Sexual intimacy challenges as markers of relational turbulence in couples with depression

Abstract

Using the relational turbulence model, I test a model in which relational uncertainty and interference from a partner mediate the relationship between depressive symptoms and sexual intimacy challenges for couples with depression. Couples in whom one or both partners were clinically diagnosed with depression completed an online survey of closed-ended items. Results suggest depressive symptoms associate with relational uncertainty, and men’s depressive symptoms predict both their own and their partner’s interference from a partner. Interference from a partner emerged as a mediator for sexual intimacy challenges. The findings highlight partner interference as a mechanism of upheaval for couples with depression, and the results stand to help practitioners identify and mitigate sexual intimacy challenges.

Keywords

Depression dyadic data romantic relationships sexual intimacy

Depression is a common and serious mental illness affecting approximately 16 million Americans each year (National Institute of Mental Health, 2015). Symptoms of depression permeate romantic relationships (Hames, Hagan, & Joiner, 2013), making couples prone to challenges to their sexual relationship (Baldwin, 2001; Cleveland Clinic, 2014; Delaney, in press). Depression is linked to problems with physical function, self-esteem, pleasure, and initiating sexual activity (Baldwin, 2001; Kennedy, Dickens, Eisfeld, & Bagby, 1999; Ostman, 2008). Nondepressed partners are affected by a depressed person’s sexual difficulties and face similar difficulties (e.g., physical function; Ostman, 2008). Depressed individuals are 5 times more likely to experience a sexual desire disorder, and sex problems appear in over 70% of patients (Casper et al., 1985; Laurent & Simons, 2009). Attention to depression-specific sexual intimacy challenges is needed to explicate relational dynamics in depression and to aid clinicians who support patients and partners (Bodenmann & Ledermann, 2007; Ostman, 2008).

Individually, mental illness and sexual dysfunction are detrimental to quality of life, and in combination, depression and sexual intimacy challenges can have an intensely negative effect (Laurent & Simons, 2009). Delaney (in press) documented layered sexual intimacy challenges in depression affecting libido as well as cognitive and interactive difficulties. Most depression literature designates decreased libido as a symptom of depression or a side effect of antidepressant medication (Higgins, Nash, & Lynch, 2010; Montejo, Montejo, & Baldwin, 2018). Sexual problems might result from chemical imbalances related to depression, but they could also be tied to strain depression puts on the relationship (Cleveland Clinic, 2014). Precisely, how relationship functioning and sexual problems connect in depression remains unclear.

Theories of depression do not yet speak to sex problems but do emphasize broad links between depression and relationship functioning. Coyne’s (1976) interactional theory and Joiner and Metalsky’s (1995) integrative interpersonal theory both theorize about social rejection of depressed individuals. The marital discord model of depression (Beach, Sandeen, & O’Leary, 1990) acknowledges how reduced positive relationship processes (e.g., cohesion, intimacy) and increased negative patterns (e.g., criticism, disrupted routines) are associated with both relationship discord and depressive symptoms. Despite substantial evidence for the existence of sexual intimacy challenges in depression, depression theories do not yet speak to antecedents and consequences of those difficulties. The relational turbulence model (RTM; Solomon & Knobloch, 2004) highlights how two relationship qualities, relational uncertainty and interference from a partner, predict outcomes for couples. The RTM offers a framework for theorizing about sexual intimacy challenges in depression.

Additionally, a depressed patient’s experiences are inherently interdependent with her or his partner’s (Hames et al., 2013). Bodenmann and Randall (2013) recommend a couple’s approach to study and treatment of depression, conceptualizing it as a “we-disease” (p. 223). The actor–partner interdependence model (APIM; Kenny, Kashy, & Cook, 2006) is a framework for analyzing couple-level data. The APIM illuminates actor effects (how an individual’s variables influence her or his own outcomes) and partner effects (how the individual’s variables affect her or his partner’s outcomes; Kenny et al., 2006). In this study, I use the RTM to assess actor and partner effects between depressive symptoms, mechanisms of turbulence, and sexual intimacy challenges.

The RTM

The RTM explains that romantic partners perceive their relationship as chaotic when they experience relational uncertainty and interference from a partner (Knobloch & Theiss, 2010). Relational uncertainty is the degree of confidence individuals have in their perceptions of involvement in the relationship and stems from three interrelated sources (Solomon & Knobloch, 2004). Self and partner uncertainty are individually focused, including questions about one’s own or one’s partner’s involvement in the relationship. Relationship uncertainty encompasses questions about the partnership as a whole. These overlapping but discrete sources of ambiguity contribute to turmoil because partners are limited in their abilities to make sense of the relationship (Knobloch & Theiss, 2010). Interference from a partner is the degree to which one partner disrupts the other’s ability to achieve day-to-day goals (Solomon & Knobloch, 2004). Interference occurs when patterns of interdependence shift (Solomon, Knobloch, Theiss, & McLaren, 2016). Relational uncertainty and interference from a partner generate upheaval in relationships.

The RTM argues that relational uncertainty and interference from a partner are responses to relationship transitions (Knobloch & Theiss, 2010). Transitions are characterized by the need to adapt to new circumstances (Solomon et al., 2016). Across depression symptomology, diagnosis, and treatment, relational partners must evaluate and alter cognitive and relational frameworks to navigate effects of the illness. Prior RTM research establishes its utility for studying depression and sexual relationships.

