which individuals use in attempts to avoid uncomfortable emotions and memories (Thompson & Waltz, 2010).

EA theory suggests that traumatic experiences resulting in distressing internal experiences (e.g., intrusive memories, negative beliefs, depressed mood) can generate attempts to reduce or numb these negative sensations (Roemer et al., 2001). Acute stress symptoms such as intrusive memories are common among individuals recently exposed to trauma, and typically subside naturally over time; however, those who use EA strategies (e.g., emotional avoidance, thought suppression) to cope with emotional responses to trauma are at higher risk for developing long-term problems including relationship problems (e.g., Zamir et al., 2018) and persistent PTSD symptoms (Marx & Sloan, 2005). Notably, there is evidence to suggest that pregnant women who use avoidant coping styles are more likely to suffer adverse mental and physical health outcomes across the transition into parenthood (see Guardino & Schetter, 2014 for a review). Thus, there is a need for research aimed at identifying factors that buffer the impact of trauma symptoms on EA, including in the context of pregnancy.

High quality support from one’s intimate partner has a substantial impact on psychological wellbeing (e.g., Brock & Lawrence, 2014) and is associated with a range of positive relational and health outcomes (e.g., Barry et al., 2009). Partner support also appears to play an important role in promoting individual wellbeing following trauma exposure (Brock et al., 2014). For example, research with military samples indicates that perceived support is among the strongest protective factors against PTSD and other mental health outcomes (for a review see Brewin et al., 2000). Such findings are consistent with a stress-buffering model (Cohen & Wills, 1985), which suggests that social support mitigates the negative impact of stress by engendering more adaptive coping skills such as open emotional expression, cognitive reframing, and problem-solving (Marroquín et al., 2017). In contrast to EA, these coping skills represent deliberate efforts to change, rather than avoid, clinically meaningful distress. Thus, partner support that is perceived and received favorably, and that helps those with trauma symptoms to use healthy coping strategies (e.g., reappraisal of a situation versus avoidance), may mitigate the impact of trauma symptoms on maladaptive coping strategies such as EA.

Trauma symptoms and experiential avoidance in a dyadic framework

The above findings suggest that partner support may play an important role in buffering against the adverse impact of trauma symptoms on the family during the perinatal period. The potential for partner effects among couples in which one or both partners are experiencing symptoms highlights a need to examine trauma symptoms within a dyadic framework. Recent conceptual models of the effect of trauma and PTSD on relationships emphasize how trauma affects survivors and their partners, both at the level of the individual and the couple (Campbell & Renshaw, 2018; Goff & Smith, 2005; Marshall & Kuijer, 2017). For example, the Dyadic Responses to Trauma (DRT) model describes myriad ways in which trauma can affect one’s own coping strategies, psychological responses, and relationship processes (e.g., communication strategies, emotional intimacy), as well as one’s partner’s responses. Partner responses, in turn, have the potential to directly impact both the trauma-exposed individual, as well as broader relationship outcomes. For example, dyadic coping is a process by which one partner perceives another’s distress and responds by either engaging in positive (e.g., problem-focused, emotion-focused) or negative (e.g., hostile, superficial) coping efforts (Bodenmann, 2005). In the context of traumatic stress, positive dyadic coping may strengthen individual coping resources (e.g., helping reduce one’s own avoidant coping) in addition to enhancing relationship satisfaction (e.g., increased perception of high relationship quality) among partners (e.g., Marshall et al., 2017).

A recent review by Campbell and Renshaw (2018) recommends that empirical testing within a dyadic framework become standard practice to better illuminate how psychological symptoms in one partner (e.g., trauma symptoms) might spill over into the other partner’s mental health functioning (e.g., use of maladaptive coping skills). Indeed, even if they were not directly exposed to those events themselves, partners can be negatively affected by one another’s traumatic experiences if they begin to perceive their loved one’s traumatic symptoms as a chronic stressor (Goff & Smith, 2005). A large body of research on secondary traumatic stress has identified associations between PTSD in one partner and greater psychiatric and marital distress in one's spouse (see Dekel & Solomon, 2007 for a review). However, considerably less research has examined whether one partner’s traumatic symptoms affects the other’s individual coping efforts. Additionally, collection of dyadic data remains rare, especially during pregnancy, resulting in limited knowledge of these transactional processes.

Purpose of the study

The purpose of this study was to: (1) examine whether trauma symptom severity predicted trajectories of daily EA over 2 weeks among pregnant couples, and (2) examine the stress-buffering role of partner support in reducing daily EA resulting from elevated trauma symptoms. We hypothesized that greater symptom severity would be associated with greater daily EA, but that this association would be weaker to the extent that partner support was of higher quality (see Figure 1). An additional aim of this study was to examine dyadic associations between partners’ trauma symptoms and coping efforts; specifically, we hypothesized that one partner’s trauma symptom severity would predict the other partner’s level of daily experiential avoidance.

