Longitudinal Coupling of Depression in Parent-Adolescent Dyads: Within- and Between-Dyad Effects Over Time

Abstract

The present work evaluated reciprocal, within-dyad associations between parent-adolescent depressive symptoms across two independent samples (N=327 and N=435 dyads, respectively; approximately 85% biological mothers) assessed every three months for two (Study 1) to three (Study 2) years. Results of random intercept cross-lagged panel models converged to support positive contemporaneous patterns of co-fluctuation in parent and adolescent depression, such that within-person deviations in parental depression were associated with same direction within-person deviations in adolescent depression at the same timepoint. In contrast, within-person fluctuations in parent depression did not predict prospective within-person fluctuations in adolescent depression, or vice versa, across the follow-up period. Results held across boys and girls, as well as dyads with and without a parental history of depressive disorder. Overall, findings advance knowledge by demonstrating that, after accounting for between-person/dyad variance, parent and adolescent depression demonstrate contemporaneous co-fluctuations, but do not demonstrate within-dyad reciprocity over time.

Parental depression has been related to enduring patterns of offspring psychosocial impairment, with implications for youth socioemotional functioning across development (e.g., Brennan et al., 2002; Goodman, 2007; Lewinsohn et al., 2005; Weissman et al., 2006). Offspring of depressed parents are approximately 3 times more likely than offspring of nondepressed parents to experience clinically significant levels of depression (Lieb et al., 2002). Elevations in depressive symptoms among children of depressed parents may be particularly likely to occur during the transition to adolescence, a developmental period during which youth demonstrate enhanced vulnerability to the onset of psychopathology (Costello et al., 2011; Merikangas et al., 2010; Paus et al., 2008). Indeed, adolescence may represent a key period of risk for children of depressed parents, given evidence that presence of parental depression predicts earlier-onset of depression among youth (Birmaher et al., 1996; Hammen & Brennan, 2003), which may portend life course persistent patterns of distress and impairment (Keenan-Miller et al., 2007; Weissman et al., 1999).

Interest in understanding processes contributing to depressive risk transmission among families affected by parental depression has inspired a rich body of research examining the influence of parental depression on child psychopathology outcomes (see Goodman, 2020; Gotlib et al., 2020 for recent reviews), generating a number of hypotheses concerning the way in which increased risk for depression may occur among children of depressed parents. Although shared genetics are presumed to play some role in the longitudinal coupling of parent-child depressive symptoms (see Goodman & Gotlib, 1999), results of studies using genetically-informed designs suggest that exposure to parental depression also functions through environmental means to increase risk for depression in offspring (McAdams et al., 2015; Natsuaki et al., 2014; Singh et al., 2011; Tully et al., 2008). Notably, this pattern of relations is observed at both clinical and subclinical levels of parental symptoms (Natsuaki et al., 2014), suggesting that child symptoms may fluctuate in tandem with symptom fluctuation in parents. Such patterns of co-fluctuation in depression levels have been observed contemporaneously among parent-child dyads (Flancbaum et al., 2011), and prospective studies indicate that within-person fluctuations in parental depression interact with individual difference factors including youth cognitive risks (Abela et al., 2006), attachment cognitions (Abela et al., 2009), and genotype (Oppenheimer et al., 2013) to predict within-person fluctuations in youth depression.

Importantly, if depression within the family system is transmitted, at least in part, via environmental mechanisms, parental depression may also be influenced by dynamic fluctuations in their children’s symptom experience. Relatively little research has rigorously addressed the ways in which parental and offspring depressive symptoms may demonstrate reciprocal patterns of relations over time; however, it has long been recognized that parent-child relationships are bidirectional in nature, with child effects on parents representing salient, if understudied, developmental phenomena (Lougheed, 2020; Pardini, 2008). Research is needed to clarify patterns of prospective, within-dyad bidirectional relations between parent and youth depressive symptoms and advance knowledge of the ways in which parent and child depressive symptoms influence one another over time. Thus, the present inquiry aimed to investigate within-dyad reciprocal patterns of associations between parent and child depressive symptoms in two independent samples of parent-adolescent dyads followed prospectively over a period of years in repeated-measures designs. Implementing an advanced statistical design aimed at disambiguating between- and within- dyad sources of variance in depressive symptom experience, the current work presents a rigorous investigation of the way in which idiographic changes in parent and adolescent depressive symptoms influence one another over time.

Theories of Within-Dyad Depression Transmission

In their foundational paper enumerating potential mechanisms of intergenerational risk transmission among children of depressed mothers, Goodman and Gotlib (1999) identified exposure to parental negative affectivity and maladaptive cognitions and behaviors as one candidate mechanism by which youth acquire risk for the onset of clinical symptoms. Such a mode of depressive transmission within parent-adolescent dyads would be consistent with tenets of social learning (Bandura, 1977) as well as emotional contagion and interpersonal theories of depression (Coyne, 1976; Hames et al., 2013; Hatfield et al., 1993). These theories suggest that modeling processes, nonconscious interpersonal mimicry behaviors, and dysfunctional patterns of interpersonal functioning promote the diffusion of mood states and associated behaviors within close interpersonal networks. Within this conceptual framework, increases in a given parent’s symptoms of depression would be hypothesized to contribute to changes in their child’s symptoms of depression, as the parent’s negative mood states and depressive behaviors trigger implicit learning and socialization processes. Less theoretical work has specifically articulated the mechanisms by which adolescent depressive symptoms may influence parental levels of depression symptom severity. However, it follows from these same social learning, emotional contagion, and interpersonal theories that youth depressive symptom experience may effect change in their parent’s experience of depression through analogous processes of emotional convergence. Consistent with this theoretical lens, meta-analytic findings support “depressive contagion” in cross-sectional studies of adult dyads (e.g., roommates, romantic partners), such that interactions with depressed peers and partners elicit proximal increases in individual partners’ levels of depression (Joiner & Katz, 1999).

Empirical Evidence Supporting Bidirectionality of Parent-Offspring Symptoms

A small number of studies using prospective, repeated-measures designs have found reciprocal patterns of association between parent and youth depressive symptoms across various stages of child development. Among a diverse sample of parent-toddler dyads, for example, Roubinov et al. (2019) demonstrated bidirectional associations between maternal depression and mother-report of child internalizing symptoms between child age 18 months and 4 years. Evidence for transactional patterns of relations between parent-offspring symptoms additionally emerged in work by Gross et al. (2009); using a latent class analysis, Gross et al. (2009) found that youth noncompliant behavior at age 18 months predicted chronic, elevated trajectories of maternal depression across an 8.5 year follow up period. Two studies Ge et al., 1995; Hughes & Gullone, 2010) demonstrated bidirectional relations between parent and child psychological distress and internalizing symptoms, respectively, using traditional cross-lagged panel model (CLPM) analyses. Specifically, Ge et al. (1995) demonstrated reciprocal relations between parent-adolescent psychological distress in a prospective study of 7^th grade students assessed annually for a period of 3 years. Hughes and Gullone (2010) demonstrated bidirectional associations between parent-adolescent internalizing symptoms in a sample of 14 to 18-year-old youth assessed twice across a 6-month period. Moreover, among a sample of mothers with a history of recurrent depression, Sellers et al., (2016) demonstrated that adolescent daughters’ depressive symptoms prospectively predicted increases in maternal symptoms of depression across a 29-month follow up period.