Depression and mechanisms of turbulence

The mechanisms of the RTM are associated with depressive symptoms and relational satisfaction (Knobloch & Knobloch-Fedders, 2010; Knobloch & Theiss, 2011; Scott & Stafford, 2018). Most of this research has highlighted relational uncertainty in depression without evaluating interference from a partner. Both relational uncertainty and interference from a partner are salient for depressed individuals and their partners (Knobloch & Delaney, 2012). Knobloch and Delaney’s (2012) results also hinted at potential for actor and partner effects between depressive symptoms and mechanisms of turbulence, as depressed and nondepressed partners alike expressed ambiguity about the relationship and frustrations over interference related to depression. Actor and partner effects exist between depressive symptoms and relational qualities (e.g., Beach, Katz, Kim, & Brody, 2003; Knobloch & Knobloch-Fedders, 2010; Knobloch, Knobloch-Fedders, & Durbin, 2011). The self-doubt, anxiety, and pessimism associated with depression likely fuel a lack of confidence in the relationship, and symptoms such as irritability and a loss of interest in activities can disrupt couples’ routines and goals. To test these assertions, a first hypothesis anticipates associations between depressive symptoms and mechanisms of turbulence.

H1: Depressive symptoms will be positively associated with (a) relational uncertainty and (b) interference from a partner for both actors and partners.

Mechanisms of turbulence and sexual intimacy challenges

The RTM asserts that relationships can become “tumultuous” as partners negotiate relationship circumstances (Solomon, Weber, & Steuber, 2010, p. 117). Delaney’s (in press) findings position sexual intimacy challenges as a way depression sparks relational chaos. Couples coping with depression face primary challenges with libido. Additionally, cognitive challenges, such as diminished self-esteem and feelings of isolation, disrupt sexual relationships. Interactive challenges exist in conversations about sex and initiation of sexual activity. These secondary sexual intimacy challenges may appear as one’s own difficulties (i.e., “I feel unworthy of a sexual connection.”) or as a partner’s (i.e., “My partner struggles to initiate sex.”). In the current study, I predict associations between mechanisms of turbulence and three categories of sexual intimacy challenges.

Relational uncertainty predicts turbulence because ambiguity makes it difficult to anticipate and interpret relationship events (Solomon et al., 2016). Relational uncertainty is associated with decreased sexual satisfaction, perceiving conversations about sex as threatening, and avoidance of sexual interactions (Theiss, 2011; Theiss & Estlein, 2014; Theiss & Nagy, 2010). The RTM suggests ambiguity about the relationship could prompt feelings of isolation or make a partner uncomfortable initiating sex.

Interference from a partner predicts turbulence because disruptions prompt negative emotions, making people reactive to relationship conditions (Solomon & Knobloch, 2004; Solomon et al., 2016). Interference from a partner correlates with lower sexual satisfaction, avoidance of sexual situations, and negative emotions surrounding sexual activity (Theiss & Estlein, 2014; Theiss & Nagy, 2010). When partners are disrupting each other’s day-to-day routines, goal blockages can fuel negative emotions, which might inhibit libido, isolate partners, or limit initiation efforts.

Potential for partner effects also exists in associations between mechanisms of turbulence and sexual intimacy challenges. Sexual costs and rewards, communication, and both mechanisms of turbulence have documented dyadic effects on sexual satisfaction (Theiss, 2011; Theiss & Nagy, 2010; Yucel & Gassanov, 2010). Difficulties with sexual function in one partner contribute to difficulties with function and satisfaction in the other (Brotto et al., 2016). Scholars have called for increased dyadic studies of sexual relationships to evaluate interdependence in partners’ experiences (Mark, 2012; Miller-Ott & Linder, 2013; Theiss, 2011). A second hypothesis anticipates actor and partner effects between mechanisms of relational turbulence and sexual intimacy challenges.

H2: In couples with depressive symptoms in one or both partners, (a) relational uncertainty and (b) interference from a partner will be positively associated with sexual intimacy challenges for actors and partners.

H1 and H2 propose associations between depressive symptoms and mechanisms of turbulence and between mechanisms of turbulence and sexual intimacy challenges. Thus, I propose a third hypothesis to test mediating effects of mechanisms of turbulence in associations between depressive symptoms and sexual intimacy challenges.

H3: Relational uncertainty and interference from a partner will mediate the association between depressive symptoms and sexual intimacy challenges.

A conceptual model of the hypothesized associations is presented in Figure 1.

Figure 1.

Hypothesized model (H1 and H2; H3 predicts mediation).

Method

University institutional review board approved all data collection procedures. Advertising materials were distributed through nationwide depression support organizations, mental health research/treatment centers, relationship therapists, and online venues including depression and relationship blogs and a Facebook page dedicated to the study.

To participate, individuals had to be involved in a romantic relationship in which both partners were willing to enroll and one or both partners had been professionally diagnosed with depression. Participants needed to be at least 18 years of age and have her or his own e-mail address. Couples who participated received US$20 in Amazon.com e-gift cards.

Participants

The sample included 106 different-sex couples (N = 212)¹ between 19 and 73 years old (M = 35.67, SD = 12.07). Individuals reported their race/ethnicity as Caucasian/White (85.8%), African American/Black (5.7%), Asian American/Asian (4.2%), Hispanic/Latino/a (2.8%), Native American/Pacific Islander (0.5%), or other (1.0%). Couples were married (62.3%), seriously dating (17.0%), casually dating (14.2%), and engaged to be married (6.6%). The mean relationship length was 8 years (SD = 9.60, range = 2 months–50.5 years). Most participants (n = 174, 82.1%) currently lived with their partner. Eighty participants (37.7%) had children with their current partner, with 77 (36.3%) reporting they (n = 39) and/or their partner (n = 38) had children from a prior relationship.