Figure 1.
Conceptual model guiding the present study. Trajectories of experiential avoidance (EA) over 14 days are represented by two latent variables (per partner) consistent with latent trajectory modeling (LTM): (1) the intercept (set to represent EA on Day 14) and (2) the slope (rate of daily change in EA across the 14 days). We predicted that greater trauma symptoms would be associated with greater EA over 14 days (i.e., greater increases in EA over 14 days and/or higher levels of trauma symptoms on Day 14), but that this effect would be buffered by higher quality support for both men and women. Note that additional parameters were ultimately tested in the statistical model consistent with APIM (e.g., covaried residuals across partners), but those have been omitted from the figure for ease of presentation.

There were several strengths to this research. First, testing our hypotheses within a dyadic framework allowed us to investigate potential partner effects (e.g., the effect of one partner’s trauma symptoms on the other partner’s EA). Second, we assessed support quality using an objective, semi-structured interview to minimize artifacts of shared method variance (self-report surveys). Third, participants rated their daily EA across 14 days during pregnancy, providing a robust measurement of daily EA in a naturalistic environment (Laurenceau & Bolger, 2005).

Method

Participants and procedures

Participants were recruited using brochures and flyers and were eligible if they were: (a) pregnant at the time of the lab session with a singleton pregnancy, (b) both biological parents of the child, (c) cohabitating in a committed intimate relationship, (d) at least 19 years of age (legal age of majority in the state where the study was conducted), and (f) English speaking. The final sample comprised 159 heterosexual couples (159 women and 159 men). On average, women were 28.67 years old (SD = 4.27) while men were 30.56 years old (SD = 4.52). The majority of women were in their second (38.4%) or third (58.5%) trimester of pregnancy (mean week of pregnancy = 28.23, SD = 7.54), and 57.9% reported they had no children. Average relationship length was 81.90 months (SD = 49.59), and average cohabitation was 61.00 months (SD = 41.80). Most participants identified as White (89.3% of women; 87.4% of men); 9.4% of women and 6.4% of men identified as Hispanic or Latina/o. The modal education was a bachelor’s degree (46.5% of women; 34.6% of men). Couples reported a median joint income of $60,000–$69,999 and the majority of participants were employed at least 16 hours weekly (74.2% of women; 91.8% of men). Five couples declined participation in the daily survey after the laboratory visit; thus, a total of 154 couples completed both the laboratory visit and daily surveys and were included in the analyses.

All procedures were approved by the university’s Institutional Review Board. Couples attended a 3-hour appointment during which they completed a clinical interview and questionnaires, among other procedures beyond the scope of the present study. Participants received $50 compensation ($100 per couple).

Subsequently, participants completed 10–15 minutes of surveys from home for 14 consecutive days. Partners were asked to complete the surveys before bedtime, separately from one another and in private, and to only report on experiences that had occurred on the same day as the survey. Participants were provided a checklist with customized daily survey dates to increase compliance. Participants were given the option to complete their daily diaries either by paper and mailed back, or online. Approximately 82% of participants chose to complete questionnaires on the internet; these were time stamped and reviewed closely to ensure daily compliance. Overall response rates for the surveys were excellent (M number of days completed by men was 11.76, SD = 3.59, and by women was 12.21, SD = 3.05). Payments were prorated based on the number of surveys completed for up to $50 ($100 per couple).

Measures

PTSD checklist for DSM-5 (PCL-5; Weathers et al., 2013)

The PCL-5 is a 20-item self-report measure assessing the DSM-5 symptoms of PTSD over the past month (e.g., having strong negative beliefs about yourself, other people, or the world). The PCL-5 was administered with Criterion A assessment; participants were asked to briefly identify their worst event, and answered questions related to the nature of that event (e.g., how long ago did it happen, how did you experience it). Items on the PCL-5 are rated on a 5-point scale 0 (not at all) to 4 (extremely). Internal consistency for the current sample was .96.

An advanced clinical psychology doctoral student coded each participant’s PCL-5 index event as either 1 = present/meets criteria for a Criterion A trauma or 0 = absent/does not meet criteria for a Criterion A trauma. To make these determinations, the coder first examined whether participants answered “Yes” to the PCL-5 item asking, “Did it involve actual or threatened death, serious injury, or sexual violence,” and then examined whether the corresponding text description clearly met Criterion A. Participants who denied exposure to any traumatic event, as well as those who described an event that ultimately did not meet Criterion A (i.e., divorce, death of a parent due to natural causes) received a 0 on PTSD symptom severity. If there was any uncertainty about whether the person’s self-identified most traumatic event met Criterion A, the coder consulted with the other authors on this paper (both clinical psychologists with expertise in PTSD) prior to making final determinations.

