Understandingtheimpactofmajorlifeeventsonyoungpeople’s
academicachievementandpost‐schoolingcareers
Youth Education-Work Nexus: Potentialities, Vulnerabilities and Resilience (July 14, 2014)
Dr. Jonathan Smith
School of Social Sciences, Monash University
Prof. Zlatko Skrbis
School of Social Sciences, Monash University
Author correspondence: [email protected]
ABSTRACT*:
Instability and conflict are pervasive features of the transition from adolescence to early
adulthood, as young people learn to manage an expanding array of academic, social and familial
commitments. Recently, theorists have suggested that developments in young people’s peer
relationships may either compound or alleviate the adverse impacts of these broader life changes.
In this paper we examine this proposition with respect to young people’s emerging educational
and occupational pathways, using longitudinal data from a large cohort of 7,000 secondary
school students in Queensland, Australia, participating in the Our Lives research project. We do
so by assessing the academic impact of peer relationship events during high school, such
bullying, friendship problems, falling in love, and breaking up with someone. Our results
indicate that bullying and romantic involvement during adolescence can exert a negative
influence on young people’s secondary school exit scores and post-schooling career pathways.
However, we also find that close, resilient friendships - in which status and identity conflicts are
more easily tolerated and resolved - may help to offset the adverse effects of these other events.
Finally, we review the implications of these findings for young people’s educational and
occupational trajectories in the longer-term.
* Please note that this abstract has been revised since being accepted.
2 Introduction
Drawing on data from a large cohort study of young people in Queensland, Australia, this paper
investigates the impact of peer relationship events during high school on young people’s
educational and occupational pathways, relative to other major life events. Research on the role
of social capital in education shows that strong social ties within and between family and the
school are critical in determining young people’s academic and career trajectories (Dika & Singh,
2002). By contrast, peer relationships are held responsible for the spread of negative attitudes
towards school amongst disengaged and marginalised youth, and for behaviors which adversely
affect academic outcomes, such as bullying, dating, sexual intercourse, and substance abuse
(Billet, 2014). Yet adolescent friendships, such as those developed through extracurricular
activities, have also been shown to improve young Australians’ educational engagement
(Fullarton, 2002), psychosocial resilience (Blomfeld & Barber, 2011) and transitions into
education and training (Semo & Karmel, 2011). With young people’s embrace of online
interaction, and their increasingly fragmented experiences of work, study, and family life in
contemporary society, we argue that peer networks have emerged as key arenas of comfort and
conflict in which young people’s future trajectories are shaped.
Arenas of comfort and conflict: Vulnerability and resilience in adolescents’ peer networks
An ‘arena of comfort’ refers to a social environment or set of relationships which offers
young people relative stability and reprieve from changes or disruptions occurring in other areas
of their lives during the transition from adolescence to adulthood. Simmons et al. (1987)
developed this concept to explain why various life events (such as changing school, experiencing
puberty, or early dating) can be particularly harmful to adolescent self-esteem and academic
achievement when experienced simultaneously rather than at separate times. Observing such
effects in the lives of American adolescents almost three decades ago, they argued that ‘if change
comes too suddenly… or if it occurs in too many areas of life at once, then individuals may
experience considerable discomfort’ (Simmons et al., 1987). The idea that young people require
‘a sense of having a secure base’ from which to explore and engage with the wider world
(Gilligan, 2000: 39) has since been widely adopted to explain adverse developmental outcomes
and to identify factors associated with psychological resilience (Call & Mortimer, 2001).
3 From this epidemiological origin, the concept has entered into sociological research via
the work of scholars examining family dynamics and early life course trajectories in the U.S.
Reviewing a wide range of studies, Hines (1997) concludes that young people struggle to cope
with developments in other areas of their lives when their divorcing families lose the capacity to
function as arenas of comfort. However, she notes that this primarily occurs when there has been
prolonged and intense marital conflict prior to divorce, and that positive parent-adolescent
relationships tends to ameliorate such effects (Hines, 1997). When these relationships are lacking,
overlapping sources of emotional support beyond the family context can buffer against academic
disengagement during adolescence. Analysing data from the U.S. National Longitudinal Study of
Adolescent Health (Add Health), Crosnoe and Elder (2004) reported that that non-parental
sources of support such as friends, siblings, and teachers, promoted educational resilience and
reduced ‘off-track’ academic behavior for adolescents who displayed emotional distance from
their parents. Yet they also found that the influence of friends varied by gender and race/ethnicity:
girls benefitted more than boys from close, supportive friendships, whereas friends sometimes
exacerbated the risk of academic disengagement amongst African-American and Hispanic youth.