Over half the sample (n = 128, 60.4%, 72 women, 56 men) reported a depression diagnosis. Most individuals reported they (n = 87, 41%) or their partner (n = 84, 39.6%) had been professionally diagnosed. The remaining 41 participants (19.3%) reported that both partners had depression diagnoses.² Participants had been diagnosed for 6 years (SD = 7.54, range = 1 month–46.75 years) with chronic mild depression/dysthymia (24.5%), major depression (26.9%), depression as a part of bipolar disorder (7.5%), seasonal affective disorder (4.2%), postpartum depression (3.3%), psychotic depression (1.4%), or other (0.9%). Most diagnosed participants (79.7%) were currently taking antidepressant medication, and approximately a third (31.3%) used nonmedicinal treatment, such as counseling or cognitive behavioral therapy.

Measures

Confirmatory factor analyses (CFAs) evaluated unidimensionality of each measure individually with a 3-item relationship satisfaction measure (Fletcher, Simpson, & Thomas, 2000) as an external factor.

Depressive symptoms

The Center for Epidemiologic Studies Depression Scale (CES-D; Radloff & Locke, 1986) measured depressive symptoms. This 20-item measure asked participants how they felt or behaved in the past week on a 4-point scale (0 = rarely, 1 = sometimes, 2 = occasionally, and 3 = most of the time). Sample items include (a) I felt lonely and (b) I felt that I was just as good as other people (reverse scored).

The set of 20 items was a poor fit in CFA tests (χ²/df = 3.23, confirmatory fit index [CFI] = .86, root mean square error of approximation [RMSEA] = .10), but removing one reverse-scored item (“I was happy”) produced a marginally acceptable fit (χ²/df = 2.93, CFI = .89, RMSEA = .09). Reverse-scored CES-D items might skew total scores because they increase cognitive demand (Carlson et al., 2011). With this in mind, I calculated two versions of the variable as means of 20 (M = 1.08, SD = 0.68) or 19 (M = 1.08, SD = 0.68) items. Reliability was high (α = .95, α = .94) for both versions. I conducted one third of the substantive analyses with both versions of the scale, and the results were identical. I used the 20-item version in substantive analyses to maintain consistency with previous publications.

Initial analyses describe the depressive symptomology of the sample. The summed scores indicated that 42.9% of the sample reported symptoms indicative of severe depression, with 17% meeting the cutoff for mild-to-moderate clinical depression (Radloff & Locke, 1986). I also analyzed scores separately for individuals reporting (n = 128) and not reporting a diagnosis (n = 84). For those with a diagnosis, 56.2% reported symptoms of severe depression, and 14.1% met the cutoff for clinical depression. In the subsample without a diagnosis, 28.6% reported severe symptoms, while 15.4% reported mild-to-moderate symptoms. Finally, I examined couple-level reports. In 39 couples (36.8%), one partner reported symptoms above the clinical cutoff, while the other did not. In 45 couples (42.5%), both partners reported symptoms indicative of clinical depression. In 22 couples (20.8%), neither partner reported symptoms at or above the clinical cutoff. Given the variation in diagnosis status and current symptomology, I elected to use the continuous measure of depressive symptoms in the substantive analyses, as opposed to self-reported diagnosis or a categorical variable based on clinical cutoffs.

Relational uncertainty

Abridged forms of Knobloch and Solomon’s (1999) scales operationalized relational uncertainty. Participants responded to 12 items, prefaced by the question “How certain are you about…?” on a 6-point scale (1 = completely uncertain and 6 = completely certain). Items were reverse scored, with higher scores indicating greater relational uncertainty. Four items measured self-uncertainty (e.g., “your view of the relationship?”), partner uncertainty (e.g., “how important your relationship is to your partner?”), and relationship uncertainty (e.g., “the future of your relationship?”). CFA tests documented unidimensionality of each subscale: (a) self-uncertainty, χ²/df = 2.08, CFI = .99, RMSEA = .07; (b) partner uncertainty, χ²/df = 2.16, CFI = .98, RMSEA = .07; and (c) relationship uncertainty, χ²/df = 1.60, CFI = .99, RMSEA = .05. I calculated the mean of each variable separately: self-uncertainty (M = 2.14, SD = 1.06, α = .92), partner uncertainty (M = 2.20, SD = 1.08, α = .90), and relationship uncertainty (M = 2.25, SD = 1.02, α = .87).

Interference from a partner

Solomon and Knobloch’s (2001) scale measured interference from a partner. The stem “My romantic partner…” preceded 6 items, and participants responded on a 6-point scale (1 = strongly disagree and 6 = strongly agree). Sample items include (a) interferes with the plans I make and (b) makes it harder for me to schedule my activities. CFA results confirmed unidimensionality, χ²/df = 1.51, CFI = .99, RMSEA = .05. Each participant’s score was calculated as the mean (M = 2.18, SD = 1.29, α = .95).

Sexual intimacy challenges

First, participants responded “yes” or “no” to an item about whether depression makes it difficult to maintain the sexual relationship. Participants then completed sexual intimacy challenges scales constructed for this study. The scales assessed libido as a primary challenge and cognitive and interactive challenges as specific assessments of one’s own and her or his partner’s barriers to sexual intimacy. Instructions asked participants to “Please continue to think about how depression might make it difficult to maintain your sexual relationship, then select the response that best indicates your agreement with the following statements.” Participants indicated agreement on a 5-point scale (1 = strongly disagree and 5 = strongly agree), with higher scores signifying greater sexual intimacy challenges.

Libido challenges

As a primary assessment of sexual intimacy challenges, the libido challenges scale measured frequency and one’s own and partner’s interest. Three items measured frequency: (a) my partner and I have sex less frequently than I would like, (b) I wish we had sex more often, and (c) my partner and I do not have sex often enough. Four items measured own interest: (a) depression has decreased my interest in sex, (b) depression makes me uninterested in sexual intimacy, (c) depression has damaged my sex drive, and (d) depression limits my desire to be sexually intimate. Four items measured partner’s interest: (a) depression has decreased my partner’s interest in sex, (b) depression makes my partner uninterested in sexual intimacy, (c) depression has damaged my partner’s sex drive, and (d) depression limits my partner’s desire to be sexually intimate.

