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. Author manuscript; available in PMC: 2022 Dec 1.
Published in final edited form as: J Adolesc Health. 2021 Jun 3;69(6):1006–1012. doi: 10.1016/j.jadohealth.2021.05.005

Family Stress and Rural African American Adolescents’ Depressive Symptoms

Ava J Reck 1, Steven M Kogan 2
PMCID: PMC8612945  NIHMSID: NIHMS1711482  PMID: 34092476

Abstract

Purpose:

Limited longitudinal research investigates the effects of family stress on the development of depressive symptoms among African American adolescents. This study tests a developmental model of the family and intrapersonal processes linking family stress to depressive symptoms from ages 11 to 15. We hypothesized that family stress would predict increases in caregiver-youth conflict, which in turn would predict decreases in adolescents' self-control, a proximal predictor of increases in depressive symptoms.

Methods:

The sample consisted of 472 African American youth and their primary caregivers from eight rural counties in southern Georgia who provided data at four time points (youth ages 11 to 15). Hypotheses were tested with structural equation modeling.

Results:

Results were consistent with study hypotheses. Family stress significantly predicted depressive symptoms via intermediate effects on caregiver-youth conflict and adolescent self-control. The indirect influence of family stress via these intermediate processes was significant.

Conclusions:

Findings suggest that, when families experience stress, caregiver-youth conflict increases, which may lead to the development of poor self-control in youth, a proximal predictor of increases in depressive symptoms. Findings have implications for the development of prevention programs for rural African American adolescents.

Keywords: Family Stress, Adolescent Depression, African American, Rural, Self-control, Caregiver-youth Conflict

Depressive symptoms during adolescence are linked with a range of adverse outcomes, including school dropout, substance abuse, and suicidal thoughts and behaviors, placing youth at risk for long-term psychological problems [1]. Family-level stressors play a critical role in the development of depressive symptoms in adolescence [2, 3]. For example, depressive symptoms occur more frequently among persons in socioeconomically disadvantaged groups through experiences of economic distress [4, 5], and the socioeconomic gradient in depression is already evident in childhood [4]. Other sources of family stress associated with youth depressive symptoms include chaotic home environments and factors directly affecting caregivers, such as negative life events and caregiver depression [6, 7]. Family stress factors are particularly influential during early and pre-adolescence when youth experience multiple developmental changes [8], fostering vulnerabilities that emerge as depressive symptomology later in adolescence [9].

African American youth are disproportionately exposed to family stressors that place them at risk for depressive symptoms [10]. Although considerable research links family stress to depression, the intervening mechanisms connecting these processes are unclear [10]. Extant data, however, has significant limitations. First, these pathways have primarily been investigated among predominantly non-Hispanic white samples [6, 7, 11, 12] and it remains to be seen if similar factors mediate family stress in Black families [13]. Second, studies with African Americans tend to be cross-sectional [see 14], precluding rigorous examination of mediating mechanisms. Third, emerging stress models underscore the importance of multiple sequential mediators in understanding stress effects [15]. Family stress is thought to initiate a sequence of risk factors in distinct developmental domains that, over time, increase vulnerability to depression [2, 3, 12]. Finally, some data suggest that depression may operate differently between male and female youth [16]. However, sex differences in family stress processes remains to be examined among African American adolescents [see 17].

Informed by family stress theory (FST) and recent research on self-control and depression [5, 18, 19, 20], we examined pathways linking family stress to depressive symptoms among African American youth. FST posits that family stressors affect depressive symptoms via intermediate effects on family relationships [9, 5]. In particular, accumulating data implicate caregiver-youth conflict in the emergence of depressive symptoms in adolescence [3, 9]. FST suggests that the emotional distress arising from family stressors will undermine skillful parenting and induce conflictual caregiver-child interactions [5, 9]. The second mediator to be considered is self-control. Self-control refers to a person's capacity to inhibit socially unacceptable impulses and regulate behavior, thoughts, and emotions [18]. Emerging research documents the influence of poor self-control on negative psychological adjustment [18, 19, 20] among adolescents and suggests that family processes figure prominently in the development of plan-oriented self-control skills [21]. Conflicted caregiver-youth relationships can compromise adolescents' ability to control their emotions and behavior [21] and reduces the availability of support that youth need to develop self-control skills such as resisting temptation and delaying gratification [21].