Such findings echo those of research showing the varied educational impact of young
people’s participation in extracurricular activities. Although certain types of structured activities
(e.g. school sport, performing arts, hobby clubs) can reinforce more ‘school-orientated’
friendships which value schoolwork and higher educational aspirations, such benefits accrue
unevenly to those who can afford to enroll these activities and who are intrinsically motivated or
encouraged by parents to do so (White & Gager, 2007). Meanwhile, those who engage primarily
in ‘out-of-school’ social activities may be more likely to form friendships which disavow
academic pursuits and privilege alternative identity roles and aspirations (Ream & Rumberger,
2008). Close friendship ties of the latter variety have prompted concerns about detrimental forms
of youth-derived social capital (e.g. ‘bad’ or ‘dark’ social capital) (Billet, 2014). Without
dismissing such concerns, the conceptualisation of peer relationships as potential arenas of
comfort and conflict can contribute to a broader understanding of what these relationships offer
young people and how they impact on their emerging life pathways.
4 Gauging the impact of different types of peer relationship events
Adolescents’ social worlds encompass the romantic and the platonic, close friends and
superficial acquaintances, competitive rivalries and collaborative alliances, many of these
overlapping and few surviving the high school years completely unchanged. Drawing together
diverse strands of literature, Giordano (2003) argues that different relationship types entail
distinct processes and outcomes for young people depending on their social location (e.g. gender,
class, and race/ethnicity). In particular, she distinguishes between the ‘intimacy processes’ which
underpin closer emotional attachments (which can serve as arenas of comfort), and ‘influence
processes’, which drive the formation of ties amongst individuals with similar values and
behaviors (i.e. ‘birds of a feather’) (Giordano, 2003). These processes are closely interconnected,
with close friendship groups providing influential yet often exclusive contexts for support and
socialisation during adolescence.
Some forms of peer influence entail clear risks for young people’s academic and social
adjustment. For instance, bullying and victimisation are closely related to the dynamics of peer
status recognition and rejection amongst high school students. Young people who are rejected by
their peers are at much greater risk of various forms of bullying (e.g. physical, verbal, relational,
cyberbullying) whilst those who engage in bullying tend to be less socially isolated (Wang et al.,
2009). Much cross-sectional evidence suggests that being bullied may lead to decreased selfesteem, increased delinquency, and poorer academic performance (Rothon et al., 2011).
However, relatively few studies have examined the longer term educational impacts of such
victimisation during school. In the Australian context, Bond et al. (2001) found that bullied
Grade 8 students (aged 13) displayed more symptoms of depression or anxiety in the following
year, and that although bullying was more common amongst males, its effects were stronger
amongst females. Although friendship networks can prevent victimization and reduce its adverse
effects, events such as schooling transitions disrupt these relationships and the protective
functions they can provide (Pellegrini & Bartini, 2000).
Some forms of peer intimacy, such as romance and dating, may also adversely affect
young people’s developing trajectories. Amongst adolescents in the U.S. Add Health study,
Joyner and Udry (2000) found that romantic involvement predicted increases in depression and
disruption to peer and parent-child relationships, particularly for females. While cross-sex
5 friendships and romantic relationships are also associated with earlier and higher-risk sexual
behaviors (Giordano, 2003), it is less clear is how such relationships affect academic outcomes.
For instance, Pham, Keenan & Han (2013) found that frequent dating and early sexual
experiences negatively affected academic outcomes, whereas moderate dating activities had a
more positive impact. The meanings given to romantic relationships, and the extent to which
feelings of love are reciprocated by those involved, may explain these varying effects. On this
note, Soller (2014) found that relationship inauthenticity, or an ‘incongruence between
thoughts/feelings and actions within relationship contexts’, helped account for the negative
impact of adolescent romance on females’ mental health. Several studies also indicate that highly
intelligent students or those with higher educational aspirations tend to avoid or postpone
romantic involvement and sexual activity until later ages (Halpern, 2000; Soller & Haynie, 2013).
