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Using observed peer discussions to understand adolescent depressive symptoms and interpersonal interactions

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Using observed peer discussions to understand adolescent depressive symptoms and interpersonal interactions

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Content Running Head: FRIEND INTERACTIONS 1

Using Observed Peer Discussions to Understand Adolescent Depressive Symptoms and
Interpersonal Interactions

Ilana Kellerman Moss

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(PSYCHOLOGY)

August 2017

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Table of Contents
Acknowledgments ................................................................................................................ 4
Overall Introduction ............................................................................................................. 6

Manuscript 1: Behaving Depressed: Links Between Depressive Symptoms, Family Risk, and
Communication Patterns During Adolescent Friend Conversations
Title Page 10
Abstract 11
Introduction 12
Methods 22
Results 31
Discussion 36
References 45
Tables
Table 1 60
Table 2 61
Table 3 62
Table 4 63
Table 5 64
Table 6 65
Figures
Figure 1 66
Figure 2 67
Figure 3 68
Figure 4 69
Supplemental Material
Supplemental Table 70

Manuscript 2: The Role of Friends’ Conversations About Interpersonal Problems in the
Continuity of Depressive Symptoms
Title Page 71
Abstract 72
Introduction 73
Methods 85
Results 93
Discussion 99
References 108
Tables
Table 1 124
Table 2 125
Table 3 126
Table 4 127
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Table 5 128
Table 6 129
Figures
Figure 1 130
Figures 2a and 2b 131
Figure 3 132
Figure 4 133
Figure 5 134
Figure 6 135

Overall Discussion 136
References for Overall Introduction and Discussion 141
Appendix A: Coding Manual 145
Appendix B: Peer Discussion Coding Sheet 158
Appendix C: Experimenter Instructions for Peer Discussion Task 161
Appendix D: Pre-discussion Topics 164
Appendix E: Discussion Follow Up Questionnaire 165
Appendix F: Beck Depression Inventory-Second Edition 166
Appendix G: Domestic Conflict Index 168
Appendix H: Parent Child Conflict Questionnaire 175
Appendix I: Symptom Checklist-90 177

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Acknowledgments
The completion of this dissertation would not have been possible without the assistance
of many people. First and foremost, I am incredibly grateful to my research advisor Dr. Gayla
Margolin, whose unwavering support, brilliant ideas, and continuous patience have helped me
navigate graduate school and encouraged me to explore various research avenues. The research
described in this dissertation was supported by NIH NICHD Grants R01 HD046807 and
R21HD072170 awarded to Dr. Margolin. I also wish to extend a big thank you to my dissertation
committee members Drs. John Brekke, Richard John, Darby Saxbe, and Marian Williams for
providing me with helpful feedback and guidance regarding my dissertation.
I am indebted to Dr. Estibaliz Iturralde, who spent countless hours sharing her vast
knowledge of observational research and dyadic data analytic techniques with me. Adela C.
Timmons and Drs. Reout Arbel, Christopher Beam, Marie-Eve Daspe, Sonya Negriff, Michelle
Ramos, Aubrey Rodriguez, and Lauren Spies Shapiro were extremely generous with their time
as they helped me with statistic and research design related questions. Thank you to my hard
working team of coders Francesca Corley, Mary Letourneau, Summer Miller, Susette Moyers,
Kaitlin Shonnard, Philippa Tucker, and especially to Corey Pettit who has greatly assisted me
with this project from day one and played an instrumental role in the piloting of the coding
system. Drs. Amanda Rose and Rebecca Schwartz-Mette graciously shared their coding systems
and/or expertise regarding observational research with me.
I feel lucky to have had a wonderful graduate cohort: John Keefe and Drs. Karan Singh,
Caitlin Smith Sayegh, and Larissa Del Piero, who was also my amazing and always supportive
lab mate (“lab-twin”). Drs. Jen Labrecque and Ali Ross have also been wonderful friends and
colleagues throughout graduate school. I wish to acknowledge and thank current and past
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members of the USC Family Studies Project Lab whom I have not yet mentioned who diligently
collected and organized study data: Dr. Brian Baucom, Diana Bennett, Claire Burgess, Theodora
Chaspari, Geoff Corner, Dr. Sarah Duman, Elyse Guran, Kristene Hossepian, Sohyun Han,
Yehsong Kim, Kelly Miller, Laura Perrone, Hannah Rasmussen, and Dr. Katrina Vickerman.
Thank you to the families who have participated in the USC Family Studies Project.
My family and friends have been constant sources of encouragement and comic relief
throughout graduate school. I owe a special thank you to my sister, Dr. Rachel Kessler, and my
mother, Dr. Faye Kellerman, who helped watched my newborn daughter so that I could finish
writing my dissertation papers, as well as proofread drafts of my dissertation manuscript. Finally,
no amount of words is sufficient to thank my husband Jordan and daughter Zoe, the newest and
greatest addition to our family. You two are the best significant results I have ever obtained in
my life, and I love you dearly.

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Overall Introduction
The two papers that make up this dissertation attempt to answer the following question:
Do the ways in which adolescent friends converse and behave with one another offer insight
regarding their emotional well-being? In particular, this dissertation focuses on links between
adolescent depressive symptoms and observed communication patterns among friend dyads.
Adolescent depression is a prevalent and costly mental health concern, as it is associated with
health and relationship challenges (Keenan-Miller, Hammen, & Brennan, 2007), increased
suicide risk (Avenevoli, Swendsen, He, Burstein, & Merikangas, 2015), and co-occurring
diagnoses such as substance abuse and anxiety (Costello, Erkanli, Federman, & Angold, 1999;
SAMSHA, 2011). Depression onset during adolescence is also characterized by a more chronic
and severe course (Klein et al., 1999; Lewinsohn, Clarke, Seeley, & Rhode, 1994).
Given the considerable psychosocial implications of depression, accurate identification of
at-risk adolescents—those who experience symptoms but do not necessarily yet meet diagnostic
criteria—is critical for successful prevention efforts. Investigating correlates and risk factors of
depressive symptoms among adolescents and young adults in the community may be a helpful
start toward accomplishing this task (Stice, Shaw, Bohon, Marti, & Rohde, 2010). Moreover,
studying depressive symptoms is consistent with emerging models asserting that depression is
not a discrete construct but rather exists on a continuum (Hankin, Fraley, Lahey, & Waldman,
2005; Ruscio & Ruscio, 2000).
This dissertation is guided by interpersonal theories of depressions, which generally
assert that at-risk individuals experience social-behavioral deficits that contribute to interpersonal
problems and greater depression vulnerability (Coyne, 1976; Joiner & Timmons). Because the
development of close friendships is a hallmark of adolescence, research has examined
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associations between adolescent interpersonal deficits, peer relationships, and depressive
symptoms (Borelli & Prinstein, 2006; Prinstein, Borelli, Cheah, Simon, & Aikins, 2005;
Schwartz-Mette & Smith, 2016). Yet, few studies have utilized direct observations between
friends to investigate interpersonal dynamics that may be linked with depressive symptoms.
Seeking to fill this gap, these two dissertation papers used video-recorded peer
discussions in order to gain a more nuanced understanding of how adolescent behaviors and
dyadic exchanges relate to depressive symptoms. Participants included adolescents who were
part of a multi-wave study of families from the community. These adolescents nominated a
same-sex friend to participate in discussions about numerous topics (e.g., solving an
interpersonal problem, talking about friends and dating relationships). We developed a
comprehensive coding system to assess affect and behaviors anticipated to correspond with
depressive symptoms.
The first paper examined whether adolescent depressive symptoms were significantly
linked with five observed communication patterns with friends: 1) irritability and cynicism, 2)
obscenities and curse words, 3) conversational self-focus, or the tendency to redirect
conversations away from friends and towards oneself (Schwartz-Mette & Rose, 2009), 4)
criticism of the other friend, and 5) supportive talk directed toward the friend. Also of interest
was how adolescents’ depressive symptoms related to the same behaviors in their friends. An
Actor-Partner Interdependence Model (APIM; Kenny, Kashy, & Cook, 2006) was specified in
order to simultaneously test these associations in self and friend. Using multilevel modeling, the
second goal of this study was to assess whether depressive symptoms and exposure to family
aggression interacted to predict these five behaviors. Risky family factors, such as maternal
depression, child maltreatment, and family conflict have been shown to have important
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implications regarding adolescent depression and experiences of interpersonal stress (Hammen,
1999; 2009; Harkness, Lumley, & Truss, 2008; Restifo & Bogels, 2009). The first paper sought
to expand upon these findings by honing in on the combination of parent-to-child and parent-to-
parent aggression in the manifestation of interpersonal behaviors possibly associated with
depressive symptoms.
Whereas paper one investigated concurrent associations between depressive symptoms
and friend behaviors, the second paper used two time points of data to study whether observable
interactional behaviors in adolescent dyads strengthened or diminished the continuity of
depressive symptoms from adolescence to young adulthood. We explored four dyadic codes: 1)
co-rumination, 2) problem-solving talk, 3) interpersonal stress talk, and 4) friend intimacy.
Grounded in theories of peer contagion (Dishion & Tipsord, 2011), this paper also explored
whether these behaviors moderated associations across time between one friend’s depressive
symptoms and the other’s depressive symptoms.
Together, these papers seek to clarify how various discrete and observable social
exchanges between friends are related to depressive symptoms. This dissertation aims to
integrate theories and research on stress-generation, cognitive and interpersonal theories of
depression, co-rumination, peer contagion, and family aggression as a first step towards
providing a more thorough picture of how different interpersonal processes disrupt functioning
and create risks for depressive symptoms. A more detailed understanding of the function that
peer processes play with respect to adolescent depressive symptoms may potentially advance the
literature on interpersonal theories of depression. It may also provide useful information
regarding how to optimally intervene to curb mental health challenges at the friendship level.
More generally, a fine-grained look at how friends talk to one another can offer valuable
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information about the nature of peer relationships during this critical developmental phase, the
types of stressors that adolescence encounter, and the pertinence of these factors in adolescent
and young adult psychosocial functioning.

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Manuscript 1
Behaving Depressed: Links Between Depressive Symptoms, Family Risk, and Communication
Patterns During Adolescent Friend Conversations

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Abstract
Adolescents' social interactions with friends may offer important clues regarding their
emotional health. Building on this premise, the current study utilizes data from both adolescents
and their friends to examine associations between depressive symptoms, observed
communication patterns, and exposure to family aggression. Participants included 111 same-sex
adolescent friend dyads (50 female dyads) who partook in a videotaped peer discussion task and
completed measures of family aggression and depressive symptoms. A comprehensive coding
system was developed to assess whether adolescent depressive symptoms translated into five
observable behaviors with friends: irritability, use of obscenities, conversational self-focus,
criticism, and supportive talk. Overall, results did not find evidence for main effects of
depressive symptoms on behaviors, though depressive symptoms were associated with friends’
tendencies to be less irritable and self-focused. Furthermore, results from multilevel models
suggested that depressive symptoms were associated with irritability and obscenity use when
adolescents were also exposed to high levels of family aggression within the previous year.
Family aggression was also associated with irritability and conversational self-focus, with a
somewhat stronger association for females than males. Results suggest that family risk variables
may continue to inform adolescents’ social interactions. Possible reasons underlying non-
significant associations between depressive symptoms and observed behaviors are addressed.
Key words: peer discussions, adolescent depressive symptoms, family aggression,
interpersonal behaviors

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Introduction
Interpersonal relationships are pivotal during adolescence. Friendships increase in
intimacy, as adolescents seek emotional support from, spend more time with, and are influenced
by their peers (Buhrmester, 1990; del Valle, Bravo, & Lopez, 2010; Rose & Rudolph, 2006;
Rubin, Bukowski, Parker, & Bowker, 2008). Yet, parent-child relationships continue to inform
adolescents’ psychosocial development (Hair, Moore, Garrett, Ling, & Cleveland, 2008;
Smetana, Campione-Barr, & Metzger, 2006; Steinberg & Monahan, 2007). At the same time that
adolescents navigate relationship changes, they are exposed to more interpersonal stressors and
are vulnerable to mental health challenges, such as depression (Rudolph, 2009). Indeed, rates of
depression rise during adolescence (Huberty, 2012), with females typically being at higher risk
than males (Cichetti & Toth, 1998, Cyranowski, Frank, & Young, 2005), and are associated with
various detrimental health and psychosocial outcomes (Keenan-Miller, Hammen, & Brennan,
2007; Korczak & Goldstein, 2009; SAMSHA, 2011). Sub-threshold depression is also
concerning, as it is a risk factor for future episodes of depression (Fergussen, Horwood, Ridder,
& Beautrais, 2005) and is related to functional and social impairments (Allen, Chango, Szwedo,
& Schad, 2014; Bertha & Balazs, 2013).
Because peer relationships take center stage during adolescence, symptoms of depression
may impact how adolescents behave and communicate with their friends. Identifying observable
behaviors associated with adolescent depressive symptoms that manifest within the context of
close friendships may thus be key in recognizing and treating at-risk youth. In addition, certain
psychosocial variables, such as exposure to family aggression, may make adolescents with
depressive symptoms more prone to engaging in maladaptive behaviors with others (Rudolph,
2009). The present study utilizes a multi-method design in order to clarify associations between
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adolescent depressive symptoms and their communication patterns with friends. Using direct
observations of adolescent peer discussions, we investigate how adolescent depressive symptoms
relate to both their own and their friends’ behaviors. We concentrate on observed irritability and
cynicism, use of swear words and obscenities, self-focused talk, being critical of friends, and
supportive talk toward friends, as many of these behaviors occur among adults with depression
(Segrin, 2000), but still have not been extensively studied via observational methods in
adolescent friends. Furthermore, we investigate family aggression as a contextual factor that may
exacerbate depressed adolescents’ likelihood of engaging in these observed behaviors.
Theoretical Models of Adolescent Depressive Symptoms

Several theoretical frameworks underscore the relevance of examining friend interactions
among adolescents with depressive symptoms. For example, stress-generation (Hammen, 1991;
2006) and interpersonal theories of depression (Coyne, 1976; Joiner & Timmons, 2009)
emphasize that it is critical to take into account individuals’ social landscapes when studying
depression. According to these models, individuals with or at risk for depression demonstrate
interpersonal deficits that may provoke negative reactions from others and disrupt relationships.
These interpersonal problems, in turn, can further fuel risks for developing depression.
Moreover, people may initially respond positively to those with depression (e.g., offering
support, suppressing negative behaviors; Heller & Tanaka-Matsumi, 1999). Yet, over time, close
others may find the negative behaviors of people with depression aversive and subsequently
reject them (Joiner & Timmons, 2009).
Interpersonal challenges associated with adolescent depression may be especially
pronounced in the friendship realm. Research suggests that depressive symptoms are associated
with peer problems and victimization (Kochel, Ladd, & Rudolph, 2012; Marsh et al., 2016).
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There is also evidence among young adults that those with depression, compared to their non-
depressed counterparts, are more likely to engage in maladaptive behaviors (e.g., criticizing the
partner) when with friends but not when with strangers (Segrin & Flora, 1998). Thus, studying
friend interactions may offer a realistic glimpse of behavioral manifestations of depressive
symptoms.
Cognitive vulnerability models suggest that adolescents at risk for depression are more
likely to experience negative thought processes. They may respond to adverse events with a
more hopeless mindset, hold negatively biased views of friends and others, and focus repetitively
on negative affect related to an event (Hyde, Mezulis, & Abramson, 2008; Rudolph, 2009).
There have been recent efforts to integrate cognitive and interpersonal models of adolescent
depression (Hankin & Abramson, 2001), especially given the research linking negative
cognitions and interpersonal problems (Caldwell, Rudolph, Troop-Gordon, & Kim, 2004;
Prinstein & Aikens, 2004). As adolescent friendships are characterized by high degrees of
emotional disclosure (Buhrmester & Prager, 1995; Collins & Steinberg, 2008), one possibility
might be that at-risk individuals are more likely to express such negative thinking patterns to
friends, which may strain relationships over time. Understanding how negative thoughts translate
into observable behaviors may be an important first step in elucidating how cognitions are linked
with interpersonal stress.
Interpersonal Deficits and Adolescent Depressive Symptoms: What Do We Know?
Links between social deficits and depression in adults have been extensively studied.
Adults at risk for depression are more likely to exhibit negative content, make inappropriate
negative self-disclosures, display negative facial affect, and continuously seek reassurance from
others (Hames, Hagan, & Joiner, 2013; Joiner & Metalsky, 2001; Segrin, 2000). Emerging
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research indicates that adolescents with depressive symptoms also engage in potentially negative
behaviors, particularly with friends. Excessive reassurance seeking (Prinstein, Borelli, Cheah,
Simon, & Aikins, 2005) and negative feedback seeking (Borelli & Prinstein, 2006) are two
related interpersonal styles that have most often been linked with adolescent depressive
symptoms. The former describes the tendency of people with mild depressive symptoms to
continuously seek reassurance about their self-worth from others until it evokes irritation and
rejection from others (Davila, 2001; Joiner & Timmons, 2009). The latter refers to when people
prone to depression request negative over positive evaluations from others (Joiner & Timmons,
2009). Depressive symptoms among adolescents have also been associated with co-rumination,
or when adolescents continuously rehash problems in a negative light without attempts to fix
them (Rose, 2002; Rose, Carlson, & Waller, 2007).
These studies are valuable for understanding interpersonal deficits among adolescents
with depressive symptoms. However, the bulk of them (for exceptions, see Rose, Schwartz-
Mette, Glock, Smith, & Luebbe, 2014; Schwartz-Mette & Rose, 2016) have relied on
questionnaire data. Observational methods may enable a more valid examination of interpersonal
patterns, how they may be related among friends, and how friends react to depressive symptoms
and behaviors. Also, because studies have typically focused on a few select behaviors, they leave
open the possibility that other interpersonal patterns warrant investigation (Schwartz-Mette &
Rose, 2016). The present study seeks to extend the interpersonal depression literature by
considering other behaviors that may be linked with adolescent depressive symptoms.
Critical and Irritable Behaviors
The adult literature suggests that individuals with depression act more negatively and
aggressively toward others. Studies have shown that mothers diagnosed with depression make
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more critical and guilt-inducing statements toward their children (Hamilton, Jones, & Hammen,
1993) and that depressed adults may be more aggressive and hostile toward their spouses (Kahn,
Coyne, & Margolin, 1985). Young adults with high levels of depressive symptoms are also more
prone to making negative statements toward their close friends (Segrin & Flora, 1998). There is
some support that adolescents with depressive symptoms may also be critical of their friends. For
example, one study found that adolescents’ hostile interpersonal styles (e.g., anger,
dismissiveness) captured during observed peer interactions were predictive of future depressive
symptoms (Allen et al., 2006). Thus, insulting friends, which can have a particularly detrimental
impact on social relationships, warrants further investigation among adolescents.
Additionally, adolescents with depressive symptoms may act more irritably or cynical in
general. Irritable mood is a diagnostic criterion of depression in children and adolescents
(American Psychiatric Association, 2013), and is predictive of depressive symptoms (Stringaris
& Goodman, 2009). One study paired adolescents with and without depression with unfamiliar
peers. Although adolescents with depression did not make significantly more negative statements
toward their assigned partner, they did engage in significantly more “depressive behavior,”
which included making negative statements about people outside of the room (Heller & Tanaka-
Matsumi, 1999, p.257). Furthermore, research on observed co-rumination and adolescent
emotional adjustment highlights that dwelling on negative affect may be the active ingredient of
co-rumination that is connected with depressive symptoms (Rose et al., 2014). Thus, exhibiting a
more negative attitude regarding one’s environment may be demonstrative of depression risk.
Related to irritability, the use of vulgar or obscene words may be a marker of emotional
distress. However, there is a paucity of research on linkages between obscenities and adolescent
depressive symptoms. One investigation of language use in young adults demonstrated that
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writing swear words in on-line blogs was associated with depressive symptoms in college age
students (Rodriguez, Holleran, & Mehl, 2010). Based on this result, the authors concluded that
swear words may be a more acceptable form of negative disclosure. Obscenity use is a discrete,
relatively easily measured behavior. Thus, it may be a useful construct for detecting adolescents
at risk for depressive symptoms.
Self-Focused Behavior
Because depression is often characterized by repetitive and passive negative thinking
patterns (Koster, Lissyder, Derakshan, & Raedt, 2011; Nolen-Hoeksama, 1991; Nolen-
Hoeksama, Wisco, & Lyubomirsky, 2008), it is unsurprising that individuals experiencing
emotional distress tend to be highly self-focused (Pyszczynski & Greenberg, 1987; Mor &
Winquist, 2002). For instance, investigating audio-recorded sound clips (Mehl, 2006) and essays
(Rude, Gortner, & Pennebaker, 2004) of college students, researchers have found that adults with
subclinical depression are more likely to use first person pronouns (e.g., “I”) in their speech.
Adults with depression are also more likely to verbalize unsolicited self-disclosures (Jacobson &
Anderson, 1982). However, there have been exceptions to these findings (Rodriguez et al., 2010;
Segrin & Flora, 1998).
Applying the concept of self-focus to adolescent depressive symptoms and interpersonal
behaviors, Schwartz-Mette and Rose (2009) developed the construct of conversational self-focus,
defined as the propensity to re-direct conversations away from others and toward oneself. They
posited that because adolescents with depressive symptoms are self-focused, they might use
social exchanges to air their own grievances while neglecting to listen to their friends in return.
Utilizing direct observations of adolescent friend dyads, they found that internalizing symptoms
were concurrently correlated with conversational-self focus (Schwartz-Mette & Rose, 2009).
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Findings from a longitudinal study demonstrated associations between depressive symptoms and
observed conversational self-focus and that depressive symptoms were prospectively associated
with poor friendship quality in the context of high levels of conversational self-focus (Schwartz-
Mette & Rose, 2016). Of note is that although this study employed a dyadic design, the extent to
which depressive symptoms in adolescents were related to conversational self-focus in their
friends was not addressed. Indeed, researchers have called for further investigation of how
adolescents behave toward their friends with depression (Rudolph, 2009).
Associations Between Depressive Symptoms and Friend Behaviors
Theories of emotion socialization assert that social interactions are critical in shaping
adolescents’ emotional experiences and regulatory abilities, providing feedback regarding which
emotions are appropriate to express at given times (Klimes-Dougan et al., 2014). Examining how
adolescents’ depressive symptoms are linked with their friends’ behaviors may illuminate how
depressive symptoms engender peer problems or, alternatively, are inadvertently reinforced by
friends. Furthermore, research on peer contagion processes underlines that adolescents have the
proclivity to associate with others who are similar to them, as well as influence one another’s
behaviors and cognitions (Brechwald & Prinstein, 2011; Stevens & Prinstein, 2005). Thus, it is
possible that adolescents’ symptomatology do not only impact their own behavioral and
communication patterns, but their friends’ as well.
Findings regarding peers’ behaviors toward adolescents with depressive symptoms is
mixed. Although youth may overall perceive their friends as responding supportively to their
expressions of anger or sadness (Klimes-Dougan et al., 2014), observations of friend dyads
suggest that adolescents with higher levels of depressive symptoms tend to receive less observed
support from friends (Lougheed et al., 2016). One study examined interactions between pairs of
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adolescents and unfamiliar peers (i.e., not friends). The researchers explored how the non-
depressed member of the dyad responded in the moment to coded depressed behaviors in
adolescents with clinical depression. Results showed that partners paired with depressed
adolescents tended to respond to their depressed behaviors (e.g., negative affect and statements
about the self) with more supportive and less aggressive behaviors (Heller & Tanaka-Matsumi,
1999). It is possible that when adolescents first encounter peers with depressive symptoms, they
may exhibit more compassionate behaviors. However, as they are further exposed to the
maladaptive behaviors of their friends with depression, they may become frustrated and less
supportive.
Sex Differences
Research consistently points to the finding that female adolescents experience higher
rates of depression than do males (Cyranowski et al., 2000; Nolen-Hoeksama & Girgus, 1994).
On average, females develop more intimate friendships and are more invested in them, but are
also more prone to experiencing disruptions in their interpersonal relationships (Rose &
Rudolph, 2006). Studies also indicate that compared to males, female adolescents are exposed to
more interpersonal stressors (Hammen, 2009a; Hankin, Mermelstein, & Roesch, 2007). Social
exchanges between female and male friends might also look differently. For example, females
are more likely to self-disclose to friends (Buhrmester & Prager, 1995; Landoll, Schwartz-Mette,
Rose, & Prinstein, 2011) and rehash problems with them (Rose & Rudolph, 2006). We consider
sex differences in the current study, testing whether associations between depressive symptoms
and behaviors vary across gender.