Together, this body of work provides initial support for a potential transactional model of parent and youth depressive symptoms across child and adolescent development, although it is important to note that some studies have yielded mixed or inconsistent patterns of findings (Ciciolla et al., 2014; Mennen et al., 2018). In a sample of children with and without developmental delays assessed annually from ages 3 to 5, Ciciolla et al. (2014) demonstrated reciprocal associations between maternal distress and child internalizing symptoms between child ages 3 and 4 among developmentally at-risk youth only. In another three-time point study analyzed using a CLPM approach, Mennen et al. (2018) found no evidence for reciprocity in parent-child self-reported depression among a sample of youth aged 9 to 13 at baseline. Moreover, unidirectional paths were moderated by child gender and maltreatment status, such that patterns of effects differed across boys and girls, and among youth with and without a history of maltreatment. Additionally, using a genetically informed design, McAdams et al. (2015) demonstrated unidirectional associations from child to parent depression, but not from parent to child depression, although differences in effect sizes between these divergent pathways were small in magnitude.

A key limitation of previous work is its reliance on traditional cross-lagged panel model (CLPM) approaches (see Ge et al., 1995; Gross et al., 2008; Hughes & Gullone, 2010; Mennen et al., 2018; McAdams et al., 2015; Roubinov et al., 2019) which fail to appropriately disaggregate between- from within-person/dyad sources of variance (Hamaker et al., 2015). This methodological limitation is significant, as simulation studies suggest that failure to account for these unique sources of variance may contribute to misleading patterns of effects, particularly when conflicting processes exist at the between- and within-person levels (Hamaker et al., 2015). Indeed, recent work using advanced structural equation modeling (SEM) techniques, such as random intercept cross-lagged panel models (RI-CLPM), which address the main limitation of traditional CLPM and appropriately partition sources of variance (between-persons from within-persons), highlights the need to re-evaluate “known” patterns of associations in developmental psychopathology literatures (see Keijsers, 2016). The theoretical models positing modeling or emotion and social contagion processes presume, and are conceptually based on, within-dyad parent-offspring effects over time. Yet studies using CLPM cannot be assumed to accurately reflect these hypothesized within-person/dyad change processes (see Keijsers, 2016). In order to rigorously and appropriately test theories of longitudinal symptom coupling, which fundamentally propose within-dyad mechanisms of action, within-dyad effects must be accurately separated from between-dyad influences so that proper inferences and conclusions can be attained.

Of the available empirical studies, to our knowledge, only Kouros and Garber (2010) employed appropriate modeling techniques to evaluate within-dyad transactional associations between parent and child depressive symptoms. In a prospective study of parent-adolescent dyads assessed annually from adolescent grade 6 through 12, Kouros and Garber (2010) applied dynamic bivariate latent difference score modeling analyses to demonstrate longitudinal coupling between parent and adolescent depressive symptoms, such that dyad members’ level of depressive symptoms reciprocally predicted one another over time. This study had a relatively long (i.e., one year) inter-assessment time interval, and thus, research is needed using more frequent assessments to precisely evaluate reciprocal associations between parent and adolescent depressive symptoms across shorter time intervals.

Additionally, research is needed to evaluate theoretically-based moderators that might be expected to modulate the strength of association between parent and child depressive symptoms. Child gender identity and parental history of depression diagnosis are two individual difference factors that may influence dyad members’ sensitivity to one another’s fluctuating levels of depression. Girls may be especially vulnerable to the depressogenic effects of fluctuations in their parents’ depression, given that girls have been found to demonstrate enhanced interpersonal sensitivity relative to boys (Cyranowski et al., 2000; Hankin et al., 2007; Rudolph, 2002). Indeed, Mennen and colleagues (2008) found that reciprocal patterns of relations between parent and child symptoms varied by child gender. Parental history of depressive disorder may also influence strength of reciprocal associations between parent and adolescent depressive symptoms. Theory and research suggest that parents with a history of depressive disorder, as well as their offspring, demonstrate elevated reactivity to stressors in their environments relative to others without such histories (e.g., Hammen, 2005; Morris et al., 2010). This suggests that dyads characterized by parental history of depression may demonstrate stronger patterns of depressive reciprocity relative to dyads characterized by a lack of parental depression history.

Study 1

Study 1 aimed to investigate within-dyad, reciprocal patterns of prospective relations between parent and youth depressive symptoms in a sample of parent-adolescent dyads recruited from the general community. Participating parents completed gold-standard diagnostic interviews to ascertain parental lifetime history of depressive disorder prior to enrollment in the study. Participating parents and adolescents then completed self-report questionnaire measures assessing symptoms of depression every three months over two years of follow-up, yielding nine total assessment points with which to evaluate within-dyad bidirectional patterns of change. Patterns of within-dyad change were evaluated using a RI-CLPM approach. In contrast to traditional cross-lagged panels models, RI-CLPMs appropriately partition within- versus between- variance (Hamaker et al., 2015; Mund & Nestler, 2019), and permit analysis of the ways in which fluctuations from one dyad member’s mean depression levels concurrently relate to and prospectively predict within-person fluctuations in the other dyad member’s symptom levels over time. In addition, these RI-CLPM analyses provide information about within-person autoregressive stability of depressive symptoms and between-persons associations between parent-offspring trait-like symptom levels. Multiple group models were conducted to examine differences in patterns of prospective associations based on adolescent gender, as well as parental history of depressive disorder.

At the between-persons/dyad level, we expected parent and adolescent random intercepts (representing trait-like levels of depression) to be positively related. Prior meta-analytic findings suggest that during adolescence, parental depression is associated with youth depression with a mean effect size of approximately r=.21 (Goodman et al., 2011); thus, we expected to observe a small but significant positive effect. At the within-dyad level, we hypothesized that parent and child depressive symptoms would be positively associated both contemporaneously and over time, such that within-person fluctuations in parental depressive symptoms would concurrently relate to and prospectively predict same-direction within-person fluctuations in child depressive symptoms, and vice versa. We hypothesized that positive patterns of prospective relations would be stronger from parent depression to child depression than from child to parent, consistent with previous research (e.g., Kouros & Garber, 2010). Additionally, we hypothesized that prospective within-dyad effects in both directions would be stronger in dyads characterized by a parental history of depressive disorder, and that within-dyad prospective effects of parental depressive symptoms on youth depressive symptoms would be stronger among adolescent girls. We made no a priori hypotheses concerning the relative strength of prospective effects from adolescent symptoms to parent symptoms based on adolescent gender.

Methods

Participants and Procedures

Participants included middle school-aged youth recruited from communities in Montreal, Quebec, Canada and Chicago, Illinois. A total of 382 youth from 327 families were recruited using ads placed in local newspapers and community locations seeking interested families for a study of adolescent development. For the purposes of the present study, one child from each family was randomly selected for inclusion in dyadic analyses, yielding a sample size of 327 parent-adolescent dyads. Participating youth ranged in age from 11 to 15 years at baseline (M[SD]=12.58[1.09]; 59.9% girls). Participants predominantly identified as European American (69.9%), with smaller numbers identifying as African American/Black (13.0%), Asian (11.8%), or of other racial or ethnic identity (5.2%). The racial and ethnic composition of the samples at each site were roughly representative of the areas in which they were recruited (see Hankin & Abela, 2011). Participating parents were primarily women (91.7%; M_age[SD]=43.89[6.16]). With regard to educational attainment, 54.7% of participating parents reported having completed a bachelor’s degree or higher. More details concerning sampling and demographics are reported in Abela and Hankin (2011).

All study procedures were approved by the institutional review boards at McGill University and the University of Illinois - Chicago. Upon enrollment in the study, participating dyads were invited to the laboratory to complete a baseline assessment during which informed consent and informed assent were received from parents and adolescents, respectively. During this baseline assessment, parents were interviewed by trained clinical staff using the Structured Clinical Interview for DSM-IV (SCID; First et al., 2002) to assess parental history of depression, and parent and adolescent depressive symptoms were assessed via self-report on the Beck Depression Inventory (BDI-II; Beck et al., 1996) and Children’s Depression Inventory (CDI; Kovacs, 2003), respectively. Youth and their parents were subsequently assessed for depressive symptoms using the CDI and BDI-II every three months for a period of two years, yielding nine total assessment points per dyad. Baseline depression assessments were administered simultaneously to parents and adolescents during their initial and final in-person visit; to minimize participant burden, dyads completed follow up assessments from the comfort of their homes, and dyad members were asked to complete measures within a two-week period. The majority completed measures on the same day; the modal number of days difference between caregiver and child assessment was 1, and the mean for difference in days was 2.12 (SD=2.44). The average number of follow-up assessments completed by participating dyads was 6.74 (SD=1.61). Number of follow-up assessments completed was not related to youth age, gender, or level of depressive symptoms (rs<|.03|, ps>.05).