Relationship quality interview (RQI; Lawrence et al., 2011)

The RQI is a validated 60–90 minute semi-structured, behaviorally anchored, individual interview of relationship functioning across multiple domains. A team of undergraduate research assistants were trained in clinical interviewing techniques, as well as detailed administration of the RQI. Approximately 15% of the interviews were randomly chosen to be double-coded, and demonstrated strong interrater reliability (average ICC = .93). For the present study, we focused on the partner support domain, which begins by soliciting an open-ended response to the following question: “I’d like to ask you about your partner’s ability to support you when you have had a bad day, are feeling down, or have a problem. How well does your partner support you in situations like these?” A multidimensional assessment of specific types of support follows, including emotional support, physical comfort, tangible support, informational support, esteem support, and network support. Across each support type, the interviewers assess the extent to which partners are responsive to solicitation of support, whether the support is provided and if it is provided skillfully, and the extent to which the recipient is satisfied with the frequency and manner in which that support is provided. In sum, the RQI support section encapsulates both the frequency and synchronicity of support interactions, providing a rich measurement of the overall quality of support received by each partner during support transactions occurring during the past 6 months.

Participants completed the RQI in separate rooms with different interviewers. Interviewers then independently rated the overall quality of support transactions using the following 1 to 9 scale: (1) Partner provides no support or partner provides some support but it is not what the participant wants. Partner almost always dismisses or ignores requests for support (or alone time) or responds with criticism. (3) In most situations, there is a mismatch between support received and support desired. Partner sometimes dismisses or ignores requests for support. (5) There is some mismatch between type of support received and type of support desired (about half the time). Participant is neutral on this topic. (7) In most situations, there is a match between type of support provided and type of support desired. Partner never dismisses or ignores requests for support. (9) High quality of support from partner. Partner is excellent at providing support and always responds well to requests for support.

Multidimensional psychological flexibility inventory (MPFI; Rolffs et al., 2016)

The MPFI assesses 12 dimensions of psychological flexibility and inflexibility, including an EA subscale. Items are rated on a 6-point scale 1 (never true) to 6 (always true). The MPFI demonstrates strong convergent and discriminant validity as well as excellent internal consistency across a variety of demographic subgroups (Rolffs et al., 2016). The authors of the original psychometric paper utilized Item Response Theory (IRT), which enhances scale properties by identifying the most effective items of each subscale. IRT is particularly useful in selecting items for use in daily diary studies, enabling researchers to minimize the number of items necessary, thus reducing burden on participants while still obtaining robust measurements of constructs of interest. The highest 2 performing items from each subscale of the MPFI were combined into a 12-item flexibility and 12-item inflexibility composite, both of which have demonstrated high internal consistency (Rolffs et al., 2016). Scores from the top 2 items of the EA subscale (i.e., When I had a bad memory, I tried to distract myself to make it go away; I tried to distract myself when I felt unpleasant emotions) were combined for use in the current study to assess daily EA. Internal consistency for the current sample was high (Cronbach’s alpha = .93).

Potential covariates

A number of demographic variables (i.e., annual joint income, employment status, age) and family characteristics (i.e., marital status, first vs. repeat parenthood status) were examined as potential covariates. We followed guidelines by Becker et al. (2016) who recommends choosing covariates for inclusion in models selectively based on (1) strong theoretical justification, and (2) the extent to which a priori hypotheses statistically align with significant correlations between covariates and primary variables in the model. No potential covariates were associated with both primary dependent and independent variables (though both paternal age and the presence of other children in the home significantly correlated with reports of experiential avoidance and were controlled for in post-hoc analyses). In primary analyses, ultimately, we did control for one variable—week of pregnancy at the time of participation—to account for method variance introduced by virtue of recruiting couples at any point during pregnancy. This enabled us to account for the possibility that change trajectories in EA might depend on the point in pregnancy when the 14 days of surveys were completed.

Data analytic strategy

Analyses were conducted with Mplus version 8.1 (Muthén & Muthén, 2012). Missing data were addressed using Full Information Maximum Likelihood (FIML) estimation (Enders, 2010). Robust ML was used to address any violations of normality assumptions. Multiple indices were used to assess global model fit. We report the Comparative Fit Index (CFI), the Root Mean Square Error of Approximation (RMSEA), and the Standard Root Mean Residual (SRMR). For the CFI, values of .90 or higher reflect adequate fit of the model. For the RMSEA and SRMR, values greater than .10 indicate a poor fitting model (MacCallum et al., 1996).