Based on the literature highlighted above, we examine the potential for various peer
relationship events to either compound or counteract the effects of other major life events on
young Australians’ developing educational and occupational pathways. In particular, our
approach is guided by two research questions:
1. How do peer relationship events (such as bullying, falling in love, breaking up,
friendship problems) which occur during high school impact on young people’s
academic achievement at the end of high school?
2. What is the longer-term impact of such events on young people’s participation in
work and study following high school?
Methods
Data and Sample Characteristics
The data for this paper are from waves 1-4 of the Social Futures and Life Pathways (‘Our
Lives’) project, which is a longitudinal cohort survey of young people in Queensland, Australia.
The survey instrument contains questions measuring young people’s values, behaviors, and
aspirations, as well as their educational and occupational trajectories, as these develop over the
course of adolescence and early adulthood. While in earlier waves the self-completed survey
questionnaires were contacted either in hardcopy or online format, in later waves they have been
contacted primarily online or via computer-assisted telephone interviewing (CATI).
6 In 2006, an attempt was made to sample all secondary schools in the state, and all Year 8
students (i.e. the first year of secondary schooling, aged 12/13 years) in those schools. This
yielded a school-level response of 55 percent (n=213 schools) and a within-school response of 34
percent (n=7,031 students). Subsequent waves of data collection were conducted in the middle of
high school (2008, aged 14/15), at the end of high school (2010, aged 16/17), and three years
after high school (2013, aged 19/20). In each wave an attempt was made to contact original
participants using contact details they provided earlier. Amongst those with valid details, these
approaches yielded response rates of 58 percent in wave 2 (n=3,649), 58 percent in wave 3
(n=3,139), and 41 percent in wave 4 (n=2,206). The analysis for this paper focuses on measures
of schooling achievement which were asked in wave 4, and measures of major life events that
were asked across waves 1-3. The final analytic sample is thus a smaller subset of respondents
(n=1,605) who completed all survey waves and were not missing data on any of these measures.
Tables 1 and 2 contain sample characteristics and frequency distributions on all analytic
variables. Although the wave 1 sample was quite representative of the QLD Year 8 population in
2006, sample attrition over subsequent waves has contributed to a growing overrepresentation of
female respondents and students from the (typically wealthier) Independent schooling sector.
This trend, observed in other Australian longitudinal studies of a similar demographic (Dwyer &
Wyn, 2001; Rothman, 2009), is addressed by controlling for these factors in the multivariate
analysis (Winship & Radbill, 1994). Despite these attrition effects, the sample remains
representative of young people living in urban and regional/rural areas in Queensland.
Dependent Variables
The analysis examines variation on two measures of educational attainment which were
asked in wave 4. The first of these is a measure of whether or not respondents received an
Overall Position (OP) at the end of Year 12. Similar to the Australian Tertiary Admission
Ranking (ATAR) system employed in other Australian states, OPs are used to rank the
educational performance of Queensland students relative to others in their cohort, and to
determine the allocation of places in any given university degree program. There are two main
reasons why a student may not receive an OP: (1) they may have left school prior to finishing
Year 12 (i.e. in order to undertake full-time work); or (2) they may have completed more
vocationally-orientated school subjects (e.g. hospitality) or Vocational Education and
7 Table 1: Frequency distributions for analytic variables
Variable
N
% / Mean (Std. Dev)
1,605
All respondents
--
Dependent variables
Received OP Rank
Yes (ref.)
No
1,391
214
OP Rank (1=Highest; 25=Lowest)
1,391
7.9 (4.9)
Smart Scale (4-36)
Events before HS (0-6)
1,605
1,605
24.6 (7.0)
1.6 (1.2)
Gender
Male (ref.)
Female
575
1,030
35.8%
64.2%
School sector
Government (ref.)
Independent
Catholic
694
612
285
43.2%
38.8%
17.9%
Geographic region
Urban (ref.)
Non-urban
1,113
492
69.3%
30.7%
764
362
431
48
47.6%
22.6%
26.9%
3.0%
86.7%
13.3%
Control variables
Parental education (highest)
Bachelor’s degree or higher (ref.)