Summary

We investigated the influence of family stressors in early adolescence on youth depressive symptoms among African American families from rural Georgia communities. For African American families with little discretionary income, residing in rural areas can be particularly stressful due to limited resources [22]. Per Figure 1, family stressors are hypothesized to increase youth depressive symptomatology by increasing caregiver-youth conflict, which in turn is expected to affect adolescent self-control. Further, we examined if these pathways significantly differed based on youth sex. Although research on sex differences in family stress models is limited, some research suggests that the relationship between negative family relationship processes and depression is stronger among female adolescents compared to male adolescents [16]. Therefore, we hypothesized that the link from caregiver-youth conflict to depression would be significantly stronger for females than for males.

Figure 1.

Figure 1.

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Conceptual model linking family stress, parent-youth conflict, adolescent poor self-control, and adolescent depressive symptoms.

Methods

Study Overview

Study hypotheses were tested with four waves of data from 472 African American youth and their caregivers participating in a randomized prevention trial [23]. In this efficacy trial, youth were assigned to one or two developmentally timed, family-centered prevention programs or a control group using simple randomization. To address potential variability introduced by random assignment to group, the experimental condition was controlled in all tests of study hypotheses. The intervention had no effects on intermediate or distal outcomes in the current analysis (see Supplemental Table 1). Sample size was determined a priori with a focus on intervention effects in the parent study. To evaluate if we had sufficient power to test the current study hypotheses, we conducted a post hoc power analysis for mediational models [24]. Power exceeded .80 for detecting a small effect (.10, p < .05) and for detecting indirect effects as small as .05.

Participants

In Southern Georgia, rural school districts provided lists of African American students in the fifth grade whose caregivers were then contacted by phone in a random order by research staff to screen for eligibility. Eligibility requirements were: youth age 11 or 12 years and youth self-identification as African American or Black. Of the 825 families screened for eligibility, 625 were eligible to participate; of these, 472 were enrolled in the study at baseline (a 76% recruitment rate).

Participants provided data at four-time points, with an average of 15 months between time points. At baseline (Time [T] 1), 472 families participated (youth age = 11). At T4, 409 (86.7 %) families participated (youth age = 15). Attrition at T4 was not associated with baseline measures, including experimental condition, youth sex, single caregiver household, youth self-control, adolescent depressive symptoms, caregiver-youth conflict, and family stressors.

At baseline, families had an average of 2.7 children, and 53.6% of the youth were female. Of the caregivers, 88.6% were the biological mothers of the youth, 5.3% were grandparents, and the remaining 3% were biological fathers. The mean age of caregivers was 38.1 years. Of the caregivers in this sample, 78.7% had completed high school or trade school or obtained a GED. In the current sample, 56.5% of youth participants and 44.5% of caregivers had depressive symptoms at or above the clinically significant level (≥ 16) [25, 27]. The sample was primarily low-income, as 64% of the participants lived below the federal poverty level, and 37.8% of the caregivers were unemployed.

Procedures

African American research staff conducted home visits during which data were collected from primary caregivers and youth via audio computer-assisted self-interviews (ACASI) on laptop computers. ACASI technology provides video and audio enhancements that obviate literacy concerns. Interviews took place in private settings so that each participant could respond without other family members viewing their responses. Informed consent/assent was obtained from caregivers and youth. Caregiver incentives were $100, and youth incentives were $40 at each assessment. The University IRB approved all study protocols.

Measures

Adolescent depressive symptoms.

Youth completed the 20-item Center for Epidemiologic Studies Depression Scale for Children [25] at T1 and T4. Youth were given a list of symptoms (e.g., "I felt down and unhappy") and asked how often each occurred within the past week, with a response scale ranging from 0 (not at all) to 3 (a lot). Reliability (Cronbach’s alpha, McDonald’s omega) was as follows: T1 α = .85, ω = .89; T4 α = .89, ω = .92.

Family stress.