We conducted analyses using actor-partner interdependence modeling (APIM) for distinguishable dyads (Kenny et al., 2006), estimating actor effects (e.g., Male X₁ → Male Y₁, Female X₂ → Female Y₂) and partner effects (e.g., Male X₁ → Female Y₂, Female X₂ → Male Y₁). Measurement of partner effects enabled us to estimate relational effects, in addition to focusing on intrapersonal (actor) effects, which can be overestimated when examined in isolation. Growth trajectories of EA over the 14 days were examined using latent trajectory modeling (LTM; Curran & Hussong, 2003). Repeated measures of symptoms were used as multiple indicators of two correlated latent factors including (a) an intercept factor which was modeled as the end of the assessment period (Day 14), and (b) a slope factor which represented the linear slope of the trajectory or change in avoidance over the 14 days. However, given that growth was not anchored in change since a discrete event (e.g., following treatment), we were most interested in examining the intercept. By modeling the intercept at the end of the assessment period (Day 14), this enabled us to create a time lag from our assessment of trauma symptoms (i.e., were trauma symptoms associated with level of EA 2 weeks later).

Results

Descriptive statistics and correlations

Means and SDs across the entire sample are reported in Table 1. The data were carefully screened for accuracy and missingness. Across the sample, 55% of mothers (66 of 120 with complete data on the PCL) and 41% of fathers (47 of 114 with complete data on the PCL5) described experiencing a Criterion A event (American Psychiatric Association, 2013). The higher rate of missing data for the PTSD measure (26.0% and 22.0% of mothers and fathers missing respectively) relative to other variables is due to a technological error which resulted in these participants not receiving the item assessing their index traumatic experience. Because we were unable to verify the index trauma for these participants, we coded their PCL scores as missing to be conservative. Missing data was addressed in Mplus using full information maximum likelihood (FIML), which is appropriate even when missing data rates are elevated (Little & Rhemtulla, 2013).

Table 1.
Descriptive statistics: Predictor and outcome variables for men and women.

Predictor variable Men Women

M (SD) N M (SD) N t ^a

Trauma Symptoms^b 7.13 (12.54) 47 9.70 (13.69) 66 −1.98

Quality of Partner Support 6.82 (1.10) 153 6.59 (1.33) 153 1.69

Experiential Avoidance at Day 14 6.35 (3.53) 123 6.32 (3.39) 125 0.41

Average Experiential Avoidance^c 6.39 (2.87) 151 6.57 (2.63) 154 0.95

Note. ^aEstimated with pairwise deletion for missing data. Paired-sample t-tests indicate that there were no significant partner differences in the key study variables.

^b41% of Men (47 of 114 with complete data on the PCL5) and 55% of Women (66 of 120 with complete data on the PCL5) reported traumas meeting Criterion A; scores represent average trauma symptoms among this subsample.

^c Represents the average level of EA across the 14 daily surveys.

The most commonly reported index traumas among women were experiencing physical/sexual abuse/assault (n = 17; 26%), experiencing a miscarriage (n = 8; 12%), and learning about an accidental/violent death (n = 8; 12%). The most commonly reported index traumas among men were learning about an accidental/violent death (n = 8; 17%), experiencing physical/sexual abuse/assault (n = 6; 13%), and experiencing a life-threatening illness/injury (n = 6; 13%). The average trauma severity score on the PCL-5 across participants with a Criterion A event was 9.70 (SD = 13.69) for women and 7.13 (SD = 12.54) for men. Approximately 20% of women (n = 13) and 15% of men (n = 7) met criteria for threshold or subthreshold PTSD (defined as meeting at least two symptom clusters of PTSD; McLaughlin et al., 2015). Though definitions of subthreshold PTSD vary across studies (McLaughlin et al., 2015), our rates are similar to, or greater than, lifetime rates identified in a large nationally representative sample of U.S. adults (17.2% of women and 8.6% of men meeting threshold or subthreshold PTSD; Pietrzak et al., 2011).

Correlations are reported in Table 2. There were no concerns about multicollinearity (rs < .70). Paired-sample t-tests indicated no significant partner differences in the key variables. Additionally, we used ANOVAs to examine whether the subsample of participants that met Criterion A significantly differed from the rest of the sample on the quality of partner support and experiential avoidance; no differences emerged. Most variables were normally distributed; however, as anticipated for a community sample, trauma symptoms across women and men were significantly skewed (women = 3.59, SE = .221; men = 5.82; SE = .226) and demonstrated high kurtosis (women = 17.28, SE = .438; men = 43.81; SE = .45). We used MLR to address any violations of normality assumptions.

Table 2.
Within and cross-spouse correlations among trauma symptoms, partner support, and experiential avoidance.

Men

Women 1 2 3 4

1. Trauma Symptoms .09 −.13 .27* .23*

2. Quality of Partner Support .03 .11 −.02 −.03

3. Experiential Avoidance at Day 14 .28 −.00 .37* .86***

4. Average Experiential Avoidance^a .23* .01 .86* .36*

Note. Estimated with pairwise deletion for missing data. Men’s data are above the diagonal. Women’s data are below the diagonal. Interspousal correlations are bold and along the diagonal. Correlations among the repeated measures, across the 14 days, ranged from .42 to .85 for women and .50 to .85 for men.

^a Represents the average level of EA across the 14 daily surveys.

p < .05. p < .01. p < .001.

Preliminary analyses

Experiential avoidance is a state-dependent regulatory strategy that is likely to fluctuate on a day-to-day basis (Machell et al., 2015). Although we speculated that pregnancy might alter the course of EA in some way, given that couples are at greater risk for internalizing symptoms during pregnancy (Grekin et al., 2017), research on the typical course of EA during pregnancy is generally lacking. Thus, to model the typical course of EA over the 14 consecutive daily reports, we compared the relative fit of two LTMs. The first model was a linear model in which EA scores follow a systematic pattern over time. The second model, often referred to as an intercept-only LTM, models repeated scores as waxing and waning over time. That is, there is no systematic pattern to EA scores over the repeated measures and, rather, scores randomly vary over time. A nested model comparison revealed that the linear LTM was a better representation of the data than the intercept-only model, χ² (9) = 186.40, p < .001. Further, the linear LTM demonstrated excellent global fit CFI = .933, RMSEA = .060, and SRMR = .054.

Closer examination of the linear LTM revealed that on average, women’s EA decreased at a significant rate over 14 days, b = −0.05, SE = 0.02, p = .001, and there was significant variability in slope factor scores, p < .000. In contrast, although EA followed a linear trend for men, that trend was in the form of relatively stable EA scores over the 14 days. On average, there was no significant linear change in men’s EA, b = −.004, SE = .02, p = .806; however, there was significant variability in slope factor scores, p < .001.

To account for the possibility that change trajectories in EA might depend on the point in pregnancy when the 14 days of surveys were completed, we examined week of pregnancy as a predictor of the intercept and slope factors representing characteristics of the EA trajectories. Week of pregnancy was not significantly associated with rates of linear change in EA (slope factor) for women, b = −.001, SE = .002, p = .533, or men, b = −.002, SE = .002, p = .293. As such, the patterns of change observed over 14 days appear to reflect a larger developmental trajectory of EA such that EA is relatively stable for men during pregnancy, regardless of week of pregnancy, whereas EA appears to decrease at a significant rate, on average, for women. Levels of EA reported on Day 14 (intercept factor) also did not vary as a function of week of pregnancy for women, b = −.041, SE = .036, p = .248, or men, b = −.014, SE = .038, p = .710.

Partner support as a buffer of trauma symptoms on EA

We tested the complete dyadic model to examine whether quality of partner support buffered the impact of trauma symptoms on EA across 14 days. This model yielded satisfactory fit, χ² (546) = 868.998, p < .01, CFI = .904, RMSEA = .064, and SRMR = .063. See Table 3 for parameter estimates. Higher levels of symptoms reported by men were associated with a faster rate of increase in EA over the 14 days (b = 0.07, p = 0.01) and with higher levels of EA at the end of the observed assessment period (b = 1.10, p = 0.00). Interestingly, a partner effect was also present such that women’s trauma symptoms were associated with men’s EA; to the extent that women reported more symptoms, their partners had higher levels of EA at day 14 (intercept effect; b = 0.85, p = 0.00). Notably, women’s symptoms were only associated with the partner intercept, not the slope (i.e., there were no differences in rates of change in men’s EA over time as a function of women’s trauma symptoms), suggesting that the entire trajectory of men’s EA was higher (across the 14 days) to the extent that women reported more symptoms.

Table 3.
PCL × Support predicting intercept and slope factors in the latent trajectory model.

Estimate SE Est./SE p Value

Men Experiential Avoidance (Intercept, Day 14) ON

Men PCL 1.10 0.27 4.04 0.00

Women PCL 0.85 0.20 4.18 0.00

Men Support 0.28 0.26 1.11 0.27

Men PCL × Men Support (Interaction) 0.10 0.31 0.34 0.74

Men Experiential Avoidance (Slope) ON

Men PCL 0.07 0.03 2.53 0.01

Women PCL 0.02 0.01 1.26 0.21

Men Support 0.01 0.01 0.44 0.66

Men PCL × Men Support (Interaction) 0.00 0.02 0.06 0.95

Women Experiential Avoidance (Intercept, Day 14) ON

Men PCL −0.13 0.23 −0.56 0.58

Women PCL^a 0.96 0.23 4.12 0.00

Women Support 0.29 0.23 1.28 0.20

Women PCL × Women Support (Interaction) −0.68 0.29 −2.31 0.02

Women Experiential Avoidance (Slope) ON

Men PCL −0.01 0.01 −0.69 0.49

Women PCL 0.02 0.01 1.29 0.20

Women Support 0.02 0.01 1.66 0.10

Women PCL × Women Support (Interaction) −0.02 0.01 −1.31 0.19

Note. Model results are unstandardized; however, PCL and support scores were standardized prior to testing the model for the purposes of creating the interaction term for testing moderation. Significant effects (p < .05) are bolded. ^aGiven the significant interaction, this is a conditional effect representing the association between PCL and Day 14 EA at average levels of support.

In contrast, among women, the link between trauma symptoms and EA was weakened to the extent that women received higher quality support (interaction effect for intercept; b = −0.68, p = 0.02). A regions of significance analysis was conducted such that simple slopes representing the links between trauma symptoms and the intercept factor were computed for values of support ranging from 2 SD below the mean to 2 SD above the mean; results revealed that trauma symptoms were no longer significantly associated with Day 14 EA when support levels were above average (≥.70 SD above the mean). Put differently, individuals varying in severity of trauma symptoms were no longer distinguishable with regard to EA at Day 14 if they received relatively high quality support from their partners. Notably, no significant effects were observed for the women’s slope factor; thus, results indicate that the entire trajectory of women’s avoidance across the 14 days is higher or lower depending on trauma severity and quality of support. See Figure 2 for a graphical depiction of women’s EA trajectories at different levels of trauma severity and partner support.

Figure 2.
Trajectories of maternal experiential avoidance over 14 days as a function of partner support and trauma symptoms. Trajectories of maternal EA are graphed as a function of low (1 SD below the sample mean, or 5.27) and high (1 SD above the sample mean, or 7.91) partner support, and average PCL (sample mean = 5.33), as well as high PCL (1 SD above the sample mean, or 16.51). Low PCL scores (1 SD below the sample mean) were below the minimum possible score of 0, and as such, were omitted from graphed trajectories. Once support scores reach .70 SD above the sample mean (and higher), the effect of PCL on EA is no longer significant.

Finally, we conducted post-hoc analyses to confirm that the hypothesized effects remained significant when controlling for paternal age and the presence of other children in the home given that both variables were associated with reports of experiential avoidance. Results replicated with this set of covariates. Specifically, bs for significant effects in the original model ranged from 0.067 to 1.042 (ps < .05) when including the covariates.

Discussion

The primary goals of this study were to: (1) examine whether trauma symptom severity was associated with daily EA among pregnant couples, a group at elevated risk for relationship dysfunction and psychopathology (Grekin et al., 2017; Lawrence et al., 2008), and (2) determine if quality of partner support buffered associations between trauma symptoms and daily EA. Results indicated that greater trauma symptom severity was associated with greater EA over 2 weeks among both men and women; however, the deleterious effect of trauma symptoms was buffered for women in the presence of higher quality partner support. In fact, trauma symptoms were no longer associated with daily EA when support quality was above average, demonstrating the protective role of partner support. Finally, to the extent that women reported higher levels of trauma symptoms, their partners had higher levels of EA, demonstrating the implications of women’s trauma symptoms on the health of the family, not just the individual. In contrast, trauma symptoms reported by men did not have an effect on their partners’ EA.

Research has examined links between trauma symptoms and EA both cross-sectionally and prospectively (e.g., Marx & Sloan, 2005); however, investigations of daily EA are lacking. The current findings reveal that men and women experiencing greater trauma symptoms were more likely, over the next 2 weeks, to employ EA in response to a bad memory or feeling unpleasant emotions. That is, individuals with more trauma symptoms may be motivated to control unpleasant internal experiences (i.e., negative thoughts, distressing emotions) through the use of maladaptive coping strategies involving emotional control tactics, such as EA (e.g., Campbell-Sills et al., 2006).