Vocational
Year 12 or less
Don’t know/Missing
1,560
6
Parental occ. prestige (0-100)
Missing parental occ.
Worked during HS
Did not work (ref.)
Worked in Y10 only
Worked in Y12 only
Worked in Y10 & Y12
Missing
502
170
328
600
5
61.0 (22.4)
0.4%
31.3%
10.6%
20.4%
37.4%
0.3%
Training courses (e.g. Certificate I or II) which do not contribute towards an OP ranking.
Although OP-ineligible students are substantially underrepresented within the longitudinal
sample - just over 13 percent (n=214) compared to around 40 percent within the actual
population (QLD Government, 2011) - they are included in the analysis so as to illustrate the
impacts of major life events on a wider range of post-schooling trajectories.
7
8 The second dependent variable to be analysed is the actual OP ranking a respondent
has received. This is a rank ranging from 1 to 25, with 1 indicating the highest level of
performance and 25 indicating the lowest. As with OP eligibility, the sample distribution on
this measure was skewed towards better performance when compared with the actual Year 12
population in 2010. Around 37 percent of the analytic sample achieved an OP rank of 5 or
higher (compared with 19 percent in the actual population). Meanwhile, only 8 percent
scored an OP of 15 or lower (compared to 25 percent in the actual population). While the
inclusion of a wide range of socio-demographic controls goes some way towards addressing
this imbalance, we accept that some restrictions on the generalisability of our findings are
inevitable with rich longitudinal data of this nature.
Explanatory variables
The analysis investigates how various major life events experienced during high
school (shown in Table 2) impacted on respondents’ educational attainment upon leaving
school. In waves 1-3, respondents were asked ‘Have the following events ever happened to
you?’ For each of the events contained in Table 2, respondents selected from the following
response options: 1= ‘Never’; 2= ‘Within the last 6 months’; 3= ‘Within the last year’; 4=
‘More than a year ago’. To create the events measures, wave-specific dummy variables were
first generated for each event/wave. These were coded 1 if a respondent reported
experiencing the event ‘Within the last 6 months’ or ‘Within the last year’ and 0 if they
responded ‘Never’ or ‘More than a year ago’. These were then used to generate a crosswave variable counting each time respondents reported each event in the year prior to a
survey. Since respondents completed three surveys during high school, there was a maximum
range of 0-3 for the number of times they could report each type of event.
Table 2: Experiences of Major Life Events During High School
Event
Did not
One
Two
happen
report
reports
Friendship problems
16%
24%
29%
Fell in love
35%
32%
21%
Death of family member/friend
37%
40%
19%
Broke up with boyfriend/girlfriend
44%
27%
21%
Family problems
43%
26%
20%
Bullied by other kids
52%
26%
15%
Serious health problems (0-2)
78%
17%
5%
Changed schools (0-2)
84%
14%
1%
Parents separated/divorced (0-1)
95%
5%
n/a
8
Three
reports
32%
12%
4%
8%
11%
7%
n/a
n/a
n/a
9 Table 2 displays the frequency of reported events, ordered by how likely they were to
happen at least once across the five year period. Friendship problems were by far the most
common type of event experienced by those surveyed, with 84 percent of the sample
reporting this during at least one survey wave. Falling in love, the death of a family member
or friend, breaking up with someone, and family problems were events which also happened
to most respondents during their time at high school. While less common, being bullied was
something that happened to many respondents at least once, whereas serious health problems,
changing school, or parental divorce/separation were rarely reported events.
Control Variables
To help ensure that any observed effect of the explanatory variables on the dependent
variables is specific to the time period under examination (i.e. high school), we controlled for
respondents’ initial levels of educational performance, and their prior experiences of the
events in question. Educational performance is measured using Trapnell’s (1994) ‘Smart’
Scale, which is a well-established self-assessed measure of IQ. The Smart Scale a range from
4 to 36 (with a high score indicating higher intelligence), a mean of 24.6, and is highly
reliable (Cronbach’s alpha = 0.88). To control for events experienced prior to high school, for
each event dummy variables were used to indicate those who answered ‘More than a year
ago’ during the first wave (as data collection occurred in the second half of Year 8). These
were combined to form a count variable adding up the overall number of such events a
respondent experienced prior to high school (MN = 1.6; SD = 1.2). Socio-demographic factors known to influence educational attainment were also
controlled for. Sex is controlled for with a dummy variable coded 0=Male and 1=Female.