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The Role of Family Risk in Depressive Symptoms and Behaviors
A drawback of the interpersonal depression literature is the lack of attention to
developmental and contextual factors that may play a part in the presentation of adolescents’
social-behavioral deficits (Starr & Davila, 2008). Although adolescents seek independence, they
continue to look to parents for guidance on how to adaptively cope with and respond to
emotionally taxing situations (Morris, Silk, Steinberg, Myers, & Robinson, 2007). Adolescents
who are exposed to family aggression and conflict may lack opportunities to learn how
adaptively cope with emotions and interpersonal challenges (Abela & Hankin, 2009).
Consequently, they might be ill equipped to handle the social complexities that accompany
adolescence (Rudolph, 2009). Adolescents who witness family aggression in addition to battling
depressive symptoms may be especially at risk for exhibiting maladaptive interpersonal
behaviors.
Research has yet to investigate whether exposure to family aggression heightens
adolescents’ susceptibility to demonstrating maladaptive communication patterns. However, the
role of family aggression is worthy of further study for several reasons. First, numerous studies
indicate that coming from families marked by high degrees of conflict and aggression as well as
low levels of warmth and support is associated with risk for depressive and internalizing
symptoms (Alloy, Abramson, Smith, Gibb, & Neeran, 2006; Bond, Toumbourour, Thomas,
Catalano, & Patton, 2005; Hussey, Chang, & Kotch, 2006; Margolin, Vickerman, Oliver, &
Gordis, 2010; Schwartz, Sheeber, Dudgeon, & Allen 2012; Sheeber, Hops, Alpert, Davis, &
Andrews, 1997; Zinzow et al., 2009). Exposure to family aggression has also been tied to
interpersonal problems during adolescence, such as peer conflict (Narayan, Englund, Carlson, &
Egeland, 2014), aggression (Moretti, Obsuth, Odgers, & Reebye, 2006) and victimization (Han
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& Margolin, 2015; Mohr, 2006). Moreover, a history of child maltreatment is related to higher
levels of interpersonal stress in adolescents, particularly following the onset of a depressive
episode (Harkness, Lumley, & Truss, 2007). Building upon this literature, the current study
examines whether family aggression, particularly parent-to-child and parent-to-parent (i.e.,
marital) aggression, intensifies associations between depressive symptoms and observed
behaviors among friends.
Present Study
The current study developed a comprehensive coding system to examine associations
between depressive symptoms and observed communication patterns that unfold during
friendship interactions. The first aim of this study is to study the extent to which participants’
depressive symptoms relate to their own as well as their friends’ potentially maladaptive
behaviors during a peer discussion task. Grounded in interpersonal theories of depression, we
hypothesized that adolescents’ depressive symptoms would be positively related to their own
tendencies to display 1) irritability, hostility, or cynical attitudes (referred to as “irritability” for
simplicity), 2) obscenities in their language, 3) conversational self-focus, and 4) critical or hostile
talk directed toward their participating friend. On the other hand, depressive symptoms were
expected to be associated with less observed support toward participating friends (Hypothesis
1a). We also explore partner effects, testing whether participants’ depressive symptoms are
associated with their friends’ observed irritability, obscenity talk, conversational self-focus,
critical behaviors, and supportive behaviors. We predicted that adolescent depressive symptoms
would be associated with more observed criticism and less observed support from their partners
(Hypothesis 1b). Partner effects of depressive symptoms on irritability, obscenity use, and
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conversational self-focus were exploratory in nature. Last we explore whether sex moderates
actor or partner effects, predicting that these effects would stronger for females (Hypothesis 1c).
The second aim of this study is to investigate whether exposure to family aggression,
specifically parent-to-child aggression and parent-to-parent aggression, moderates associations
between depressive symptoms and observed communication patterns. In line with previous
research, we predicted that depressive symptoms would confer greater risk for these behavioral
patterns, but that family aggression would moderate these associations. In particular, we
proposed that depressive symptoms would be associated with more irritability, obscenity,
conversational self-focus, and critical talk, and with less supportive talk in the context of high
family aggression (Hypothesis 2). Further, we conduct exploratory analyses to examine whether
these moderation analyses vary across sex.
Methods
Participants
The present study utilized data from 111 adolescent same-sex friend pairs (50 female
dyads). Although participants ranged in age from 14 to 24 years (M = 17.63, SD = 1.32), the
majority (92.8%) were between the ages of 15 to 19 years old. Regarding ethnicity, 34.2% of
participants identified as Hispanic/Latino, and reported racial breakdown was as follows: 1%
American Indian/Alaska Native/Native Hawaiian or Pacific Islander, 5.9% Asian, 16.7% Black
or African American, 56.8% Caucasian, and 19.8% Multiracial.
Participants were part of a larger longitudinal project investigating associations between
mental health, interpersonal relationships, and various stressors among parents and their children.
Families from the greater Los Angeles community were initially recruited for participation via
fliers, advertisements, and word-of-mouth. To be eligible for participation, parents needed to be
together and living with each other for at least three years, be able to complete study procedures
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in English, and have a child (i.e., “youth”) who was of the appropriate age at the time of
recruitment. Two cohorts of families participated in the study. The first cohort was recruited
during wave 1 of data collection, and a second cohort of families during wave 3 (for a more
detailed description of study participants, see Margolin et al., 2010). The current study used data
from participants in both cohorts during wave 5. At this time, youth selected a same-sex friend
(“peer”) to participate in the lab with them. Youth and their nominated peer are hereby referred
to collectively as dyads or friend dyads and individually as adolescents or participants.
Adolescents reported knowing their participating friend for an average of 5.86 years (SD
= 4.23 years, range: 0-18 years), with 79.5% knowing their friend for at least three years.
Approximately 88.2% of adolescents reported that the friend with whom they were participating
was one of their five closest friends. Most adolescents lived with at least one parent (94.9%), and
68.4% reported residing with both parents.
In order to be included in this study, friend dyads needed to participate in an in-lab,
video-recorded peer discussion task and complete relevant questionnaire data. One-hundred-
thirty-one youth participated in the study wave, but 20 were excluded from this study because
they were unable to bring a friend into the in-lab procedure (n = 16), participated in the
videotaped discussion remotely with a peer, but the quality of the recording was too poor for
coders to make accurate ratings (n =3), or participated in the in-lab procedure but did not consent
to be video recorded (n = 1).
Procedures
Consent was obtained from parents or legal guardians prior to in-lab visits for all
participants who were under 18-years-old. At the start of the in-lab procedure, participants
completed consent (18-years or older) or assent (under 18-years-old) forms. The Institutional
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Review Board approved all study procedures. Youth and peers filled out questionnaires
regarding mental health symptoms, family history, and interpersonal relationships on individual
computers in separate rooms to ensure privacy.
As part of the in-lab protocol, dyads participated in structured videotaped discussions,
which were adapted from the Peer Interaction Task (Dishion, Andrews, & Crosby, 1995). We
utilized coded data from six separate discussion segments, each lasting 5 minutes. Adolescents
were instructed to discuss the following during these six segments: 1) a problem with a person
the youth identified from an earlier list, why it is a problem, ways to solve the problem, and how
the peer can help; 2) a problem with a person the peer identified from an earlier list, why it is a
problem, ways to solve the problem, and how the youth can help; 3) goals for the following year;
4) aspects that they like and don’t like about people they are dating or would like to date; 5) their
friends, what they do together, and what they like and don’t like about them and; 6) something
that they would like to change about themselves. Prior to the discussions, each participant
completed a form identifying individuals with whom they had unresolved issues in order to help
them select specific topics for the first two discussion segments. In addition, experimenters
provided dyads with cue cards to remind them of the topics, as well as knocked on the door to
signal the beginning and end of each discussion topic.
Discussions took place in a room set up with cameras and a one-way mirror. Youth and
peers sat alongside each other in separate chairs. The dyad was video recorded at three angles so
that recordings could capture a close up of the youth, a close up of the peer, and a shot of the
dyad.
Development of the Peer Relationship Coding Manual. A coding manual was created
to rate content and behaviors theorized to relate to friendship quality, depressive symptoms, and
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25
interpersonal difficulties. Published research and theory on adolescent depression (e.g., Rudolph,
2009; Segrin, 2000), previously established coding manuals (e.g., Rusby, Estes, & Dishion,
1991; Schwartz-Mette & Rose, 2007), and consultations with coding experts were all used to
inform the development of the system. We used a global rating system such that coders
separately rated the youth and peer after observing each five-minute discussion segment.
Consistent with previous coding systems (Iturralde & Margolin, 2015), ratings were given based
on both severity and frequency of the behavior (0 = None and 3 = A lot). Scores for each code
were then averaged across the six segments.
After an initial coding system was developed, a subset of videotaped discussions was
selected to pilot the coding system. During this time, research assistants watched videos
individually, in coding pairs, and as a group in order to discuss and clarify codes, remove codes
that were irrelevant or unclear, and add new informative codes. After finalizing the coding
system, research assistants who were unaware of participants’ mental health status or
questionnaire data were randomly assigned to watch and code the videotaped discussions. Two
coders, trained in this rating system, independently rated each video-recorded discussion. The
coding team met weekly in order to prevent coder drift.
Coders (all female) viewed each 5-minute discussion twice—once to watch and rate the
youth and once for the peer. Whether coders rated the youth or peer first was counterbalanced
across coders and discussion. That is, one coder rated the youth first in the odd-numbered
discussions and the peer first in even-numbered discussions; the second coder of that pair rated
the peer first in the odd-numbered discussions and the youth first in the even-numbered ones..
Inter-rater reliability for all the codes was conducted using intra-class correlations, and ratings
were subsequently averaged across the two coders.
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26
Measures
Observed Behaviors. Table 1 displays the five codes used in the present study, examples
of each code, and inter-rater reliability (ICC range = .62- .90). Irritability was rated when
adolescents behaved or spoke in a way that indicated that they held a hostile or distrusting
perspective of the world or other people. This included making generalized negative statements
about people, expressing annoyance about a number of events, or exhibiting a generally
frustrated or angry attitude that was not directed toward the other person in the room. Verbal
Obscenities captured the extent to which adolescents used profane, vulgar, or discriminatory
words. To aid in consistent ratings, a sample list of obscene words was created that was adapted
from the Linguistic and Inquiry Word Count’s (LIWC; Pennebaker, Booth, & Francis, 2007)
dictionary of curse words. Based on coding team discussions, other relevant obscenities were
added and commonly used curse words were assigned ratings. Conversational Self-Focus,
grounded in research by Schwartz-Mette and Rose (2009, 2016) and adapted from the
Interpersonal Processes in Friendships Observational Coding System (Schwartz-Mette & Rose,
2007), captured instances when adolescents redirected the conversation away from friends and
toward themselves. Examples included participants inserting examples about themselves during
their friends’ discussion of a problem, continuing to talk about themselves regardless of their
friends’ responses, dominating a conversation without taking into account their friends’ opinions,
or changing the topic in the middle of their friend discussing something personal. Criticism of
Friend, adapted from the Negative Interpersonal Code (Rusby et al., 1991), combined two
codes: 1) Verbal Criticism: Putting-down or insulting the other person in the room. Some friends
tended to coat their insults with humor, making it difficult to discern intent of the comment.
Therefore, even critical comments that could be perceived as jokes were coded. 2) Non-verbal
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27
Criticism: Displaying non-verbal critical or disapproving behaviors (e.g., eye rolling, glaring)
toward the other person. These two codes were highly correlated (r = .55), so we computed a
composite score by summing the ratings for each discussion segment and then averaging the
scores across all six segments. Therefore, the final code was rated on a 0-6 scale. Supportive
Talk, modified from the Positive Interpersonal Code (Rusby et al., 1991), was assigned when
adolescents made positive, complimentary, or supportive comments toward the friend in the
room.
Adolescent Depressive Symptoms. Adolescents reported on their own depressive
symptoms using the Beck Depression Inventory, Second Edition (BDI-II, Beck, Steer, & Brown,
1996), a questionnaire that taps into cognitive (guilty feelings), affective (sadness), and
behavioral (changes in sleep) components of depression. The BDI-II has been used in previous
research assessing adolescent depressive symptoms and coded behaviors (e.g., Lougheed et al.,
2016). Scores are based on a 4-point scale, anchored at 0 and 3. In this study, one item assessing
suicide risk was dropped due to reporting concerns. Items were averaged to create a composite
depressive symptoms score, with good internal consistency (alpha = .88), and scores were treated
as continuous variables. In terms of endorsement, 91.4% of adolescents reported experiencing at
least one depressive symptom, with approximately 20% reporting at least mild levels of
symptoms of depression (scores of 14 or above), 7.7% moderate levels (20 or above), and 2.7%
severe depressive symptom levels (29 or above).
Family Aggression. We created this variable by taking into account both exposure to
parent-to-child aggression and parent-to-patent aggression, modifying an approach used by Del
Piero, Saxbe, and Margolin (2016). We combined data from two questionnaires and re-scaled
items from both measures so that they were all scored as 0 = never, 1 = 1 per year, 2 = 2-5 times
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28
per year, and 3 = 6 or more times a year. Parent-to-child aggression was measured with
seventeen items from an adapted version of the Conflict Tactics Scale (Straus, 1979). Target and
peers reported on how frequently they were recipients of psychological (“called child dumb or
lazy”) and physical (“slapped child”) aggression from their mother, father, or parental
figure/caregiver within the past year. We first calculated the mean score across questionnaire
items, and scores were then averaged across both parents. The average of thirty-nine items from
the Domestic Conflict Index (Margolin, Burman, John, & O’Brien, 2000) was used to assess
parent-to-parent conflict. Youth and peers reported on the extent to which their mother and father
(or parents’ current romantic partner) engaged in emotional (“ridiculed”) and physical (“thrown
an object”) conflict with their partners. Scores were averaged across mothers, fathers, and
respective romantic partners. Because the parent-to-parent and parent-to-child aggression
measures were highly correlated (r = .65, p < .001), we averaged them together to create a
composite family aggression score. Seventeen participants were not administered the DCI
because the items did not apply to them (e.g., did not have contact with one or both parents,
parents were separated and not in romantic relationships). For these participants, just the parent-
to-child aggression score was used.
Measures of Task Validity. Three approaches were used to explore whether discussion
tasks were accurate reflections of friends’ actual conversations. First, after completing the
discussion, participants reported on, 1) how “honest or frank” they were during the discussion (0
= not at all and 4 = very), 2) how much they were able to express their points of view during the
discussion (0 = not at all and 4 = a lot), 3) how often they have similar discussions with any
friends (0 = never and 4 = very often), and 4) how similar the discussion was to other discussions
that adolescents had with their participating friends ( 0 = not at all similar, 4 = very similar).
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Second, an Engagement code (ICC = .76) was developed to assess whether participants adhered
to discussion task instructions and displayed interest in what their friends were saying (e.g.,
asking questions to get more information, maintaining eye contact). Scores ranged from 0 (not at
all) to 3 (a lot). Last, an Artificial code, previously created for these discussions (Iturralde &
Margolin, 2015), assessed whether participants appeared to be performing for the camera or
exhibiting stiff, unnatural, or artificial mannerisms. The presence (1) or absence (0) of these
behaviors was assigned to the target and peer for each discussion segment.
Covariates. We tested several covariates for inclusion in moderation analyses due to
possible associations with depressive symptoms or observed behaviors (Aneshensel & Sucoff,
1996; Roberts & Sobhan, 1992). Ethnicity was a dichotomized variable with -.5 = non-
Hispanic/Latino and .5 = Hispanic/Latino. Sex was categorized as -.5 = males and .5 = females.
Applying an approach used by Iturralde (2015), Neighborhood Poverty was the percentage of
families in the participants’ neighborhood who lived below the federal poverty line and was
computed using the American Community Survey zip code indexed dataset (U.S. Census
Bureau, 2011). Age was the value provided by participants.
Analytic Strategy
Descriptive statistics were calculated using SPSS version 24. All coded variables were
log transformed prior to correlation and regression analyses in order to handle right skew.
Bivariate correlations were run using a pairwise or “checkerboard” dataset, and p values were
adjusted for non-independence. That is, in addition to accounting for the interdependent nature of
the data (e.g., friends within a dyad would be expected to be more similar to one another than to
other dyad members), such methods also take into account statistically that the dyads are
theoretically indistinguishable or exchangeable, which is when they are not distinct from one
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30
another on a non-arbitrary variable (Fitzpatrick, Gareau, Lafontaine, & Gaudreau, 2016; Griffin
& Gonzalez, 1995).
To test Hypotheses 1a (HO1a: adolescent depressive symptoms would be related to more
of their own observed irritability, obscenity use, conversational self-focus, and criticism, and less
supportive talk) and Hypothesis 1b (HO1b: adolescent depressive symptoms would be related to
more criticism and less support from their friends), we used structural equation modeling (SEM)
in Mplus 7.0 (Múthen & Múthen, 2007), using robust standard errors to account for data non-
normality. In particular, an actor-partner interdependence model (APIM) was specified in order
to simultaneously examine associations between each person’s depressive symptoms and, a) their
own observed communication behaviors, and b) their friends’ observed communication patterns,
while also taking into account variance shared across participants in their levels of depressive
symptoms (Kenny, Kashy, & Cook, 2006). Because we wanted to treat the two dyad members as
exchangeable, we followed guidelines recommended by Olsen and Kenny (2006) and
constrained the following parameters to be equal: 1) actor effects, 2) partner effects, 3) predictor
means, 4) predictor variances, 5) outcome intercepts, and 6) residual variances. Five separate
APIMs were run in order to test associations between depressive symptoms and the five coded
behaviors. Figure 1 visually depicts a simplified model of the APIM used for all five analyses.
We statistically tested for indistinguishability by examining differences in model fit between the
constrained (i.e., indistinguishable) and unconstrained (i.e. distinguishable) models using the
Satorra-Bentler scaled chi-square difference test. Multiple group analysis was used to examine
gender as a moderator of the five APIM models (HO1c). First, we allowed all parameters to be
free across gender. Next, we individually constrained actor and partner paths to be equal across
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31
gender and tested changes in model fit, again using the Satorra-Bentler scaled chi-square
different test.
We ran a series of multilevel regression models in Mplus 7.0 in order to test Hypothesis 2
(HO2), which is that family aggression moderates associations between depressive symptoms
and individuals’ own observed communication patterns. Variables were grand mean centered
prior to moderation analyses, as we were interested in how adolescent’s depressive symptoms
and exposure to family aggression relative to the entire sample was related to their own observed
behaviors. There were two cases of missing data for depressive symptoms and one case of
missing data for the family aggression variable, and full information maximum likelihood
estimation was used to handle missing data. Robust standard errors (MLR) were used in order to
mitigate the non-normality of the data. For the final component for Aim 2, which was to examine
the role of gender in these moderation analyses, we again used multiple group analyses.
Results
Authenticity of Peer Discussion Task
Overall, discussions tended to be ecologically sound. An estimated 73.2% of participants
reported being very honest or frank during the discussion (M = 3.68, SD = .61), 91.3% reported
being at least moderately able to express their opinions (M = 3.53, SD = .67), 71.3% reported
that they at least often have conversations similar to the lab discussions with friends (M = 2.94,
SD = 1.02), and 69.5% reported that the discussion was at least moderately similar to other
conversations that they have had with their participating friend (M = 2.97, SD = 1.10). The
average Engagement score (M = 2.64, SD = .40, with “3” being the maximum score) indicated
that coders rated participants as being quite interested in what the other was saying and sticking
closely to the discussion instructions. Thirteen (1.95%) out of the 666 5-minute discussion
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32
segments, involving 6 dyads, were assigned an Artificial score by at least one coder, suggesting
that dyads overall appeared to speak genuinely about topics during the discussion. Dyads who
were and were not assigned an Artificial score did not significantly differ from each other in
terms of levels of depressive symptoms, family aggression, or observed behaviors, so they were
retained in analyses.
Descriptive Statistics
Means, standard deviations, and ranges for the entire sample are presented in Table 2.
With respect to frequency of observed variables, irritability was coded as being present in at least
one of the dyad members during at least one of the discussion segments 50% of time, obscenities
64.9%, conversational self-focus 55.9%, criticism 63.5%, and supportive talk 86%.
Table 3 illustrates descriptive statistics stratified by sex and ethnicity (Hispanic/Latino
versus Non-Hispanic Latino). With respect to gender, males reported lower levels of depressive
symptoms, t(182.51) = -2.39, p = .02, engaged in less conversational self-focus, t(185.37) = -
2.44, p = .02, and showed less supportive talk during the discussions, t(180.64) = -2.67, p = .01,
compared to females. Non-Hispanic/Latino participants, compared to Hispanic/Latino
participants, used fewer obscenities, t(115.83) = -2.23, p = .03, and engaged in more
conversational self-focus, t(205.54) = 3.60 p < .001. No other group differences were found.
Intraclass correlations between the scores of adolescents nested within friend dyads were
calculated to assess similarity among friend dyads on variables of interest. Dyad members were
not significantly related to one another in terms of their levels of depressive symptoms (ICC =
.06, p = .38). They also were not alike regarding family aggression exposure (ICC = - .02, p =
.79). However, as would expected of adolescents nested within friend dyads (Rose et al., 2016),
they were statistically similar to one another on all other variables of interest: irritability (ICC =
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33
.35, p < .001), obscenity (ICC = .66, p < .001), conversational self-focus (ICC = .15, p = .03),
criticism (ICC = .59, p <.001), peer support (ICC = .41, p < .001), age (ICC = .65, p < .001),
ethnicity (ICC = .44, p < .001), and neighborhood poverty (ICC = .45, p < .001).
Table 4 provides correlations among the primary continuous variables for the entire
sample. Depressive symptoms were positively associated with family risk and irritability, but
were not significantly correlated with any of the other coded variables. Family risk was
positively correlated with observed irritability and conversational self-focus. Obscenity use,
irritability, and conversational self-focus were all positively associated with one another.
Obscenity use was also positively correlated with criticism. Age, supportive talk, and
neighborhood poverty were not significantly associated with any study variables.
Empirical Test of Indistinguishability
Prior to estimating APIMs, we conducted tests of model invariance to determine if the
data supported our treatment of the dyad members as indistinguishable. In particular, we tested
whether differences in model fit were statistically significant between SEM models that treated
dyads as distinguishable (free model) versus indistinguishable (constrained model). We also
constrained model covariates, gender and ethnicity, to be equal across dyad members. Results
did not suggest a significantly worsened model fit for the indistinguishable model when either
irritability, Δ χ
2
(9) = 7.08, p = .63, obscenity, Δ χ
2
(9) = 9.19, p = .37, conversational self-focus,
Δ χ
2
(9) = 6.17, p = .72, criticism, Δ χ
2
(9) = 12.70, p = .18, or support, Δ χ
2
(9) = 9.95, p = .35,
were the outcome variables. Thus, the APIM models can be conceptualized as statistically
indistinguishable in addition to being considered exchangeable on theoretical grounds.
Actor and Partner Effects of Depressive Symptoms on Observed Behaviors
In order to test associations between depressive symptoms and observed communication
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34
patterns, we conducted five parallel APIM models, each one with depressive symptoms as the
predictor variable and one of the coded communication patterns (irritability, obscenity,
conversational self-focus, criticism of friend, support of friend) as the outcome variable. Table 5
provides results of actor and partner effects of all five APIM models. Contrary to HO1a, there
were no significant actor effects for irritability, obscenity use, conversational self-focus,
criticism, or supportive talk. However, significant negative partner effects emerged for both
irritability (ß = -.13, SE = .05, p = .02) and conversational self-focus (ß = -.13, SE = .06, p = .02).
That is, adolescents’ depressive symptoms predicted their friends’ tendencies to engage in less
irritable and self-focused talk. HO1b, that adolescent depressive symptoms would be related to
less support and more criticism from friends, was not supported.
Gender as a Moderator of Actor and Partner Effects
Multigroup analyses suggested that gender moderated the actor effect of depressive
symptoms on criticism, Δ χ
2
(1) = 7.21, p = .007. For females, adolescents’ level of depressive
symptoms was positively related to their own tendency to criticize their friends during the
discussion (ß = .17, SE = .08, p = .03). For males, the path was not significant (ß = -.07, SE =
.07, p = .35). Gender also moderated the partner effect for depressive symptoms on criticism.
The direction of the partner effect was negative for males and positive for females, although
neither path was statistically significant. Gender did not moderate actor or partner effects for any
of the other observed behaviors.
Family Aggression as a Moderator of Associations Between Depressive Symptoms and
Communication Behaviors
We then examined the hypothesis (HO2) that exposure to family aggression would
moderate associations between depressive symptoms and observed communication behaviors.
Multilevel models, which adjust for the nested nature of the data, used individual coded
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35
behaviors from all individuals as the outcome. We included within level covariates (e.g.,
ethnicity, age, and neighborhood poverty) on level one and dyad sex, a between level covariate,
on level two. Neighborhood poverty did not significantly predict any of the observed behaviors,
nor did it change the significance of the effects, so it was subsequently dropped from the models.
We conducted five parallel multilevel regression analyses, testing each observed behavior
separately. Table 6 provides results from these analyses. Three significant two-way interactions
emerged. First, there was a significant Family Aggression X Depressive Symptoms interaction
for irritability (ß = .27, SE = .11, p = .02). As shown in Figure 2, associations between depressive
symptoms and observed irritability were significantly positive in the context of high (+1 SD; b =
.04, p = .047), but not low (minimum value; b = -.02, p = .36), levels of family aggression. There
was also a significant Family Aggression X Depressive Symptoms interaction for obscenity use
(ß = .16, SE = .06, p = .01), which is displayed in Figure 3. At high levels of family aggression,
there were positive associations between depressive symptoms and obscenity talk, (b = .06, p =
.002). At low levels of family aggression, associations were not significant (b = .003, p = .92).
Figure 2 visually depicts these two interaction patterns.
Last, there was a significant interaction when conversational self-focus was the outcome
variable (ß = .19, SE = .07, p = .01), yet not in a direction that was in accordance with
hypotheses. Figure 4 illustrates that at low levels of family aggression, associations between
depressive symptoms and conversational self-focus were significant and negative, (b = -.04, p =
.02). At high levels of family aggression, the relationship was not significant, (b = .003, p = .81).
Family aggression did not moderate associations between depressive symptoms and criticism or
supportive talk.