Measures

Demographics.

Basic demographic information including parent and child age and gender identity, as well as parental educational attainment, was assessed via parent self-report upon enrollment in the study. Gender identity was coded using a dichotomous variable reflecting participant identification as a boy/man (0) or girl/woman (1).

SCID (First et al., 2002).

Parental history of depression prior to enrollment in the study was assessed at baseline using the SCID (First et al., 2002). All interviewers were trained and supervised by Ph.D. level, licensed clinical psychologists in administering the K-SADS and assigning clinical diagnoses according to criteria described in the Diagnostic and Statistical Manual of Mental Disorders – Fourth Edition (DSM-IV; American Psychiatric Association, 1994). Details concerning interviewer training and supervision procedures are described elsewhere (see Abela & Hankin, 2011). For the purposes of the present analyses, history of caregiver depression comprised a dichotomous score indicating presence of caregiver lifetime MDD definite, MDD Probable, or mDD definite following criteria described in the DSM-IV (American Psychiatric Association, 2000). Diagnoses were collapsed into a single variable given evidence that depression is distributed dimensionally at the latent level (Hankin et al., 2005; Slade & Andrews, 2005) and that all diagnoses included in the present study (MDD definite, MDD probable, and mDD definite) are associated with significant distress and impairment (Cuijpers, 2004; Kessler et al., 1997). In total, n=83 (25.4%) parents reported a history of depressive disorder occurring prior to enrollment in the study.

CDI (Kovacs, 2003).

Youth depressive symptoms were measured at each assessment point via self-report on the CDI (Kovacs, 2003). The CDI comprises 27-items assessing youths’ experience of a range of psychological, social, and somatic symptoms associated with depression. Each item is scored on a 3-point Likert scale from 0 to 2, with total scores ranging from 0 to 54, with higher scores indicated higher levels of depressive symptoms. The CDI demonstrates good psychometric properties (Klein et al., 2005). Coefficient alpha ranged from .87 to .91 across administrations in the present study, indicating strong internal consistency.

BDI-II (Beck et al., 1996).

Parental depressive symptoms were similarly measured at each assessment point via self-report on the BDI-II (Beck et al., 1996). The BDI-II comprises 21 items assessing parents’ experience of a range of psychological, social, and somatic symptoms associated with depression. Items are scored on a 4-point Likert scale, with total scores ranging from 0 to 63, with higher scores indicating higher levels of depression. The BDI-II demonstrates strong psychometric properties, including reliability and validity, in diverse samples of adults (Beck et al., 1996). Coefficient alpha ranged from .89 to .95 across assessment points, indicating good internal consistency.

Data Analytic Plan

Analyses were conducted using structural equation modeling (SEM) implemented in the ‘lavaan’ library in R (Rosseel, 2012; R Core Team, 2018) using the maximum likelihood robust (MLR) estimator due to nonnormality of manifest variables, and full-information maximum likelihood (FIML) estimation to account for missing data. Goodness of fit was assessed using convergence across multiple fit indices, including Root Mean Square Error of Approximation (RMSEA), Standardized Root Mean Square Residual (SRMR), and Comparative Fit Index (CFI), consistent with recommendations proposed by Hu and Bentler (1999). Specifically, good fit was indicated by RMSEA≤.06, SRMR≤.08, and CFI≥.95 (Hu & Bentler, 1999). Acceptable fit was indicated by RMSEA≤.08 and CFI≥.90. We prioritized convergence across indices over reliance on any one particular measure of fit (Chen et al., 2008; Kenny, 2015; Marsh et al., 2004). Study hypotheses and data analytic plan were preregistered using the Open Science Framework (OSF) prior to data analysis (osf.io/t6dhf/).

We modeled prospective, reciprocal patterns of association between parent and adolescent depressive symptoms using a RI-CLPM approach (Hamaker et al., 2015; Mund & Nestler, 2019; see Figure 1). To appropriately partition within- versus between-person/dyad variance, the variances of observed variables were constrained to zero such that all variance will be captured by the within- and between-person/dyad latent factors. To account for between-person/dyad variance in constructs of interest, we created latent factors (i.e., random intercepts) corresponding to trait-like aspects of parent and adolescent depression. Observed variables at all nine time points were loaded onto their respective random intercept factor, with factor loadings constrained to one. These latent factors were permitted to covary to account for associations in trait-like levels of depression between parent and offspring. To model within-person/dyad change, each of the observed scores at each time point was loaded onto its own latent factor, resulting in a total of nine latent factors. These nine latent factors were used to model within-person autoregressive stability of depression, as well as cross-lagged paths representing bidirectional, within-dyad effects parent and adolescent depression across time. As we did not hypothesize differences in the magnitude of autoregressive or cross-lagged paths between any two given assessment points, all autoregressive paths at the within-person/dyad level were constrained to be equal to one another, and all cross-lagged paths from parent to adolescent depression, as well cross-lagged paths from adolescent to parent depression were similarly constrained to be equal. Contemporaneous, within-timepoint covariances between latent factors corresponding to parent and adolescent depressive symptoms at the same time point were modeled to account for interdependence of parent and adolescent depression at the within-dyad level, and were also constrained to be equal.

Figure 1.

Random intercept cross-lagged panel model (RI-CLPM) examining reciprocal patterns of within-dyad associations of parent and adolescent depressive symptoms over time, as implemented in Study 1. The RI-CLPM implemented in Study 2 is conceptually identical to the model described in the above figure, with the addition of four additional time points of observed CDI and BDI data which were loaded onto their respective random intercept factors as well as individual latent factors used to model within-person/dyad patterns of change over time. CDI = child depressive symptoms assessed using the Children’s Depression Inventory; BDI = parental depressive symptoms assessed using the Beck Depression Inventory.

Sensitivity Analyses.

To account for potential effects of seasonality on parent and adolescent depressive symptoms (e.g., Harmatz et al., 2000; Nillni et al., 2009), additional sensitivity analyses were conducted in which all within-persons latent factors were regressed onto month of assessment. Additionally, site, parent and child age and gender identity, as well as parental level of education were included as between-persons covariates to account for potential effects of site and demographic characteristics in contributing to patterns of effects.

Multiple Group Analyses.

To evaluate whether patterns of effects varied according to child gender or parent history of depressive episode, multiple group models were conducted. One set of analysis examined whether the model fit equally well across parent diagnostic history groups (i.e., no parental history of depression versus parental history of at least one lifetime depressive episode). Separate multiple group analyses were also conducted to examine whether the model fit equally well across adolescent genders. Each multiple group analysis proceeded according to the following steps. First, we specified a model in which all within-dyad, prospective cross-lagged paths were constrained to be equal across groups (e.g., parents with and without a history of depressive episode, boys and girls). Next, we specified a model in which all cross-lagged paths were allowed to vary between groups. We then compared the fully constrained model to the relatively unconstrained model using chi-squared difference tests, as well as on multiple fit indices, including change in RMSEA and CFI. Models were determined to be invariant if the chi-square difference test was not significant and/or comparison across multiple fit indices indicated equivalent fit, including change in AIC and BIC, with lower numbers indicating better fit. ΔRMSEA≤.015, ΔCFI≤.01, and ΔAIC/BIC≤10 were applied as criterion indicating relative equivalence in model fit (Chen, 2007; Cheung & Rensvold, 2002).