Schooling sector is an important predictor of educational attainment in the Australian context,
with OP-eligibility and OP achievement typically higher for Independent school students than
it is State or Catholic school students. The sector variable differentiates between these three
school types based on a respondent’s wave 1 school, with State as the reference category.
Educational attainment and university participation tends to be lower amongst young people
living outside major cities in Australia. Geographic location is thus controlled for with a
measure of whether a respondents’ postcode at wave 1 was inside or outside a major city area.
Parental education and occupation strongly predict educational attainment as
university-educated parents and those in more prestigious occupations tend to devote more
time and resources to cultivating their children’s academic dispositions. We control for the
9
10 highest level of education achieved by either parent as measured in wave 1, distinguishing
between those with a university degree or higher, those with a vocational qualification (e.g.
TAFE certificate or apprenticeship), and those with school-level qualifications. Those who
were missing data or responded ‘Don’t know’ to the parental education question were coded
as such and included in the analysis. Responses to an open-ended question about parental
occupation were coded according to the Australian Statndard Classification of Occupations
(ASCO) and then assigned a score from 0-100 on the ANU4 occupational prestige scale.
Finally, young people’s involvement in part-time work during school may adversely
affect their academic performance by reducing the overall amount of time they have to devote
to study. In waves 2 and 3 respondents were asked whether or not they worked in a part-time
job. These measures were combined to create a variable with four categories indicating a
respondent’s work status across the latter years of high school.
Analytic Approach
The analysis proceeded in two stages, each dealing with a particular research question. We
addressed the second question first: since respondents needed to receive a tertiary entrance
ranking (OP score) in order to attend university, we examine this outcome as an indicator of
respondents’ post-schooling pathways. Logistic regression analysis was used to analyse this
binary measure (where 0 = Received an OP and 1 = Did not receive an OP). Coefficients for
these models are presented as odds ratios. These are interpreted as the change in odds
associated with a one unit change in the predictor, net of all other variables in the model.
In line with the first research question, the second stage of the analysis examines
respondents OP scores as a measure of their academic achievement. For ease of interpretation,
the original OP measure has been mirrored and rescaled to create a new academic
achievement variable ranging 0-100, where a higher score indicates higher achievement. We
use ordinary least squares (OLS) regression to estimate the each of the models, and each
regression coefficient represents the expected increase or decrease in a respondents’
achievement ranking (as a percentage) resulting from a one unit change in the predictor, net
of all other variables in the model. All models included an option to account for withinschool clustering when calculating standard errors, allowing for more robust tests of
significance. All analyses were estimated using Stata 12.
10
11 Results
Not Receiving an Overall Position (OP) Ranking
Table 3 displays the results for logistic regression models examining the odds of not
receiving an Overall Position (the main determinant of university entrance in Queensland) at
the end of school. This could occur either because a respondent completed more vocationally
orientated subjects during Year 12 which did not contribute towards an OP rank, or because
they left school before the end of Year 12.
Model 1 (column 1) examines the impact of major life events on the likelihood of not
receiving an OP rank, controlling for their self-assessed intelligence and prior experiences of
such events at the start of high school. The pseudo R2 value indicates that the model accounts
for 12 percent of the total variation in odds of receiving an OP. The odds ratio for the Smart
Scale (0.9, p < 0.001) indicates that, after controlling for the events in the model, every one
point increase in self-assessed intelligence at wave 1 predicted a 10 percent decrease in the
likelihood that they would not receive an OP five years later. With this measure and the
events experienced during high school were included in the model, the number of events
reported prior to high school was uncorrelated with not receiving an OP.
Bullying, friendship problems, changing school, and breaking up with a girlfriend or
boyfriend were significantly related to whether or not respondents received an OP. Having
been bullied displayed the strongest positive association: for each wave during which a
respondent reported being bullied by other kids, there was a 60 percent increase in their
likelihood of not receiving an OP, net of the other events controlled for in the model. While
less significant, changing schools and breaking up with someone were also associated with
higher odds of not receiving an OP. Meanwhile, respondents who experienced friendship
problems during school were 30 percent more likely to receive an OP than those who did not.