Family stress was indexed at T1 using four caregiver-reported variables: family poverty status, caregiver depressive symptoms, chaotic home environment, and caregiver negative life events. Per past FST research [11, 26], each measure was assigned a score of 1 (risk factor present) or 0 (risk factor not present) to create a family stress index ranging from 0-4. Continuous variables without specific cutoffs (chaos in the home and negative life events) were assigned a 1 or 0 based on a median split. Caregivers reported their income and household size. Family poverty status was calculated based on federal guidelines (1 = beneath federal poverty threshold, 0 = above federal poverty threshold). Caregivers reported their employment status (1 = unemployed; 0 = employed full- or part-time). Caregiver depressive symptoms were assessed with the Center for Epidemiologic Studies Depression Scale [27]. Caregivers were given a list of symptoms (e.g., "How often were you bothered by things that usually don't bother you?") with a response scale ranging from 0 (not at all) to 3 (a lot), α = .87, ω = .87. A score of 1 was assigned if caregiver depression was more than or equal to 16, indicating clinically significant depressive symptoms per Radloff [27]. Chaotic home environment was measured using a 16-item self-report survey [28]. The survey asked caregivers to score statements such as, "You cannot hear yourself think in our home," as 0 (false) or 1 (true) for their households (α = .77, ω = .78). Caregiver negative life events were assessed with a 27-item checklist [12] that asked caregivers if certain events had happened to them in the past six months, such as, "Did you have an unwanted pregnancy?".

Caregiver-youth conflict.

At T1 and T2, caregivers and youth completed their respective versions of 3 scales indexing caregiver-youth conflict. The scales included the 8-item Conflict subscale of the Interaction Behavior Questionnaire [29]. The subscale included questions such as, "You and your (child/caregiver) have big arguments about little things." Youth responses ranged from 1 (really false) to 4 (really true), and caregiver responses were rated 0 (false) or 1 (true). Youth reported reliability was as follows: T1 α = .83, ω = .82, T2 α = .82, ω = .86. Parent-reported reliability was as follows: T1 α = .77, ω = .77, T2 α = .86, ω = .86. Participants completed the 8-item Destructive Arguing Scale [30] on which caregivers and youth responded to statements such as, "You and [caregiver/youth] go for days being mad at each other." Youth responded using a 5-point scale ranging from 0 (strongly disagree) to 4 (strongly agree), and caregivers responded on a 5-point scale ranging from 1 (disagree strongly) to 5 (agree strongly). Youth reported reliability was as follows: T1 α = .58, ω = .59, T2 α = .71, ω = .71 at T2. Parent report reliability was as follows: T1 α = .71, ω = .73, T2 α = .74, ω = .76. Caregivers and youth completed the 4-item arguing subscale of the Discussion Quality Scale [31]. Youth and caregivers responded to statements such as, "When you and your (teen/caregiver) talk about (their/your) choice of friends, how often do you end up arguing?" with a response scale from 0 (never) to 4 (always/nearly every time). Youth reported reliability was as follows: T1 α = .81, ω = .83, T2 α = .78, ω = .77 at T2. Parent reported reliability was as follows: T1 α = .70, ω = .72, T2 α = .79, ω = .80. The caregiver and youth versions of each scale were significantly correlated. For each set of scales, the two versions were standardized and then averaged to create a multi-reporter composite. We then used the three composites as indicators of a latent caregiver-youth conflict variable at T1 and T2.

Adolescent poor self-control.

At T1 and T3, caregivers completed the 6-item Poor Self-control subscale of the Child Self-control scale [32]; an example item is, “How often does your child make careless mistakes because they rush?” (T1 α = .80, T1 ω = .80; T3 α = .80, T3 ω = .80). Youth completed the 8-item Poor Self-control subscale of Will's Self-control Scale [33]. Example items included, “I often do things without stopping to think,” (T1 α = .78, T1 ω = .80; T3 α = .78, T3 ω = .78). Caregiver and youth reports were significantly correlated. They were standardized and averaged within each wave to create a multi-reporter, poor self-control composite.

Controls.

Youth’s self-reported sex was coded as (0 = female, 1 = male). Intervention assignments were coded with three dummy variables (0 vs. 1), with one indicating the presence in the corresponding intervention group. We also controlled for single-caregiver households (0 = not a single caregiver household, 1 = single caregiver household).

Plan of Analysis

Descriptive statistics and correlations were calculated using SPSS. Hypotheses were tested with structural equation modeling (SEM) as implemented in Mplus 8.0 [34]. SEM is a diverse set of statistical methods that fit networks of constructs to data [34]. Before hypothesis testing, we examined the measurement model with a confirmatory factor analysis (CFA) to test the expectation that a latent caregiver-youth conflict construct fit the data. We then tested the extent to which the measurement model had longitudinal measurement invariance across time. Missing data due to skipped survey items were minimal (< 2% per variable). Attrition at T4 was not associated with any baseline measures, suggesting that the data met the requirements for "missing at random." Thus, missing data were managed with full information likelihood estimation. We ran the model presented in Figure 1 with baseline levels of intermediate outcomes (caregiver-youth conflict, poor self-control) and depressive symptoms as well as youth sex, single caregiver status, and intervention condition controlled. We entered all direct and indirect pathways into the model simultaneously. Model fit was assessed using various fit indices. Comparative Fit Index (CFI) values greater than 0.95, Root Mean Square Error of Approximation (RMSEA) values less than 0.08, and a χ 2/df ratio less than 3.0 indicate acceptable model fit [35]. The significance of the model's indirect effects was tested using bootstrapping procedures [36]. Unstandardized indirect effects were computed for each of 5,000 bootstrapped samples, and we determined significance using a 95% confidence interval [36]. To ascertain if youth sex conditioned the primary pathways, we first tested the latent variable, caregiver-youth conflict, for metric invariance by sex and then examined sex differences with multi-group analysis.

Results

Table 1 presents the study variables' correlations, means, and standard deviations. We first conducted a CFA of the measurement model. The model fit the data as follows: χ2(5) = 8.34, p = .14, CFI = 0.99, RMSEA = .04. All factor loadings were above 0.56 on the expected latent factor, in the expected direction, and significant. To test if the item loadings in the measurement model had psychometric equivalence across time points, we next tested for measurement invariance using protocols from Putnick and Bornstein [37]. A chi-square difference test suggest that the model fit is not significantly different in the metric invariance model compared to the configural invariance model, (Δ χ2 (2) = 0.37, p = 0.83). This indicates that the factors loaded similarly across time 1 and time 2.

Table 1.

Means, standard deviations, and correlations of study variables

Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1 Youth's Gender -
2 Intervention Category One 0.00
3 Intervention Category Two 0.04 −0.30**
4 Intervention Category Three −0.02 −0.30** −0.37**
5 Family Contextual Stress −0.06 0.04 −0.12* 0.02
6 T1 Conflictive Interactions 0.00 0.03 0.00 0.00 0.29**
7 T2 Conflictive Interactions 0.01 −0.03 0.08 0.00 0.25** 0.53**
8 T1 Discussion Quality: 0.01 −0.03 0.02 0.04 0.19** 0.42** 0.40**
9 T2 Discussion Quality: 0.09 −0.04 0.14** −0.08 0.23** 0.37** 0.56** 0.43**
10 T1 Destructive Arguing −0.01 0.04 −0.07 −0.03 0.26** 0.61** 0.44** 0.44** 0.32**
11 T2 Destructive Arguing 0.01 0.01 0.04 −0.06 0.24** 0.44** 0.71** 0.34** 0.54** 0.47**
12 T1 Poor Self-Control 0.11* 0.07 0.02 −0.04 0.18** 0.40** 0.33** 0.39** 0.31** 0.40** 0.33**
13 T3 Poor Self-Control 0.05 −0.01 0.03 −0.04 0.21** 0.42** 0.47** 0.36** 0.36** 0.38** 0.43** 0.47**
14 T1 Depressive Symptoms −0.05 0.01 0.01 −0.02 0.08 0.13** 0.16** 0.09 0.12* 0.19** 0.17** 0.28** 0.15**
15 T4 Depressive Symptoms −0.17** 0.02 −0.08 −0.03 0.07 0.13* 0.11* 0.09 0.11* 0.14** 0.16** 0.14** 0.24** 0.10
16 Single Caregiver Household 0.01 −0.04 0.04 −0.09 0.08 0.02 −0.02 −0.02 0.06 0.02 0.08 −0.05 0.02 0.03 −0.03 -
M 0.49 0.19 0.26 0.27 2.68 0.00 0.00 1.57 1.94 0.00 0.00 0.00 0.00 16.76 7.20 0.38
SD 0.50 0.40 0.44 0.45 1.36 0.81 0.81 1.88 2.09 0.76 0.79 0.77 0.80 10.75 2.77 0.49
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T1 = time 1; SD = standard deviation.