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36
Sex Differences
In order to examine sex differences regarding main and interactive effects of depressive
symptoms and family aggression on the observed behaviors, separate multi-group analyses were
conducted for each of the observed behavior outcome. Participant sex did not moderate any of
the interaction effects. However, sex did moderate the main effect of family aggression on three
observed behaviors. First, sex moderated associations between family aggression and irritability,
Δ χ
2
(1) = 70.53, p <.001. Family aggression was significantly associated with irritability for both
females (ß = .40, SE = .12, p = .001), and males (ß = .17, SE = .09, p = .046), but females
appeared to be more sensitive to family aggression. A similar pattern emerged regarding
associations between family aggression and conversational self-focus, Δ χ
2
(1) = 5.32, p = .02.
The separate paths were significant for both males (ß = .11, SE = .05, p = .04) and females (ß =
.33, SE = .12, p = .01), though the path was stronger for females. Finally, sex moderated
associations between family aggression and support, Δ χ
2
(1) = 57.11, p <.001. The path was
negative and non-significant for males (ß = -.06, SE = .08, p = .44). For females, the association
between family risk and supportive talk was positive and just missed significance (ß = .20, SE =
.10, p = .052).
Discussion
This study developed a novel coding system in order to investigate whether adolescent
depressive symptoms manifested as observable communication patterns during interactions
between friends. Using an APIM, we first examined whether adolescents’ depressive symptoms
related to both their own and their friends’ behaviors during a peer discussion task. In support of
HO1a, for adolescent females, depressive symptoms were related to their own propensity to
criticize friends. However, contrary to that hypothesis, there was no additional evidence that
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37
adolescents’ depressive symptoms were associated with their own irritability, obscenity use,
conversational self-focus, or supportive talk. We also found support for the general idea that one
person’s level of depressive symptoms is associated with their friends’ behavior, which was
exhibited in decreased irritability and conversational self-focus. However, the specific
predictions of HO1b that adolescent depressive symptoms would be related to higher levels of
criticism and lower levels of support in their friends were not supported. In partial support of H2,
depressive symptoms were associated with observed irritability and obscenity use when
adolescents were also exposed to family aggression within the past year. Unexpectedly,
conversational self-focus was negatively associated with depressive symptoms under conditions
of low family aggression. We did not find any sex differences regarding these interactions. Yet,
overall family aggression was associated with irritability and conversational self-focus (of
somewhat greater magnitude for females); family aggression also was differentially associated
with supportive talk for males versus females.
Actor and Partner Effects of Depressive Symptoms on Observed Behaviors
Adolescent females’ level of depressive symptoms was related to their observed tendency
to criticize their friends during the peer discussion task. Literature premised on interpersonal
theories of depression and stress-generation propose that females are more prone to experiencing
social stress, such as peer problems, than their male counterparts (Hankin et al., 2007; Shih,
Eberhart, Hammen, & Brennan, 2006). Building on these findings, adolescent females who are at
risk for depression may be critical toward their close friends, which may lead to peer resentment
and friendship dissolution. Because this study did not investigate associations between criticism
and friendship difficulties, this idea is speculative and worthy of investigation in future studies.
Depressive symptoms and criticism were not correlated for males. Important to note is that in our
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38
coding system, insulting comments were counted as critical even if they may have been jokes. It
is thus possible that the “criticism” that was rated for males actually reflected humor, which has
been found to be related to closeness in male adolescent friendships (Rose, Smith, Glick, &
Schwartz-Mette, 2016). A more detailed analysis of the types of behaviors that were coded as
criticism for males versus females may be informative.
It is surprising that depressive symptoms were not directly related to any of the other
observed behaviors, as these codes were designed to capture communication patterns that have
been linked with depression (Segrin, 2000). It is possible that a 30-minute conversation with one
close friend may not be sufficient to comprehensively tap into interpersonal behaviors associated
with depressive symptoms. Indeed, much of the research that has successfully found links
between depressive symptoms and maladaptive interpersonal behaviors (e.g., excessive
reassurance seeking, negative feedback seeking), have utilized self-report questionnaires that ask
about the presence of interpersonal deficits more broadly (Prinstein et al., 2005; Schwartz-Mette
& Smith, 2016). Furthermore, some behaviors that may be indicative of emotional distress in
older individuals, such as using curse words, may be more normative during adolescence.
This study extends research on depressive symptoms and communication patterns by
investigating how adolescents’ depressive symptoms impact their friends’ behaviors, even after
accounting for friends’ symptoms. Counter to hypotheses, adolescent depressive symptoms were
unrelated to their friend’s tendencies to criticize them or offer less support. Research that has
identified links between depressive symptoms and these types of peer behaviors typically use a
micro-level coding system, rating how adolescents respond in the moment to their friends’
behaviors (Lougheed et al., 2016). In contrast, in the present study, we assigned participants one
rating per each discussion segment. Thus, we were unable to capture adolescents’ direct
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39
reactions to behaviors (e.g., rolling one’s eyes in response to a particular comment that a friend
makes, offering a supportive comment in direct reaction to a friends’ negative comment about a
situation), and whether these responses varied based on level of depressive symptoms. A more
fine-grained analysis of adolescent behaviors may be necessary in order to test how individuals
act toward friends struggling with depressive symptoms.
Adolescent depressive symptoms were associated with less irritability and
conversational-self focus in friends. This finding merges with research that implies that there
may be a reinforcing quality to depressive symptoms (Heller & Tanaka-Matsumi, 1999;
Schwartz et al., 2012). Individuals who recognize that their close friends are depressed may
temporarily curtail their own negative or potentially distracting behaviors in order to attend to
their friends. For example, they might hold back from sharing their own frustrations about the
world or limit discussions about themselves. Overtime, however, they may become resentful and
behaviorally distance themselves from their depressed friends. Alternatively, although
conversational self-focus was carefully constructed to assess adolescents’ tendencies to redirect
conversations away from others and toward themselves (Schwartz-Mette & Rose, 2016), this
code may have also picked up on adolescent attempts to connect and empathize with friends
(e.g., That also happened with my mom and me.) The negative partner effect of depressive
symptoms on conversational self-focus may thereby reflect participants’ tendencies to withdraw
from their depressed friend. Overall, minimal work has studied links between depressive
symptoms and observed friend behaviors, and extending this line of research to include how it
may be linked with friendship difficulties and future risk for depression may be productive.

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40
Family Aggression as a Moderator and Main Effect of Communication Patterns
The significant interaction between depressive symptoms and family aggression on
observed irritability and obscenity use highlights the importance of considering both distal and
proximal risk factors for interpersonal patterns. Emotion socialization grounded research
emphasizes that adolescents continue to learn to regulate and express emotions based on
exchanges with their parents, as well as view interactions with their parents as blue prints for
how to act in other close relationships (Lougheed et al., 2016; Morris et al., 2007; Patterson,
Dishion, & Bank, 1984). Thus, adolescents exposed to anger and dismissiveness from family
members may lose out on learning opportunities to successfully handle emotions and
consequentially be more likely to resort to behaviors indicative of anger, such as irritability and
cursing.
Moreover, individuals from aggressive families might be at risk for developing hostile
attributional biases (Dodge, Bates, & Pettit, 1990; Taft, Schumm, Marshall, Panuzio, &
Holtworth-Monroe, 2008). That is, they may hold negative perceptions of their surroundings
(Nelson & Coyne, 2009), which may play out as irritability or other maladaptive behaviors when
with close friends (Dodge, Bates, Pettit, Valente, 1995). Although adolescents with depressive
symptoms are more prone to negative cognitive biases (e.g., negative world schemas, feelings of
hopelessness; Abela & Hankin, 2009), they may be able to temporarily control their behavioral
tendencies with friends. However, when also faced with family aggression, the resources and
behavioral regulatory abilities of these already vulnerable adolescents may be overtaxed.
Research that considers the developmental context regarding at-risk adolescents’ interpersonal
functioning has mainly focused on parent, particularly maternal, depression as a family risk
FRIEND INTERACTIONS

41
factor (Hammen, 2009b; Hammen, Shih, & Brennan, 2004). Results from the present study
underline the importance of considering additional family risk variables.
An unanticipated finding was the significant interaction between family aggression and
depressive symptoms on conversational self-focus. The inverse relationship between
conversational self-focus and depressive symptoms was significant at low levels of family
aggression. These complicated results further point to the importance of fully unpacking the
meaning of the conversational self-focus code across different discussion segments and levels of
friendship quality.
Although not included as part of our original set of hypotheses, participant sex
moderated the main effect of family aggression on irritability and conversational self-focus.
Links between family aggression and irritability and conversational self-focus were significant
for both males and females. However, females appeared to be more sensitive to the effects of
family aggression, in line with research suggesting that the impact of interpersonal stressors may
be particularly potent for females (Rose & Rudolph, 2006). Family aggression was associated
with increased supportive talk for females. Females place a lot of importance on social
relationships. Perhaps, in order to compensate for their aversive family experiences, they are
especially invested in forming close peer relationships, and it may be adaptive for them to show
positive and supportive behaviors toward others. Yet, this notion is in need of empirical testing.
Finally, although not the focus of the present study, it is worth noting that we did not find
similarities between youth and peers’ depressive symptoms. Currently, the literature is mixed
regarding homophily of depressive symptoms among friends. Whereas some research suggests
that adolescents gravitate toward others with similar levels of depressive symptoms (Brechwald
& Prinstein, 2011; Stevens & Prinstein, 2005), other research indicates that they actually select
FRIEND INTERACTIONS

42
friends with different levels of depressive symptoms (Giletta et al., 2011). Different conditions,
such as the social status of the friend with depressive symptoms (Prinstein, 2007) or the amount
of time spent together might alter when depressive symptoms between friends are correlated.
Limitations
There are various limitations of this study that are worthy of discussion. Perhaps the
biggest shortcoming was that we did not assess whether observed behaviors were related to
friendship quality or rejection. A main premise of interpersonal theories of depression is that
adolescents prone to depression may engage in maladaptive interpersonal patterns that
subsequently strain close relationships (Coyne, 1976; Joiner, Coyne, & Blalock, 1999; Joiner &
Timmons, 2009). We developed codes to capture certain behaviors that we hypothesized, based
on prior research, were linked with either depressive symptoms or social behavioral deficits. Yet,
because we did not actually assess whether these behaviors predicted peer problems, we cannot
conclusively identify them as interpersonal deficits. Future research that examines whether these
observed behaviors are related to decreased friendship satisfaction or friendship dissolution, for
example, can shed light on behaviors that are indicative of depressive symptoms or interpersonal
problems.
Also, the cross-sectional nature of the data impedes the use of any causal claims
regarding depressive symptoms, family aggression, and observed communication patterns. That
is, it is unknown whether the interaction between family aggression and depressive symptoms
predicts observed communication patters, whether family aggression in conjunction with these
behaviors actually confers greater risk for depression, or whether there may be additional
unstudied variables jointly influencing all of these factors. Furthermore, although the majority of
our participants were middle and late adolescents, a few (n = 4) were over the age of twenty. Age
FRIEND INTERACTIONS

43
was not significantly associated with any of our variables, though it would have been ideal for all
participants to be within the adolescent age range.
Due to reasons of parsimony and sample size limitations, we averaged family aggression
scores across mothers and fathers. Yet, the literature suggests that mother and father aggression
may differentially impact offspring (Baldry, 2007; Han & Margolin, 2015). Furthermore, we
averaged together family-to-child aggression and parent-to-parent aggression as one variable
instead of looking at the distinct impact of these family risk factors. Examining mother and
father aggression, as well as parent-to-child and parent-to-parent aggression separately as
moderators and main effects of observed communication patterns may offer further insight into
how family factors influence adolescent friend interactions.
All members of the coding team were female, which raises the possibility of coding
biases, although extensive discussions were conducted with team members about how to
recognize and overcome gender biases when assigning ratings. Finally, we focused on depressive
symptoms in a community sample of adolescents, as we were interested in identifying behaviors
of individuals at risk for but not necessarily diagnosed with depression. Although it has been
argued that depression is best thought of as a dimensional rather than categorical construct
(Hankin, Fraley, Lahey, & Waldman, 2005), it is possible that adolescents who are clinically
depressed may act qualitatively different than those with sub-clinical symptoms. Furthermore,
the majority of participants did not endorse high levels of depressive symptoms, with only 7.7%
reporting symptoms indicating moderate levels of depression or above. The restricted range of
scores may have prevented the ability to detect interpersonal behaviors in people with more
meaningful levels of depressive symptoms. Thus, our coding system may be better designed to
capture behaviors of individuals with higher levels of psychopathology.
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44
Summary and Implications
Despite the limitations of the present study, this study has many strengths, including the
use of a novel coding system, both observational and questionnaire data, data from both
adolescents and their friends (rather than relying on adolescents to report on their perceptions of
their friends’ behaviors and depressive symptoms), and dyadic data analytic approaches.
Although this study did not find extensive evidence to support the behavioral manifestations of
depressive symptoms in brief conversations, findings do add to the growing literature on parents
as important agents of emotion socialization. In other words, results suggest that family factors,
particularly when combined with adolescent depressive symptoms, continue to influence
individuals’ interpersonal behaviors with friends as they transition to adolescence and young
adulthood. Thus, interventions that seek to target interpersonal behaviors of adolescents may
benefit from including parents. Furthermore, depressive symptoms in adolescents may influence
their friends’ behaviors during casual conversations. A better understanding of how adolescents
respond to their friends at-risk for depression both in the moment and overtime can clarify links
between depression and interpersonal problems.
Overall, there is a dearth of research on how friends at-risk for depression interact with
friends. Continuing to identify behaviors that are and are not linked with depressive symptoms
can help researchers and clinicians become more adroit at detecting and helping adolescents at
risk for socio-emotional problems.

FRIEND INTERACTIONS

45
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Table 1.

Examples of Coded Behaviors and Inter-rater Reliability

Code Examples
Inter-rater
Reliability
Irritability/Cynicism • I don’t really trust my friends…I don’t really trust anybody
• That’s kind of how friends work in a cynical way. It’s like they take
everything that they can from you or need from you, and the rest,
they are not going to try to give you emotional support…people can
be very self-absorbed, very selfish.
• That’s what I hate about chicks they always want to change
stuff…they fake.
• People have always stepped over me…I’m tired of getting treated
like that.
• In this world, you can’t really look forward for the next year.
.65
Verbal Obscenities • He’ll be like ‘get the fuck out of here’ or stupid shit like that, and I’m
like ‘what the fuck, dog?’
• He would just be happy to fuck anyone.
• Coach is a dick, huh?
• I wish they only knew the shit they put us through.
.90
Conversational
Self-Focus
• Well, at least your parents talk. They can be in the same building.
Mine can’t.
• That’s just like me with my aunt. I had a problem with my cousin, it’s
resolved, but it’s like me and my aunt…
• Yeah my mom does that in the car too…my mom does that every time
we’re in the car.
.62
Criticism of Friend • So all you’re gonna be is a football player (said in judgmental tone)?
• Shut the fuck up.
• You’re crazy.
• Adolescent 1: I’m kind of indecisive.
Adolescent 2: You are, I’ll give you that. You’re pretty indecisive.
• Adolescent 1: What would you change about yourself?
Adolescent 2: Probably my attitude
Adolescent 1: Oh really? I figured you would have said to be taller
(both laugh). I actually didn’t realize how short you were until
someone called you a midget (laugh). I really didn’t, I was like oh
dang [Adolescent 2] really is pretty short.

.73
Supportive Talk • You’ve really helped in that you actually really believed in me.
That’s really cool.
• I think that’s a great goal.
• We know you’re really, really pretty. You get so many compliments.
Everyone is like ‘[name of adolescent] is so gorgeous.’
.77
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Table 2.

Descriptive Statistics of Study Variables

Note.
a
Reflects the percentage of families living below the poverty line in the participants’
neighborhoods.

M SD Min. Max. Possible Max
Depressive Symptoms 8.60 7.44 0 43.16 60
Family Aggression .35 .35 0 2.19 3
Obscenities .43 .59 0 3 3
Irritability .15 .26 0 1.50 3
Conversational Self-Focus .14 .19 0 .83 3
Peer Support .33 .30 0 1.42 3
Criticism .33 .56 0 3.42 6
Neighborhood Poverty
a
11.66 9.19 0 46.10 100
Age 17.63 1.32 14 24 N/A
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Table 3.

Mean Score Differences in Study Variables Across Gender and Ethnicity

Note. Means with matching superscripts differ from one another at p < .05. Standard deviations are in parenthesis next
to their means.
Dyad Sex

Ethnicity

Male Female Hispanic/Latino Non-Hispanic Latino

(N= 122) (N = 100) (N=76) (N=146)
Depressive Symptoms 7.50 (6.47)
a
9.94 (8.31)
a
8.95 (8.67) 8.41 (6.72)
Family Aggression .35 (.37) .36 (.33) .38 (.35) .34 (.35)
Irritability .15 (.26) .15 (.26) .14 (.24) .16 (.26)
Obscenities .48 (.66) .38 (.50) .57 (.71)
d
.36 (.51)
d

Conversational Self-Focus .11 (.17)
b
.18 (.21)
b
.09 (.14)
e
.17 (.21)
e

Critical Talk .37 (.57) .28 (.55) .37 (.57) .31 (.56)
Supportive Talk .28 (.25)
c
.39 (.34)
c
.31 (.29) .34 (30)
Neighborhood Poverty 11.15 (9.00) 12.28 (9.43) 12.41 (9.43) 11.27 (9.07)
Age 17.68 (1.39) 17.56 (1.23) 17.75 (1.43) 17.56 (1.25)
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Table 4.

Bivariate Correlations Between Continuous Variables of Interest
Note. Obscenity, irritability, conversational self-focus, criticism, and support have all been
log-transformed. A pairwise dataset was used to compute correlations, with adjustments
made to p values in order to account for non-independence.
+p < .10, * p < .05, **p < .01, ***p < .001.

1 2 3 4 5 6 7 8
1. Depressive Symptoms -
2. Family Aggression .29*** -
3. Obscenity .07 .05 -
4. Irritability .14* .31*** .24** -
5. Conversational Self-Focus .01 .19** .23** .33*** -
6. Criticism .01 -.05 .32** .04 .13+ -
7. Support .05 .05 .12 .02 .02 -.08 -
8. Neighborhood Poverty .001 .01 .12+ .13+ -.03 .03 -.04 -
9. Age .00 .06 .10 -.07 -.07 .05 -.06 .04
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Table 5.

Actor Partner Interdependence Models of Depressive Symptoms and Observed Behaviors
Note. Coeff = Standardized coefficient, SE = Standard error.

Outcome Variable Actor Effect
Coeff (SE)
P Value Partner Effect
Coeff (SE)
P Value
Irritability .15 (.10) .15 -.13 (.05) .02
Obscenity Use .08 (.06) .19 -.07 (.05) .18
Conversational Self-Focus -.003 (.08) .97 -.13 (.05) .02
Criticism .03 (.06) .56 .03 (.08) .71
Supportive Talk .02 (.06) .73 -.01 (.07) .88
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Table 6.

Multi-level Regression Analyses Examining Associations Between Depressive Symptoms and Coded
Behaviors, Moderated by Family Aggression
Note. Each observed behavior was run in a separate model. Coeff = Standardized coefficient, SE =
Standard error, DepXFamAgg = Interaction between depressive symptoms and family aggression.
* p < .05, ** p < .01, *** p < .001

Irritability

Coeff (SE) Obscenities Coeff (SE)
Level 1 Level 1
Ethnicity -.07 (.08) Ethnicity .13 (.09)
Age -.09 (.08) Age .03 (.12)
Depressive Symptoms .07 (.08) Depressive Symptoms .13 (.09)
Family Aggression .27 (.08)** Family Aggression .04 (.06)
DepXFamAgg .27 (.11)* DepXFamAgg .16 (.06)*
Level 2
Sex -.07 (.13) Sex -.11 (.11)

Conversational Self-Focus Coeff (SE)

Criticism Coeff (SE)
Level 1 Level 1
Ethnicity -.24 (.06)*** Ethnicity .16 (.10)
Age -.05 (.06) Age .21 (.10)*
Depressive Symptoms -.12 (.08) Depressive Symptoms .02 (.10)
Family Aggression .22 (.06)*** Family Aggression -.02 (.09)
DepXFamAgg .19 (.07) * DepXFamAgg .01 (.10)
Level 2 Level 2
Sex .40 (.21) Sex -.12 (.10)
Supportive Talk Coeff (SE)
Level 1
Ethnicity -.04 (.08)
Age -.07 (.07)
Depressive Symptoms -.03 (.08)
Family Aggression .05 (.09)
DepXFamAgg .12 (.08)
Level 2
Sex .27 (.12)*

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Figure 1. Simplified version of Actor-Partner Interdependence Models (APIM) used to examine associations between adolescents’
depressive symptoms with their own (actor) as well as their friends’ (partner) observed behaviors.
Depressive Symptoms
Observed Behavior

Depressive Symptoms

Observed Behavior
e

e

Actor Effect
Actor Effect
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Figure 2. Adolescents’ exposure to family aggression within the past year moderates the
association between adolescent depressive symptoms and observed irritability.
Coefficients are unstandardized. * p <. 05.

0
0.02
0.04
0.06
0.08
0.1
0.12
Irritability
Low Depression High Depression
Low Family
Aggression
High Family
Aggression
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Figure 3. Adolescents’ exposure to family aggression within the past year moderates the
association between adolescent depressive symptoms and observed obscenity use.
Coefficients are unstandardized. * p <. 05.
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
Obscenity
Low Depression High Depression
Low Family
Aggression
High Family
Aggression
b = .003 (ns)
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Figure 4. Adolescents’ exposure to family aggression within the past year moderates the
association between adolescent depressive symptoms and observed conversational self-focus.
Coefficients are unstandardized. * p <. 05.
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
Conversational Self-Focus
Low Depression High Depression
Low Family
Aggression
High Family
Aggression
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Supplemental Table.

Bivariate Correlations Between Continuous Variables Separated by Dyad Sex

Note. Females are above the diagonal, and males are below the diagonal.
*p < .05, **p < .01, *** p < .001

1 2 3 4 5 6 7 8 9
1. Depressive Symptoms -- .36*** .10 .22* -.09 .17 .01 -.02 .06
2. Family Aggression .23** -- .16 .48*** .26** .04 .17 .06 .11
3. Obscenity .08 -.01 -- .28** .31** .17 .16 .03 .06
4. Irritability .05 .20* .21* -- .25** .17 .03 .11 .02
5. Conversational Self-Focus .08 .14 20* .43*** -- .18 -.10 -.03 -.03
6. Criticism -.10 -.11 .40*** -.07 .13 -- -.17 .19 .17
7. Support .04 -.05 .11 .01 .11 .03 -- -.06 -.01
8. Neighborhood Poverty -.00 -.03 .20 .16 -.05 -.08 -.05 -- -.01
9. Age -.04 .02 .13 -.14 -.09 -.03 -.10 .09 --
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Manuscript 2
The Role of Friends’ Conversations About Interpersonal Problems in the Continuity of
Depressive Symptoms

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Abstract
Do the ways in which adolescent friends interact with each other and approach
interpersonal problems play a role in the endurance of their depressive symptoms? Seeking to
address this question, the present study utilizes direct observations of adolescent peer
interactions to investigate whether certain relationship dynamics alter the conditions under which
young adult depressive symptoms are predicted from 1) their own depressive symptoms during
adolescence, and 2) their friends’ depressive symptoms during adolescence. Ninety-three (45
females) participants completed measures of depressive symptoms during late adolescence (Time
1) and young adulthood (Time 2). At Time 1, video-recorded discussions between close friends
were coded for dyadic co-rumination, problem-solving talk, intimacy, and interpersonal stress
talk. Results suggested that participants’ depressive symptoms during adolescence were
associated with depressive symptoms during young adulthood only in the context of mean or
high levels of co-rumination and low or mean levels of problem-solving talk. Interpersonal stress
talk also conferred greater risk for males only. Young adult depressive symptoms were predicted
from their peers’ depressive symptoms at an earlier time point for males in the presence of co-
rumination and highly intimate friendships. Together, results suggest the importance of taking
into account adolescent peer processes when investigating risk factors for young adult depressive
symptoms and designing prevention efforts. Gender considerations when examining risk factors
for depressive symptoms are also addressed.