Note that controlling for other peer relationship events, such as bullying and romantic
involvement, most likely restricts ‘friendship problems’ to more benign types of conflict that
result from having close interpersonal ties with others. Supporting this view, the positive
association for friendship problems disappears if bullying is omitted from the model.
11
12 Table 3: Logistic Regression of Odds of Receiving an Overall Position (OP)
(1)
(2)
O.R.
95% C.I.
O.R.
95% C.I.
Events during HS (0-3)
0.7***
1.1
1.1
(0.6, 0.9)
(1.0, 1.3)
(0.9, 1.3)
0.7**
1.1
1.1
(0.6, 0.9)
(0.9, 1.3)
(0.9, 1.3)
1.2*
(1.02, 1.4)
1.2*
(1.02, 1.4)
1.0
1.6***
1.5*
1.2
1.2
(0.9, 1.2)
(1.3, 1.9)
(1.0, 2.1)
(0.9, 1.6)
(0.6, 2.4)
1.0
1.5***
1.7*
1.2
1.1
(0.8, 1.2)
(1.3, 1.8)
(1.1, 2.5)
(0.9, 1.6)
(0.5, 2.4)
Gender
Male (Ref.)
Female
0.6**
(0.4, 0.9)
School sector
State school (Ref.)
Independent school
Catholic school
0.6*
0.7
(0.4, 0.9)
(0.4, 1.1)
Remoteness
Urban
Rural
1.7**
(1.2, 2.5)
Highest Parental Education
Bachelor’s degree or higher
Vocational/Trade certificate
Year 12 or less
Missing/don’t know
2.8***
2.3***
3.9***
(1.8, 4.2)
(1.5, 3.3)
(1.9, 7.9)
Parental occ. prestige (0-100)
0.9*
(0.9, 0.99)
Work status during HS
Did not work (ref.)
Worked in Y10 only
Worked in Y12 only
Worked in Y10 & Y12
1.8*
1.1
0.8
(1.1, 2.9)
(0.7, 1.7)
(0.5, 1.2)
0.9***
1.1
(0.9, 0.9)
(0.9, 1.3)
Friendship problems
Fell in love
Death of family member/friend
Broke up with
boyfriend/girlfriend
Family problems
Bullied by other kids
Changed schools (0-2)
Serious health problems (0-2)
Parents separated/divorced (0-1)
Controls
W1 Smart Scale (4-36)
Events before HS (0-6)
0.9***
1.0
No. of obs.
Adj. R2
*
(0.9, 0.9)
(0.9, 1.1)
1,605
0.12
p < 0.05, ** p < 0.01, *** p < 0.001
12
1,605
0.20
13 When Model 2 (column 2) includes a range of socio-demographic controls, the total
variance explained rises to 20 percent. The effects the life events outlined above persist when
these controls are added. All control measures are independently associated with whether or
not respondents received an OP, with parental education displaying the strongest relationship.
Compared to respondents with at least one university-educated parent, those who did not
know or provide their parents’ education were 3.9 times more likely to not receive an OP.
Meanwhile, those whose parents’ highest education level was vocational or school-level were
2.8 and 2.3 times more likely, respectively, to leave school without an OP. Males were 40
percent less likely than females to receive an OP, whilst respondents living outside major
cities were 70 percent less likely to do so than their urban counterparts. Attending a State
school rather than an Independent one, having parents in less prestigious occupations and
being employed during Year 10 were all associated with higher odds of not receiving an OP.
Overall Position (OP) Ranking Achieved
Table 4 shows the results of the OLS regression models examining the achievement level of
those who received an OP. The OP measure has been rescaled to 0-100 so that covariate
effects may be interpreted as a percentage increase or decrease in ranking (where a higher
ranking denotes better educational performance). Model 1 (column 1) examines how each of
the major life events during high school influenced respondents’ rankings, independently of
self-assessed intelligence and prior experiences of these events upon entering high school.
This model accounts for 19 percent of the overall variation in rankings. Net of the other
measures in the model, each increment of one point on the Smart Scale in wave 1 predicted a
1.4 percent increase in respondents’ achievement at the end of high school 5 years later.
As in the previous analyses, having been bullied by other kids displayed the strongest
negative influence on a respondent’s eventual ranking. For each wave in which a respondent
reported having been bullied, their ranking was reduced by 4 percent. This means that, on
average, and net of the other events and baseline controls, this meant that persistent bullying
across the course of high school predicts up to a 12 percent decrease in respondents’ rankings.
Besides this, the two occurrences that most adversely impacted rankings were falling in love
(a 2.6 percent decrease per report) and family problems (a 2.3 percent decrease per report).
There were smaller, albeit still significant, negative effects for experiencing the death of a
family member/friend and breaking up with a girlfriend/boyfriend. Lastly, as in the previous
analysis, respondents who reported encountering friendship problems tended to achieve a
higher ranking than those who did not.
13
14 Table 4: OLS Regression of OP Ranking (0-100)
(1)
b
se
(2)
b
se
1.7*
-2.5**
-1.9**
-0.9
-1.8**
-3.4***
-0.0
-0.4
2.6
0.7
0.8
0.7
0.7
0.6
0.8
1.9
1.0
2.7
Events during HS (0-3)
Friendship problems
Fell in love
Death of family member/friend
Broke up with boyfriend/girlfriend
Family problems
Bullied by other kids
Changed schools (0-2)
Serious health problems (0-2)
Parents separated/divorced (0-1)
1.8*
-2.6**
-2.1**
-1.9*
-2.3***
-3.9***
0.1
0.0
1.2
0.8
0.8
0.7
0.8
0.7
0.8
2.0
1.1
2.6
Controls
Gender
Male (Ref.)
Female
1.3
1.5
School sector
State school (Ref.)
Independent school
Catholic school
7.7***
1.6
1.5
2.2
Remoteness
Urban
Rural
-0.6
1.4
Highest Parental Education
Bachelor’s degree or higher
Vocational/Trade certificate
Year 12 or less
Missing/don’t know
-6.0***
-7.4***
-13.8***
1.6
1.7
3.9
Parental occ. prestige (0-100)
1.0***
0.3
Work status during HS
Did not work (ref.)
Worked in Y10 only
Worked in Y12 only
Worked in Y10 & Y12
-0.3
-1.5
-4.9**
1.8
1.6
1.6
W1 Smart Scale (4-36)
Events before HS (0-10)
1.4***
-0.8
0.1
0.5
1.4***
-1.0
0.1
0.5
Constant
30.1***
3.8
23.0***
4.1
No. of obs.
Adj. R2
*
1391
0.19
p < 0.05, ** p < 0.01, *** p < 0.001
14
1391
0.28
15 Model 2 (column 2) includes the socio-demographic controls, which raise the total
variance explained to 28 percent. Including these measures slightly reduced the size of the
coefficients for most of the life event measures, with ‘breaking up with boyfriend/girlfriend’
dropping to non-significance. As well as whether or not they received a ranking, parental
education was a major determinant of the actual ranking respondents earned. Respondents
whose parents’ highest education level was vocational or school-level achieved rankings that
were 6 percent and 7.4 percent lower, respectively, than respondents with a universityeducated parent. The relative decrease was even larger - almost 14 percent - for those who
did not know or provide their parents’ education. The type of school they attended was the
other main influence on respondents’ ranking. Respondents who began high school in an
Independent school achieved OPs that ranked on average 7.7 percent higher than those who
had enrolled in a State school. Finally, respondents who were persistently employed (i.e.
working in Years 10 and 12) achieved rankings that were around 5 percent lower than those
who did not work during high school.
Discussion
The aim of this paper has been to investigate the relative impact of peer relationship events
during high school on young Australians’ educational and occupational pathways, relative to
other major life events. To this end, we identified the influence of events such as being
bullied, falling in love, breaking up with someone, and friendship problems, on two main
outcomes for the respondents in our sample: (1) whether or not they received a tertiary
entrance ranking; and (2) the particular ranking achieved by those who did receive this.
Most of the major life events we examined were experienced at least once by a
majority of the sample throughout high school. Even after controlling for contemporaneous
changes, including health or family problems, moving schools, and the death of family
members or friends, the role of peer relationship events stands out clearly and consistently in
these analyses. In some cases, the lasting effects of these events on respondents’ schooling
achievement and post-schooling pathways were larger than they were for the other
developments examined here. Such findings are consistent with the idea that changes in
adolescent peer relationships can either compound or ameliorate the adverse impacts of other
major life events on adolescent development and life pathway formation.
Prior work has highlighted the potential for peer networks to serve as ‘arenas of
comfort’ during adolescence, offering young people a reprieve from changes occurring in
15
16 elsewhere in their lives (Simmons et al., 1987; Call & Mortimer, 2001; Crosnoe & Elder,
2004). This protective function demonstrates the better side of peer intimacy and influence,
in the form of ‘school-orientated’ friendships such as those developed through structured
extra-curricular participation (Ream & Rumberger, 2008). However, our research shows that
young people encounter much conflict alongside comfort in their peer relationships during
high school, and this too may significantly affect their future trajectories.
As a case in point, conflicts involving romance negatively impacted young people in
two ways: (1) those who experienced break-ups during school were less likely to pursue
higher education, and (2) falling in love or breaking up with someone were both associated
with lower achievement amongst those who did receive an OP. The fact that these seemingly
contrary romantic events display similar effects supports Soller’s (2014) ‘relationship
inauthenticity’ thesis. At the core of this argument is the idea that romantic relationships can
create a disjuncture between adolescents’ own idealised identity roles and the identities they
enact in order to win and maintain a partners’ approval (Soller, 2014). While earlier research
indicates that such conflict may adversely affect young people’s mental health, the findings
presented here suggest that poorer academic performance may also result from this tension.
However, of all the events we examined, it was bullying which displayed the most
corrosive impact on young people’s academic achievement and post-schooling pathways.
Respondents who said on each survey occasion that they had been bullied in the previous
year were 150 percent less likely to receive an OP than never-bullied students, and those who
did receive an OP performed 12 percent worse than never-bullied students. Previous research
has found a cross-sectional association between bullying and poor academic performance,
and a longitudinal association between bullying and depression (Bond et al., 2001). The
results presented here build on this existing work, demonstrating the longer-term impact that
bullying can have on young people’s educational and occupational trajectories.
If respondents’ experiences of bullying and romance displayed the most potential to
compound the stress of changes in adolescence, then their friendships may offer a reprieve
from this stress. Respondents who experienced friendship problems were more likely to
receive an OP, and a higher-ranking OP, than those who never reported such problems. This
finding suggests that young people who form close and resilient friendships - in which status
and identity conflicts are more easily tolerated and resolved - may indeed benefit from the
protective function that such relationships offer (Crosnoe & Elder, 2004; Giordano, 2003).
16
17 Figures 1 & 2: Marginal effects of bullying and friendship problems on post-school
work/study status^
^ Obtained using MARGINS command in Stata following multinomial regression of post-school work/study
status (all covariates in prior models held at their means).
To further illustrate how these different experiences impacted on young people’s post-
schooling pathways, supplementary analysis was undertaken to estimate the effects of
bullying and friendship problems on respondents’ work/study status in wave 4 (i.e. three
years following high school). Figures 1 and 2 display the marginal effect of these events on
respondents’ probability of being in one of four possible combinations of work and postsecondary study. Bullying can be seen to substantially decrease the odds of being engaged in
both work and study, whilst increasing the odds of being only working, or neither working
nor studying. While not as strong, these effects are reversed for those experiencing friendship
problems. Such findings are consistent with the results from the main analysis, strengthening
our case that the more immediate effect of these events on tertiary entrance (e.g. not receiving
an OP) has a longer-term repercussion in terms of labour market participation. By examining
respondents’ school-to-work transitions over a longer period, and including measures of their
mental health and wellbeing, future waves of the Our Lives study will allow us to further
understand the impact of adolescent peer relationships across the life course.
Acknowledgements
The authors would like to acknowledge the generous support of the Australian Research
Council (DP0557667 / DP0878781 / DP130101490). For information about the Our Lives
project visit: http://artsonline.monash.edu.au/ourlives/.
17
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