Results

Preliminary Analyses

Means and standard deviations for all assessments of parent and adolescent depression are reported in Table 1. Gender differences in adolescent depressive symptoms were inconsistently observed, with differences generally demonstrating higher levels of depression among girls. Parental symptom scores did not vary according to adolescent gender at any assessment point. Across assessment points, an average of 12.19% of youth and 12.19% of parents reported depressive symptoms scores in the clinically significant range according to cutoff values of CDI ≥ 16 (Timbremont et al., 2004) and BDI ≥ 14 (Beck et al., 1996), respectively.¹ At the time of study enrollment, 3.7% of youth were currently receiving psychotherapy or antidepressant treatment according to parent-report; 15.9% of parents reported having received psychotherapy at some time in their life.

Table 1.

Study 1: Means and Standard Deviations of Primary Variables of Interest

	Overall M(SD)	Boys M(SD)	Girls M(SD)	t(df)	Cohen’s d	p
CDI BSL	8.81 (6.58)	8.15 (5.71)	9.33 (7.06)	−1.57 (316)	.18	.118
CDI 3mo	7.37 (6.36)	7.37 (6.65)	7.40 (6.15)	−.05 (305)	.01	.962
CDI 6mo	7.60 (7.23)	7.72 (7.68)	7.64 (6.92)	.09 (299)	.01	.926
CDI 9mo	7.80 (7.23)	7.75 (7.08)	7.96 (7.35)	−.24 (276)	.03	.813
CDI 12mo	7.75 (6.76)	6.69 (5.56)	8.49 (7.36)	−2.23 (250.28)	.27	.027
CDI 15mo	7.26 (6.30)	6.61 (6.06)	7.63 (6.42)	−1.28 (258)	.16	.202
CDI 18mo	6.80 (6.31)	6.47 (6.85)	6.95 (5.94)	−.59 (254)	.07	.558
CDI 21mo	7.25 (7.55)	6.77 (8.07)	7.64 (7.21)	−.89 (254)	.11	.373
CDI 24mo	7.06 (6.45)	5.89 (5.39)	7.80 (6.98)	−2.53 (259.46)	.31	.012
BDI BSL	6.86 (7.41)	6.52 (6.69)	7.13 (7.88)	−.72 (319)	.08	.475
BDI 3mo	6.70 (6.99)	6.95 (7.21)	6.55 (6.90)	.47 (283)	.06	.642
BDI 6mo	6.74 (6.44)	7.05 (6.26)	6.61 (7.66)	.55 (268)	.07	.582
BDI 9mo	6.59 (7.02)	6.70 (7.66)	6.58 (6.60)	.13 (254)	.02	.894
BDI 12mo	6.16 (6.44)	6.27 (6.70)	6.15 (6.25)	.13 (226)	.02	.895
BDI 15mo	6.55 (6.84)	6.50 (6.62)	6.60 (7.01)	−.15 (218)	.02	.881
BDI 18mo	5.76 (5.55)	6.08 (5.63)	5.56 (5.51)	.65 (205)	.10	.516
BDI 21mo	6.69 (7.11)	7.08 (7.65)	6.43 (6.76)	.61 (182)	.09	.546
BDI 24mo	6.94 (6.73)	6.68 (6.46)	7.11 (6.93)	−.42 (180)	.06	.677

Note. Boys coded as 0 and girls coded as 1. Gender data was not available for three participants. CDI = child depressive symptoms assessed using the Children’s Depression Inventory; BDI = parental depressive symptoms assessed using the Beck Depression Inventory; BSL = baseline assessment.

Intraclass correlations (ICC) quantifying between- versus within- sources of variance in parent and adolescent depressive symptoms indicated that 49.2% of the variance in child depression (ICC=.51) and 34.4% of the variance in parental depression (ICC=.66) could be attributed to within-person differences. Bivariate correlations between parent and adolescent depressive symptoms at any given time point ranged in magnitude from r=.04 to r=.19 and were not consistently different from zero. A full correlation matrix describing bivariate correlations between all parent and child depressive symptom scores is available on OSF (osf.io/t6dhf/). Parental history of depression significantly predicted youth odds of having experienced a depressive episode at baseline (OR=3.65, p=.001), as assessed by trained interviews using the Schedule for Affective Disorders and Schizophrenia for School Age Children Present and Lifetime version (K-SADS-PL; Kaufman et al., 1996).

RI-CLPM

A RI-CLPM examining within-person/dyad patterns of change in parent and adolescent depressive symptoms demonstrated adequate fit to the data across most fit indices (χ²(145)=304.80, CFI=.93, RMSEA=.06, SRMR=.11). Random intercept factors capturing between-person/dyad variance in parent and adolescent depression were positively correlated (β=.14, b(SE)=3.56(1.68), p=.034), such that individual differences in parent trait-like depression were associated with individual differences in offspring trait-like depression. Results of within-person/dyad analyses are reported in Table 2. Both parent and adolescent depression demonstrated autoregressive stability over time (b=.24, p<.001 and b=.29, p<.001, respectively), such that deviations from an individual’s expected depression score at time t predicted same direction deviations in that individual’s depression at time t+1. Within time-point covariance estimates indicated that within-person fluctuations in parent depression were positively related to contemporaneous within-person fluctuations in offspring depression (b=1.06, p=.055). In contrast, no within-dyad cross-lagged associations were observed; fluctuations in parental depression at time t did not predict fluctuations in adolescent depression at time t+1 (b=.03, p=.432), or vice versa (b=.03, p=.449).

Table 2.

Study 1: Random intercept cross-lagged panel model results describing patterns of within-persondyad change

	b(SE)	[95% CI]	p
Autoregressive paths
CDI(t) → CDI(t+1)	.29 (.05)	[.20, .38]	<.001
BDI(t) → BDI(t+1)	.24 (.05)	[.13, .34]	<.001
Cross-lagged paths
CDI(t) → BDI(t+1)	.03 (.03)	[−.04, .09]	.449
BDI(t) → CDI(t+1)	.03 (.03)	[−.04, .09]	.432
Within-time point covariances
CDI(t) with BDI(t)	1.06 (.56)	[−.03, 2.15]	.055

Note. Paths represent the prospective association between parent/child depressive symptoms at any time t with parent/child depressive symptoms at time t + 1 across all 9 time points. CDI = depressive symptoms assessed using the Children’s Depression Inventory; BDI = parental depressive symptoms assessed using the Beck Depression Inventory; b = unstandardized coefficients.

Multiple Group Models.

Complete model fit statistics for all multiple group models, including fully constrained and relatively unconstrained model fit statistics, are reported in Supplemental Table S2. With regard to group differences based on parental history of depression, a fully constrained model in which cross-lagged associations were constrained to be equal across parental diagnostic groups demonstrated adequate fit that was not worse than a model in which cross-lagged associations were free to vary across groups (Δχ²=.44, Δdf=2, p=.80, ΔCFI=.001, ΔRMSEA=.001), indicating that prospective within-dyad associations between parent and adolescent depression did not differ based on parental history of depression. With regard to group differences based on adolescent gender, the fully constrained and relatively unconstrained models did not significantly differ from one another in terms of model fit (Δχ²=.08, Δdf=2, p=.96, ΔCFI=.001, ΔRMSEA<001). Thus, results suggest that within-dyad patterns of cross-lagged associations did not differ based on adolescent gender.²

Sensitivity Analysis.

Patterns of results held after accounting for effects of month of assessment, recruitment site, parental educational attainment, and parent and child gender identity and age at baseline (see Supplemental Table S4).

Comparison with CLPM.