Key words: depressive symptoms, adolescence, peer processes, co-rumination, interpersonal
stress

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Introduction
Depression and depressive symptoms increase in frequency during adolescence and are
associated with high recurrence rates and a range of psychosocial problems (Bertha & Balazs,
2013; Cicchetti & Toth, 1998; Fergusson, Horwood, Ridder, & Beautrais, 2005; Korczak &
Goldstein, 2009; Hankin, 2006; Reinherz, Paradis, Giaconia, Stashwick, & Fitzmaurice, 2003).
Although depression is often conceptualized as an internalizing disorder, interpersonal theories
of depression underscore the importance of considering social processes in its development,
maintenance, and recurrence (Allen & Badcock, 2003; Hammen, 2009a; Joiner & Timmons,
2009). For example, at-risk individuals may present with maladaptive social skills or coping
techniques that exacerbate the likelihood of experiencing interpersonal chaos and subsequent
depression (Coyne, 1976; Hammen, 2006; Rudolph, 2009; Segrin, 2000). The development of
close peer relationships is a salient developmental task during adolescence, and friendships play
an important role in adolescents’ psychosocial functioning (Rubin, Bukowski, & Parker, 2006).
Investigating potentially beneficial versus maladaptive interpersonal processes within the context
of friendship interactions may thus shed light on how various social interactions differentially
heighten or dampen adolescents’ risk for experiencing depressive symptoms as they transition to
adulthood. This paper sought to capture the extent to which friends experience and openly
discuss interpersonal stress (interpersonal stress talk), jointly approach interpersonal problems
(co-rumination and problem-solving talk), as well as the quality of their interactions (intimacy),
and investigate whether these observed friend dynamics moderate longitudinal associations
between individuals’ depressive symptoms during late adolescence and young adulthood.

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Adolescent and Young Adult Depressive Symptoms
Although the majority of individuals are able to successfully navigate the biological,
social, and cognitive changes that accompany adolescence, a portion is prone to experiencing
mental health challenges, such as depression (Abela & Hankin, 2009; Hankin et al., 1998). The
transition to adulthood can also been conceptualized as a period of vulnerability, as individuals
struggle to solidify their identity amid a torrent of financial, educational, and residential
uncertainties (Arnett, 2000). Indeed, research suggests that depressive episodes or symptoms
usually first manifest or rise in prevalence during mid-adolescence or young adulthood (Huberty,
2012; Lewinsohn, Rohde, & Seeley, 1998; Rohde, Lewinsohn, Klein, Seeley, & Gau, 2013).
Moreover, approximately a quarter of individuals report experiencing major or sub-clinical
depression during their lives by the time they are young adults (Kessler & Walters, 1998), and
the 30-day prevalence rate of major depression tends to be highest among those 15-24 years old
(Blazer, Kessler, McGonagle, & Swartz, 1994). Whereas some research suggests that symptoms
of depression decline overall from adolescence to young adulthood (Galambos, Barker, & Krahn,
2006; Meadows, Brown, & Elder Jr., 2006), other studies indicate that rates remain stable
(Leadbeater, Thompson, & Gruppuso, 2012; Marmorstein, Iacono, & Malone, 2010).
The continuity of depression between adolescence and young adulthood is well
documented (Lewinsohn, Rohde, Klein, & Seeley, 1999; Pelkonen, Marttunen, & Aro, 2003).
Yet, adolescents with depression are by no means sealed to a lifetime fate of depression
(Wickrama & Wickrama, 2010), with studies examining various factors that may increase
adolescent vulnerability for experiencing depression later as young adults. For example, negative
life events and parent depressive symptoms discriminated males with persistent depression
versus those whose symptoms declined as young adults (Stoolmiller, Kim, & Capaldi, 2005).
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History of family depression (Lewinsohn, Rohde, Seeley, Klein, & Gotlib, 2000), low self-
esteem, legal troubles, a difficult home environment, and lack of close friends (Pelkonen et al.,
2003) have also been posited as risk factors for depression relapse during young adulthood.
Peer Relationships and the Interpersonal Nature of Depressive Symptoms
Stress-generation theory (Hammen 1991, 2006, 2009a) provides a useful theoretical lens
for understanding possible links between adolescent friend interactions and depressive
symptoms. According to this theory, adolescents with depressive symptoms are not passive
recipients of stressful events. Rather they exhibit characteristics and behaviors that at least
partially contribute to experiences of interpersonal chaos, placing them at greater risk for
depression. Along these lines, adolescents with depressive symptoms may have a difficult time
resolving interpersonal problems effectively (Becker-Weidman, Jacobs, Reinecke, Silva, &
March, 2010; Hankin, Stone, & Wright, 2010). This might prolong their exposure to and distress
related to the interpersonal concern, increase their chances of igniting further interpersonal
stressors, and generate vulnerability for continuous depression struggles.
Peers greatly influence adolescents’ emotions and behaviors and may thus impact how
they tackle problems. The peer context, particularly how friends communicate with one another
and approach life stressors, may thus be a critical avenue to explore when considering risk
factors for depressive symptoms. Theories of deviancy training emphasize that continuous verbal
exchanges between friends reinforce adolescents’ beliefs and behaviors (Dishion, Spracklen,
Andrews, & Patterson, 1996; Granic & Dishion, 2003). For example, observed social exchanges
between friends play an important role in both reducing (Iturralde, 2015) and exacerbating
(Dishion, Nelson, Winter, & Bullock, 2004; Dishion et al., 1996) risky and antisocial behaviors.
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In a similar vein, manners in which friends communicate and approach interpersonal problems
together may mitigate or intensify negative emotions.
Co-Rumination
Co-rumination is a dyadic communication pattern, during which friends repeatedly
discuss problems, encourage problem talk, and focus on negative emotions without leading to
resolution (Rose, 2002). Co-rumination can be considered a social extension of ruminative
coping, a cognitive style strongly associated with depression that is characterized by
perseverating on the causes and consequences of one’s distress without active attempts to reduce
them (Nolen-Hoeksema, 1991; Nolen-Hoeksema, Wisco, & Lyubomirsky, 2008). Similarly,
when friends co-ruminate with one another, they may engage in fewer effortful strategies and
more involuntary ones in reaction to their interpersonal problems.
Co-rumination is a complex social process in that it has been simultaneously associated
with higher friendship quality and emotional closeness, as well as greater levels of internalizing
symptoms (Calmes & Roberts, 2008; Rose, 2002; Rose, Carlson, & Waller, 2007; Rose &
Rudolph, 2006). That is, friends who continuously self-disclose and rehash interpersonal
problems may feel closer and better momentarily. However, heightened attention to concerns
without actively trying to deal with them may prevent the use of effective coping strategies,
reinforce affective and cognitive styles linked to depression, and exacerbate risks for continued
interpersonal problems and emotional distress (Hankin et al., 2010).
Supporting this argument, numerous studies utilizing questionnaire data have found self-
reported co-rumination to be a significant correlate of concurrent (Rose, 2002; Starr & Davila,
2009; Tompkins, Hockette, Abraibesh, & Witt, 2011) and prospective depressive symptoms and
episodes (Hankin et al., 2010; Rose et al., 2007; Schwartz-Mette & Rose, 2012; Stone, Uhrlass,
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& Gibb, 2010). Co-rumination may strengthen associations between depressive symptoms and
the generation of stress (Rose, Glick, Smith, Schwartz-Mette, & Borowski, 2016), and has also
been suggested as an explanatory factor for why females experience higher rates of depressive
symptoms than do males (Calmes & Roberts, 2008; Rose, 2002). Research utilizing daily diary
methodologies has also found associations between reported co-rumination and depressed mood
(White & Shih, 2012).
Although co-rumination is conceptualized as a dyadic process, the bulk of the literature
has relied on individuals’ self-reports of co-rumination with friends. Participants’ perceptions of
co-rumination provide meaningful information, but observing co-rumination processes among
friends may offer a more nuanced, ecologically valid look at how this dyadic process impacts
psychosocial functioning (Starr & Davila, 2009). To date, only a few studies have tried to
capture co-rumination using observational methods. Observational research using college aged
female friend-dyads found links between co-rumination— particularly focusing on negative
emotions— and higher cortisol levels, but did not examine depressive symptoms (Byrd-Craven,
Geary, Rose, & Ponzi, 2008; Byrd-Craven, Granger, & Auer, 2010). In the only published study
examining associations between observed co-rumination and depressive symptoms in adolescent
dyads, results suggested that dwelling on negative affect was the primary characteristic of co-
rumination that was concurrently linked to depressive symptoms (Rose, Schwartz-Mette, Glick,
Smith, & Luebbe, 2014). Thus, similar to rumination, constantly focusing on negative affect
related to events with friends may amplify aversive emotional experiences.
Friendship Intimacy
Though definitions vary, intimacy and closeness can be broadly operationalized as
including mutual self-disclosure, satisfaction, loyalty, and connectedness (Reis & Shaver, 1988;
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Shulman, Laursen, Kalman, & Karpovsky, 1997). Friendship intimacy during adolescence
accords multiple benefits, including higher self-esteem (Giordano, Cernkovich, Groat, &
Swinford, 1997), and lower levels of anxiety and depressive symptoms (Buhrmester, 1990).
Friendships that are perceived to be high in support and self-disclosure buffer young adolescent
females against the deleterious effects of peer victimization (Cuadros & Berger, 2016). In
contrast, adolescents with low quality friendships experience higher levels of depressive
symptoms compared to adolescents in more intimate, interdependent friendships (Selfhout &
Branje, 2009).
However, emotional intimacy, like co-rumination, may not always predict wellbeing. For
example, whereas self-disclosure, a primary component of intimacy (Bauminger, Finzi-Dottan,
Chason, & Har-Even, 2008; Berndt & Hanna, 1995; Parks & Floyd, 1996), may buffer male
adolescents from developing depressive symptoms (Landoll, Schwartz-Mette, Rose, & Prinstein,
2011), high levels of disclosure have also been shown to predict symptoms of anxiety,
depression, and stress in individuals (Kenny, Dooley, & Fitzgerald, 2013). It is possible that
when friendships are highly intimate, they confer greater opportunity for adolescents to express
negative emotions and reiterate distressing events. Thus, intimacy may either lessen or amplify
longitudinal associations between depressive symptoms.
Interpersonal Stress Talk
Research suggests strong ties between interpersonal stressors and depressive symptoms.
According to life-stress and diathesis-stress models of depression, adolescents’ exposure to
stressful events can trigger depressive symptoms or episodes, especially when combined with
pre-existing vulnerabilities (Hankin & Abramson, 2001). More transactional models of
depression (e.g., Hammen, 1991, 2006), postulate that individuals prone to depression may
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engender interpersonal stress in their lives, subsequently placing them at greater risk for future
depression (Joiner & Timmons, 2009; Rudolph, 2009).
Both theories have been supported in the adolescent depression literature. Studies have
found that exposure to interpersonal stress, such as peer problems, predicts depression and
depressive symptoms in adolescents and young adults, especially for females (Davila, Hammen,
Burge, Paley, & Daley, 1995; McLaughlin, Hatzenbuehler, & Hilt, 2009; Shih, Eberhart,
Hammen, & Brennan, 2006). One study found that interpersonal stressors mediated associations
between past and subsequent depression for females but not males (Rudolph, Flynn, Abaied,
Groot, and Thompson, 2009). Being faced with chronic or more severe interpersonal stressors
during adolescence may therefore increase the likelihood that these individuals will continue to
experience depressive symptoms later in life.
Less is known about how close friends’ conversations about their interpersonal stressors
influence their levels of depressive symptoms. Moreover, studies assessing interpersonal stress
have typically utilized questionnaires or semi-structured interviews (Liu, 2013). It is possible that
being subjected to and becoming involved in friends’ interpersonal problems may induce further
distress. Alternatively, conversations about interpersonal stressors with friends may be realistic
reflections of the degree of chronic challenges that adolescents face and their consequences.
Thus, adolescent friends who talk about more severe interpersonal stressors may experience
greater social upheaval in their daily lives, placing them at risk for continuing to battle mental
health concerns later in life. This study aims to capture adolescents’ exposure to social stressors
through direct observations of adolescent friend discussions of interpersonal problems.

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Problem-Solving Talk
Whereas co-rumination and interpersonal stress-talk may exacerbate risks for future
depressive symptoms, discussing and encouraging the use of problem-solving strategies, a
potentially more adaptive technique, may be protective (Compas, Connor-Smith, Saltzman,
Thomsen, & Wadsworth, 2001). Problem-solving Therapy (PST), which focuses on enhancing
people’s abilities to recognize problems and identify potential solutions, is an effective
intervention for depressive symptoms (Bell & D’Zurilla, 2009; Eskin, Ertekin, & Demir, 2008).
On the other hand, low self-perceived problem-solving skills have been linked with adolescent
depressive symptoms (Marcotte, Alain, & Gosselin, 1999). Self-reported avoidant problem-
solving style approaches may also relate to adolescent depression (Becker-Weidman et al.,
2010), and young adult depressive symptoms (Siu & Shek, 2009). One study measured
interpersonal problem-solving by assessing adults’ generated solutions to hypothetical vignettes
and found that although poor interpersonal problem-solving did not directly predict depressive
symptoms, there was an indirect effect through increased interpersonal stress (Davila et al.,
1995).
Friends mutually influence one another and look to each other for guidance on how to
feel and behave (Brechwald & Prinstein, 2011). Adolescents exposed to friends who model
problem-solving tactics may too incorporate this strategy, better preparing them to handle
stressors. Yet, research has primarily focused on how individual adolescents approach problems,
rather than examining how friends engage in problem-solving jointly. An exception is a study
that utilized ecological momentary assessment to examine connections between depression and
co-problem-solving with a peer (Waller, Silk, Stone, & Dahl, 2014). Researchers assessed this
construct by asking adolescents if they were with someone while trying to use problem-solving
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to improve a negative situation. They found that adolescents without clinical depression engaged
in problem-solving with friends twice as often as those with depression. Extending these
findings, the present study uses actual friend conversations about negative events to capture
problem-solving as a dyadic process and examine its function regarding depressive symptoms.
Peer Contagion of Depressive Symptoms
Research on peer influences highlights a darker side to adolescent friendships. Friends
may not only resemble one another in their characteristics (e.g., homophily), but can also
negatively shape one another’s behavior and affect (e.g., peer contagion or peer socialization; for
reviews see Brechwald & Prinstein, 2011; Dishion & Tipsord, 2011). Theories of peer contagion
have mainly been investigated with respect to deviant and delinquent behaviors (Dishion,
Andrews, & Crosby, 1995; Dishion et al., 1996; Dishion & Tipsord, 2011; Granic & Dishion,
2003). Yet, there is emerging support that peer contagion of internalizing symptoms also occurs.
For instance, longitudinal research indicates that adolescent depressive symptoms are predicted
from friends’ depressive symptoms at earlier time points, even after adjusting for baseline
symptoms (Stevens & Prinstein, 2005; Schwartz-Mette & Rose, 2012; van Zalk, Kerr, Branje,
Stattin, & Meeus, 2010; though for non-significant findings, see Fortuin, van Geel, & Vedder,
2014). Peer socialization processes have also been implicated in adolescent non-suicidal self-
injury (for a review, see Heilbron & Prinstein, 2008).
Research on factors that reduce or increase the likelihood of peer contagion of depressive
symptoms is limited. Some findings have suggested that adolescents are more susceptible to
depressive contagion when either they (Guan & Kamo, 2016) or their friends (Prinstein, 2007;
Rose et al., 2007) are more popular. Whereas some studies suggest that peer contagion is
especially likely to occur in the context of close friendships (Giletta et al., 2011; Giletta et al.,
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2012), others suggest that, at least for males, adolescents with lower quality friendships are more
prone to peer socialization of depressive symptoms (Prinstein, 2007).
Observational research of anti-social behavior demonstrates that adolescents reinforce
deviant talk during conversations, which subsequently increases the likelihood of problematic
behavior during adolescence and young adulthood (Dishion et al., 2004). Friendship dynamics
may also play a vital part in peer contagion of depressive symptoms. For example, when friends
co-ruminate, they share and reinforce negative emotions, conferring greater risk for depressive
symptoms in both friend members (Rose, 2002; Schwartz-Mette & Rose, 2012). Minimal work
has explored observed co-rumination as a moderator of peer socialization processes. Other social
processes that may exacerbate or lessen depression risk are also largely unknown. This study
examines whether associations between close friends’ depressive symptoms are more likely to
occur when friends bolster one another’s ruminative coping strategies and stress talk, but lessen
when friends encourage problem-solving approaches. It also investigates whether associations
are stronger or weaker when adolescent friendships are more emotionally intimate.
Sex Differences
A robust finding is that during adolescence, sex differences regarding depression rates
emerge, with these discrepancies remaining stable throughout adulthood (Bennett, Ambrosini,
Kudes, Metz, & Rabinovich, 2005; Nolen-Hoeksama & Girgus, 1994). Although rates of
depression increase across sex during adolescence, the increase may be more dramatic for
females (Hankin et al., 1998). Theories aiming to explain these sex differences have pointed to
biological factors (Angold, Costello, & Worthman, 1998) and greater likelihood of adopting
coping styles (e.g., rumination) that elevate risk for depression (Nolen-Hoeksama & Girgus,
1994; Rose & Rudolph, 2006). Moreover, female adolescents experience greater exposure to
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stressful interpersonal life events (Hankin, Mermelstein, & Roesch, 2007) and may be more
negatively impacted by them, perhaps because they are more emotionally invested in
relationships compared to males (Cyranowski, Frank, Young, & Shear, 2000; Hankin et al.,
2007; for reviews of various theories, see Hankin & Abramson, 2001; Hyde, Mezulis, &
Abramson, 2008).
Certain interpersonal patterns may also function differently for males and females. For
instance, co-rumination may predict depressive symptoms for females but not males (Rose et al.,
2007), and the use of humor during discussions of problems predicted increased closeness for
male but not female adolescents (Rose, Smith, Glick, & Schwartz-Mette, 2016). Given findings
regarding gender differences, this study examines whether longitudinal associations between
depressive symptoms, as well as the moderating effects of observed friend interactions vary as a
function of participant sex.
Present Study
This study uses two time points of data and direct observations of friend interactions to
examine whether the manner in which friends interact with one another and approach
interpersonal problems heighten or reduce adolescents’ risk of experiencing depressive
symptoms as young adults. A novel coding system was developed to assess adolescent behaviors
and communication patterns that may be related to depressive symptoms and interpersonal
relationships. For our first aim, we investigate the continuity of depressive symptoms from when
participants are adolescents at Time 1 (TI) to when they are young adults ate Time 2 (T2).We
hypothesize associations between depressive symptoms at T1 and T2 (Hypotheses 1a). We
examine whether gender moderates this association, though based on previous research (Ge,
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Nausaki, & Conger, 2006), do not expect associations to be different for males versus females
(Hypothesis 1b).
The second overarching aim of the study is to examine whether observed interpersonal
dynamics between friends influence the strength of the association between depressive
symptoms at T1 and T2. In particular, co-rumination and interpersonal stress talk are anticipated
to heighten participants’ risks of experiencing depressive symptoms at T2. On the other hand,
problem-solving talk is predicted to serve as a protective factor, lessening relations between T1
and T2 depressive symptoms (Hypothesis 2a). Given mixed findings regarding intimacy and
emotional adjustment, no specific hypothesis is offered regarding intimacy as a moderator.
Gender differences in these interactions are also explored. Because research suggests that
adolescent social interactions, interpersonal stress, and coping behaviors are especially potent in
the context of female mental health, we expect that interactions between observed behaviors and
depressive symptoms would be stronger for females than males (Hypothesis 2b).
As a third aim of this study, we test whether the same observed communication patterns
(e.g., co-rumination, problem-solving, intimacy, and interpersonal stress-talk) moderate whether
young adults’ depressive symptoms at T2 are predicted from their friends’ (i.e., ‘peer’) self-
reported depressive symptoms at T1. Based on the extant research on depression peer contagion
(Giletta et al., 2012; Dishion & Tipsord, 2011), we hypothesize that associations between T1
peer depressive symptoms and T2 youth depressive symptoms will be significant only when
adolescent friends are observed to display high levels of co-rumination, intimacy, and
interpersonal stress talk. In contrast, we expect that observed problem-solving talk during T1
would buffer youth from experiencing higher depressive symptoms at T2 (Hypothesis 3a). We
also explore three-way interactions between depressive symptoms, coded variables, and
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participant sex. Given research suggesting that females are more relationship oriented and
empathic toward their friends (Rose & Rudolph, 2006), we predict that females would be more
sensitive to these interaction effects than would males (Hypothesis 3b).
Methods
Overview
Data are drawn primarily from, a) individuals, also referred to as ‘youth’, who are part of
a larger multi-wave study and have been followed over many waves of data collection, and b)
adolescents whom youth identified as friends and selected to bring into the laboratory to
participate in wave 5 data collection procedures only. These adolescents are referred to in this
study as ‘peers’. Wave 5 procedures included participation in a video-recorded peer discussion
task and completion of questionnaires, which we describe in more detail below. We use the term
‘friend dyads’ when referring to ‘youth’ and ‘peers’ collectively.
Participants
The present study includes 93 youth (45 females) who were part of a longitudinal study
examining interpersonal relationships and how family members respond to various forms of
stressors (Margolin, Vickerman, Oliver, & Gordis, 2010). Youth and their parents were
originally recruited through word of mouth and print advertising. Families were eligible for
participation if the parents lived together for at least three years, youth and both parents were
able to participate, and all members were able to complete study measures in English. The
present study utilized data during waves 5 and 6 of data collection. During wave 5, when youth
were adolescents, they selected a same-sex friend (i.e., ‘peer’) to bring into the lab. As young
adults during wave 6, youth completed and submitted study measures of interest electronically.
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Peers did not participate in wave 6. The average lag time between wave 5 and 6 procedures was
4.18 years (SD = 1.25).
In order to be included in analyses for the present study, youth needed to have, a)
participated in a videotaped peer discussion task and completed measures of depressive
symptoms during wave 5, and b) completed a follow up measure of depressive symptoms during
wave 6. To simplify the description of the current study, we hereon refer to waves 5 and 6 as T1
and T2, respectively, in the current study. Of the 111 youth who participated in the peer
discussion task, 18 did not complete T2 data either because they declined participation (n = 5),
were unable to be reached (n = 5), expressed interest in participating but had not yet completed
measures (n= 6), passed away (n=1), or had data that was suspected to be compromised (n = 1).
We conducted t-tests to compare youth who did and did not complete T2 measures. There were
no significant differences with regards to T1 depressive symptoms, age, or observed co-
rumination, problem-solving, or interpersonal stress talk. However, non-completers had
significantly lower observed intimacy scores (M = 2.15, SD = .52) compared to completers (M =
2.40, SD = .47), t (109) = -2.02, p = .05. Fisher’s Exact Test did not suggest any significant
gender or ethnic differences between completers and non-completers.
Of the youth participating in the present study, 33.3% identified as Hispanic/Latino. In
terms of race, 6.5% reported being Asian, 18.3% Black or African American, 59.1% Caucasian,
and 16.1% multi-racial. Youth were between the ages of 14 and 20 years at time 1 (M = 17.57
SD = 1.05), and 18 and 26 years at time 2 (M = 22.28, SD = 1.88).
Procedure
At T1, youth and peers completed in-laboratory procedures together. Youth consented to
the study if they were over 18-years-old or, if younger, they provided assent with parental
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consent. After completing consent procedures, youth and peers completed questionnaires in
separate rooms. As part of their visit, youth and peers participated in 8 5-minute video-recorded
discussions modeled after the Peer Interaction Task (Dishion et al., 1995). These discussions
took place in an observation room equipped with three video cameras and a one-way mirror. The
present study used the two discussions that focused on interpersonal problems that the youth and
friend were currently experiencing. Prior to these discussions, each participant completed a
questionnaire identifying various individuals (e.g., teacher, mother, friend), with whom they had
an unresolved issue or problem.
At the beginning of this discussion task, an experimenter provided youth and peers with
the following instructions:
Now, I’d like the two of you to talk about a current problem with a person that [youth]
identified a few minutes ago. [Youth], you selected a few people on this list with whom you have
an unresolved issue. Please talk about why it is a problem and then if you’ve tried to solve it,
what you did and if it worked. Then, talk with [invited friend] about ways you might solve the
problem and any ways that [invited peer] could help.
The dyads were informed that they would have five minutes to discuss the youth’s
interpersonal problems. During the next five-minute discussion segment, the dyads received
identical instructions, except that the focus shifted to an unresolved problem that the peer was
encountering. In order to help the friend dyads remain on task, experimenters provided them with
written instruction prompts as well each member’s respective questionnaire listing the
individuals with whom they had unresolved issues. Following the discussion, youth and peers
were again separated and finished completing questionnaires. At T2, youth completed a variety
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of questionnaires, including measures of depressive symptoms, via Qualtrics, a secure on-line
survey platform.
Coding System Development
We designed a global system for this study to assess behaviors and affect that are
potentially indicative of interpersonal dynamics that may be associated with depressive
symptoms. For the purposes of this study, we focus on four rated behaviors: Interpersonal Stress
Talk and Problem-solving (which were separately rated for each individual) and Co-rumination
and Intimacy (which captured a quality of the interaction and were rated for the dyad).
Undergraduate and B.A. level research assistants underwent several weeks of training in the
coding system and observational research. Once trained, coders were randomly assigned to
independently watch discussions, and all discussions were scored by at least two coders. Coders
first watched a discussion segment and rated the behaviors of one of the dyad members (e.g.,
youth) and then watched the segment again for the other dyad member (e.g., peer). The
exception to this was for the two dyadic level codes, which were co-rumination and intimacy. In
these instances, coders assigned a single rating for the dyad after watching the discussion
segment twice. We counterbalanced the order of which dyad member (youth versus peer) was
coded first across both coders and discussion segments. Consistent with previous global coding
systems (e.g., Iturralde & Margolin, 2011), coders took into account both severity and frequency
of a given code when assigning a rating, with 0 = none, 1 = a little, 2 = a moderate amount, and
3= a lot.
Measures
Coded behaviors. Table 1 presents a list of the four coded behaviors examined in this
study, along with code examples, and inter-rater reliability. Co-rumination was developed based
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on Rose’s (2002) theory and definition of the construct, and modified from her coding system
(Rose, 2006; Rose et al., 2014). Ratings were based on the extent to which participating friend
dyads reinforced each other’s problem talk, discussed and rehashed problems, speculated about
possible causes and consequences of the problem, and focused on negative feelings related to the
event. Simply bringing up an interpersonal problem was not sufficient to receive a score. Rather,
the co-rumination code was reserved for instances when friend dyads appeared to go around in
circles discussing a problem without trying to identify strategies for resolving it. Problem-
Solving Talk was coded when adolescents discussed possible strategies for solving a problem or
reaching a goal, as well as when they referenced techniques that they have used to solve past
problems. Problem-solving talk was coded for solutions that were proactive or neutral, but not
coded when adolescents mentioned strategies that were clearly maladaptive, such as self-harm,
substance use, or aggression. Interpersonal Stress Talk assessed the degree of social and
interpersonal chaos occurring in adolescents’ lives, specifically concerns beyond transient
hassles and annoyances that instead reflected more chronic stressors (e.g., longstanding problem
with a friend) with larger consequences. Adolescents were assigned high scores if they either
discussed a single severe stressor or discussed several moderate ones. Intimacy assessed the
extent to which communication patterns between friends suggested comfort and closeness. This
code was assigned when both friends commented on shared experiences or their intimate bond,
as well as when dyad members appeared to be mutually candid with one another.
For the analyses, we computed a single mean code score for each dyad. First, we
averaged the two individual codes (Problem-Solving, r = .65 and Interpersonal Stress Talk, r =
.40, both ps < .001) across the two participants. For all codes, we then calculated the average
score across the two discussion segments. Inter-rater reliability on the final averaged scored was
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calculated with intra-class correlation coefficients (ICC), which computes the mean agreement
across two randomly assigned coders (range = .51 to .85; See Table 1). We then calculated the
average score across the two raters for analyses.
Depressive symptoms. Youth completed the Beck Depression Inventory, Second Edition
(BDI-II, Beck, Steer, & Brown, 1996) at both time points. Peers completed the BDI-II at T1
only. Participants reported on the extent to which they experienced 20 symptoms of depression
within the previous two weeks. The BDI-II is comprised of 21 items, but we dropped one item
assessing suicidal ideation due to ethical and reporting concerns. The BDI-II had good internal
consistency in the current study (Youth: α = .87 at T1 and .90 at T2; Peers: α = .87). Per BDI-II
scoring guidelines, those who obtain scores of 14 or above are considered to have at least mild
levels of depression
Covariates. When testing coded behaviors as moderators of youth’s depressive
symptoms at T1 and T2, the T1 peer depressive symptoms variable was included as a covariate.
Similarly, when investigating observed behaviors as moderators of associations between T1 peer
depressive symptoms and T2 youth depressive symptoms, the T1 youth depressive symptoms
variable was added as a covariate. We also tested maternal and paternal depressive symptoms as
covariates in moderation analyses, due to potential associations with offspring depression (e.g.,
Kane & Garber, 2004; Hammen & Brennan, 2003). Youths’ parents completed the Symptom
Check List 90-Revised (SCL-90; Derogatis, 1983) during three time points. Thirteen items assess
depressive symptoms, and responses were scored on a 5-point likert scale, ranging from 0 (Not at
all) to 4 (Extremely). Scores were averaged across all three-time points. Mothers’ and fathers’
mean depressive symptom scores (r = .25, p = .02) were analyzed separately. Other considered
covariates included participant sex and participants’ whole value age.
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Measures of Task Validity. We used several approaches to assess the authenticity of the
peer discussions. First, an Engagement (ICC = .82) code was developed for this study, which
measured the extent to which dyad members were involved in the discussion and adhered to task
instructions. As with the other codes, coders assigned targets and participants scores ranging
from 0 (not at all) to 3 (a lot), and we averaged the scores across dyad members and across
discussion segments 1 and 2. An Artificial code was also assigned when it appeared that
adolescents were being inauthentic or performing for the camera. This code was developed and
applied in a previous study using observational methods (Iturralde, 2015), for which another set
of trained coders rated the same videotaped interactions. These coders assigned dyad members
either a 1 or 0 to indicate the suspected presence or absence of artificial behaviors, respectively.
A participant was then assigned a 1 for a discussion segment if either coder rated them as
displaying artificial behaviors. Ratings were then summed across the two discussion segments
and across the youth and peers to calculate the total amount of suspected artificial behavior.
Finally, after completing all of the discussion segments, the youth and peer reported on, 1) how
similar the discussions were to other ones that they have had with the participating friend (0 =
not at all, 4 = very similar), 2) how much they were able to express their own points of views
during the discussions ( 0 = none, 4 = very often), 3) how often they have had similar discussions
with the participating friend or any of their friends ( 0 = never, 4 = very often), and 4) how
“honest or frank” they were during the overall discussion ( 0 = not at all, 4 = very).
Analytic Plan
All statistical analyses were conducted using SPSS software, version 24.0. We
conducted bivariate correlations to examine associations between continuous variables.
Independent t-tests were used to examine differences in variable scores across gender. We
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employed the PROCESS SPSS Macro (Hayes, 2013) to assist with conducting moderation
analyses for aims 2 and 3. Separate analyses were run to test each observed behavior (co-
rumination, problem-solving, interpersonal stress-talk, and intimacy) as a moderator. For
moderation analyses, PROCESS uses 5000 bootstrapped samples to estimate 95% bias-corrected
confidence intervals in addition to p values. Predictor and moderator variables were grand mean
centered prior to analyses. Participant sex was effect coded, with females = -.5 and males = .5.
We initially winsorized the T2 depressive symptom scores, such that the highest score (39) was
brought down to the next highest score (35), and subsequently ran moderation analyses with and
without the winsorized scores. Results did not change, so we used non-winsorized values for
ease of interpretation. Significant interactions were probed with simple slopes (Aiken and West,
1991), with associations tested at 1 SD below and above the mean of the moderator
1
.
For aim 2, we ran a series of regression analyses with T1 youth depressive symptoms as
the predictor. Participant age and paternal depressive symptoms were not significantly related to
T2 depressive symptoms, nor did they change the significance of any of the associations, so they
were dropped from the model for reasons of parsimony. Participant sex, maternal depressive
symptoms, and T1 peer depressive symptoms were kept as covariates on either empirical or
theoretical grounds.
We ran a similar set of analyses for aim 3 except that we specified T1 peer depressive
symptoms as the predictor variable. All analyses included T1 youth depressive symptoms as a
covariate in order to test whether T2 youth depressive symptoms were predicted from T1 peer
depressive symptoms, above and beyond youth’s own depressive symptoms at T1. We also
adjusted for participant sex and youth’s maternal depressive symptoms.