*

p < .05.

**

p < .01.

Tests of the study hypotheses with standardized parameter estimates are presented in Figure 2. The model fit the data as follows: χ2 (56) = 111.9, p = .00, CFI = 0.95, RMSEA = .05, χ2/df = 2.0. As hypothesized, T1 family stress significantly predicted T2 caregiver-youth conflict (β = 0.14, p = .006). For every one-unit increase in family stress, caregiver youth conflict increases by 0.14. Further, for every one-unit increase in T2 caregiver-youth conflict, poor adolescent self-control increased by 0.43 (β = 0.43, p < .001). As hypothesized, T3 poor self-control was a positive, significant predictor of T4 adolescent depressive symptoms (β = 0.19, p = .004). That is, for every one-unit increase in poor self-control, adolescent depressive symptoms increased by 0.19. T2 caregiver-youth conflict was also a positive predictor of T4 depressive symptoms (β = 0.22, p = .002), meaning that for every unit increase in caregiver youth conflict, depressive symptoms directly increased by 0.22. T1 family stress was not a significant predictor of T4 adolescent depressive symptoms (β = −0.02, p = .69). T1 family stress was not a significant predictor of T3 poor self-control (β = −0.04, p = .38).

Figure 2.

Figure 2.

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Structural Equation Model Predicting Adolescent Depressive Symptoms. Standardized parameter estimates are shown. All covariates were controlled at time 1 (T1) and are not shown in model. Note: Dotted lines depict non-significant pathways. *p < .05. **p < .01.

Unstandardized indirect effects, standard errors, and confidence intervals are presented in Table 2. The 95% confidence intervals for all indirect effects did not contain zero, suggesting the effects are statistically significant [36]. Family stress indirectly predicted adolescent poor self-control through caregiver-youth conflict (β = 0.06, p = .01). For every unit change in family stress, adolescent poor self-control increases by 0.06 through caregiver-youth conflict. Caregiver-youth conflict indirectly predicted adolescent depressive symptoms through adolescent poor self-control (β = 0.08, p = .01). For every unit increase in caregiver-youth conflict, adolescent depressive symptoms increase by 0.08 via adolescent poor self-control. Lastly, family stress indirectly predicted adolescent depressive symptoms via caregiver-youth conflict and poor self-control (β = 0.05, p = .01). For every one unit increase in family stress, adolescent depressive symptoms increased by 0.05 through both caregiver-youth conflict and poor self-control.

Table 2.

Unstandardized Indirect effects, estimates, standard errors and bootstrapped 95% confidence intervals

Indirect effect Est. SE 95% CI
Family Stress → Caregiver-Youth Conflict → Adolescent Poor Self-Control → Depressive Symptoms 0.10 0.05 0.02, 0.19
Family Stress → Caregiver -Youth Conflict → Poor Self-Control 0.03 0.01 0.01, 0.06
Caregiver -Youth Conflict → Poor Self-Control → Depressive Symptoms 0.72 0.29 0.27, 1.21
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Next, we examined if youth sex moderated model pathways. We first tested the latent variable, caregiver-youth conflict, for metric invariance. Chi-square difference tests were non-significant (p = .31; see supplemental appendix for additional details), suggesting that items loaded similarly for males and females. Chi-square difference tests also indicated no significant differences between males and females in study pathways (see supplemental appendix).

Discussion

We investigated the intervening variables through which family stress affected depressive symptoms among African American adolescents. We hypothesized a cascade of risk factors where family stress would predict adolescent depressive symptoms via caregiver-youth conflict and adolescent poor self-control. Notably, the majority of both youth and caregivers had depressive levels above clinical cutoffs [25, 27]. In the context of a community sample, these rates are quite high and exceed estimates found in other studies [9]. Study results supported the hypothesized model. We confirmed an indirect pathway linking family stress to adolescent depressive symptoms via caregiver-youth conflict and poor self-control. Results also indicated a direct effect between caregiver-youth conflict and depressive symptoms.

These findings support past research that suggests the accumulation of family stressors has important implications for adolescent mental health [11] and extend these findings to African American adolescents. Consistent with family stress models, study findings suggest that family stressors promote caregiver-youth conflict, a reliable risk factor for depressive symptoms [2, 3]. FST posits that irritability and negative affect induced by a range of stressors that caregivers experience affect the quality of their interactions with youth [9, 5, 13]. Similarly, youth may experience the effects of family stressors and hardships directly and bring these challenges into dyadic interactions with their caregivers [9, 5, 13].

We found that heightened caregiver-youth conflict predicts increases in poor self-control among adolescents. The ability to regulate thoughts and behaviors across adolescence is partially learned through social influences [38]. Our findings further indicate that increases in poor self-control among African American youth predict increases in adolescents' depressive symptoms. Research emerging during the past decade has found that impairments in controlling one's thoughts, behaviors, and emotions can increase depressive symptomatology [19, 20].

The indirect effects were significant for all pathways in the current study. We found no evidence for a direct relationship between family stress at T1 and depressive symptomatology at T4. Taken together, these findings provide evidence that the effect of family stress on depressive symptoms operates through intermediate factors such as caregiver-youth conflict and adolescent self-control. This is consistent with previous findings demonstrating that family stress is often indirectly related to psychosocial outcomes through family-level and individual-level processes [9]. Moreover, consistent with past research, we found that caregiver-youth conflict directly predicted adolescent depressive symptoms [2, 3]. The experience of conflict with a caregiver, particularly if they are emotionally charged and chronic, has been linked to a range of psychopathology [9]. The pathways in the current model did not differ based on youth sex. This may suggest that family stress operates similarly among male and female youth, yet future research should explore sex differences in other intermediate family stress processes.

These findings underscore the potential for family stressors to promote cascading problems with depressive symptoms among rural African American youth and the need to screen for, accompanied by policy to reduce, stress exposure in this population. Referral to family-centered programs may be indicated, particularly to interventions that address caregiver-youth conflict and youth self-control. For example, the Strong African American–Teen program was designed for rural African Americans and their caregivers and has demonstrated efficacy in reducing youth depressive symptoms [39]. Findings also suggest that mental health professionals in school and social service settings should consider working with youth to improve poor-self-control in order to affect changes in depressive symptoms.

Several study limitations should be noted. This study's findings are limited to African American youth and caregivers living in rural communities in Georgia. We tested our hypotheses with an autoregressive model, indicated for testing mediating processes [31]. Future research, however, should consider trajectory-based models that consider the influence of changing levels of family stress and mediating processes. We also did not have multiple self-control or depression measures to construct latent variables similar to parent-youth conflict. Future research should explore intermediate processes that were not addressed in the present study, for example, youth experiences with trauma [40], biological markers of stress [40], rumination [20] or peer relationships [16]. It is also important to note that African American families are routinely exposed to stress due to race-related stressors not included in our model such as discrimination, negative encounters with police and other authority figures, limited educational and employment opportunities, limited health care, and unequal housing opportunities.

These limitations notwithstanding, this study's findings add to the literature by identifying a process through which family stress leads to increases in depressive symptoms among African American youth living in rural areas of the southern United States.

Supplementary Material

1
2

Implications and Contribution Statement:

This study contributes to the existing literature by identifying how family stress can "spill over" to impact caregiver-youth conflict, youth self-control, and adolescent depressive symptoms. Prevention program curricula may target caregiver-youth relationships and adolescent self-control to prevent depressive symptoms among African American youth.

Acknowledgements.

This research was supported by Award Number R01 AA021774 from the National Institute on Alcohol Abuse and Alcoholism and Award Number P50 DA051361 from the National Institute on Drug Abuse. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Alcohol Abuse and Alcoholism, the National Institute on Drug Abuse, or the National Institutes of Health. We would like to thank Eileen Neubaum-Carlan for her assistance in editing this manuscript.

Footnotes

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