CFA tests established each set of items as unidimensional and documented a second-order factor including all three subscales, χ²/df = 2.61, CFI = .96, RMSEA = .09. Each participant’s score was calculated as the mean of the 11 items (M = 2.89, SD = 0.91, α = .90).

Cognitive challenges

Fifteen items assessed cognitive challenges to a sexual connection. Four items measured participants’ own self-esteem challenges: (a) my low self-confidence hinders our sex life, (b) my difficulties with self-esteem weaken our sexual relationship, (c) my low self-esteem challenges our sexual partnership, and (d) our sex life is damaged by my poor self-confidence. Three items captured participants’ own isolation issues: (a) feelings of isolation make it difficult for me to be sexually intimate, (b) depression makes me feel sexually distant from my partner, and (c) for me, feelings of isolation are a barrier to our sexual relationship. Four items assessed partners’ self-esteem challenges: (a) my partner’s low self-confidence hinders our sex life, (b) my partner’s difficulties with self-esteem weaken our sexual relationship, (c) my partner’s low self-esteem challenges our sexual partnership, and (d) our sex life is damaged by my partner’s poor self-confidence. Finally, 4 items addressed partners’ isolation challenges: (a) feelings of isolation make it difficult for my partner to be sexually intimate, (b) depression makes my partner not want to be touched, (c) depression makes my partner feel sexually distant from me, and (d) for my partner, feelings of isolation are a barrier to our sexual relationship.

CFA tests confirmed these four dimensions and revealed two second-order factors as measures of one’s own cognitive challenges, χ²/df = 2.13, CFI = .98, RMSEA = .07, and of a partner’s cognitive challenges, χ²/df = 1.92, CFI = .98, RMSEA = .07. I calculated means and reliabilities for the second-order factors (own cognitive: M = 2.60, SD = 1.15, α = .95; partner cognitive: M = 2.54, SD = 1.12, α = .95).

Interactive challenges

The third scale measured interactive challenges to sexual intimacy. Six items measured one’s own difficulties with conversations: (a) conversations about our sexual relationship are frustrating for me, (b) I find conversations with my partner about sex to be difficult, (c) talking with my partner about sex is challenging for me, (d) I don’t know how to talk to my partner about our sex life, (e) I’m unsure how to have a conversation about sex with my partner, and (f) I am hesitant to talk about sex with my partner. Four items assessed one’s own challenges with initiation: (a) it is hard for me to let my partner know when I am interested in sex, (b) it is difficult for me to start sexual activity with my partner, (c) I’m unsure how to initiate a sexual interaction with my partner, and (d) I don’t know how to initiate sexual activity with my partner. Ten parallel items measured perceptions of a partner’s conversational and initiation challenges (e.g., “my partner finds conversations with me about sex to be difficult.”).

CFA tests verified the four subscales and confirmed two second-order factors: own interactive, χ²/df = 2.59, CFI = .96, RMSEA = .09, and partner interactive, χ²/df = 1.75, CFI = .98, RMSEA = .06. I calculated means and reliabilities for the second-order factors (own interactive: M = 2.71, SD = 1.03, α = .96; partner interactive: M = 2.62, SD = 0.98, α = .96).

Independent samples t tests compared men and women with and without a depression diagnosis. Men and women with a clinical diagnosis reported significantly higher levels of own cognitive challenges than those without. No other statistically significant differences emerged based on diagnosis status. I additionally examined differences based on the initial item about difficulties with the sexual relationship. People who responded “yes” to the initial item scored significantly higher on all five scales (Table 1).

Table 1.

Means and t tests on sexual intimacy challenges measures.

Sexual Intimacy Challenge	Depression diagnosis status
	Women			Men
	Yes	No		Yes	No
	M (SD)	M (SD)	t(104)	M (SD)	M (SD)	t(104)
Libido	2.95 (0.77)	2.66 (1.06)	1.41	2.97 (1.01)	2.89 (0.89)	0.42
Own cognitive	3.00 (1.14)	2.34 (1.20)	2.76*	2.67 (1.14)	2.12 (0.94)	2.72*
Partner cognitive	2.34 (1.04)	2.46 (1.27)	0.47	2.73 (1.16)	2.68 (1.05)	0.24
Own interactive	2.81 (1.00)	2.60 (1.15)	0.87	2.69 (1.04)	2.66 (0.99)	0.14
Partner interactive	2.52 (0.95)	2.61 (1.09)	0.40	2.64 (0.96)	2.73 (0.98)	0.42
	Sexual difficulties
	Women			Men
	Yes	No		Yes	No
Sexual Intimacy Challenge	M (SD)	M (SD)	t(104)	M (SD)	M (SD)	t(104)
Libido	3.40 (0.61)	2.29 (0.75)	8.40**	3.59 (0.61)	2.36 (0.82)	8.61**
Own cognitive	3.57 (0.79)	1.98 (0.99)	9.14**	2.99 (1.01)	1.91 (0.88)	5.84**
Partner cognitive	2.98 (0.99)	1.75 (0.86)	6.78**	3.42 (0.70)	2.10 (1.02)	7.81**
Own interactive	3.23 (0.90)	2.23 (0.95)	5.54**	3.14 (0.94)	2.27 (0.89)	4.86**
Partner interactive	2.94 (0.96)	2.15 (0.87)	4.42**	3.17 (0.82)	2.27 (0.89)	5.33**

*p < .01; **p < 001.