1
For co-rumination, simple slopes were tested at the minimum value of co-rumination rather than 1 SD below the
mean, as a value of co-rumination at 1 SD below the mean was outside the range of data (Hayes, 2013).
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Results
Descriptive Statistics
Participants were coded as using Artificial speech in seven instances (3.76%) out of the
possible 186 5-minute discussion segments used for this study (2 discussions X 93 dyads),
indicating that participants overall were comfortable and genuine during the first two discussion
tasks. Youth assigned an Artificial score (n = 3) did not significantly differ from other youth
regarding T1 or T2 depressive symptoms or on any of the observed variables. A mean dyadic
engagement score of 2.61 (3 = maximum score of ‘a lot’; SD = .49) indicated that youth and their
friends were involved in and followed task instructions. Approximately 75.6% of youth reported
that the discussion was at least moderately similar to other ones that they have had with the
participating friend (M = 3.10, SD = 1.01), 94.1% reported being able to express their points of
views at least a “moderate amount” of the time during the discussion (M = 3.60, SD = .60),
75.5% of youth reported that they at least “often” had discussions similar to the ones in the lab
with friends (M = 3.03, SD = .96), and 75.5% reported being “very” honest or frank (M = 3.70,
SD = .58).
Approximately 58.6% of participants were coded as exhibiting some degree of co-
rumination, and almost all participants engaged in some problem-solving (93.7%) and
interpersonal stress-talk (99.1%). All participants displayed some degree of intimacy, which was
to be expected, given that youth selected a close friend to participate with them. All observed
variables were relatively normally distributed, with skewness ranging from -.34 (intimacy) to
1.37 (co-rumination).
Gender Differences. Table 2 illustrates means and standard deviations of variables of
interest for the entire sample, as well as stratified by gender. Female peers reported greater
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depressive symptom scores (female M = 11.68, SD = 9.19, male M = 7.90, SD = 5.38), t (70.01)
= 2.40, p = .02) than males, but there were no significant differences for youth depressive
symptoms at either T1 or T2. Females were observed to engage in more problem-solving (female
M = 1.07, SD = .70, male M = .80 SD = .55), t (91)= 2.08, p = .04, and interpersonal stress talk
(female M = .84, SD = .42, male M = .64 SD = .29), t (91)= 2.72 p = .01, as well as to exhibit
more intimacy with friends (female M = 2.54, SD = .37, male M = 2.27, SD = .51), t (85.44) =
2.88, p < .01. Gender differences for co-rumination and age were not statistically significant.
Interrelationships among study variables. Table 3 displays correlations between
continuous study variables separated by sex, with correlations for females below the diagonal
line, and males above. T1 and T2 youth depressive symptoms were significantly correlated for
males (r = .48, p = .001), but not for females (r = .23, p = .14). T1 depressive symptoms were
positively correlated with co-rumination for males (r = .42, p = .003), but not females (r = .07, p
= .65). T2 depressive symptoms were significantly negatively associated with problem-solving
talk for males (r = -.31, p = .03), but not females (r = -.11, p = .47). Co-rumination and problem-
solving talk were significantly negatively associated for females (r = -.32, p = .03). For males,
co-rumination and problem-solving talk were also negatively associated, although the
relationship did not reach statistical significance (r = -.24, p = .10). For females only, co-
rumination was significantly positively associated with observed intimacy (r = .30, p = .05) and
negatively associated with interpersonal stress-talk (r = -.32, p = .03). Furthermore, for females
only, T1 depressive symptoms were positively associated with paternal depressive symptoms (r
= .43, p = .003), whereas T2 depressive symptoms were positively associated with maternal
depressive symptoms (r = .48, p = .001). For females only, maternal depressive symptoms were
positively correlated with participant age (r = .30, p = .05). For males only, T1 peer depressive
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symptoms and youths’ maternal depressive symptoms were significantly correlated (r = .33 p =
.02). Finally, maternal and paternal depressive symptoms were significantly correlated with each
other for females (r = .35, p = .02), but not males (r = .08, p = .64). Of note is that peer
depressive symptoms were not significantly correlated with T1 or T2 depressive symptoms for
either sex.
Frequency and Patterns of Depressive Symptoms
Paired sample t-tests show that the mean difference between levels of depressive
symptoms was not significant, t (93) = -1.26, p = .21. At T1, 11.8% of youth, and at T2, 21.5%
of youth scored a 14 or higher on the BDI-II, reflecting at least minor levels of depression. Table
4 shows the number of female and male participants at T1 and T2 who reported experiencing at
least minor levels of depression. Overall, 73.1% of the sample (n = 68) reported scores (<14) that
were below the value indicating minor levels of depression at both time points, 5.4% (n = 5)
reported at least minor levels of depression at T1 only, 15.1% (n = 14) reported at least minor
levels of depression at T2 only, and 6.5% (n = 6) reported at least minor levels of depression at
both time points. Figure 1 visually displays youth depressive symptom scores at T1 and T2.
Points in the upper left quadrant reflect youth who scored a 14 or above at T2 but not T1, lower
left those who did not score a 14 or above at either time point, lower right those who scored a 14
or above at T1 but not T2, and upper right those who scored a 14 or above at both time points.
In support of Hypothesis 1a, youth depressive symptoms at T1 and T2 were significantly
associated with each other (r = .39, p < .001). Although separating the correlations based on sex
revealed that T1 and T2 youth depressive symptoms were significantly correlated for males but
not for females, fisher r-to-z transformations suggested that the two correlation coefficients were
not significantly different from one another (z = -1.38, p = .17). We also tested whether gender
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moderated the association between T1 and T2 depressive symptoms. Consistent with Hypothesis
1b, there was neither a significant interaction (b = .35, SE = .12, p = .14), nor main effect of sex
(b = -.10, SE = 1.51, p = .95). Thus associations between T1 and T2 depressive symptoms did
not significantly vary by sex.
Do Observed Behaviors Moderate Links Between T1 and T2 Youth Depressive Symptoms?
Table 5 presents regression analyses testing the four observed behaviors as moderators of
the association between T1 and T2 depressive symptoms. In line with Hypothesis 2a, co-
rumination (b = .42, p = .01) exacerbated the association between T1 and T2 depressive
symptoms. Figure 2a visually depicts this interaction effect. When using simple slopes to further
probe the significant two-way interaction, we found that depressive symptoms during
adolescence were associated with depressive symptoms during young adulthood when
participants engaged in mean-level (b = .30, p = .02), or high levels (b = .57, p < .001), of co-
rumination with their friends. However, this association was not significant at low levels of co-
rumination (b = .12, p = .51). Thus, co-ruminating with friends appears to heighten the risk that
depressive symptoms during adolescence predict symptoms during young adulthood.
In line with Hypothesis 2a, problem-solving talk (b = -.46, p = .03) buffered the
association between T1 and T2 depressive symptoms. Figure 2b illustrates the interaction effect
for problem-solving and T1 depressive symptoms. Simple slopes suggested that T1 and T2
depressive symptoms were associated at low (b = .61, p < .001) and mean (b = .32, p = .01)
levels of problem-solving talk. However at high levels, the relationship was not significant, (b =
.03, p = .88). Results are consistent with the hypothesis that problem-solving talk serves as a
protective factor against associations between T1 and T2 depressive symptoms. There were no
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significant interactions for interpersonal stress talk (b = -.05, p = .89) or intimacy (b = .45, p =
.15).
Sex Differences in Moderation Analyses
Hypothesis 2b tested whether the four observed behaviors moderated the continuity of
depressive symptoms for females but not males. Three-way Participant Sex X Observed
Behavior X Time 1 Depressive Symptoms moderation analyses were conducted. There was a
significant three-way interaction when interpersonal stress talk was the moderating variable (b =
1.83, p = .04), although the interaction between interpersonal stress talk and T1 depressive
symptoms was not statistically significant for either females, (b = -40, p = .34) or males (b =
1.42, p = .07). For exploratory purposes, we plotted simple slopes of the interactions for females
and males separately (Figure 3), and it appeared that the pattern of the interactions was different
for females versus males. For females, associations between T1 and T2 depressive symptoms
were marginally associated at low levels of interpersonal stress talk (b = .46, p = .08). At high
levels, the association was not significant (b = .16, p = .50). Alternatively, for males
associations between T1 and T2 depressive symptoms were significant when adolescents
engaged in high (b = 1.09, p = .001), but not low (b = 02, p = .95), levels of interpersonal
stress talk. No other three-way interactions were observed.
Do Observed Behaviors Moderate Links Between Peer and Youth Depressive Symptoms?
Hypothesis 3a proposed that peer depressive symptoms would predict youth depressive
symptoms in the context of high co-rumination, intimacy, and interpersonal stress-talk. It also
predicted that problem-solving talk would attenuate these associations. Table 6 presents
regression analyses testing observed behaviors as moderators of the relation between T1 peer and
T2 youth depressive symptoms. A significant moderation was found for co-rumination (b = .38,
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p = .047). As shown in Figure 4, associations between T1 peer and T2 youth depressive
symptoms were not significantly associated at low levels of co-rumination (b = -.07, p = .61).
However, at high levels of co-rumination, the association was positive and just missed statistical
significance (b = .31, p = .052). No significant moderations were found for interpersonal stress
talk, intimacy, or problem-solving talk, although the moderation for intimacy was marginally
significant (b = .39, p = .056).
Sex Differences in Moderation Analyses
For aim 3, we also tested for sex differences regarding interactions between observed
variables and T1 peer depressive symptoms. Two three-way interaction effects emerged, though
they were not in the hypothesized direction of effects. There was a significant three-way
Participant Sex X Co-rumination X T1 Peer Depressive Symptoms interaction (b = 1.18, SE =
.45, p = .01). Co-rumination significantly moderated associations between T1 peer and T2 youth
depressive symptoms for males (b = 1.33, p = .002), but not females (b = .15, p = .46). As shown
in Figure 5, for females, associations between T1 peer and T2 youth depressive symptoms were
not significant at any value of co-rumination. For males, associations between T1 peer and T2
youth depressive symptoms were inversely related at low levels of co-rumination (b = -.44, p =
.03), whereas they were positively related at high levels of co-rumination (b = .82, p = .02). A
similar three-way interaction pattern emerged for intimacy (b = 1.37, p = .01). As shown in
Figure 6, intimacy did not moderate associations between T1 peer and T2 youth depressive
symptoms for females (b = .13, p = .59), but it did for males (b = 1.50, p = .001). For males,
T1 peer and T2 youth depressive symptoms were significantly negatively associated at low
levels (b = -.47, p = .04), but significantly positively associated at high levels (b = .96, p = .01)
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of intimacy. No three-way interactions were found for problem-solving talk or interpersonal
stress talk.
Discussion
This study investigated longitudinal links between depressive symptoms during late
adolescence and young adulthood. Utilizing direct observations of peer conversations, it also
examined whether interpersonal dynamics among friends conferred risk or offered protection
against experiencing depressive symptoms as young adults. Consistent with Hypothesis 1,
depressive symptoms during adolescence were related to one’s own symptoms during young
adulthood. In addition, in partial support of Hypothesis 2, several interaction effects qualified
this association. As anticipated, associations were stronger for adolescents who engaged in co-
rumination with friends when discussing interpersonal problems. Also as expected, engaging in
problem-solving talk during interpersonal conflict discussions buffered associations between
depressive symptoms during adolescence and later depressive symptoms during young
adulthood. Moreover, contrary to predictions, for males rather than females, the relation between
depressive symptoms at both time points was only evident when the dyads were rated as talking
about more interpersonal stressors. There was no evidence that friendship intimacy moderated
associations. With respect to Hypothesis 3, observed co-rumination and intimacy moderated
relationships between T1 peer depressive symptoms and T2 youth depressive symptoms, but in a
way that was contrary to predictions. More specifically, for males but not females, young adults’
depressive symptoms were predicted from their friends’ depressive symptoms at an earlier time
point only under conditions of high dyadic intimacy and co-rumination. We did not find
moderating effects of peer contagion effects for problem-solving or interpersonal stress talk.

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Depressive Symptoms During Adolescence and Young Adulthood
In line with previous research (Lewinsohn et al., 2000), depressive symptoms during
adolescence significantly predicted symptoms during young adulthood, emphasizing that the
emotional difficulties that adolescents experience may be indicative of longer-term health
concerns. It is also worth noting that in our community sample of young adults, over 20%
obtained scores that indicated at least minor levels of depression. The risk for depression may
still be quite pronounced in non-clinical populations, so targeting these young adults (e.g.,
college students, primary care clinics) may prove fruitful for depression prevention efforts.
A higher percentage of individuals reported depressive symptom scores that suggested at
least minor levels of depression during young adulthood. This finding is inconsistent with
previous research suggesting that rates remain stable or decline into young adulthood (Hankin et
al., 1998; Meadows et al., 2006), although other research has also found that depressive
symptoms increase as adolescents get older (Kiuru, Burk, Laursen, & Nurmi, 2012). More likely,
as the descriptive data of our study hints at, there is heterogeneity in the progression of
depressive symptoms across individuals (Costello, Swendson, Rose, & Dierker, 2008;
Stoolmiller et al., 2005). For example, Costello et al., (2008) found that as adolescents
transitioned into young adulthood, they followed one of several depression related trajectories:
no depressed mood, stable low depressed mood, early high declining depressed mood, and late
escalating depressed mood. Because we only had two time points of data, we were unable to
capture how patterns of depressive symptoms changed over time within individuals (Curran,
Obeidat, & Losardo, 2010). Thus, we cannot definitively ascertain that depressive symptoms
significantly increased for individuals. Research that includes three or more time points can
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employ more sophisticated data analytic strategies (e.g., growth curve modeling) to better
analyze growth patterns of depressive symptoms across adolescence and young adulthood.
Co-rumination and Problem-Solving Talk: Differential Responses to Stress
Adolescent depressive symptoms were only predictive of their own symptoms at a later
time point when they co-ruminated with friends about interpersonal problems. These results fit
with research documenting the important role of co-rumination in the emergence and
maintenance of depression (Rose, 2002; Rose et al., 2007). Depressive symptoms during
adolescence were predictive of later depressive symptoms at both mean and high levels of co-
rumination. That is, any degree of co-rumination may be sufficient to maintain pre-existing
depressive symptoms, highlighting the potentially deleterious nature of this stress response. It
may be enticing in the moment for friends to rehash and dwell on negative emotions related to
interpersonal problems, as it may temporarily relieve frustration and bring friends closer
together. Along these lines, we found a positive correlation between observed co-rumination and
dyadic intimacy in our sample (r = .21, p = .04). Yet, by continuously focusing on stressors and
negative feelings, as well as by avoiding potentially more approach-oriented and effective coping
strategies (Compas et al., 2001), adolescents may be ill equipped to handle interpersonal
challenges and subsequently experience greater stress and more negative emotions (Rose et al.,
2016). Moreover, our co-rumination construct was not in and of itself correlated with T2
depressive symptoms. Thus, it appears that co-rumination may be particularly harmful for those
who are already dealing with mental health concerns.
Problem-solving talk can be conceptualized as the social version of an alternative, more
active strategy for handling social challenges, with results suggesting buffering effects. Findings
align nicely with studies suggesting the efficacy of problem-solving as an intervention for
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depression (Klein et al., 2011), as well as research that indicates that more voluntary and active
coping strategies are associated with better psychological adjustment (Compas et al., 2001).
Adolescents prone to depression may be at risk for exhibiting social-behavioral deficits, such as
poor interpersonal problem-solving skills, that create challenges for regulating emotions and for
navigating complex social situations that arise during this developmental period (Rudolph, 2009;
Waller et el., 2014). However, interacting with friends who prompt them to identify more active
coping strategies may mitigate these effects. Adolescents in our study did not need to apply
sophisticated strategies in order to receive high ratings. Rather, brainstorming simple tactics
(e.g., talk to them about how you feel) was sufficient. Therefore, interventions that educate
adolescent friends on how to implement basic problem-solving techniques together may be
helpful in preventing the continuity of depression.
Together, results on dyadic co-rumination and problem-solving dovetail findings from
another study that found that adolescents with major depression were three times more likely to
report using co-rumination and two times less likely to report using problem-solving with friends
(Waller et al., 2014). Although studies mainly focus on co-rumination, examining dyadic co-
rumination alongside problem-solving talk with friends may yield more insight regarding how
these interpersonal stress-responses are linked with emotion regulatory abilities, coping skills,
and long-term psychosocial adjustment (Marroquin, 2011; Waller et al., 2014).
The Role of Interpersonal Stressors in Male Depressive Symptoms
Associations between T1 and T2 depressive symptoms were significant and positive at
high levels of interpersonal stress talk for males. However, for females, there was a marginally
significant association between T1 and T2 depressive symptoms at low levels of interpersonal
stress talk. These results were unexpected and run counter to the literature showing that
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interpersonal stressors tend to be particularly damaging and more strongly linked with depression
for females (Cyranowski et al., 2000; Hammen, 2003; Hankin & Abramson, 2001). In fact, some
studies have even excluded males when studying interpersonal stress and depression (Davila et
al., 1995; Hammen & Brennan, 2002).
There are several possibilities for these discrepant findings. Methodologically,
interpersonal stress is typically measured by having individuals undergo extensive interviews or
complete thorough questionnaires asking them about various events that have occurred over
lengthier periods of time (Liu & Alloy, 2010). In contrast, for this study, we only requested that
adolescents discuss a few current interpersonal problems for five minutes. Thus, we may not
have completely captured the degree of interpersonal chaos that these adolescents had
encountered. Providing participants with longer discussion times and encouraging them to
discuss various social challenges that transpired during a longer time frame may have yielded
more accurate portrayals of their interpersonal stress encounters. Second, depressive symptoms
in females are especially related to dependent stressors, which are those that are considered to be
at least partially due to characteristics or behaviors of individuals with depressive symptoms
(Hammen, 2006). Our study did not distinguish between dependent stressors (e.g., getting into a
fight with a friend, having trouble with a boss) and stressors that are beyond the adolescents’
control (e.g., family stressors due to parent losing a job), and it is possible that doing so may
have influenced results. A final possibility might be that females are more likely to disclose
personal information with friends (Buhrmester & Prager, 1995; Rose & Rudolph, 2006), so
discussing social stressors may be more commonplace, familiar, and even comforting for them.
On the other hand, because divulging interpersonal problems is less the norm for males, when
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males did discuss interpersonal problems, it may have been reflective of more severe and chronic
concerns that create greater risk for mental health problems.
Dyadic Processes as Moderators of Peer Contagion of Depressive Symptoms
Although co-rumination has often been theorized to play a critical role in depression
contagion (Giletta et al., 2011; Dishion & Tipsord, 2011), this study is the first to our knowledge
to demonstrate observed co-rumination as a moderator of peer socialization of depressive
symptoms. This study also found that for males, adolescent depressive symptoms were
longitudinally linked with their friends’ depressive symptoms in the context of highly intimate
friendships. Intimate friends may spend more time with one another, partake in more emotional
disclosure, and influence each other more strongly. These individuals may thereby encounter
greater exposure to distressing emotions, as well as develop vulnerability to conforming to the
depressogenic feelings and behaviors of their friends over time (Heilbrun & Prinstein, 2008).
That co-rumination and intimacy interacted with depressive symptoms for males and not females
was unexpected, especially given research that negative emotional consequences of co-
rumination tend to be more salient for females (Rose & Rudolph, 2006) and that self-disclosure
among males may be protective against depressive symptoms (Landoll et al., 2011). Important to
note is that the bulk of studies on co-rumination have relied on self-report data, suggesting that
different methodologies may pick up on different components of co-rumination. Whereas
questionnaires may more accurately measure individuals’ perceptions of how often they co-
ruminate with various close friends, observing co-rumination (albeit only for a brief period of
time) may capture some of the nuances of this stress-response that may be particularly potent for
males. Research that incorporates both questionnaire and observational measures of co-
rumination may be best suited to understand how this construct differentially influences males
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and females across time. Finally, whereas previous studies have focused on young and middle
adolescents and used relatively shorter time gaps, such as less than a year (Landoll et al., 2011;
Rose, 2002; Rose et al., 2007), the present study examined older adolescents and young adults,
with an average time gap of 4.18 years. It is therefore possible that friendship dynamics may
have differing effects on males and females as they developmentally mature.
Study Limitations
The present study has several limitations that warrant discussion. First, there was an
overlap in the ages of late adolescents and young adults. Although the bulk of late adolescents
were under the age of 20 and the majority of young adults were over the age of 19, the lack of a
discrete age cut off limits developmental interpretations of how social processes may offer risk
or protection as adolescents mature into young adulthood. Similarly the amount of time that
elapsed between T1 and T2 procedures was variable across participants. A more consistent time
gap would be preferable, though amount of elapsed time between the two data collection points
was not significantly correlated with depressive symptoms or with any of the observed variables.
The study’s use of a community sample has both benefits and drawbacks. Because a large
percentage of adolescents with depression do not seek mental health treatment (Essau, 2005),
examining non-clinic referred adolescents and young adults may be a more accurate
representation of individuals who experience depressive symptoms. A community sample may
also be more appropriate in light of our aim to focus on adolescents and young adults who might
be at risk for but do not necessarily yet meet diagnostic criteria for clinical depression. On the
other hand, as would be expected when using a community sample, the majority of participants
did not endorse high levels of depressive symptoms at either time-points. Thus, it is possible that
study findings may not generalize to adolescents experiencing clinically diagnosable major
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depression. Also, we examined depressive symptoms on a continuum, but individuals who
scored an eight on the BDI-II may not be meaningfully different from those with a score of one,
for example, given that both reflect minimal levels of depression. Future research would benefit
from further studying observed interpersonal dynamics in clinic referred adolescents and young
adults, as well as comparing outcomes in individuals who do and not meet diagnostic criteria for
depression.
We asked participants to engage in discussions about interpersonal challenges and to
devise problem-solving strategies. Thus, it is possible that some of our codes picked up on
participants’ efforts to comply with task instructions. Yet, there was sufficient variability within
the rated behaviors to suggest that not all participants were simply following directions.
Furthermore, other studies assessing observed co-rumination have also utilized a problem-
solving paradigm (Byrd-Craven et al., 2011; Rose et al., 2014). However, assessing dyadic
processes in a more open-ended discussion or in more naturalistic settings (e.g., online social
networking sites, randomly recorded discussions of adolescents throughout the week) may yield
more realistic measures of these constructs. Finally, we rated adolescent dyads on co-rumination
based on five-minute long conversations, whereas co-rumination typically involves continuously
discussing and rehashing interpersonal problems. Therefore, we were only able to obtain a
glimpse of these maladaptive interactions. At the same time, the fact that we were still able to
obtain significant findings speaks to the potency of co-rumination as a potentially disruptive
social process. However, future observational research may benefit from using longer discussion
times to more accurately measure co-rumination.
Despite the aforementioned limitations, this study also presents with various strengths,
namely the use of observational data with respect to meaningful discussions between close
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friends. The use of multiple methods and measurement of depressive symptoms at two time
points are also strengths.
Conclusion
In sum, results point to the relevance of considering adolescent peer interactions,
particularly how friends talk about and resolve interpersonal problems, when considering risk
factors for mental health problems. Although research on young adulthood suggests that other
forms of interpersonal connections, such as romantic relationships, become critical during young
adulthood (Fincham & Cui, 2011), the social experiences that individuals encounter as
adolescents may still inform their psychosocial health and ability to confront interpersonally
complex situations. Furthermore, whereas females tend to receive the most attention with regards
to interpersonal processes and internalizing symptoms, findings from this study attest to the
importance of focusing on the intersection of mental health and social processes for male
adolescents and young adults. From an intervention standpoint, targeting adolescent friendships
may prove beneficial for preventing depression. For example, teaching basic problem-solving
strategies to adolescent friends at risk for depression, as well as educating them about how to
recognize and curtail co-ruminative behaviors may help bolster their interpersonal coping
repertoire and reduce the chances of developing internalizing problems as they face the many
shifts that accompany young adulthood.