In response to interested reviewers, we additionally fit a traditional CLPM to study data with constraints applied in an analogous fashion to those described with regard to the RI-CLPM but without the addition of random intercept factors accounting for between-persons/dyad trait-like variance. The result of this analysis demonstrated poor fit to the data (CFI=.82, RMSEA=.09, SRMR=.17), and model fit was significantly worse than for the RI-CLPM (Δχ²=84.53, Δdf=3, p<001, ΔCFI=.11, ΔRMSEA=.03). Model parameters are reported in Supplemental Table S5. Cross-lagged paths were not significantly different from zero, although poor fit statistics indicate that caution is needed in interpretation, as estimates may not be reliable.

Study 1 Discussion

Using an RI-CLPM approach to appropriately partition between- versus within- sources of variance, results of Study 1 suggest that associations between parent and adolescent depressive symptoms are driven by between-dyad individual differences, rather than prospective within-dyad reciprocal change processes. Consistent with a wealth of previous research (see Goodman, 2020; Gotlib et al., 2020), results support concordance in trait-like depression levels between parents and offspring such that elevated levels of trait parental depression were associated with elevated levels of offspring depression. Additionally, a small, positive contemporaneous association between parent and offspring depression was observed at the within-dyad level. However, contrary to hypotheses, dynamic fluctuations in parental depression did not prospectively predict future fluctuations in adolescent depression, nor vice versa. Moreover, patterns of results held across adolescent gender groups and across dyads with and without a parental history of depression. Overall, findings suggest that among parents and their adolescent youth, longitudinal coupling of depression occurs via largely stable individual difference mechanisms, as well as contemporaneous processes of co-fluctuation, rather than prospective reciprocal change processes manifesting at the within-dyad level, per se. That is, results are suggestive of some level of depressive contagion or social learning of depression manifesting on a micro-level, contemporaneous timescale; however, these contagion or social learning processes do not appear to explain within-dyad patterns of reciprocal change over time.

After accounting for divergent sources of variance in parent and adolescent depressive symptoms, expected between- and within-person associations were noted to emerge, although hypothesized longitudinal within-dyad patterns of relations were not observed. Specifically, results supporting within-person stability and between-person covariance between parent and adolescent depressive symptoms align with what is known about depression; namely, that depression is highly stable, even at subthreshold levels, in both adolescents and adults (e.g., Merikangas et al., 2003; Tram & Cole, 2006), and tends to cluster in parent-child dyads (Goodman, 2020; Hammen, 1991). That within-dyad cross-lagged associations were not observed, although inconsistent with some previous research (e.g., Ge et al., 1995; Hughes & Gullone, 2010, but see Ciciolla et al., 2014; Mennen et al., 2018) may be reflective of the analytic strategy we used to accurately separate between- from within-dyad effects in the present work relative to existing studies. Indeed, most previous studies supporting reciprocal relations between parent and adolescent symptoms relied upon traditional CLPMs, with potentially misleading results (Hamaker et al., 2015). As demonstrated by a number of recent studies, the application of statistically advanced models, such as RI-CLPMs, may clarify patterns of prospective, within-person/dyad patterns of relations, particularly in literatures littered with mixed findings and competing theoretical models (e.g., Barzeva et al., 2019; Keijsers, 2016; Long et al., 2019; Masselink et al., 2018).

Given that some of the main study findings were unexpected a priori, particularly the non-significance of longitudinal within-dyad cross-lagged influences, conclusions of Study 1 must be considered tentative. We sought to replicate these patterns in order to confidently interpret results and make more definitive conclusions. Accordingly, similar data (sample, method, design, analyses) from Study 2 were analyzed to replicate and extend results from Study 1 in an independent sample of parent-adolescent dyads.

Study 2

Study 2 aimed to evaluate within-dyad patterns of reciprocal associations between parent and child depressive symptoms using an RI-CLPM approach in an independent, moderately sized sample of adolescent youth and their parents assessed via self-report measures of depression every three months for a period of three years (13 total assessment points). Youth included in Study 2 included both middle school- and high school- aged youth, extending the scope of the present inquiry to include older adolescents. Given findings observed in Study 1, we hypothesized that random intercepts representing trait-like variance in parent and adolescent depression would be positively correlated, and that within-persons’ parent and adolescent depressive symptoms would demonstrate autoregressive stability over time. Moreover, we expected to observe positive contemporaneous associations between parent and offspring deviations in depression at the within-persons/dyad level. In contrast, we hypothesized that no prospective within-dyad cross-lagged associations would be found; we did not expect within-person fluctuations in a parent’s level of depression to predict within-person fluctuations in their adolescent’s level of depression, or vice versa, over time. Consistent with our previous analyses, we examined whether patterns of cross-lagged effects differed across adolescent genders or according to parental history of depression. Informed by our previous findings, we expected patterns of results to replicate across genders and parental diagnostic groups. That is, we expected no differences in patterns of cross-lagged associations across these groups.

Methods

Participants and Procedures

Participants in Study 2 included 435 parent-adolescent dyads recruited from the greater Denver and central New Jersey areas in association with the Genes, Environment, and Mood study (Hankin et al., 2015). Participants included in the present analyses represent a subset of 6^th and 9^th grade youth recruited as part of this larger study in order to more directly replicate analyses conducted in Study 1. In instances in which parents participated with more than one child, one sibling was randomly chosen to be included in the present analyses, as in the previous study. Participating youth ranged in age from 10 to 16 at baseline (M=13.41, SD=1.55; 57% girls). Racial demographics were approximately representative of the broader United States population at the time of sampling, although individuals identifying as Latinx were relatively underrepresented (66.7% European American, 12.2% African American/Black, 9.7% Asian/Pacific Islander, .5% American Indian/Alaskan Native, 11% Multiracial or identifying with another racial group with 11% of participants reported a Latinx ethnic identity). Participating parents were primarily women (92.5%; M_age[SD]=45.08[6.56]; 85.1% biological mothers). With regard to educational attainment, 58.6% of participating parents reported having completed a bachelor’s degree or higher. Median family income was approximately $90,000 according to parent-report.

All procedures were approved by the institutional review boards at the University of Denver and Rutgers University. Upon enrolling in the study, participants completed a baseline laboratory visit during which parents provided informed consent, and youth provided informed assent to participation in the study. Parent and adolescent depressive symptoms were subsequently assessed every 3 months for a period of 3 years via self-report on the BDI-II (Beck et al., 1996) and CDI (Kovacs, 2003), respectively, yielding a total of 13 possible assessments. Similar to Study 1, parent and adolescent baseline, 18- and 36-month depression assessments were completed at the same time as one another; follow-up assessments were completed from home and requested to be returned within a specified two-week period. The majority completed measures on the same day; the modal number of days difference between caregiver and child completion of measures was 1, and the mean for the difference in days was 3.35 (SD = 5.2). The mean number of assessments completed was 10.61 (SD=3.51). Number of assessments completed was negatively correlated with age (r=−.11, p=.03) and adolescent depressive symptoms at baseline (r=−.19, p<.001). Number of assessments completed was not related to adolescent gender (r=.06, p=.23). Parents completed a diagnostic interview measure (i.e., the SCID; First et al., 2002) to evaluate lifetime history of depressive disorder.

Measures

Demographics.

Relevant demographic information was obtained using parent-self report on a brief demographic information questionnaire, similar to that described in Study 1. As in Study 1, gender identity was representing using a dichotomous variable reflection boy/man (0) or girl/woman (1) gender identity.

SCID (First et al., 2002).

Parental history of depression prior to enrollment in the study was assessed using the SCID (First et al., 2002). Full details concerning interviewing training and supervision are reported elsewhere (see Hankin et al., 2015). As in Study 1, history of caregiver depression was representing using a dichotomous score indicating presence of caregiver lifetime MDD definite, MDD Probable, or mDD definite following criteria described in the DSM-IV (American Psychiatric Association, 2000). In total, n=121 (27.8%) parents reported an onset of depression occurring prior to enrollment in the study.

CDI (Kovacs, 2003).

Youth depressive symptoms were measured at each assessment point via self-report on the CDI (Kovacs, 2003). Internal consistency ranged from α = .79 to .90 across assessment points, indicating good reliability.

BDI-II (Beck et al., 1996).

Parental depressive symptoms were similarly measured at each assessment point via self-report on BDI-II (Beck et al., 1996). Cronbach’s alpha ranged from α = .89 to .94 across assessment points, indicating strong internal reliability.

Data Analytic Plan

As in Study 1, analyses were implemented in the ‘lavaan’ library in R (Rosseel, 2012; R Core Team, 2018) using the MLR estimator and FIML estimation to account for missing data. Study hypotheses and data analytic plan for this replication effort were preregistered prior to data analysis (osf.io/swbc2/).

Hypotheses were tested using an RI-CLPM approach, as described above. Model specification proceeded according to the same steps outlined in Study 1, with the addition of four additional assessment points with which to estimate reciprocal change. Multiple group models were conducted to examine group differences in cross-lagged effects according to parental history of depression and adolescent gender, as described in Study 1, and sensitivity analyses were conducted to evaluate robustness of effects covarying for month of assessment, site, and relevant demographic characteristics, as described above.

Results

Preliminary Analyses

Means and standard deviations for all assessments of parent and adolescent depression are reported in Table 3. When gender differences in adolescent depressive symptoms were observed, girls were found to report higher symptom levels than boys, consistent with prior research. As in Study 1, parental symptom scores did not vary according to adolescent gender at any assessment point. Across assessment points, an average of 4.84% of youth and 12.61% of parents reported depressive symptoms scores in the clinically significant range according to cutoff values of CDI ≥ 16 (Timbremont et al., 2004) and BDI ≥ 14 (Beck et al., 1996), respectively.³ Among adolescent participants, 21.6% of youth reported having received some form of treatment over the course of the study. Among parents, information regarding psychological treatment history was collected only among individuals reporting high levels of symptoms on the SCID (n=164); of these parents, 67.1% reported having received psychopharmacological, psychotherapeutic, and/or inpatient treatment at some time during their life.

Table 3.

Study 2: Means and Standard Deviations of Primary Variables of Interest

	Overall M(SD)	Boys M(SD)	Girls M(SD)	t(df)	Cohen’s d	p
CDI BSL	7.42 (5.99)	7.13 (5.98)	7.63 (5.99)	−.93 (429)	.09	.355
CDI 3mo	5.64 (5.42)	5.45 (5.42)	5.77 (5.42)	−.58 (391)	.06	.563
CDI 6mo	4.68 (4.63)	4.39 (4.20)	4.89 (4.92)	−1.04 (378)	.11	.300
CDI 9mo	5.10 (5.19)	4.95 (4.84)	5.21 (5.45)	−.484 (372)	.05	.629
CDI 12mo	4.21 (4.52)	3.77 (4.24)	4.53 (4.70)	−1.65 (358.17)	.17	.099
CDI 15mo	4.32 (4.59)	4.22 (4.58)	4.38 (4.61)	−.34 (364)	.03	.737
CDI 18mo	6.23 (6.32)	5.72 (6.17)	6.59 (6.41)	−1.29 (358)	.14	.198
CDI 21mo	4.44 (4.57)	3.76 (3.93)	4.89 (4.91)	−2.27 (305.03)	.25	.024
CDI 24mo	3.56 (3.76)	3.13 (3.30)	3.89 (4.05)	−1.81 (323)	.21	.072
CDI 27mo	4.57 (4.80)	4.03 (4.41)	4.96 (5.04)	−1.79 (324)	.20	.074
CDI 30mo	3.85 (4.08)	3.40 (3.67)	4.18 (4.33)	−1.70 (324)	.19	.089
CDI 33mo	4.62 (5.24)	3.51 (3.58)	5.38 (6.01)	−3.36 (292.45)	.38	.001
CDI 36mo	5.97 (6.00)	4.88 (4.94)	6.73 (6.55)	−2.95 (331.72)	.32	.003
BDI BSL	5.09 (6.17)	5.17 (6.51)	5.03 (5.92)	.22 (428)	.02	.825
BDI 3mo	6.46 (7.66)	6.50 (7.25)	6.43 (7.97)	.09 (398)	.01	.925
BDI 6mo	4.88 (6.39)	5.05 (7.15)	4.75 (5.80)	.45 (375)	.05	.657
BDI 9mo	5.98 (7.60)	6.04 (7.88)	5.93 (7.40)	.14 (380)	.01	.888
BDI 12mo	5.06 (6.94)	5.21 (6.82)	4.95 (7.04)	.37 (369)	.04	.713
BDI 15mo	5.93 (7.56)	5.50 (7.42)	6.22 (7.66)	−.92 (377)	.10	.359
BDI 18mo	5.45 (7.22)	5.37 (6.62)	5.51 (7.63)	−.19 (359)	.02	.852
BDI 21mo	5.84 (7.56)	6.00 (7.55)	5.74 (7.58)	.31 (319)	.03	.761
BDI 24mo	5.10 (6.76)	5.38 (7.00)	4.89 (6.58)	.65 (323)	.07	.518
BDI 27mo	5.63 (7.12)	5.98 (7.60)	5.37 (6.76)	.80 (347)	.09	.427
BDI 30mo	4.88 (6.35)	4.75 (6.72)	4.97 (6.08)	−.30 (324)	.03	.763
BDI 33mo	5.42 (7.31)	5.52 (7.30)	5.36 (7.34)	.19 (299)	.02	.852
BDI 36mo	5.00 (7.34)	5.03 (7.60)	4.97 (7.16)	.08 (329)	.01	.935

Note. Boys coded as 0 and girls coded as 1. CDI = child depressive symptoms assessed using the Children’s Depression Inventory; BDI = parental depressive symptoms assessed using the Beck Depression Inventory; BSL = baseline assessment.

Intraclass correlations (ICC) indicated that 46.5% of the variance in child depression (ICC=.54) and 41.9% of the variance in parental depression (ICC=.58) could be attributed to within-person differences. Bivariate correlations between parent and adolescent depressive symptoms at any given time point ranged in magnitude from r=.12 to r=.27. A full correlation matrix describing bivariate correlations between all parent and adolescent depressive symptom scores is available on OSF (osf.io/swbc2/). Parental lifetime history of depression significantly predicted youth odds of having experienced a depressive episode at baseline, as assessed using the KSADS-PL (OR=3.99, p=.028).

Given that youth were recruited in distinct grade cohorts, multiple group models were conducted to evaluate potential grade differences in patterns of effects. Results indicated that a model in which cross-lagged paths were constrained to be equal across grade cohorts fit equivalently well relative to a model in which cross-lagged paths were permitted to vary (Δχ²(2)=.26, p=.880, ΔCFI=.001, ΔRMSEA<.001), indicating invariance across grades. Thus, data from both grade cohorts were combined in all analyses to maximize statistical power.

RI-CLPM

A RI-CLPM examining within-person/dyad patterns of change in parent and adolescent depressive symptoms demonstrated adequate fit to the data across most fit indices (χ²(317)=597.86, CFI=.93, RMSEA=.05, SRMR=.09). Random intercept factors capturing between-person variance in parent and adolescent depression were positively correlated (β=.27, b(SE)=5.15(1.25), p<.001), such that individual differences in parent trait-like depression were associated with individual differences in offspring trait-like depression. Results of within-person/dyad analyses are reported in Table 4. Both parent and adolescent depression demonstrated autoregressive stability over time (b=.17, p<.001 and b=.23, p<.001, respectively), such that deviations from an individual’s expected depression score at time t predicted same direction deviations in that individual’s depression at time t+1. Within time-point covariance estimates indicated that within-person fluctuations in parental depression were positively related to contemporaneous within-person fluctuations in offspring depression (b=1.57, p<.001). In contrast, no prospective within-dyad cross-lagged associations were observed; fluctuations in parental depression at time t did not predict fluctuations in adolescent depression at time t+1 (b=−.04, p=.138), or vice versa (b=.01, p=.557).

Table 4.

Study 2: Random intercept cross-lagged panel model results describing patterns of within-person/dyad change

	b (SE)	[95% CI]	p
Autoregressive paths
CDI(t) → CDI(t+1)	.23 (.03)	[.17, .28]	<.001
BDI(t) → BDI(t+1)	.17 (.03)	[.11, .23]	<.001
Cross-lagged paths
CDI(t) → BDI(t+1)	.01 (.02)	[−.02, .04]	.564
BDI(t) → CDI(t+1)	−.04 (.03)	[−.10, .01]	.138
Within-time point covariances
CDI(t) with BDI(t)	1.57 (.33)	[.92,.2.21]	<.001

Note. Paths represent the prospective association between parent/child depressive symptoms at any time t with parent/child depressive symptoms at time t + 1 across all 9 time points. CDI = depressive symptoms assessed using the Children’s Depression Inventory; BDI = parental depressive symptoms assessed using the Beck Depression Inventory; b = unstandardized coefficients.

Multiple Group Models.

Complete model fit statistics for multiple group models, including fully constrained and relatively unconstrained model fit statistics, are reported in Supplemental Table S7. With regard to group differences based on parental history of depression, a fully constrained model in which cross-lagged associations were constrained to be equal across parental diagnostic groups fit no worse than a model in which cross-lagged associations were free to vary across groups (Δχ²=4.91, Δdf=2, p=.09, ΔCFI=.001, ΔRMSEA<001), indicating that prospective within-dyad associations between parent and adolescent depression did not differ based on parental history of depression. With regard to group differences based on adolescent gender, a chi-square difference test indicated that the relatively unconstrained model fit the data slightly better than the fully constrained model (Δχ²=6.26, Δdf=2, p=.04); however, models were equivalent according to ΔCFI=.001, ΔRMSEA<.001. Differences in AIC and BIC values similarly demonstrated equivalent fit across models (ΔAIC=4.36, ΔBIC=2.55). Thus, results suggest that within-dyad patterns of cross-lagged associations did not differ based on adolescent gender.⁴

Sensitivity Analysis.

As in Study 1, patterns of results held after accounting for effects of month of assessment, recruitment site, parental educational attainment, and parent and child gender identity and age at baseline (see Supplemental Table S9).

Comparison with CLPM.

As in Study 1, a traditional CLPM was also fit to the data. Model fit for this CLPM was poor (CFI=.71, RMSEA=.09, SRMR=.25), and significantly worse than that of the RI-CLPM (Δχ²=430.29, Δdf=3, p<.001, ΔCFI=.22, ΔRMSEA=.04). Model parameter estimates are provided in Supplemental Table S10. Cross-lagged paths from parent to child depression (b=.03, p=.002) and from child to parent depression (b=.04, p=.046) were significant, although caution is needed in interpretation given poor model fit.

Study 2 Discussion

Results of Study 2 replicated and extended findings from Study 1 in an independent sample of parent-adolescent dyads. As hypothesized, random intercepts representing parent and offspring between-persons, trait-like levels of depression were positively related, with an effect size consistent with effects observed in Study 1, as well as in previous meta-analytic findings (Goodman et al., 2011). Positive within-person autoregressive stability paths were also observed for both parents and adolescents, with effect sizes similar to those observed in Study 1. Moreover, positive contemporaneous within-person/dyad associations between parent-offspring depression indicate that within-timepoint, parent and adolescent levels of depression co-fluctuate with one another, such that deviations from a parent’s expected level of depression at a given time point are associated with same-direction deviations in their adolescent child’s expected level of depression at that timepoint, as suggested in Study 1. Consistent with hypotheses, no prospective cross-lagged associations were observed; within-dyad, fluctuations in parental depression did not predict future fluctuations in their offspring’s depression. Patterns of effects held across girls and boys, as well as dyads with and without a parental history of depression.

General Discussion

Interest in understanding mechanisms contributing to risk for depression among children of depressed parents has inspired a robust literature, as well as a number of plausible hypotheses concerning the pathways by which risk is conferred (Goodman, 2020; Goodman & Gotlib, 1999; Gotlib et al., 2020). The present series of studies aimed to evaluate the hypothesis that within-person fluctuations in parent and adolescent depressive symptoms demonstrate prospective patterns of reciprocal relations at the within-dyad level. Results of Study 1 and Study 2 converge to suggest that between-person/dyad individual differences and contemporaneous within-dyad effects at the same time point, and not prospective cross-lagged within-dyad change processes, characterize the longitudinal coupling of depressive symptoms among parents and adolescent youth across months-long timescales. Using an RI-CLPM approach that is appropriately suited to accurately disentangle between- versus within- sources of variance in prospective relations between parent and adolescent depressive symptoms, findings across these two independent samples yielded remarkably similar results. Parent and adolescent symptoms covary at the between-dyad level, such that parents high in depressive symptoms relative to other parents are likely to have adolescents who exhibit high levels of depressive symptoms relative to other adolescents. Within-person fluctuations in parent and adolescent depression also covary contemporaneously such that idiographic deviations in a parent’s depression (i.e., fluctuations around their own individual average) are related to same direction deviations in their offspring’s depression at a given point in time. However, within-person fluctuations in parental depression do not prospectively predict associated within-person fluctuations in adolescent depression, or vice versa, over time. In both samples, results held across boys and girls, as well as across dyads with and without a parental history of depression.

Across both studies, expected patterns of between- and within-person autoregressive associations were supported by RI-CLPM results. Specifically, positive correlations between parent- and adolescent- random intercept factors align with a wealth of literature demonstrating familial clustering of depressive symptoms (Cicchetti, 1993; Cicchetti & Rogosch, 2002) and suggests that trait-like levels of depression covary among parents and their adolescent offspring. Moreover, effect sizes describing these associations in the present work are largely consistent with those indicated by meta-analytic findings, which demonstrate modest but significant associations between parental depression and child internalizing symptoms, with a mean effect size of approximately r=.21 (Goodman et al., 2011), providing additional confidence in results. Further, observed within-person autoregressive stability of dyad members’ depressive symptoms aligns with research suggesting that symptoms of depression are highly stable across both adolescence and adulthood (e.g., Merikangas et al., 2003; Tram & Cole, 2006). Thus, findings reflect expected, reliable trends observed across the broader literature.

Leveraging advances in statistical modeling, the present work advances knowledge of longitudinal coupling of parent-adolescent depressive symptoms by demonstrating that, after accounting for between-dyad sources of variance, parent and adolescent depression demonstrate contemporaneous co-fluctuations, but do not demonstrate within-person/dyad reciprocity over time. That is, at any given assessment point, incremental changes in a parent’s depression relative to their own idiographic mean were related to same-direction within-person fluctuations in their adolescent’s depression, consistent with tenets of social learning and depressive contagion theories (Bandura, 1977; Coyne, 1976; Hames et al., 2013; Hatfield et al., 1993). Across three months, however, fluctuations in parental depression relative to parents’ own idiographic means do not predict within-person fluctuations in adolescents’ depression, nor vice versa, suggesting that social learning and contagion processes may be operant across temporally-brief (e.g., hours, days) timescales, but effects of social learning or depressive contagion processes may attenuate over the course of several months. This pattern of findings aligns with previous research by Gjerde et al. (2017) demonstrating contemporaneous but not prospective associations between parental depression and offspring internalizing symptoms among a large sample of preschool aged youth. Null findings with respect to prospective cross-lagged, within-person/dyad effects suggest that varying mechanisms of risk may be differentially salient across diverse developmental timescales, consistent with a developmental psychopathology framework emphasizing the role of developmentally-contextualized, multiple pathways in contributing to adolescent risk (Cicchetti, 1993; Cicchetti & Rogosch, 2002).