Data analysis

Preliminary analyses

A first test examined bivariate correlations on all variables for women, men, and between couples (Table 2). A second preliminary test examined differences among men and women through paired samples t tests. Women reported greater depressive symptoms (M = 1.19, SD = 0.64) than men (M = 0.97, SD = 0.70), t(105) = 2.95, p <.01. Women exhibited greater own cognitive challenges (M = 2.79, SD = 1.19) than men (M = 2.41, SD = 1.08), t(105) = 3.44, p <.01. Men, however, reported greater partner cognitive challenges (M = 2.71, SD = 1.10) than women (M = 2.38, SD = 1.11), t(105) = 3.68, p < .001.

Table 2.

Bivariate correlations among men, women, and within couples.

Variable	V1	V2	V3	V4	V5	V6	V7	V8	V9	V10
V1: Depressive symptoms	.37**	.33**	.22*	.37**	.34**	.35**	.65**	.37**	.38**	.40**
V2: Self uncertainty	.46**	.58**	.68**	.87**	.37**	.28**	.28**	.31**	.34**	.37**
V3: Partner uncertainty	.47**	.76**	.59**	.81**	.32**	.28**	.19	.38**	.30**	.31**
V4: Relationship uncertainty	.48**	.88**	.78**	.64**	.42**	.28**	.31**	.34**	.32**	.37**
V5: Interference from a partner	.33**	.45**	.28**	.47**	.40**	.40**	.35**	.43**	.32**	.27**
V6: Libido challenges	.35**	.31**	.34**	.36**	.42**	.73**	.68**	.90**	.69**	.71**
V7: Own cognitive challenges	.53**	.36**	.37**	.40**	.40**	.78**	.50**	.68**	.64**	.59**
V8: Partner cognitive challenges	.33**	.40**	.38**	.37**	.54**	.76**	.63**	.65**	.67**	.74**
V9: Own interactive challenges	.42**	.33**	.32**	.39**	.45**	.72**	.69**	.66**	.59**	.80**
V10: Partner interactive challenges	.23*	.26**	.29**	.33**	.40*	.74**	.54**	.82**	.80**	.75**

Note. n = 106 men, women, or couples. Correlations for men appear above the diagonal, and correlations for women appear below the diagonal. Within-couple correlations appear on the diagonal and are underlined.

*p < .05; **p < .01.

Age and relationship length shared statistically significant associations with several variables. Significant associations also appeared for six dichotomous variables: depression diagnosis status, medication, marital status, parental status, cohabitation, and yes/no report of sexual intimacy challenges.³ Accordingly, the eight variables were included as covariates.

Substantive analyses

The hypothesized mediation model was tested in several steps. A first set of models examined the presumed association between depressive symptoms and each sexual intimacy challenge. Then, I evaluated the associations for H1 (depressive symptoms and mechanisms of turbulence) and H2 (mechanisms of turbulence and sexual intimacy challenges) separately before testing the hypotheses together to evaluate H3 (mediation).

I used structural equation modeling (AMOS 20) with maximum likelihood estimation to test the proposed associations. I regressed each study variable onto the set of eight covariates and used the residuals to construct the substantive models. I formed parcels to represent the latent variables, set the error variance for each latent variable to (1 − α) × σ² and standardized the variables across the full sample (Bollen, 1989; Kenny et al., 2006). Each model included both actor and partner effects for the hypothesized associations, and the exogenous variables and error terms for the endogenous variables were covaried within couples (Ledermann, Macho, & Kenny, 2011). Criteria for model fit were: χ²/df < 3.00, CFI > .90, and RMSEA < .10 (Kline, 2011). If fit criteria were not met, I examined the path coefficients and deleted statistically nonsignificant paths individually, then consulted the modification indices to make theoretically reasonable additions to the models. After achieving model fit, I examined each path that remained for both men and women, then added constraints to set those paths as equal across sexes (Kenny et al., 2006) and evaluated model fit to determine whether constrained paths offered a more precise assessment of the data. To examine indirect effects in the full-model tests, I employed bootstrapping procedures recommended by Preacher and Hayes (2008).

Results

Depressive symptoms and sexual intimacy challenges

As a preliminary test of the logic driving the investigation, I tested a model in which depressive symptoms directly predicted each sexual intimacy challenge for both actors and partners. The first model examined libido challenges. This model (χ²/df = 1.26, CFI = .99, RMSEA = .05) identified an actor effect for women and men (b = .20, p < .01).

A second model predicted cognitive challenges. To account for conceptual overlap, I included both own cognitive and partner cognitive challenges in the test. The fit model (χ²/df = 1.02, CFI = .99, RMSEA = .02) supported (a) actor effects for men and women between depressive symptoms and perceptions of own cognitive challenges (b = .32, p < .001), (b) an actor effect for men between depressive symptoms and perceptions of their partner’s cognitive challenges (b = .28, p < .01), and (c) a partner effect for men, in which men’s depressive symptoms predicted women’s perceptions of their partner’s cognitive sexual intimacy challenges (b = .44, p < .001). The modification indices for this test also documented effects in which partner cognitive challenges predicted own cognitive challenges for actors (women: b = .25, p < .001, men: b = .42, p < .001), and partners (women: b = .28, p < .001, men: b = .43, p < .001).

A third model evaluated own and partner interactive challenges (χ²/df = 1.18, CFI = .99, RMSEA = .04). An actor effect appeared for men’s and women’s depressive symptoms predicting their own interactive challenges (b = .38, p < .001). Additional paths revealed associations between own interactive challenges and perceptions of a partner’s interactive challenges, both in actor effects (women and men: b = .64, p < .001) and in partner effects (women: b = .25, p < .001; men: b = .44, p < .001). These preliminary results identified direct associations between depressive symptoms and sexual intimacy challenges.