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Table 1.

Code Examples and Inter-rater Reliability
Code Examples
Inter-rater
Reliability
Co-
Rumination
• Let’s get back to [Name] (after talking about her without any
solution for the entire previous discussion).
• I don’t know what to do with her, she’s so stressful.
• This is another friend issue…we just keep going on in
different tangents.
• Adolescent 1:Talk about the degrading stuff she said to you.
Adolescent 2: I think that no friend should keep you on a
leash like that…It’s just this unresolved issue.
.69
Problem-
Solving
• Maybe talk it out with him, her, and you. Go somewhere and
talk it out.
• (In the context of girl troubles) I would talk to someone in an
intimate relationship… go to a female you trust who is older.
• Have you ever really tried to talk to your dad about what
issues you have?…A lot of times people don’t know what they
are doing…because nothing has been said…I wouldn’t cut
him off completely, because that’s your father and you do
love him, but try to talk to him, even if you can’t talk to him
face-to-face, write him a letter.
• Adolescent 1:What are you going to do to try to resolve it?
Adolescent 2: Try to meet him on his level more.
Adolescent 1:Yeah, it’s a two way street.
.85
Intimacy • You’re the first person I told about that.
• He’s like, you guys are always talking. I’m like, we’re
friends.
.51
Interpersonal
Stress Talk
• We’re in a really bad place right now…I’m kind of angry at
my dad for letting this all happen…he [dad] was talking
about how he feels like the only reason he is alive is because
he’s afraid [family member] will find his body.
• She was my best friend and then she did some not so nice
things and now she’s my ex-best friend…she thinks she didn’t
do anything wrong but I think what she did was completely
wrong.
.73
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Table 2.

Descriptive Statistics of Depressive Symptoms, Observed Behaviors, and Covariates
Males
M (SD)
Females
M (SD)
Total
M (SD)
T1 Depressive Symptoms 7.21 (7.24) 7.82 (5.94) 7.51 (6.61)
T2 Depressive Symptoms 8.40 (9.03) 8.73 (6.54) 8.56 (7.88)
T1 Peer Depressive Symptoms 7.90 (5.38)
a
11.68 (9.19)
a
9.73 (7.67)
Co-Rumination .37 (.48) .51 (.64) .44 (.57)
Problem-Solving Talk .80 (.55)
b
1.07 (.70)
b
.93 (.64)
Intimacy 2.27 (.51)
c
2.54 (.37)
c
2.40 (.47)
Interpersonal Stress Talk .64 (.29)
d
.84 (.42)
d
.74 (.37)
T2 Age 22.48 (1.88) 22.07 (1.88) 22.28 (1.88)
Father Depressive Symptoms .33 (.33) .35 (.39) .34 (.36)
Mother Depressive Symptoms .44 (.36) .48 (.46) .46 (.41)
Note. Matching superscripts denote that males and females differed on this variable at p <
.05. T1 = Time 1, T2 = Time 2.
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Table 3.

Correlations Among Study Variables For Males (Above Diagonal) and Females (Below Diagonal)

Note: n = 48 males and 45 females.
p < .05, ** p < .01.
1. 2. 3. 4. 5. 6. 7. 8. 9. 10.
1. T1 Youth Depressive Symptoms -- .48** .19 .42** -.20 .18 .14 .07 -.12 -.06
2. T2 Youth Depressive Symptoms .23 -- .03 .18 -.31* .04 .06 -.18 -.03 -.13
3. T1 Peer Depressive Symptoms -.08 .17 -- .03 -.02 .04 .31* .23 .09 .33*
4. Co-Rumination .07 .02 -.01 -- -.24 .10 -.03 -.09 .04 .28
5. Problem Solving .06 -.11 .11 -.32* -- -.10 .20 -.02 .03 -.21
6. Intimacy .15 -.09 -.25 .30* .20 -- .19 .13 .10 .08
7. Interpersonal Stress Talk -.21 .24 -.07 -.32* .16 .14 -- .21 .29 .01
8. Age -.01 .01 -.16 -.06 .08 .05 .14 -- -.03 .06
9. Father Depressive Symptoms .43** .27 .05 .15 .13 .06 -.03 -.05 -- .08
10. Mother Depressive Symptoms .21 .48** .08 .07 .02 .04 .16 .30* .35* --
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Table 4.

Number of Youth Who Scored a 14 or Higher on the BDI-II at Time 1 and Time 2
Note. T1 = Time 1; T2 = Time 2. Scores of 14 or above indicate at least minor levels of
depression.

Female Male
T2 Score of 14 or Above
Yes No Yes No
T1 Score of 14
or Above
Yes 3 4 3 1
No 9 29 5 39
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Table 5.

Co-rumination, Problem-Solving Talk, Intimacy, and Interpersonal Stress Talk as Moderators of
Associations Between Time 1 and Time 2 Depressive Symptoms
Note. All coefficients are unstandardized. T1 Youth Dep = Youth depressive symptoms at time 1; T2
Peer Dep = Peer depressive symptoms at time 2; Maternal Dep = Youths’ maternal depressive symptoms.
*p < .05, ** p < .01, ***p < .001.

R
2
b

SE

95% CI R
2
b

SE

95% CI
Co-
Rumination
.07**
Problem-
Solving Talk
.04*
Constant 8.20** .75 [6.71, 9.70] Constant 8.47** .74 [7.01, 9.93]
Sex -.64 1.58 [-3.78, 2.51] Sex -1.04 1.58 [-4.17, 2.10]
T1 Peer Dep .01 .10 [-.20, .22] T1 Peer Dep .06 .10 [-.14, 26]
Maternal Dep 2.64 1.88 [-1.09, 6.38] Maternal Dep 1.94 1.84 [-1.72, 5.60]
T1 Youth Dep .30* .16 [.04, .56] T1 Youth Dep .32* .12 [.08, .57]
Co-Rumination -.92 1.42 [-3.74, 1.90] Problem
Solving
-2.68* 1.21 [-5.08, -.28]
Depressive
Symptoms X
Co-Rumination
.42* .16 [.10, .74] Depressive
Symptoms X
Problem
Solving
-.46* .20 [-.86, -.05]
Intimacy
.02
Interpersonal
Stress Talk
.00
Constant 8.32 .78 [6.78, 9.87] Constant 8.54*** .76 [7.03, 10.06]
Sex -.16 1.65 [-3.43, 3.11] Sex .92 1.63 [-2.33, 4.16]
Maternal Dep 2.53 1.91 [-1.27, 6.32] Maternal Dep 1.84 1.92 [-1.97, 5.65]
T1 Peer Dep .03 .11 [-.18, 25.] T1 Peer Dep .07 .10 [-.14, .27]
T1 Youth Dep .40** .13 [.15, .65] T1 Youth Dep .47*** .12 [.23, .70]
Intimacy -.53 1.82 [-4.14, 3.09] Interpersonal
Stress Talk
3.00 2.27 [-1.51, 7.50]
Depressive
Symptoms X
Intimacy
.45

.32 [-.17, 1.08] Depressive
Symptoms X
Stress Talk
-.05 .37 [-.80, 69]
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Table 6.

Behaviors as Moderators of Associations Between Peer and Youth Depressive Symptoms

Note. All coefficients are unstandardized. Dep = Depressive symptoms; T1 Youth Dep = Youth
depressive symptoms at time 1; T2 Peer Dep = Peer depressive symptoms at time 2; Maternal Dep =
Youths’ maternal depressive symptoms.
+p < .10, *p < .05, **p < .01, ***p < .001
CoruC R
2
b

SE

95% CI R
2
b

SE

95% CI
Co-
rumination
.04*
Problem-
Solving Talk
.02
Constant 8.50*** .75 [7.01, 10.00] Constant 8.47*** .75 [6.98, 9.96]
Sex .27 1.56 [-2.84, 3.39] Sex -.21 1.57 [-3.33, 2.92]
T1 Youth Dep .40** .12 [.16, .64] T1 Youth Dep .45*** .11 [.22, .68]
Maternal Dep 2.20 1.90 [-1.57, 5.98] Maternal Dep 1.51 1.89 [-2.24, 5.26]
T1 Peer Dep .10 .10 [-.11, .31] T1 Peer Dep .10 .10 [-.11, .30]
Co-
Rumination
-.41 1.41 [-3.21, 2.40] Problem
Solving
-2.64 1.24 [-5.10, -.18]
Dep X Co-
Rumination
.38* .19 [.01, .75] DepX Problem
Solving
.18 .12 [-.07, .43]
Intimacy
.03+
Interpersonal
Stress Talk
.001
Constant 8.60*** .75 [7.10, 10.10] Constant 8.52*** .76 [7.01, 10.04]
Gender -.29 1.63 [-3.53, 2.96] Gender .82 1.64 [-2.44, 4.09]
T1 Youth Dep .44** .12 [.20, .67] T1 Youth Dep .47*** .12 [.23, .70]
Maternal Dep 1.90 1.89 [-1.85, 5.66] Maternal Dep 1.77 1.93 [-2.07, 5.61]
T1 Peer Dep .13 .11 [-.09, .35] T1 Peer Dep .06 .11 [-.15, .27]
Intimacy -1.66 1.74 [-5.12, 1.80] Interpersonal
Stress Talk
3.11 2.14 [-1.14, 7.37]
Dep X
Intimacy
.39+

.20 [-.01, .78] Dep X Stress
Talk
.08 .26 [-.43, .59]
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Figure 1. Scatterplot graph of youth depressive symptoms at times 1 and 2 for males and
females.

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Figure 2a. Associations between youth time 1 and time 2 depressive symptoms at low, mean,
and high levels of co-rumination. *p <.05 ***p <.001.

Figure 2b. Associations between youth time 1 and time 2 depressive symptoms at low, mean,
and high levels of problem solving talk. *p <.05 ***p <.001.
0
2
4
6
8
10
12
Low T1 Depressive
Symptoms
High T1
Depressive
Symptoms
T2 Depressive Symptoms
Low Co-rumination
Mean Co-rumination
High Co-rumination
0
2
4
6
8
10
12
14
16
Low T1 Depressive
Symptoms
High T1 Depressive
Symptoms
T2 Depressive Symptoms
Low Problem Solving
Mean Problem Solving
High Problem Solving
b = .03 (ns)
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Figure 3. Associations between time 1 and time 2 youth depressive symptoms moderated
by interpersonal stress talk for females (top graph) and males (bottom graph). + p < .10 ** p <
.01.

0
2
4
6
8
10
12
14
16
18
Low T1
Depressive
Symptoms
High T1
Depressive
Symptoms
T2 Depressive Symptoms
Female T1 and T2 Depressive Symptoms, Moderated by
Interpersonal Stress Talk
Low Interpersonal
Stress Talk
High Interpersonal
Stress Talk
0
2
4
6
8
10
12
14
16
18
Low T1
Depressive
Symptoms
High T1
Depressive
Symptoms
T2 Depressive Symptoms
Male T1 and T2 Depressive Symptoms, Moderated by
Interpersonal Stress Talk
Low Interpersonal
Stress Talk
High Interpersonal
Stress Talk
b = .02 (ns)
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Figure 4. Associations between time 1 peer and time 2 youth depressive symptoms at low and
high levels of co-rumination. + p < .10.
0
2
4
6
8
10
12
Low T1 Peer
Depressive
Symptoms
High T1 Peer
Depressive
Symptoms
T2 Youth Depressive Symptoms
Low Co-rumination
High Co-rumination
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Figure 5. Associations between time 1 peer and time 2 youth depressive symptoms moderated
by co-rumination for females (top graph) and males (bottom graph). * p < .05.
0
2
4
6
8
10
12
14
16
18
Low T1 Peer Depressive
Symptoms
High T1 Peer Depressive
Symptoms
T2 Youth Depressive Symptoms
Females
Low Co-rumination
High Co-rumination
b = .07 (ns)
0
2
4
6
8
10
12
14
16
18
Low T1 Peer Depressive
Symptoms
High T1 Peer Depressive
Symptoms
T2 Youth Depressive Symptoms
Males
Low Co-rumination
High Co-rumination
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Figure 6. Associations between time 1 peer and time 2 youth depressive symptoms moderated
by intimacy for females (top graph) and males (bottom graph). * p < .05.

0
2
4
6
8
10
12
14
16
18
Low T1 Peer Depressive
Symptoms
High T1 Peer Depressive
Symptoms
T2 Youth Depressive Symptoms
Females
Low Intimacy
High Intimacy
b = .06 (ns)
0
2
4
6
8
10
12
14
16
18
Low T1 Peer Depressive
Symptoms
High T1 Peer Depressive
Symptoms
T2 Youth Depressive Symptoms
Males
Low Intimacy
High Intimacy
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Overall Discussion

This dissertation was designed to better understand links between adolescent peer
interactions and depressive symptoms. Research on how adolescents with depressive symptoms
behave with friends and how these dyadic exchanges inform long-term psychosocial health is
limited. Using an observational research paradigm, this project offers new information by
highlighting peer behaviors that may or may not be key for identifying and preventing adolescent
depression. In the following sections, I highlight some of the main findings of the two papers
comprising this dissertation and summarize possible future research directions.
Overall Findings
In Paper 1, we aimed to identify behavioral indicators of depressive symptoms. We found
an association between depressive symptoms and female adolescents’ criticism of friends.
Adolescent depressive symptoms were also negatively associated with their friends’ observed
irritability and conversational self-focus. Furthermore, findings suggested that adolescent
depressive symptoms interacted with exposure to family aggression to predict increased
irritability and the use of obscenities with friends. Interpersonal theories of adolescent depression
often overlook the role of the family, but this study’s findings speak to the importance of
considering how family risk factors interact with adolescent mental health to inform
interpersonal relationships (Rudolph, 2009). Results did not support our hypotheses of
significant associations between depressive symptoms and our coded behaviors. As discussed in
Paper 1, there are several possibilities underlying the lack of significant results, ranging from
methodological to theoretical reasons. For example, the coded behaviors we studied simply may
not be related to depressive symptoms, or these connections may only be evident under certain
conditions. Alternatively, the 30-minute peer discussions might not have been sufficiently long
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to capture these behaviors. Further unpacking the meaning of these coded behaviors and how
they may vary across differing circumstances may elucidate their relationships with depressive
symptoms.
Adding to the growing literature on co-rumination, Paper 2 investigated observed co-
rumination as a moderator of associations between participant depressive symptoms during
adolescence and young adulthood. In accordance with previous research (Rose, Carlson, &
Waller, 2007), findings suggested that adolescents who engage in co-rumination, even for short
amounts of time, may be at greater risk for experiencing depressive symptoms as young adults.
Furthermore, results indicated that when adolescents are observed to discuss problem-solving
tactics with friends, they may be buffered from experiencing later depressive symptoms. We
propose that co-rumination and co-problem-solving are two coping responses friends can assume
when handling interpersonal problems (Waller, Silk, Stone, & Dahl, 2014).
These findings may have important clinical implications. Interventions that provide
adolescents who are at-risk for depression with skills on how to adaptively address interpersonal
problems may be particularly useful. For example, school-wide prevention programs can educate
adolescent students about the risks of co-rumination, as well as teach them problem-solving tools
to adaptively handle different social challenges. Mental health professionals who work with
adolescents with depression may also find it beneficial to pay particularly close attention to how
these individuals talk about and handle different interpersonal stressors.
Paper 2 also found that males’ depressive symptoms predicted their friends’ depressive
symptoms when these two adolescents engaged in high levels of co-rumination as adolescents.
Although the literature on adolescent depression mostly focuses on depression risk factors for
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females, study results highlight the importance of continuing to examine how various
interpersonal factors differentially influence depression in males versus females.
Future Research
The two papers thoroughly examined different adolescent behaviors and communication
patterns, but did not investigate peer relationship outcomes. In order to further integrate the lines
of research presented in this dissertation with the interpersonal depression research, it would be
helpful to examine how the coded behaviors in our papers are connected with friendship outcome
variables. Second, a more detailed analysis of these peer discussions (e.g., linguistic analysis of
discussion content, coding each talk-turn to understand how behaviors in one adolescent
temporally precede behaviors in the other one) may offer an even deeper scientific understanding
of whether depressive symptoms predict the unfolding of certain interpersonal patterns.
In contrast to research that employs peer nomination techniques, which require that
participants reciprocally nominate each other as friends, the friend selection process in these
dissertation papers was unidirectional. That is, youth who were part of a larger longitudinal study
chose a close friend to bring into the lab, but it is unknown whether these selected peers would
have chosen the youth in return if given the chance. Also, we required that friends within a dyad
be the same sex. However, some youths’ closest friends may have been of the opposite sex,
thereby requiring youth to identify friends with whom they were not as close. The nature of
friendships also varied across friend dyads. For example, whereas some youth brought in one of
their closest friends, others may have had a difficult time identifying a friend willing to
participate with them and consequentially brought in a friend who was not a first choice. Some
friends knew each other from school and had many friends in common, and other friend dyads
knew each other outside of the school setting and may not have been familiar with each other’s
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peer networks. Furthermore, because we did not require friends to be the same age, some youth
may have selected friends who were older or younger in age. These varied peer selection
processes may have important implications regarding participants’ interpersonal skills as well as
how the friends interacted with one another during the videotaped discussions. Future research
would benefit from considering how these friend selection processes differentially relate to
observed interpersonal dynamics, maladaptive social styles, and adolescent and young adult
mental health.
Examining friendship interactions among a more extensive peer network and outside of
the laboratory setting can enhance the generalizability of study findings. For example, although
we focused on friend dyads, adolescents often spend time in cliques (Rubin, Bukowski, Parker,
& Bowker, 2008) or utilize technology, such as social networking sites, to maintain interpersonal
relationships (Shapiro & Margolin, 2014). It would be informative to examine the behavioral
correlates and interpersonal consequences of depression in these circumstances. Furthermore,
cutting edge methodologies via smartphones are being employed to capture speech segments
from individuals in naturalistic settings (Timmons et al., 2017). Researchers can also apply these
methods to gain an ecologically valid understanding of how adolescents with depressive
symptoms act with friends.
Finally, we focused on depressive symptoms, but the coded behaviors in our sample may
be behavioral indicators of other forms of adolescent psychopathology. For example, non-
suicidal self-injury and eating disorders are also prevalent during adolescence and might be
linked between friends (Dishion & Tipsord, 2011; Heilbron & Prinstein, 2008; Hutchinson &
Rapee, 2007; Paxton, Schutz, Wertheim, & Muir, 1999). Examining how these mental health
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concerns are associated with coded friend behaviors therefore may yield additional findings
regarding the intersection of interpersonal behaviors and adolescent psychosocial development.
In sum, this dissertation underscores the importance of considering friend interactions
when studying risk factors for depression. Exploring how specific and targetable interpersonal
behaviors are connected with depression may prove critical in preventing the escalation of
depressive symptoms as youth transition through adolescence and young adulthood.