Indeed, differences between the present results and previous findings by Kouros and Garber (2010) may be attributed to issues of timescale. In a sample of parent-adolescent dyads assessed annually across a period of six years, Kouros and Garber (2010) applied a rigorous analytic strategy to demonstrate longitudinal coupling between parent and offspring depressive symptoms, such that within-person change in parental depression was associated with witinin- person change in adolescent depression across periods of one year. That such coupling was observed on the order of years in work by Kouros and Garber (2010), but not months in the present study, again highlights the salience of timescale in processes of depressive risk transmission and supports a multiple pathways perspective. Thus, the present work complements previous findings by further refining the timescale on which varying mechanisms of risk may unfold. On the scale of years, for example, the accumulation of life stress may contribute to co-occuring escalations in parent-offspring depression, given the role of stress as both a risk factor for and consequence of depressive symptoms among both adolescents (e.g., Cole et al., 2006; Jenness et al., 2019) and adults (see Hammen, 2005, 2006). It is also possible that the magnitude of change represented by within-person symptom fluctuations varies across divergent timescales. That is, relatively large fluctuations in parental depression, which unfold over the course of a year or more, may be needed to elicit prospective fluctuations in adolescents’ depression, and vice versa. Further clarifying which mechanisms are active when and across what timescales represents a key area for ongoing research.

Differences between present results and other previous research (e.g., Ge et al., 1995; Hughes & Gullone, 2010) may be attributed to differences in both timescale and analytic approach. Ge et al. (1995), for example, used a traditional CLPM approach to demonstrate reciprocal associations between parent and adolescent distress as assessed annually across a three-year period. Hughes and Gullone (2010) also tested hypotheses concerning bidirectional relations between parent and adolescent internalizing symptoms using traditional CLPM analyses, demonstrating reciprocity in dyad members’ symptoms across six months. Traditional CLPMs conflate within- and between- sources of variance, rendering them ill-equipped to rigorously evaluate within-dyad patterns of relations, and therefore clarify within-dyad mechanisms of depressive contagion (Hamaker et al., 2015). In the present work, CLPMs demonstrated poor fit to the data, and yielded patterns of estimates that diverged both from one another, as well as the better-fitting RI-CLPMs. In the case of Study 2, results of CLPM analyses may have contributed to type I error, yielding inaccurate conclusions regarding the prospective relations between parent and child depression. Comparisons across these models in the present work converge with results of simulation studies (e.g., Hamaker et al., 2015), to suggest that results of traditional CLPM analyses may be misleading in nature, and highlight the need to re-evaluate patterns of relations using appropriately rigorous statistical models.

Strengths and Limitations

The present work demonstrates a number of strengths that advance knowledge of within- and between-dyad patterns of association between parent and adolescent depression. Across both samples included in the present work, dyad members’ depressive symptoms were assessed every three months for a period of years, permitting rigorous analysis of autoregressive and cross- lagged associations as they unfold a period of several months. Moreover, hypotheses were tested using a sophistocated analytic strategy that was appropriately equipped to disambiguate within- from between- sources of variance, representing a methodological improvement upon previous work conducted within a traditional CLPM framework. Importantly, study aims were addressed and results were replicated across two independent samples of parent-adolescent dyads. This is particularly important given that primary results of Study 1 were unexpected a priori, and is consistent with efforts to promote replicability and open science practices in the field of clinical psychology (Tackett et al., 2017).

Findings must also be interpreted in the context of several limitations, which represent important directions for future research. The present study design permitted analyses of contemporaneous and well as cross-lagged associations between within-person fluctuations in parent-offspring depression as they occur across three month intervals; however, contemporaneous findings do not provide information regarding the directionality of effects. Research is needed to evaluate patterns of reciprocal within-person/dyad change processes in parent-offspring depression as they unfold across micro-level timescales (e.g., hours, days) to elucidate directions of effects and further clarify mechanisms of risk. Research is also needed to account for potential third variables that, while outside the scope of the present investigation, may have influenced observed patterns of effects, including parenting styles, adolescent externalizing symptoms, and other contextual factors (e.g., broader family functioning and dynamics). More broadly, it is possible that patterns of findings observed in the present work were influenced by unmeasured genetic factors, including both genetic similarities between parents and offspring and passive gene-environment correlations (e.g., Harold et al., 2011; Reiss et al., 1995; Silberg et al., 2010). Genetically informed designs are needed to appropriately disaggregate genetic versus environmental factors contributing to risk for depression among children of depressed parents.

Additional limitations relate to the generalizability of the present findings. Specifically, youth were sampled during a specific developmental stage; it is possible that younger children, for example, may be more sensitive to fluctuations in their parents’ depressive symptoms. Indeed, meta-analytic work has demonstrated stronger associations between parental symptoms and youth psychopathology among younger children relative to adolescent youth (Goodman et al., 2011), highlighting the need for research evaluating reciprocal associations between parent and child depression using appropriate statistical methods (e.g., RI-CLPM) among primary school-aged youth. No group differences were detected in patterns of effects based on parental history of depression; however, participating youth represent adolescents sampled from the general community with relatively low levels of self-reported depression. Research is needed to evaluate patterns of effects among youth with clinical levels of psychopathology. Moreover, although approximately representative of the racial and ethnic composition of the communities from which they were recruited, samples across both studies included predominantly white, non-Latinx parent-adolescent dyads, limiting generalizability of findings. Future research should aim to examine transactional, within-dyad change processes as they unfold in samples of more diverse racial, ethnic, and social identities. It is also important to note that equality constraints applied in the present study analyses, although providing parsimonious and reliable estimates of within-dyad effects, necessarily limit insight into the ways in which the strength of within-dyad associations may or may not change over time. Future studies with larger samples are needed to evaluate whether effect sizes meaningfully differ across successive measurement occasions to better describe longitudinal patternings in prospective within-dyad relations. Larger samples are also needed to replicate multiple group model results, given relatively limited numbers of parents with a history of depression included in the present work.It is likely that group comparisons in the present work were insufficiently powered to detect modest differences in effect size, and future work should include a priori power analyses to ensure sufficient power to detect group differences. Finally, only one parent was included in the present study, and participating parents in the present work were predominantly mothers; it is critical that future work includes both mothers and fathers, as previous work indicates that maternal and paternal depression may relate to youth depression in differing and interactive ways (Natsuaki et al., 2014).

Clinical Implications

Results of the present study indicate that prevention efforts aimed at reducing adolescent risk for psychopathology would be well-served to attend to between-dyad contextual factors, influencing both parent- and adolescent- depression risk. Additionally, interventions may wish to target parent-adolescent interactional processes unfolding on microsocial timescales, which may contribute to contemporaneous contagion of parent/adolescent depressive experience. Parental expression of negative, conflictual affective behavior during interactions with youth, for example, has been linked to contemporanous decreases in adolescents’ momentary experience of positive affect in daily life (Griffith et al., 2018), as well youths’ prospective risk for an onset of depression (Griffith et al., 2019; Schwartz et al., 2014). Similarly, recent research suggests that augmenting youth interpersonal functioning through a skills-based preventitive intervention program may have downstream effects of parental depressive symptoms (Spiro-Levitt et al., 2019).

Conclusions

The present work employed an RI-CLPM approach to evaluate prospective, within-dyad relations between parent and adolescent depression. Findings across two independent samples converged to suggest that associations between parent and adolescent depressive symptoms covary on a between-persons level, and demonstrate within-persons co-fluctuation on a contemporaneous timescale; however, within-person fluctuations in parental depression do not predict associated within-person fluctuations in adolescent depression over a period of several months. Overall, results highlight the salience of timescale to inquiries of depressive risk transmission, and support a multiple pathways perspective for understanding the etiology of depression among children of depressed parents.