H1: Depressive symptoms and mechanisms of turbulence

I tested H1 with a model including depressive symptoms, all three sources of relational uncertainty, and interference from a partner. The hypothesized model included both actor and partner paths from depressive symptoms to each source of relational uncertainty and to interference from a partner and actor paths for men and women from self and partner uncertainty to their own relationship uncertainty (following prior work, e.g., Knobloch, Sharabi, Delaney, & Suranne, 2016; Solomon et al., 2016). The final model (χ²/df = 1.42, CFI = .98, RMSEA = .06) confirmed several hypothesized paths: an actor effect for both men and women from depressive symptoms to self-uncertainty (b = .35, p < .001), actor and partner effects from men’s depressive symptoms to their own (b = .35, p < .001) and their partner’s (b = .32, p < .001) interference from a partner, from self-uncertainty to relationship uncertainty for women (b = .97, p < .001) and men (b = .68, p < .001), and from partner uncertainty to relationship uncertainty for men (b = .41, p < .001). The modification indices indicated several associations among mechanisms of turbulence: a path from self-uncertainty to partner uncertainty for men (b = .69, p < .001) and women (b = .87, p < .001) a partner effect between men’s partner uncertainty and women’s self-uncertainty (b = .63, p < .001) and a path from men’s partner uncertainty to their own (b = .25, p < .05) and their partner’s (b = .44, p < .001) interference from a partner. H1 results document actor effects from depressive symptoms to self-uncertainty and actor and partner effects from men’s depressive symptoms to interference from a partner.

H2: Mechanisms of turbulence and sexual intimacy challenges

I tested this prediction with one model for each category of sexual intimacy challenges (libido, own and partner cognitive, own and partner interactive). Across tests, I replicated the associations among mechanism of turbulence documented in tests of H1, then tested for both actor and partner effects between each predictor (self, partner, and relationship uncertainty, interference from a partner) and the sexual intimacy challenges. Across models, all paths for relational uncertainty were statistically nonsignificant. The libido model (χ²/df = 1.62, CFI = .97, RMSEA = .08) documented an actor effect between interference from a partner and libido challenges for both men and women (b = .28, p < .001) and no partner effects.

A second test evaluated associations between mechanisms of turbulence and own/partner cognitive sexual intimacy challenges. Paths from interference from a partner to own cognitive challenges were statistically nonsignificant. The final model (χ²/df = 1.91, CFI = .95, RMSEA = .09) identified actor effects from interference from a partner to perceptions of a partner’s cognitive sexual intimacy challenges for both women (b = .52, p < .001) and men (b = .29, p < .01) and a partner effect from women’s interference from a partner to men’s partner cognitive challenges (b = .23, p < .05). Similar to preliminary tests, partner cognitive challenges predicted both actor and partner effects for own cognitive challenges.

A final test of H2 investigated associations between mechanisms of turbulence and interactive challenges. In the fitted model (χ²/df = 1.68, CFI = .96, RMSEA = .08), women’s interference from a partner demonstrated actor (b = .37, p < .001) and partner (b = .23, p < .05) effects on own interactive challenges. Similar to preliminary tests, actor and partner effects remained between own interactive and partner interactive challenges. Together, tests of H2 failed to document associations between relational uncertainty and sexual intimacy challenges (H2a) but identified actor and partner effects between interference from a partner and libido, cognitive, and interactive challenges (H2b).

H3: Mechanisms of turbulence as mediators

H3 proposed mechanisms of turbulence as mediators between depressive symptoms and sexual intimacy challenges. I constructed three full models to evaluate this logic and test the statistically significant actor and partner effects from H1 and H2 together. The first model evaluated libido challenges and confirmed the associations documented in the preliminary and hypothesis tests (χ²/df = 1.27, CFI = .98, RMSEA = .05). A partial indirect effect existed between men’s depressive symptoms and sexual intimacy challenges for both women = .10, p < .01 [.03–.21] and men = .10, p < .01 [.04–.20]. In this effect, men’s depressive symptoms predicted both men’s and women’s perceptions of interference, which exhibited actor effects for both men and women on libido challenges. Path coefficients are available in Figure 2.

Figure 2.

Final model predicting libido sexual intimacy challenges.

A second model evaluated cognitive challenges. The previously identified associations remained statistically significant, except the actor path linking men’s depressive symptoms to perceptions of a partner’s cognitive challenges (p = .27). After removing this path, the model demonstrated acceptable fit (χ²/df = 1.46, CFI = .97, RMSEA = .07). Four statistically significant indirect effects also emerged. In a first set, men’s depressive symptoms were indirectly associated with (a) men’s partner cognitive challenges = .22, p < .01 [.12–.32] and (b) women’s partner cognitive challenges = .18, p < .01 [.07–.34]. This indirect effect includes the paths between men’s depressive symptoms and men’s and women’s interference and the actor and partner paths (for men) and the actor path (for women) to perceptions of a partner’s sexual intimacy challenges. Given that partner cognitive challenges maintained actor and partner effects for own cognitive challenges, an additional set of indirect effects was significant for (c) men’s own cognitive challenges = .25, p < .001 [.15–.36] and (d) women’s own cognitive challenges = .22, p < .001 [.13–.33]. Figure 3 features path coefficients for this test.

Figure 3.

Final model predicting own and partner cognitive sexual intimacy challenges.

A final test evaluated interactive challenges. The previous associations remained statistically significant, except for the partner path from women’s interference from a partner to men’s own interactive challenges (p = .14). After removing this path, the model achieved fit (χ²/df = 1.49, CFI = .96, RMSEA = .07). A trio of statistically significant indirect effects also emerged, in which men’s depressive symptoms were indirectly associated with (a) women’s own interactive challenges = .12, p < .001 [.05–.22], (b) women’s partner interactive challenges = .26, p < .001 [.17–.35], and (c) men’s partner interactive challenges = .26, p < .001 [.16–.36]. Men’s depressive symptoms predicted women’s interference from a partner, which predicted women’s own interactive challenges. Then, women’s interactive challenges predicted their perceptions of partner interactive challenges (actor effect) and men’s perceptions of partner interactive challenges (partner effect). Path coefficients for this test appear in Figure 4.

Figure 4.

Final model predicting own and partner interactive sexual intimacy challenges.

Discussion

Depression has well-known individual and relational effects (Hames et al., 2013; National Institute of Mental Health, 2015), but a gap exists in theorizing how depression affects a couple’s sexual connection. Prior research documented sexual troubles for couples with depression (Baldwin, 2001; Kennedy et al., 1999; Laurent & Simons, 2009); however, theoretical insight into relationship dynamics of these sexual difficulties is needed. Through an RTM (Solomon & Knobloch, 2004) framework, the current study sheds new light on depression in romantic relationships by documenting associations between (a) men’s and women’s depressive symptoms and their own self uncertainty and (b) men’s depressive symptoms and men’s and women’s interference from a partner (H1). The data did not document associations between relational uncertainty and sexual intimacy challenges (H2a). Interference from a partner predicted sexual intimacy challenges for both women and men (H2b) and, thus, emerged as a mediator between depressive symptoms and sexual intimacy challenges (H3). In the following pages, I situate these findings within the existing theory and research on depression and sexual intimacy.

Implications for theory and research

Depression and relational turbulence

Previous studies (e.g., Knobloch & Delaney, 2012; Knobloch et al., 2011) have used the RTM as a framework for understanding depression. Knobloch and Delaney (2012) identified themes of both mechanisms of turbulence as important to the context of depression, but their qualitative data did not allow for testing of associations. Quantitative studies (e.g., Knobloch & Knobloch-Fedders, 2010; Knobloch et al., 2016) have documented associations between depressive symptoms and relational uncertainty but did not test interference from a partner, which has demonstrated ties with other health concerns such as infertility and breast cancer (Solomon et al., 2010). In this sample, depressive symptoms associated with both relational uncertainty (H1a) and interference from a partner (H1b).

Theories of depression identify ambiguity and disruptions to routines as central relational effects (Beach et al., 1990; Coyne, 1976). Here, depressive symptoms predicted men’s and women’s self-uncertainty, with self-uncertainty then predicting partner and relationship uncertainty. This comports with research documenting actor effects for women’s depression predicting their own self uncertainty, although men’s depressive symptoms predicted partner uncertainty in prior work (Knobloch et al., 2016). In the current study, men’s depressive symptoms predicted both men’s and women’s interference from a partner. Perhaps men notice goal blockages when they are cognitively and emotionally taxed by depression, whereas women perceive interference when their partners are limited by depressive symptoms. Men’s partner uncertainty was also associated with men’s and women’s interference from a partner. Prior work has linked the mechanisms of turbulence (Knobloch & Delaney, 2012; Knobloch & Theiss, 2010; Steuber & Solomon, 2008). Relational turbulence scholars should continue considering how these mechanisms connect to each other and with depressive symptoms.

Relational turbulence and sexual intimacy challenges

Prior research has failed to capture nuance and scope of partners’ experiences with depression-related sexual intimacy challenges. Quantitative work documented prevalence of sexual difficulties (e.g., Kennedy et al., 1999; Laurent & Simons, 2009), whereas qualitative work underscored complexity of sexual troubles (e.g., Knobloch & Delaney, 2012; Ostman, 2008; Sharabi, Delaney, & Knobloch, 2016). This study offers quantitative measures of multilayered sexual intimacy challenges. Future use will allow scholars and practitioners to specify causes and consequences of challenges related to depression.

The current results suggest that some sexual intimacy challenges are directly tied to symptoms of depression. The path from men’s and women’s depressive symptoms to their own libido challenges comports with existing perspectives of decreased libido as a symptom of depression (Kennedy et al., 1999). The actor path from depressive symptoms to own cognitive challenges implies that as depression diminishes feelings of self-worth and prompts social withdrawal (Coyne, 1976; Coyne, Gallow, Klinkman, & Calarco, 1998), symptoms disrupt the sexual relationship. Men’s depressive symptoms also predicted women’s partner cognitive challenges, adding evidence of partner effects between depressive symptoms and perceptions of sexual relationships. The actor path linking depressive symptoms to men’s and women’s own interactive challenges echoes theorizing tying depression to communication difficulties (Beach et al., 1990; Coyne, 1976) and specifies struggles with interactions about sex and initiation of sexual activity. These results align with previous research linking depression and its treatment to sexual dysfunctions and difficulties (e.g., Montejo et al., 2018), and the mediating effects of interference (H3) emphasize the function of qualities of the relationship within depression.

These data did not reveal associations between relational uncertainty and sexual intimacy challenges. Even though H2a was not supported, additional speculation about the role of relational uncertainty in this process is justified. Relational uncertainty is theorized to associate with communicative engagement and communication valence (Solomon et al., 2016), so perhaps ambiguity about the relationship is more tied to people’s approach to conversations with their partner than their evaluations of sexual intimacy challenges. Evidence exists that relational uncertainty predicts negative feedback seeking, topic avoidance, and indirect sexual communication (Knobloch et al., 2011, 2016; Theiss & Estlein, 2014). Although relational uncertainty was not associated with perceptions of sexual intimacy challenges in this study, it may predict people’s approach to communicating about sex with their partners more generally.

Tests of H3 integrated the findings from H1 and H2 to evaluate indirect effects. In most cases, interference from a partner (as predicted by men’s depressive symptoms) was a statistically significant mediator. In a literature privileging relational uncertainty, this finding suggests difficulties with dyadic coordination facilitate sexual issues in depression. When partners block each other’s goals, struggle to coordinate routines, and disrupt day-to-day activities, they might be disinterested in sexual activity, feel withdrawn, or become frustrated over a lack of initiation. The marital discord model of depression (Beach et al., 1990) identifies disrupted routines and scripts as one connection between relationship troubles and depressive symptoms. These findings align with that framework. The RTM adds explanatory power by positing that interference from a partner sparks intensified emotions (Solomon & Knobloch, 2004; Solomon et al., 2016). If perceptions of partner interference prompt negative emotions in the already negative emotional climate of depression, this likely inhibits positive emotional responses that facilitate sexual connection (Gonzaga, Turner, Keltner, Campos, & Altemus, 2006). Given the current findings connecting dyadic interference with sexual intimacy challenges, additional investigations into emotional processes in this association are warranted.

This study integrates theory into predicting sexual intimacy challenges for couples. Prior research attributes lost libido or difficulties with function to the depression or medication used to treat it (Higgins et al., 2010; Kennedy et al., 1999), and sexuality scholars have called for insight into contextual and interpersonal factors in sexual challenges (e.g., Brotto et al., 2016). The RTM has proved useful in predicting outcomes for depressed couples such as communication behaviors (Knobloch et al., 2011, 2016) and relationship satisfaction (Knobloch & Knobloch-Fedders, 2010), and now, sexual intimacy challenges are another noteworthy marker of relational turbulence.

Practical implications

Scholars and practitioners recommend approaching depression from a dyadic perspective (Barbato & D’Avanzo, 2008; Bodenmann & Randall, 2013). In working with depressed individuals and couples, practitioners can evaluate sexual intimacy challenges within the context of the relationship. Practitioners might also find it useful to target partner interference in intervention. If couples can coordinate to reduce disruptions to routines and goals that accompany depression, they may be able to also address sexual intimacy challenges in their partnership. By considering the range of sexual intimacy challenges, examining both partners’ perceptions and experiences, and developing specific strategies for unique problems, practitioners will be able to help couples mitigate sexual intimacy challenges.

Limitations and future directions

The study and results should be considered in the light of methodological limitations. These data represent a first test of quantitative measures of sexual intimacy challenges and might not comprehensively capture sexual effects of depression. An open-ended item on this questionnaire (not analyzed here) suggested that negativity may drive difficulty with conversations and tiredness and motivation could present additional challenges. Both negativity and fatigue have documented destructive effects in depression (Beach et al., 1990; Targum & Fava, 2011). The sexual intimacy challenges measured here also have conceptual overlap with symptoms measured by the CES-D (e.g., self-esteem). I conducted Harman’s test to evaluate the potential for common method variance to artificially inflate effects and less than 50% of variance was explained by a common factor. As with any new measure, additional refinement and testing of the sexual intimacy challenges measures is needed.

Second, the sample represents a subset of couples with depression. This sample (approximately 80% currently receiving medicinal treatment) does not represent experiences of couples with untreated or undiagnosed depression. Additional research must explore experiences of couples in different stages of their illness trajectory. The sample includes individuals with a variety of depressive illnesses, including illnesses that may have unique effects on sexual intimacy. For example, manic episodes in the context of bipolar disorder may include increased libido (Kopeykina et al., 2016), and postpartum depression includes depressive symptoms along with physical and relational changes that could influence a couple’s sexual connection (Leeman & Rogers, 2012). Future research will be useful for comparing across depressive illnesses and examining physical health concerns that include depressive symptoms and other unique sexual intimacy difficulties, such as heart disease or breast cancer (Driel, de Hosson, & Gabel, 2013; Ussher, Perz, & Gilbert, 2012).

Recently, relational turbulence scholars advanced the tenets of the model to introduce relational turbulence theory, which emphasizes cognitive and emotional processes (Solomon et al., 2016). Depression disrupts both (Joorman & Gotlib, 2010). Tests of relational turbulence theory will illuminate how cognitions and emotions shape subjective experiences of turbulence in depression. Moreover, the current study documents a handful of differences in predictors of men’s and women’s sexual intimacy challenges. Gender differences exist in the experience of depression (e.g., Girgus & Yang, 2015), and the current findings invite additional research on how gender shapes depression and sexuality.

Conclusion

The RTM (Solomon & Knobloch, 2004) designates relational qualities that facilitate turbulent relationship outcomes. The current study builds on recent findings about how depression can damage a couple’s sexual relationship (Delaney, in press; Knobloch & Delaney, 2012) by pinpointing interference from a partner as a mediating variable between depressive symptoms and sexual intimacy challenges. The dyadic analyses also suggest that women’s interference predicts men’s partner cognitive challenges, and men’s depressive symptoms predict women’s partner cognitive challenges. The findings exemplify the value of studying depression from a relationships perspective and inform future research and intervention into the dynamics of depressed couples’ partnerships.

Footnotes

Author’s note

This article represents a portion of the author’s dissertation.

Acknowledgements

The author would like to thank Leanne Knobloch, John Caughlin, Brian Quick, and Brian Ogolsky for their guidance and feedback throughout the study and would also like to thank Isabelle Gordon, Blake Herrman, Emily Brennan, Kelly Kennedy, and Danielle Bertini for contributions across the project.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was funded by the Ruth Anne Clarke Student Scholar Award and the University of Illinois Graduate College Dissertation Completion Fellowship.

Open research statement

This research was not pre-registered because data collection occurred in 2015, before the encouragement of pre-registration was commonplace. Future efforts in this line of research will be pre-registered. The data used in the research are available from the author via email at aldelaney@millikin.edu.

Notes

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