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Appendix A: Coding Manual

Peer Discussion Coding Manual

Ilana Kellerman Moss & Gayla Margolin
Coding Procedure- Global Version (Adapted from Iturralde, 2011)
● Discussions for individual topics all take 5 minutes each. The coding sheet has a place to
record the starting and stopping time for each topic. The starting time begins when the first
person starts talking. Observations should not be coded beyond 5 minutes past that
starting time. Even if the conversation lasts past 5 minutes, you should stop coding at the 5-
minute mark and make a note that the discussion lasted longer.
● Raters watch one youth at a time. Therefore, they watch each discussion at least twice,
once to code for their designated first youth, and a second time to code for their designated
second youth. If necessary, raters may rewind to re-watch difficult sections of the discussion.
● For every dyad, a coding log (which is located in a binder in room 932 with the title
“Friend Discussion Coding”) lists which of the two youth should be coded first for Topic 1. This
“Youth 1” is counterbalanced across dyads and alternated between coders. The target youth (T)
is always the youth who presents “the problem with a person” in Discussion 1. Unless otherwise
noted, this is also the youth who sits on the right side of the room. The invited peer (P) presents a
problem in Discussion 2 and sits on the left side of the room.
● After Topic 1, raters switch which youth they code first per topic. For example, if the
rater codes the target first for Topic 1 (and therefore the peer second for Topic 1), then for Topic
2, the rater codes the peer first, followed by the target.
● On a single coding sheet, raters record a score (ranging from 0-3) for each youth for each
code for every discussion topic (discussions 1-8). However, for the dyadic codes, a 0-3 score is
assigned to the dyad, not to each youth individually. These codes should be scored after the rater
has finished scoring both the target and peer for the individual codes.
● If you are unsure about whether or how to assign a code to a
comment/behaviors/interaction. Please mark when it occurred in the video, take notes on what
was confusing about this for you, and bring this up during the next coder meeting.
● After coding each topic, please make sure to take notes on anything interesting, please
make sure to take notes on anything interesting, unusual, or confusing about the discussion or
about the coding system.
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● After coding the discussion, there are seven questions that ask you to rate your general
impression of the discussion and dyad. Please answer these questions after you are done coding
the video. You do not need to go back and watch anything before answering this question.
III. Coding Scale & Definitions
The following scoring guide applies to most codes (from Iturralde et al., 2011)

In many cases, the definitions below (None, Some, A moderate amount, A lot) are enough to
know what score is appropriate for a given code. The additional Description information is
provided to assist the rater in deciding more difficult cases, such as when trying to decide
between a 2 or a 3 on a given code.

Code Definition Description
(See below for definitions of terms used in this column)
0 None No hints, statements, or non-verbal indications of the behavior
1 A Little 1-2 hints OR
1 statement or non-verbal cue of regular intensity
2 A moderate amount, 3+ hints, OR
2 statements of regular intensity OR
2+ non-verbal cues of regular intensity OR
1 statement of high intensity
3 A lot 3+ statements or non-verbal cues of regular intensity OR
2+ statements or non-verbal cues of high intensity OR
1+ statement or non-verbal cue of extremely high intensity
Hint
● Vague or ambiguous statements that might match the code but are difficult to interpret
● Statements that match the code in content but not affect, or in affect but not content
● Bound by ordinary grammatical constraints, such as sentences or sentence fragments. One
speaker turn may contain multiple hints.
● Non-verbal cues that are ambiguous or contain incongruent affect. Bound by the behavior,
or if continuous, by speaker turn. Could be coded while the youth is speaking or while listening.

Statement
● A verbal remark that matches the code
● Bound by ordinary grammatical constraints, such as sentences or sentence fragments
● One speaker turn may contain multiple statements

Non-Verbal Cue
● Non-verbal behavior that matches the code
● Bound by the behavior, or if continuous, by speaker turn
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● Could be coded while the youth is speaking or listening

IV. CODES
1) Negative Interpersonal (Criticism): Negative statements made toward the other adolescent
in the room. Includes negative statements about friend’s idea, behavior, qualities or
characteristics. Also includes verbal indications of frustrations or dismissive comments. Negative
comments may be overt, but they may also be subtler in nature, or be coated with humor or
something even positive. This would not get coded if the adolescent insults a friend who is not in
the room/part of the discussion task. This code only includes verbal negative comments. Non-
verbal indications of frustration or irritation would be coded under non-verbal negative.
EXAMPLES:
“You can be annoying sometimes.”
“ That’s a weird thing of you to say.”
“She is way out of your league. Haha, just kidding!”
“Why would you even think about doing something like that?”
This would not get coded: “ Yeah, Sam (person not in room) sucks,” or “why are all of our
friends so annoying?” (consider the latter example for Irritability/Hostility)
This would not get coded: Someone laughing at someone else’s comment, unless it is
accompanied by a negative statement. (2/24/16)
2) Positive Interpersonal (Supportive Talk): Verbal positive or supportive statements made
toward the other adolescent in the room. Includes specific praise about the person’s ideas,
behavior, or characteristics, as well as acknowledgements that the friend in the room is doing
something positive. This would not get coded if the adolescent compliments a friend who is not
in the room/part of the discussion task.
EXAMPLES:
“I really like that you are always honest to people.”
“I like your shirt”
“You are one of my closest friends” (Double code with intimacy)
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Note: If a adolescent spontaneously tells the other person that they are their best friend, this can
be counted as a high intensity statement.
3) Reassurance Seeking: This is coded when adolescents ask their friends for reassurance about
their worth, their actions, or that their friends really cares about them. It can also include asking
their friends to provide a positive opinion about them or asking the friends for reassurance about
others’ opinions about them. Asking for reassurance about a problem solving technique (“do you
think it is a good idea to talk to my mom about this?”) would not be coded as reassurance the
first time. But, if the participant continues to ask for reassurance that this strategy is a good idea,
then it gets coded.
EXAMPLES:
“Do you consider me to be one of your close friends?”
“Do you think that he likes me?”
Hint: Adolescent makes a comment that seems as if it is encouraging the friend to provide a
compliment or reassurance (e.g., “ I wonder what he thinks about me.”)
4) Negative Feedback Seeking: Soliciting criticism and negative feedback from other friend in
the room. Although similar to reassurance seeking, this code is different in that instead of asking
for positive reassurance, youth encourage their friends to say something negative about them.
EXAMPLES:
“What do you think I should change about myself?”
“She is a lot prettier than I am, don’t you think?”
“ I can get annoying sometimes, can’t I?”
5) Negative Self-Evaluation: The adolescent makes a verbal critical or negative statement about
him/herself, or says something negative about an idea he/she has. Many adolescents will point
out something they want to change about themselves, but this code pulls for when youth
negatively evaluate an aspect of themselves, want to change something that is not easily
changeable, frame what they want to change in a non-constructive way, or continue to discuss
things they want to change about themselves. When figuring out whether to assign this score,
and how severe it should be, it may help to consider the following:
● Are they framing what they want to change about themselves in a constructive way (“I
want to study harder to do better in school”) or not?
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● Are they mentioning things that are hard to change (“I want a smaller nose” versus “I
want to try and be more patient with others”)?
● Are they naming just one thing or going on about things they want to change about
themselves?
EXAMPLES:
“ I want to be skinnier, taller, and better looking”
“Gosh, why am I such a bitch sometimes?”
“I know this is a dumb thing to worry about, but...” (would get a 1)
This would NOT get coded: “I want to try and study harder in school”
6) Positive Self-Evaluation: Adolescent makes a verbal positive statement about themselves.
This includes saying something clearly positive about themselves, as well as acknowledging that
they are trying to better themselves. This includes saying something positive about something
they did (“I did a good job in the play”) or something positive about themselves more globally
(“I like myself overall.”)
EXAMPLES:
“I am really good at languages”
“I think I have become a better listener.”
“ I like who I am”
“I am working really hard at this” (would get a 1)
7) Conversational Self-Focus (Adapted from the Interpersonal Processes in Friendships:
Observational Coding Manual; Schwartz-Mette & Rose, 2007) : Redirecting the conversation
away from the friend and toward their own problem or another topic related to themselves. This
shift in focus to the self can be in response to someone else’s disclosure about something more
personal/vulnerable or about a problem they have. However, self-focus can also occur in the
context of positive or neutral topics. This code is also given when an adolescent, 1) Continues to
talk about him/herself regardless of the partner’s response, 2) Dominates a conversation with
his/her problems/personal information/opinions without taking into account or listening to the
friend’s opinion or by interrupting the friend. Conversational self-focus may contain the
following components:
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• Shifting conversations to make statements about the self and making “me” or “I”
statements.
EXAMPLES:
Adolescent 1: I am having a hard time trying to get my dad to trust me.
Adolescent 2: Yeah, I had a similar issue recently. I am totally responsible, but he would just pry
into my business all the time.

Adolescent 1: I really like Zoe.
Adolescent 2: Oh my gosh, me too. I saw her the other day, and she looked really cute!

Note: If adolescent 2 just says “Oh my gosh, me too” then brings the attention back to adolescent
1 immediately, then this would probably not get coded. However, if adolescent 2 then continues
to talk about how he/she likes Zoe, conversational self-focus would be coded. Alternatively if
adolescent 2 repeatedly makes comments like the one above, he/she would get coded for
conversational self-focus.

General Notes:
If the adolescent says something like “me too” or “oh, I know what that’s like, that happened to
me,” you want to consider the number and intensity of these comments and what happens in the
conversation. For example, do they go back to the person who was talking or do they continue to
talk about themselves? If it is only once and does not interrupt the conversation, then it probably
would not get coded. However, if a standard response is to take what the friend says and make it
about themselves, then it would get coded. Similarly, with very short statements (“Oh yeah, I
procrastinate too”), if they say it two or more times, it probably warrants a code

• Changing the subject abruptly to be about themselves when the friend is talking
about a problem or something personal.
EXAMPLES:

Adolescent 1: I am really stressed out about what I am going to do right.
Adolescent 2: I could go for some pizza right now.

Adolescent 1: “I am really struggling in that class.”
Adolescent 2: “Sarah said the weirdest thing to me the other day.”

Even though Adolescent 1 is talking about something and Adolescent 2, says, “Okay let’s talk
about this [another topic]”

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Adolescent 1: I really like Zoe.
Adolescent 2: Uch, this week has been so stressful for me.

Sometimes a youth may interrupt his/her friend 2 to say something off topic or irrelevant to what
the other friend is saying. Generally, you want to code this, particularly if it seems that the youth
is changing the subject out of disregard for what the friend is saying. However, this would not
get coded if the youth gets interrupted accidentally, and they try to attend to what the friend is
saying (e.g., if the youth’s phone rings, he/she apologizes and shuts off the phone while
continuing to encourage the friend to talk)

• Taking a friend’s comment and “one-upping” it.
EXAMPLES:

Adolescent 1: I really like Zoe. I am not sure if she likes me.
Adolescent 2: She just invited me to a party!

Adolescent 1: I am worried about getting all of my classwork done.
Adolescent 2: You think that you have a lot of school-work? Let me tell you what I have to do!

Sometimes Adolescent 2 may reflect on how Adolescent 1’s problem relates to them and give an
example of how they were in the same situation in order to be supportive. If Adolescent 2 goes
on about how the problem relates to them but brings the conversation back to help Adolescent 1,
then Adolescent 2 would get scored a lower score, such as a 1 (depending on how long they kept
the conversation focused on themselves).
Overall, when deciding if and how much to code comments that can either be supportive or self-
focus, you want to consider the number and intensity of these comments and what happens in the
conversation (do they go back to the person who was talking or do they continue to talk about
themselves?)
OTHER EXAMPLES:
Adolescent 1: “I really like Jessica.”
Adolescent 2: “Oh yeah, she’s cool.”
Adolescent 1: “Yeah.”
Adolescent 2: “I am really into Rachel. She’s pretty awesome.”

Adolescent 1: “It would be nice to find someone to date.”
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Adolescent 2: “Yeah, you should have someone nice, not like Max (Adolescent 2’s ex). He is the
worst” Note: This might receive a lower score because it starts as a reflection but then turns to be
about Adolescent 2.

Adolescent 1: I don’t like it how he doesn’t follow through when he says he will
Adolescent 2: He does the exact same thing with me.

8) Verbal Obscenities: Using curse words or obscene words. When trying to decipher whether
statements count as curse words or not, the general rule to use is to think to yourself: “Would I feel
comfortable using this word in front of a teacher who I respected or in front of a young child?”
Examples of curse words: Fuck, cunt (saying one of these words once is generally sufficient to give
a three), bitch, shit, f*ggot, n*gger, asshole, slut, damn/dammit, hell, dick, slut, ho, skank, prick,
douche, titties, cock, wanker.
Words that would count if said in a pejorative way: dyke, homo, queer, gay, retarded
More mild obscenities: crap, piss/pissed off, screwed, arse
Examples of variations of curse words (often count as hints): d-bag, freaking, sonofa, DTF, effing,
SOB (counting for son of a bitch), mofo…
9) Non-Verbal Positive Affect: Non-verbal expressions indicative of happiness, enthusiasm, or
non-verbal support of friend. Includes:
• Smiling
• Laughing
• Leaning toward the person in a friendly manner
• Touching the other person in an affectionate manner
10) Non-Verbal Negative Affect: Expressions of disapproval, anger, irritability, frustration, or
annoyance through actions toward the other adolescent in the room. Can be simultaneous to
words. Includes:
• Rolling eyes
• Grimacing, frowning, or scowling at other person
• Shaking head no without smiling
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• Sighing at other person.
• Mocking mimicry of other’s gestures
• Behaviors that suggest the someone is mocking the other person
• Having an overall sarcastic or irritable tone toward the other person.
11) Irritability/Hostility: Having a hostile/angry view of the world (e.g., complaining about a
lot of things). Includes having sarcastic, frustrated, angry, or irritable attitude in general that is
not directed toward the other person in the room. Think of this code as more of a global hostility.
EXAMPLES:
Listing off a bunch of people that they don’t like.
“I just don’t like people in general. People are annoying.”
12) Engagement: This includes verbal and non-verbal behaviors that demonstrate that the
adolescent is actively participating in the conversation and/or is interested in what his/her friend
is saying. This code also reflects how much participants are staying on task. Behaviors include:
• Leaning forward to communicate interest.
• Maintaining eye contact.
• Saying things like, “right,” or “I know!”
• Asking the friend questions to get more information.
• Staying on task/sticking to the conversation prompt.
EXAMPLES:
Adolescent 1: “I really would like to go to college next year.”
Adolescent 2: “Which college?”

Adolescent 1: “I don’t like it when Pete doesn’t call back.”
Adolescent 2: “Yeah”

13) Emotional Support and Reflection: Verbally reflecting on the other friend’s statement or
verbally expressing signs of support or empathy. Includes:
● Reflections (e.g., “that sounds so hard,”)
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● Reflecting on the other person’s statement (“ It sounds like what’s going on is…”)
● Encouraging statements, statements that validate the other person’s emotions, or
statements to make the other person feel better (“Even though it’s tough now, it’ll get easier”; “I
think you did the right thing.”).
● Statements could also contain humor when it is supportive and friendly in nature (NOT
when there is a negative hint to it).
● “awwww” or “ooohhh man” in response to someone’s comment may count depending on
how it is expressed. If people make these sounds in a way that indicates they are sorry for or
“feel for” the other person, then you would code as both emotional support/reflection as well as
engagement. If these sounds are more expressions of interest, this would not get coded here and
instead get coded for engagement.
EXAMPLES:
Adolescent 1: “She always gets mad at me, and I don’t know why.”
Adolescent 2: “That must be really annoying.”

Adolescent 1: “I am so stressed.”
Adolescent 2: “Awww, I’m sorry.”

Adolescent 1: “I’ll never graduate.”
Adolescent 2: “Don’t say that, yes, you will.”

Adolescent 1: “I sort of want to confront her to tell her that it upsets me, but I sort of kind of,
like, think, whatever.”
Adolescent 2: “It sounds like what you want to talk to her about it, but then you are also hesitant
and not sure if it will lead to a good outcome.”

14) Co-rumination (Dyadic Code; Rose, 2006): This code is meant to capture when dyad
members reinforce each other’s problem talk, discuss and rehash problems, speculate about
possible causes and consequences of the problem, and focus on negative feelings related to the
event (sad, worried, angry) without solving the problem. This code does not involve coming up
with problem-solving strategies. Rather, friends go around in circles discussing issues and spend
a lot of time talking about the problems, with conversations containing no clear resolutions or
ideas for how to solve or help the problem.
EXAMPLES (Note that although these are examples of what Co-rumination may look like,
you want to base your code on what the entire 5-minute discussion looks like):
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“I’m so stressed about school!”
“I know, we have to study for the SAT, and get more extracurriculars.”
“Ugh, my extracurriculars are so bad.”

“This is really frustrating”
“Yeah, you must feel really crappy.” (Can also be emotional support/reflection)

“I know we already talked about this, but I really can’t believe that happened”
“Yeah, I know, it is seriously really messed up.”

“ Why do you think he keeps doing this?”
“ I don’t know, maybe he is insecure”

“ I know we keep talking about this but, but it just really bugs me.”
“Yeah, seriously, it is annoying when Jack…”

Another example may be when an adolescent is talking about something and the second
adolescent asks, “and then what happened?” or asks questions such as “why do you think he does
that?” and then the first adolescent continues to talk about this stressful event.

15) Intimacy (Dyadic): Behaviors during the discussion that suggest intimacy, comfort, and
closeness between friends. This may include references to past experiences, personal jokes, ease
and candidness of the conversation, and mutual openness with each other. This code also
includes when friends make inside jokes, finish one another’s sentences, or make reference to the
fact that they understand or get one another.
When a dyad demonstrates a lot of indications of intimacy in the room, but does not seem to
have shared experiences, this likely gets scored a 2. Similarly, if the dyad has a lot of shared
experiences, but does not demonstrate a lot of intimate behaviors in the room, this could also get
a 2.
EXAMPLES:
Adolescent 1: “So you know how funny Sara gets. Remember that time during the summer?”
Adolescent 2: (Laughing) “Oh yeah!”

“ Because we are both on the soccer team, we understand what that’s like.”
“You and I, I feel like we get one another.”
16) Constructive Problem Solving of Self/Friend (Problem-Solving Talk): This is used both
when adolescents are talking about current problems or when they make references to strategies
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that they used to solve a past problem. This is also used when adolescents have a goal they are
trying to reach and want advice on how to reach the goal. This code is given when an adolescent
presents strategies that might lead to a better outcome, takes into account different perspectives, or
indicates that they have though through the consequences of this strategy. Strategies may be more
proactive (“talk to your mother about this,”) or more neutral (“ignore it”; “You only have a month
left in school, so you just need to get through this tough class.”). Consider anything that is not
maladaptive as constructive, even if it is more passive. Scores of 2-3 are reflective of generation of
a lot of potential problem solving ideas that are not maladaptive.
EXAMPLES:
“I think you should sit down with her and express how you are feeling.”
“Don’t avoid the things you want to do just because you know she is doing those things too.”
“I was doing badly in the class, so I just needed to study really hard.”
“If they give you a look, just ignore it and do your thing.”
Note: Saying something along the lines of, “I don’t know how I am going to solve this,” or “I don’t
know what I am going to do about this,” does not count as an example of constructive problem
solving.
17) Maladaptive Problem Solving of Self/Friend: This is used both when adolescents are talking
about current problem they need to solve or when they make references to strategies that they used
to solve a past problem. This is also used when adolescents have a goal they are trying to reach and
want advice on how to reach the goal. This code involves the use of aggressive tactics (“punch
him” or “show him who’s boss”), self-destructive behaviors (“I’m just getting drunk so I don’t have
to think about it.”), or strategies that are impulsive and would likely lead to a negative outcome.
Planning a party with alcohol or discussing that they drink alcohol/engage in substance use does not
count as maladaptive problem solving unless the adolescents indicate doing this in order to solve a
problem or reach a particular goal (added 8/25/15).
EXAMPLES:
“Flirt with other guys. That way, your boyfriend will appreciate you.”
“If Max makes fun of you again, just beat him up. That’ll make him stop.”
18) Interpersonal Stress Talk: This code is meant to pick up on the amount of social/interpersonal
stress and chaos occurring in adolescent’s lives. This code is based on the content of discussions,
rather than the interaction or behaviors occurring in the room. Higher scores reflect interpersonal
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stressors that are more chronic rather than transient, higher in severity, have bigger consequences,
and/or are beyond minor, temporary hassles or annoyances that are more typical during
adolescence. It can help to ask yourself the following (not all of these need to occur):
● How severe is the type of interpersonal stress (e.g., they don’t like their English teacher-
very mild- versus they feel like they do not have any friends-a little more moderate- versus one
of their parents left home and has left the family financially broke- more severe)?
● Are they only mentioning one interpersonal stressor or are there several?
● Do they have the coping resources to deal with it?
● Is it having a negative impact on their lives?
● Is the problem more transient/temporary (“my mom got annoyed with me because I
didn’t clean my room”) or chronic (“My mom and I just don’t get along,” “My mom just does
things that makes me not trust her”)?
EXAMPLES:
“My boyfriend got me pregnant and then dumped me, so I had an abortion.” (More severe)
“My dad drinks too much, and I have take care of things around the house for him.”
“ Jake is always bailing on me, and he can be such a jerk to me. I really can’t count on him for
anything anymore even though we have been friends forever” (This would get a lower score,
such as a 1).
19) Flat/Blunted Affect: The absence or reduction of facial expression/emotional
expressiveness and /or vocal tone (e.g., speaking in a monotone), especially when talking about
things that would be expected to draw out emotions.

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Appendix B: Peer Discussion Coding Sheet

0= not at all

Target ID

1= a little

Target Sex

2= moderate amount

Coder
3= a lot

T or P?

Date:

Start Time (when T or P starts talking):

End time (five minutes later):

Code (circle who you code first in each
discussion)
1 2 3 4 5 6 7 8
T P T P T P T P T P T P T P T P
Discussion Topic:

1. Negative Interpersonal

2. Positive Interpersonal

3. Reassurance Seeking

4. Negative Feedback Seeking

5. Negative Self-Evaluation

6. Positive Self-Evaluation

7. Conversational Self-Focus

8. Verbal Obscenities

9. Non-Verbal Positive Affect

10. Non-Verbal Negative Affect

11. Irritabiity/Hostility

12. Engagement

13. Emotional Support/Reflection

14. Co-rumination (Dyadic)

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15. Intimacy (Dyadic)

16. Constructive Problem Solving

17. Maladaptive Problem Solving

18. Interpersonal Stress Talk

19.Flat/Blunted Affect

Interpersonal Stress Talk Target Rating:
Interpersonal Stress Talk Peer Rating:
Overall, how supportive do you believe the target was toward the peer?

Overall, how supportive do you believe the peer was toward the target?

Overall, how close and intimate is this relationship?

Overall, how frustrated was the target with the peer?

Overall, how frustrated was the peer with the target?

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Please note problems discussed for Discussion 1 and problems discussed for Discussion 2:
Please note what target and peer note that they want to change about themselves in
Discussion 7. Was it changeable? Did they have specific plans as to how they were going to
change?

Please write down any questions you had about certain codes or comments. Please note
when these comments occurred during the video.

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Appendix C: Experimenter Instructions for Peer Discussion Task

Give Discussion Topic list to each peer in dyad to fill out before beginning discussion task.
“We are going to use this form later to find a topic for discussion.”

INTRODUCTION to DISCUSSIONS:

• Make sure the Target is sitting in chair (right) closest to computer
• Ask them not to move the chairs during the discussion

“You are going to have series of discussions on a number of different topics. Each discussion
will last 5 minutes. So we encourage you to jump right and get to the topic. We will tell you
each topic before you begin. I will leave the room after giving you the instructions for each
discussion topic and then I’ll come back in when the 5 min is over.

This is a confidential videotaped discussion; we won’t share the information with your parents or
anyone else outside of the Family Studies Project research team, so you can talk freely. And
because we want to keep this video confidential, please use only first names when talking about
each other or other people.

Please try to talk in as much detail as you can, and try to use up the full 5 minutes for each
discussion topic. Please talk in a normal voice tone and try to sit up in your chair. Also please
don’t get out of your chairs or move them around at all during the discussions.

Do you have any questions before you begin your discussions?”

START TIMING

Introductions for Video:

“Please introduce yourselves with only your first names. For the next 45 minutes we would like
you to talk about several topics. You may have talked with each other about some of these
things before and some may be new. We’ll give you a cue card for each topic to help guide your
discussion.”

Discussion #1: Current Problems for TC, should be seated on right (problems from list)
“Now I’d like the two of you to talk about a current problem with a person that (TC) identified a
few minutes ago. (TC), you selected a few people on this list with whom you have an
unresolved issue. Please talk about why it is a problem and then if you’ve tried to solve it what
you did and if it worked. Then talk with (friend name) about ways you might solve the problem
and any ways that (friend name) could help. You’ll have 5 minutes for this discussion. Here’s
your card. Do you have any questions?”

Card 1,2: Talk about a current problem that you identified a few minutes ago.

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Discussion #2: Current problems for Friend
“Now I’d like the two of you to talk about a current problem with a person that (friend name)
identified a few minutes ago. (Friend name), you selected a few people on this list with whom
you have an unresolved issue. Please talk about why it is a problem and then if you’ve tried to
solve it what you did and if it worked. Then talk with (TC) about ways you might solve the
problem and any ways that (TC) could help. You’ll have 5 minutes for this discussion. Here’s
your card. Do you have any questions?”

Card 1,2: Talk about a current problem that you identified a few minutes ago.

Discussion #3: Alcohol and Drug Use
“For the next 5 minutes please talk about your beliefs about drinking alcohol, and using tobacco,
marijuana, and other drugs. Please talk about each one separately. If you think that use is
appropriate for people your age, please say why and in what settings it is appropriate to drink
alcohol, use tobacco, marijuana, and other drugs. Again, please talk about each separately. Here
is a card to guide your discussion. Any questions?”

Card 3: Talk about your beliefs about drinking alcohol, and using tobacco (e.g., cigarettes),
marijuana and other drugs.