Among women, the impact of trauma symptoms on the 2-week trajectory of EA was no longer significant when support from their partner was above average quality. These findings are consistent with a stress-buffering model (Cohen & Wills, 1985), as well as research demonstrating associations between higher social support and lower PTSD symptoms among women (Dworkin et al., 2018). In contrast, men’s trauma symptom severity was associated with greater daily EA regardless of the quality of partner support—a result that converges with others demonstrating that social support serves a more salient role in buffering the impact of trauma and stress on negative psychological outcomes among women, compared to men (e.g., Vogt et al., 2005; Whalen & Lachman, 2000). Women are socialized from a young age to place a strong emphasis on social relationships (Moskowitz et al., 1994), and thus may have a higher propensity to capitalize on intimate partner support. Further, women are more likely to affiliate with others under conditions of stress (i.e., “tend-and-befriend”; Taylor et al., 2000). Self-esteem may also be undermined by the mere act of soliciting help among men (Addis & Mahalik, 2003). Alternatively, men may prefer to receive invisible support that does not threaten their sense of self efficacy (i.e., support that goes unnoticed, such as giving advice indirectly; Bolger et al., 2000).

To the extent that women experienced more trauma symptoms, their partners experienced more EA over 2 weeks, suggesting that women’s psychological symptoms may have downstream effects on their partners’ emotional coping strategies. These findings, while exploratory, align with theory and empirical evidence suggesting that trauma may have ripple effects that manifest in negative mental health outcomes for partners (e.g., Campbell & Renshaw, 2018; Marshall & Kuijer, 2017). However, the reverse partner effect was not present; men’s trauma symptoms did not impact women’s EA. Women are commonly viewed as contributing to the affective climate of the relationship more than men (see Brody & Hall, 2008 for a review). Thus, if women struggle with symptoms of trauma and express negative affect more openly, their partners may respond by using avoidance strategies to manage discomfort with their partner’s symptoms. By contrast, if men express symptoms of trauma more covertly (e.g., through avoidance and numbing), then dyadic effects may be reduced, such that women’s tendency to engage in avoidant coping might not be impacted to the same degree.

Although not a primary aim of the study, analyses revealed that, for men, EA was relatively stable across the 14 consecutive days regardless of the week of pregnancy during which participants responded. On the other hand, the average trajectory for women showed significant decline in EA over the repeated measures, a rate of change that was similar regardless of week of pregnancy. This finding aligns with a broader literature suggesting that pregnant mothers are more likely to use positive coping behaviors during pregnancy (e.g., Yali & Lobel, 1999). In the current study, there could also be a method effect explaining this pattern such that the mere process of self-monitoring may have induced reactive effects (e.g., Kazdin, 1974), functioning as a kind of intervention to decrease women’s avoidant coping across the assessment. Future research using a longer interval is required to better understand the course of EA during pregnancy.

Limitations and future directions

Findings of this study are remarkable in that among pregnant women with sub-threshold—but potentially impairing (e.g., Gold et al., 2007)—trauma symptoms, support from intimate partners buffered the association of these symptoms on daily maladaptive coping. Given these findings, it will be important for future research to examine whether similar processes extend to couples meeting diagnostic criteria for PTSD. For example, partner support may improve the mental health of military couples who struggle during the prenatal period and have high rates of PTSD (Shivakumar et al., 2015). The source of trauma may also moderate findings during the prenatal period. For example, it is possible that women who developed PTSD in the context of a prior miscarriage may experience an exacerbation of symptoms and increased EA to a greater degree during subsequent pregnancies.

Though theory and prior work suggests that PTSD increases use of avoidance as a coping mechanism, there is also evidence that use of EA following trauma puts individuals at greater risk of developing PTSD (e.g., Marx & Sloan, 2005). Thus, future research should incorporate multiple assessments of PTSD and EA to investigate whether reciprocal processes account for linkages between these constructs over time. Further, the current sample was predominantly White, non-Latinx, and well-educated; study aims should be pursued in pregnant samples of different cultural backgrounds. For example, different sociocultural factors including variations in posttraumatic responses and prioritization of family values may influence coping styles among racial and ethnic minority groups (Alcántara et al., 2013).

Clinical implications

The present results indicate that partner support weakens the link between trauma symptoms and EA among women. Thus, for women experiencing trauma symptoms, interventions that incorporate partner-assisted components may serve as a vehicle for change. For example, Cognitive-Behavioral Conjoint Therapy for PTSD (CBCT for PTSD; Monson & Fredman, 2012) seeks to harness the intimate relationship to promote enhanced conflict management and communication, decrease couple-level behavioral and EA patterns, and modify cognitive distortions related to trauma experiences. Consistent with this approach, our findings suggest that high quality partner support might be especially important for pregnant women experiencing trauma symptoms given the potential for support to interrupt the negative coping patterns that arise in the context of trauma-related dysfunction. Further, results indicate that prenatal interventions aimed at promoting the mental health of women during pregnancy might be enhanced by incorporating couple-based modules. Targeting support processes during pregnancy is particularly important given the possibility of increased stress, and even further trauma during childbirth (Grekin, O'Hara, & Brock, in press) that could exacerbate trauma symptoms and EA. Importantly, clinicians and researchers have repeatedly emphasized the need for screening, assessment, and interventions for mothers experiencing subthreshold PTSD symptoms, given rising evidence that these symptoms negatively impact relationship functioning (e.g., McKenzie-McHarg et al., 2015) .

Conclusion

To our knowledge, this study is the first to examine whether partner support buffers the impact of trauma symptoms on daily EA among couples. This study also represents an important step toward clarifying the protective role of partner support for reducing maladaptive coping among couples with trauma symptoms during pregnancy, a highly sensitive transitional period, which may have significant implications for promoting healthy family functioning. Results indicate that partner support may in fact play a critical role in mitigating the impact of trauma symptoms on daily EA—a maladaptive coping style associated with a range of negative psychological outcomes. However, while women were less likely to engage in EA when receiving high quality partner support, their partners did not experience the same benefit. Furthermore, our finding that men reported increased daily EA when their partners experienced higher trauma symptoms suggests that men and women may be differentially affected by their partner’s mental health symptoms. Together, these findings suggest that interventions for trauma symptoms may be enhanced by helping partnered individuals capitalize on support processes within the intimate relationship to enable them to safely approach and manage their distress.

Predictor variable	Men		Women
Trauma Symptoms^b	7.13	(12.54)	47	9.70	(13.69)	66	−1.98
Quality of Partner Support	6.82	(1.10)	153	6.59	(1.33)	153	1.69
Experiential Avoidance at Day 14	6.35	(3.53)	123	6.32	(3.39)	125	0.41
Average Experiential Avoidance^c	6.39	(2.87)	151	6.57	(2.63)	154	0.95

	Men
1. Trauma Symptoms	.09	−.13	.27*	.23*
2. Quality of Partner Support	.03	.11	−.02	−.03
3. Experiential Avoidance at Day 14	.28**	−.00	.37***	.86***
4. Average Experiential Avoidance^a	.23*	.01	.86***	.36***

		Estimate	SE	Est./SE
Men Experiential Avoidance (Intercept, Day 14)	ON
Men PCL	1.10	0.27	4.04	0.00
Women PCL	0.85	0.20	4.18	0.00
Men Support	0.28	0.26	1.11	0.27
Men PCL × Men Support (Interaction)	0.10	0.31	0.34	0.74
Men Experiential Avoidance (Slope)	ON
Men PCL	0.07	0.03	2.53	0.01
Women PCL	0.02	0.01	1.26	0.21
Men Support	0.01	0.01	0.44	0.66
Men PCL × Men Support (Interaction)	0.00	0.02	0.06	0.95
Women Experiential Avoidance (Intercept, Day 14)	ON
Men PCL	−0.13	0.23	−0.56	0.58
Women PCL^a	0.96	0.23	4.12	0.00
Women Support	0.29	0.23	1.28	0.20
Women PCL × Women Support (Interaction)	−0.68	0.29	−2.31	0.02
Women Experiential Avoidance (Slope)	ON
Men PCL	−0.01	0.01	−0.69	0.49
Women PCL	0.02	0.01	1.29	0.20
Women Support	0.02	0.01	1.66	0.10
Women PCL × Women Support (Interaction)	−0.02	0.01	−1.31	0.19

Footnotes

Authors’ note

Some of the findings and ideas reported in this paper were presented at the annual meeting of the Association for Behavioral and Cognitive Therapies.

Acknowledgments

The authors thank the families who participated in this research and the entire team of research assistants who contributed to various stages of the study. In particular, they thank Erin Ramsdell, Jennifer Blake, Kailee Groshans for project coordination, and Elizabeth Alexander and Olivia Maras for assistance with manuscript preparation.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by several internal funding mechanisms awarded to PI Rebecca L. Brock from the UNL Department of Psychology, the Nebraska Tobacco Settlement Biomedical Research Development Fund, and the UNL Office of Research and Economic Development. Dr. Franz was supported by a grant from the National Institute of Mental Health (5T32MH019836).

ORCID iD

Molly R. Franz

Open research statement

As part of IARR’s encouragement of open research practices, the authors have provided the following information: This research was not pre-registered. The data used in the research are not available. The materials used in the research are available. The materials can be obtained via email.

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Predictor variable	Men			Women
Predictor variable	M	(SD)	N	M	(SD)	N	t ^a
Trauma Symptoms^b	7.13	(12.54)	47	9.70	(13.69)	66	−1.98
Quality of Partner Support	6.82	(1.10)	153	6.59	(1.33)	153	1.69
Experiential Avoidance at Day 14	6.35	(3.53)	123	6.32	(3.39)	125	0.41
Average Experiential Avoidance^c	6.39	(2.87)	151	6.57	(2.63)	154	0.95