Discussion #4: Goals
“For the next 5 minutes we would like each of you to talk about a major goal you have for the
next year. We would like you each to describe your goal, why it’s important and how you are
going to get there. You can also react to each other’s goals, or talk about how you can help each
other reach your goals. Please make sure that each of you has an opportunity to describe your
goal. Here is a card to guide your discussion. Do you have any questions?” Note: the next year
would be from now until a year from now.

Card 4: Talk about a major goal you have for the next year.

Discussion #5: Relationships
“This next activity is about dating. Please discuss some of the things you like and don’t like
about people you might date. Please discuss personality traits that you like or dislike, or things
that they do. Think about the whole person, not just one characteristic. Here is a card to guide
your discussion. You will have 5 minutes for this discussion. Do you have any questions?”

Card 5: Discuss some of the things you like and don’t like about someone you date, or someone
you might date, or someone you would like to date.

Discussion #6: Friends
“This next topic is about group of friends you spend time with. We’d like you to describe your
friends, and the kinds of things you like to do together. Then talk about what you like and don’t
like about the friends you spend time with.

If you don’t hang out with a group, what group would you like to spend time with and why?
Once again, here is a card to guide your discussion. Any questions? I’ll be back in 5 minutes.”
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Card 6: Describe your friends and the kinds of things you like to do together.

Discussion #7: If you could change one thing about yourself, what would it be?
“The next topic is about something you would change about yourself. For the next five minutes,
we would like each of you to discuss one thing you would like to change about yourself.

Card 7: If you could change one thing about yourself, what would it be?

Discussion #8: Planning a Party
“For the last 5 minutes we’d like you to plan a party. This is a party you would have at one of
your houses. Please talk about who would be there, what you would do, and about how long it
would last and anything else that you think is important. Here is a card to guide your discussion.
Do you have any questions?”

Card 8: For the next 5 minutes, plan a party. This is a party you would have at one of your
houses.

Debriefing:
“We are all done. Thank you. We’re interested in what you thought about this discussion. Was
this discussion typical of how you talk together?
Do you have any other comments or suggestions?
Thank you very much for participating.” When you get back to your room please wait for one of
us before you return to your online questionnaires.

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Appendix D: Pre-discussion Topics

ID#_______

Discussion Topics
Wave 5

We all have people in our lives we interact with on a regular basis. Sometimes
we wish we could improve our interactions with these people.

From the list below, put a check mark (√) next to people who you have an
unresolved issue or problem with.

_____Brother or Sister _____Boyfriend or Girlfriend

_____Mom _____Dad

_____Friend _____Teammate

_____Coach _____Boss

_____Classmate _____Teacher

_____Someone you have a crush on _____School
principle/administrator

_____Relative: Who? ____________________

_____Other: Who? ____________________

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Appendix E: Discussion Follow Up Questionnaire
ID #:
_____-3 (Youth)

_____-9 (Peer)

DISCUSSION FOLLOW-UP WAVE 5

Please circle an answer for each of the questions.

1. HOW SIMILAR WAS THIS DISCUSSION TO OTHER DISCUSSIONS YOU HAVE HAD WITH
YOUR FRIEND?

Not at all Slightly Somewhat Moderately Very
Similar Similar Similar Similar Similar
0 1 2 3 4

2. HOW MUCH WERE YOU ABLE TO EXPRESS YOUR OWN POINT OF VIEW ON THE
TOPICS?

Not at all A Little Some Moderate Amount A Lot
0 1 2 3 4

3. HOW OFTEN DO YOU HAVE DISCUSSIONS LIKE THIS WITH THIS FRIEND OR ANY
OTHER FRIEND?

Never Once in a while Sometimes Often Very Often
0 1 2 3 4

4. HOW HONEST OR FRANK WERE YOU DURING THE DISCUSSION?

Not at all A Little Some Moderate Amount Very
0 1 2 3 4

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Appendix F: Beck Depression Inventory-Second Edition

BDI-II

Instructions: This questionnaire consists of 21 groups of statements. Please read each group of statements
carefully, and then pick out the one statement in each group that best describes the way you have been feeling
during the past two weeks, including today. Circle the number beside the statement you have picked. If several
statements in the group seem to apply equally well, circle the highest number for that group. Be sure that you do
not choose more than one statement for each group, including Item 16 (Changes in sleeping pattern) or Item 18
(Changes in Appetite).

1. Sadness
0 I do not feel sad.
1 I feel sad much of the time.
2 I am sad all the time.
3 I am so sad or unhappy that I can’t stand it.

2. Pessimism
0 I am not discouraged about my future.
1 I feel more discouraged about my future
than I used to be.
2 I do not expect things to work out for me.
3 I feel my future is hopeless and will only
get worse.

3. Past Failure
0 I do not feel like a failure.
1 I have failed more than I should have.
2 As I look back, I see a lot of failures.
3 I feel I am a total failure as a person.

4. Loss of Pleasure
0 I get as much pleasure as I ever did from
the things I enjoy.
1 I don’t enjoy things as much as I used to.
2 I get very little pleasure from the things I
used to enjoy.
3 I can’t get any pleasure from the things I
used to enjoy.

5. Guilty Feelings
0 I don’t feel particularly guilty.
1 I feel guilty over many things I have done
or should have done.
2 I feel quite guilty most of the time.
3 I feel guilty all of the time.

6. Punishment Feelings
0 I don’t feel I am being punished.
1 I feel I may be punished.
2 I expect to be punished.
3 I feel I am being punished.

7. Self-dislike
0 I feel the same about myself as ever.
1 I have lost confidence in myself.
2 I am disappointed in myself.
3 I dislike myself.

8. Self-criticalness
0 I don’t criticize or blame myself more than usual.
1 I am more critical of myself than I used to be.
2 I criticize myself for all of my faults.
3 I blame myself for everything bad that happens.

10. Crying
0 I don’t cry anymore than I used to.
1 I cry more than I used to.
2 I cry over every little thing.
3 I feel like crying, but I can’t.

11. Agitation
0 I am no more restless or wound up than usual.
1 I feel more restless or wound up than usual.
2 I am so restless or agitated that it’s hard to stay
still.
3 I am so restless or agitated that I have to keep
moving or doing something.

12. Loss of Interest
0 I have not lost interest in other people or
activities.
1 I am less interested in other people or things than
before.
2 I have lost most of my interest in other people or
things.
3 It’s hard to get interested in anything.

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13. Indecisiveness
0 I make decisions about as well as ever.
1 I find it more difficult to make decisions than usual.
2 I have much greater difficulty in making decisions
than I used to.
3 I have trouble making any decisions.

14. Worthlessness
0 I do not feel I am worthless.
1 I don’t consider myself as worthwhile and useful as
I used to.
2 I feel more worthless as compared to other people.
3 I feel utterly worthless.

15. Loss of Energy
0 I have as much energy as ever.
1 I have less energy than I used to have.
2 I don’t have enough energy to do very much.
3 I don’t have enough energy to do anything.

16. Changes in Sleeping Pattern
0 I have not experienced any change in my sleeping
pattern.
___________________________________________
1a. I sleep somewhat more than usual.
1b. I sleep somewhat less than usual.
___________________________________________
2a. I sleep a lot more than usual.
2b. I sleep a lot less than usual.
___________________________________________
3a. I sleep most of the day.
3b. I wake up 1-2 hours early and can’t get back to
sleep.

17. Irritability
0 I am no more irritable than usual.
1 I am more irritable than usual.
2 I am much more irritable than usual.
3 I am irritable all the time

18. Changes in Appetite
0 I have not experienced any change in my
appetite.
________________________________________
1a. My appetite is somewhat less than usual.
1b. My appetite is somewhat greater than usual.
________________________________________
2a. My appetite is much less than before.
2b. My appetite is much greater than usual.
________________________________________
3a. I have no appetite at all.
3b. I crave food all the time.

19. Concentration Difficulty
0 I can concentrate as well as ever.
1 I can’t concentrate as well as usual.
2 It’s hard to keep my mind on anything for very
long.
3 I find I can’t concentrate on anything.

20. Tiredness or Fatigue
0 I am no more tired or fatigued than usual.
1 I get more tired or fatigued more easily than
usual.
2 I am too tired or fatigued to do a lot of the things I
used to.
3 I am too tired or fatigued to do most of the things
I used to.

21. Loss of Interest in Sex
0 I have not noticed any recent change in my
interest in sex.
1 I am less interested in sex than I used to be.
2 I am much less interested in sex now.
3 I have lost interest in sex completely.

FRIEND INTERACTIONS

168
Appendix G: Domestic Conflict Index
ID # ________
Domestic Conflict Index- Youth Report on Parents – Wave 5 (revised 6.20.08)
Margolin, G., Burman, B., John, R. S., & O’ Brien, M. (1990)
University of Southern California

No matter how well parents get along, there are times when they disagree on major decisions, get annoyed about something the other parent
does, or just have spats or fights because they’re in a bad mood, or tired, or for some other reason. People have many different ways of
expressing frustration, annoyance, or hostility with one another. Below you will find a list of some things that your parents may have done.
Please be sure to consider all items, even if they seem extreme.

In this questionnaire, there are two sections. One asks how often your mom does each behavior to your dad and the other section asks how often
your dad does each behavior to your mom.

In this section, please answer how frequently your mother did each behavior to your father within the
past year, and then indicate whether each behavior has happened prior to the past year.

Within the past year has your MOTHER …
(check one)
Prior to the past year…
(circle one)
0 Per
year
1 Per
year
2-5 per
year
6-12 per
year
2-4
per
month
More than
1 per
week
1. screamed or yelled at your father

Never A few times A lot
2. insulted or swore at your father

Never A few times A lot
3.
damaged a household item, or some part of your home,
out of anger towards your father

Never A few times A lot
6. sulked or refused to talk about an issue

Never A few times A lot
10.
been angry if your father told her that she was using too
much alcohol or drugs

Never A few times A lot
11.
been very upset if dinner, housework, or home repair
work was not done when she thought should it be

Never A few times A lot
12. done or said something to spite your father

Never A few times A lot
FRIEND INTERACTIONS

169
Within the past year has your MOTHER …
(check one)
Prior to the past year…
(circle one)
0 Per
year
1 Per
year
2-5 per
year
6-12 per
year
2-4
per
month
More than
1 per
week
15.
purposely damaged or destroyed your father’s clothes,
car, and/or other personal possessions
Never A few times A lot
16. insulted or shamed your father in front of others Never A few times A lot
17. locked your father out of the house (not accidentally) Never A few times A lot
20. had an extramarital affair (cheated on your father) Never A few times A lot
22. made threats to leave your father (or the family) Never A few times A lot
23. blamed your father for her problems Never A few times A lot
24. tried to turn family, friends, or children against your father Never A few times A lot
25. ordered your father around Never A few times A lot
26. been insensitive to your father’s feelings Never A few times A lot
27. frightened your father (not as a joke) Never A few times A lot
28. treated your father like he was stupid Never A few times A lot
29. given your father the silent treatment/cold shoulder Never A few times A lot
30. criticized your father Never A few times A lot
31. called your father names Never A few times A lot
32. stomped out of the room, house, or yard Never A few times A lot
33.
stayed away from the house (due to being upset at your
father)
Never A few times A lot
34. ridiculed your father Never A few times A lot
FRIEND INTERACTIONS

170
Within the past year has your MOTHER …
(check one)
Prior to the past year…
(circle one)
0 Per
year
1 Per
year
2-5 per
year
6-12 per
year
2-4
per
month
More than
1 per
week
35. physically twisted your father’s arm Never A few times A lot
36.
threatened to hit your father or throw something at him in
anger
Never A few times A lot
37. pushed, grabbed, or shoved your father Never A few times A lot
38. slapped your father Never A few times A lot
40. burned your father (not accidentally) Never A few times A lot
41. shaken your father Never A few times A lot
42. thrown, smashed, hit, or kicked something Never A few times A lot
44. thrown or tried to throw your father bodily Never A few times A lot
45. thrown an object at your father Never A few times A lot
46. choked or strangled your father Never A few times A lot
47. kicked, bit or hit your father with a fist Never A few times A lot
48. hit your father, or tried to hit your father, with something Never A few times A lot
49. beat up your father (multiple blows) Never A few times A lot
50. threatened your father with a knife or gun Never A few times A lot
51. used a knife or a gun on your father Never A few times A lot
55. slammed your father against the wall

Never A few times A lot
56.
physically prevented your father from leaving an
argument or blocked his exit

Never A few times A lot
FRIEND INTERACTIONS

171
Within the past year has your MOTHER …
(check one)
Prior to the past year…
(circle one)
0 Per
year
1 Per
year
2-5 per
year
6-12 per
year
2-4
per
month
More than
1 per
week
62. driven recklessly when she was angry at your father (n)

Never A few times A lot
63. argued with your father when she was driving the car (n)

Never A few times A lot

FRIEND INTERACTIONS

172
In this section, please answer how frequently your father did each behavior to your mother within the
past year, and then indicate whether each behavior has happened prior to the past year.

Within the past year has your FATHER …
(check one)
Prior to the past year...
(circle one)
0 per
year
1 per
year
2-5
per
year
6-12
per
year
2-4
per
month
More than
1 per
week
1. screamed or yelled at your mother

Never A few times A lot
2. insulted or swore at your mother

Never A few times A lot
3.
damaged a household item, or some part of your home,
out of anger towards your mother

Never A few times A lot
6. sulked or refused to talk about an issue

Never A few times A lot
10.
been angry if your mother told him that he was using
too much alcohol or drugs

Never A few times A lot
11.
been very upset if dinner, housework, or home repair
work was not done when he thought should it be

Never A few times A lot
12. done or said something to spite your mother

Never A few times A lot
15.
purposely damaged or destroyed your mother’s clothes,
car, and/or other personal possessions

Never A few times A lot
16. insulted or shamed your mother in front of others

Never A few times A lot
17. locked your mother out of the house (not accidentally)

Never A few times A lot
20. had an extramarital affair (cheated on your mother)

Never A few times A lot
22. made threats to leave your mother (or the family?)

Never A few times A lot
23. blamed your mother for his problems

Never A few times A lot
24.
tried to turn family, friends, or children against your
mother

Never A few times A lot
25. ordered your mother around Never A few times A lot
FRIEND INTERACTIONS

173
Within the past year has your FATHER …
(check one)
Prior to the past year...
(circle one)
0 per
year
1 per
year
2-5
per
year
6-12
per
year
2-4
per
month
More than
1 per
week
26. been insensitive to your mother’s feelings Never A few times A lot
27. frightened your mother (not as a joke) Never A few times A lot
28. treated your mother like she was stupid Never A few times A lot
29. given your mother the silent treatment/cold shoulder Never A few times A lot
30. criticized your mother Never A few times A lot
31. called your mother names Never A few times A lot
32. stomped out of the room, house, or yard Never A few times A lot
33.
stayed away from the house (due to being upset at your
mother)
Never A few times A lot
34. ridiculed your mother Never A few times A lot
35. physically twisted your mother’s arm Never A few times A lot
36.
threatened to hit your mother or throw something at her
in anger
Never A few times A lot
37. pushed, grabbed, or shoved your mother Never A few times A lot
38. slapped your mother Never A few times A lot
40. burned your mother (not accidentally) Never A few times A lot
41. shaken your mother Never A few times A lot
42. thrown, smashed, hit, or kicked something Never A few times A lot
FRIEND INTERACTIONS

174
Within the past year has your FATHER …
(check one)
Prior to the past year...
(circle one)
0 per
year
1 per
year
2-5
per
year
6-12
per
year
2-4
per
month
More than
1 per
week
44. thrown or tried to throw your mother bodily Never A few times A lot
45. thrown an object at your mother Never A few times A lot
46. choked or strangled your mother Never A few times A lot
47. kicked, bit or hit your mother with a fist Never A few times A lot
48.
hit your mother, or tried to hit your mother, with
something
Never A few times A lot
49. beat up your mother (multiple blows) Never A few times A lot
50. threatened your mother with a knife or gun Never A few times A lot
51. used a knife or a gun on your mother Never A few times A lot
55. slammed your mother against the wall Never A few times A lot
56.
physically prevented your mother from leaving an
argument or blocked her exit
Never A few times A lot
62. driven recklessly when he was angry at your mother (n) Never A few times A lot
63. argued with your mother when he was driving the car (n) Never A few times A lot

FRIEND INTERACTIONS

175

Appendix H: Parent Child Conflict Questionnaire
ID# __________
Parent Child Conflict — Youth Report on Mother Wave 5 (revised 6.20.08)

DIRECTIONS: Below is a list of some things that parents sometimes do when having an argument or disciplining a child.
Please indicate if your mom has done any of these items with you within the past year.

Who will you be answering these questions about? _________________________________

Never Once Twice
3 to 5
times
6 to
10
times
11 to
20
times
More
than
20
times
1. Explained why something you did was wrong
2. Sent you to your room
3. Shook you
4. Shouted, yelled, or screamed at you
5. Spanked you with her hand
6. Swore or cursed at you
7. Said she would send you away or kick you out of the house
8. Slapped you
9. Threatened to hit you, but did not actually do it
10. Spanked you with an object
11. Took away privileges or grounded you
12. Twisted your arm behind your back
13. Called you dumb or lazy or some other name like that
14. Purposely destroyed something that belongs to you
15. Threw something at you out of anger
16. Pushed, grabbed or shoved you
17. Threatened to lock you out of the house
18. Said something hurtful (e.g. about your appearance or
FRIEND INTERACTIONS

176

Never Once Twice
3 to 5
times
6 to
10
times
11 to
20
times
More
than
20
times
friends)
19. Refused to talk to you
20. Refused to hear what you wanted to say
21. Insulted or shamed you in front of others
22. Told you that you are not as good as someone else (n)
23.
Told you that you are a failure or will be a failure or won’t
succeed at anything (n)

24. Told you that you are acting like a jerk (n)
25. Kicked you out of the car (n)
26. Kicked you out of your home (n)
27. Told you that you would not be part of the family anymore (n)
28.
Threatened to stop supporting you financially or told you that
she would not pay for something important such as
schooling etc. (n)

29.
Threatened to pull you from extracurricular or organized
activities that you like (n)

30.
Did pull you from extracurricular or organized activities that
you like (n)

31.
Grounded you (didn’t let you go to social events or fun
activities) for a month or less (n)

32.
Grounded you (didn’t let you go to social events or fun
activities) for more than a month (n)

33.
Took away your driving privileges or use of the car for a
period of time (n)

34. Disciplined you by assigning extra work chores (n)
35.
Showed you that she cares about your well-being even when
disciplining you (n)

FRIEND INTERACTIONS

177

Appendix I: Symptom Checklist-90 (Parent Report)

SCL-90- Parent

DIRECTIONS: Below is a list of problems that people sometimes have. Please mark the response that best describes how
much discomfort that problem has caused you during the past week, including today. Please do not skip any items.

Not at all A little bit Moderately Quite a bit Extremely
1. Headaches
2. Nervousness or shakiness inside
3. Repeated unpleasant thoughts that won't leave your mind
4. Faintness or dizziness
5. Loss of sexual interest or pleasure
6. Feeling critical of others
7. The idea that someone can control your thoughts
8. Feeling others are to blame for most of your troubles
9. Trouble remembering things
10. Worried about sloppiness or carelessness
11. Feeling easily annoyed or irritated
12. Pains in the heart or chest
13. Feeling afraid of open spaces or on the streets
14. Feeling low in energy or slowed down
15. Thoughts of ending your life
16. Hearing voices that other people do not hear
17. Trembling
18. Feeling that most people cannot be trusted
19. Poor appetite
20. Crying easily
21. Feeling shy or uneasy with the opposite sex
22. Feeling of being trapped or caught
23. Suddenly scared for no reason
24. Temper outbursts that you could not control
25. Feeling afraid to go out of your house alone
FRIEND INTERACTIONS

178
Not at all A little bit Moderately Quite a bit Extremely
26. Blaming yourself for things
27. Pains in lower back
28. Feeling blocked in getting things done
29. Feeling lonely
30. Feeling blue
31. Worrying too much about things
32. Feeling no interest in things
33. Feeling fearful
34. Your feelings being easily hurt
35. Other people being aware of your private thoughts
36. Feeling others do not understand you or are unsympathetic
37. Feeling that people are unfriendly or dislike you
38. Having to do things very slowly to ensure correctness
39. Heart pounding or racing
40. Nausea or upset stomach
41. Feeling inferior to others
42. Soreness of your muscles
43. Feeling that you are being watched or talked about by others
44. Trouble falling asleep
45. Having to check and double-check what you do
46. Difficulty making decisions
47. Feeling afraid to travel on buses, subways, or trains
48. Trouble getting your breath
49. Hot or cold spells
50.
Having to avoid certain things, places, or activities because
they frighten you

51. Your mind going blank
52. Numbness or tingling in parts of your body
53. A lump in your throat
54. Feeling hopeless about the future
55. Trouble concentrating
56. Feeling weak in parts of your body
57. Feeling tense or keyed-up
58. Heavy feeling in your arms or legs
59. Thoughts of death or dying
60. Overeating
FRIEND INTERACTIONS

179
Not at all A little bit Moderately Quite a bit Extremely
61.
Feeling uneasy when people are watching or talking about
you

62. Having thoughts that are not your own
63. Having urges to beat, injure, or harm someone
64. Awakening in the early morning
65.
Having to repeat the same actions such as touching,
counting or washing

66. Sleep that is restless or disturbed
67. Having urges to break or smash things
68. Having ideas or beliefs that others do not share
69. Feeling very self-conscious with others
70. Feeling uneasy in crowds, such as shopping or at a movie
71. Feeling everything is an effort
72. Spells of terror or panic
73. Feeling uncomfortable about eating or drinking in public
74. Getting into frequent arguments
75. Feeling nervous when you are left alone
76. Others not giving you proper credit for your achievements
77. Feeling lonely even when you are with people
78. Feeling so restless you couldn’t sit still
79. Feelings of worthlessness
80.
The feeling that something bad is going to happen to your
body

81. Shouting or throwing things
82. Feeling afraid that you will faint in public
83.
Feeling that people will take advantage of you if you let
them

84. Having thoughts about sex that bother you a lot
85. The idea that you should be punished for your sins
86. Thoughts and images of a frightening nature
87. The idea that something serious is wrong with your body
88. Never feeling close to another person
89. Feelings of guilt
90. The idea that something is wrong with your mind

Abstract (if available)

Abstract The two papers that comprise this dissertation seek to answer the following question: Do the ways in which adolescent friends converse and behave with one another offer insight regarding their emotional well-being? In particular, this dissertation investigates links between adolescent depressive symptoms and observed communication patterns among friend dyads. Both papers use video-recorded peer discussions in order to gain a more nuanced understanding of how adolescent behaviors and dyadic exchanges relate to depressive symptoms. Participants included adolescents who were part of a longitudinal study of families from the community. These adolescents nominated a same-sex friend to participate in discussions about various topics. A coding system was developed to assess affect and behaviors anticipated to correspond with depressive symptoms. The first paper utilized data from both adolescents and their friends to examine associations between depressive symptoms, observed communication patterns (irritability, obscenities, conversational self-focus, criticism, and supportive talk), and exposure to family aggression. Findings suggested an association between depressive symptoms and female adolescents’ criticism of friends. Adolescent depressive symptoms were also negatively associated with their friends’ observed irritability and conversational self-focus. Furthermore, results suggested that adolescent depressive symptoms interacted with exposure to family aggression to predict increased irritability and the use of obscenities with friends. The second paper used two time points of data to examine whether four observable interactional behaviors (co-rumination, problem-solving talk, interpersonal stress talk, and friend intimacy) in adolescent dyads strengthened or diminished the continuity of depressive symptoms from adolescence to young adulthood. The second paper also explored whether these behaviors moderated associations across time between one friend’s depressive symptoms and the other’s depressive symptoms. Results suggested that participants’ depressive symptoms during adolescence were associated with depressive symptoms during young adulthood only in the context of mean or high levels of co-rumination and low or mean levels of problem-solving talk. For males only, interpersonal stress talk also conferred greater risk. Young adult depressive symptoms were predicted from their peers’ depressive symptoms at an earlier time point for males in the presence of co-rumination and highly intimate friendships. This dissertation highlights the importance of considering family factors and friend interactions when studying adolescent depressive symptoms. Study implications and suggestions for future research are addressed.

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Asset Metadata

Creator Moss, Ilana Kellerman (author)

Core Title Using observed peer discussions to understand adolescent depressive symptoms and interpersonal interactions

School College of Letters, Arts and Sciences

Degree Doctor of Philosophy

Degree Program Psychology

Publication Date 08/02/2017

Defense Date 06/20/2017

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag adolescent depressive symptoms,co-rumination,interpersonal behaviors,OAI-PMH Harvest,peer discussions

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Margolin, Gayla (committee chair), Brekke, John (committee member), John, Richard (committee member), Saxbe, Darby (committee member), Williams, Marian (committee member)

Creator Email ikellerm@usc.edu,ilana.kellerman@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c40-421526

Unique identifier UC11265264

Identifier etd-MossIlanaK-5670.pdf (filename),usctheses-c40-421526 (legacy record id)

Legacy Identifier etd-MossIlanaK-5670.pdf

Dmrecord 421526

Document Type Dissertation

Rights Moss, Ilana Kellerman

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA