Short Literature Review (READ 3 articles and write a summary)

– Extend your “Literature Review” part. Structure your paper thematically, in a way that enables you to bring the articles into conversations with each other in each sections.

– The two-paragraph reflection does not count toward your 1,500 words. Add a Conclusion section before that.

Don't use plagiarized sources. Get Your Custom Essay on

Just from $13/Page

Order Essay

– There are a lack of in-text citations throughout the paper. Plus, the citations you made have some APA mistakes. Structure your paper thematically, in a way that enables you to bring the articles into conversations with each other in each sections.

I
r
p
i

i
c
s
l

n
l

P
5

arent–Child Connectedness and Behavioral and
motional Health Among Adolescents

iann M. Ackard, PhD, Dianne Neumark-Sztainer, PhD, Mary Story, PhD, Cheryl Perry, PhD

ackground: This study sought to examine teen perceptions of mother– child and father– child
connectedness, with focus on valuing parental opinions and perception of parental
communication and caring, and associations with behavioral and emotional health.

ethods: A population-based sample of 474

students in public schools completed the 2001 Project
EAT (Eating Among Teens) survey.

esults: Overall, the majority of girls and boys reported valuing their parents’ opinion when making
serious decisions and believing that their parents cared about them. Yet, one fourth of girls
and boys felt unable to talk to their mother about problems, and over half of girls and one
third of boys felt unable to talk to their father. Valuing friends’ opinions over parents’
opinions, and perceiving low parental communication and caring were associated with
unhealthy weight control, substance use, suicide attempts, body dissatisfaction, depression,
and low self-esteem. Of significant concern, compared to their peers who reported feeling
that their mother cared quite a bit or very much, youths who reported feeling as though
their mother cared very little or not at all about them reported particularly high prevalence
rates of unhealthy weight control behaviors (63.49% girls, 25.45% boys); suicide attempts
(33.51% girls, 21.28% boys); low self-esteem (47.15% girls, 24.56% boys); and depression
(63.52% girls, 33.35% boys).

onclusions: Adolescents’ perceptions of low parental caring, difficulty talking to their parents about
problems, and valuing their friends’ opinions for serious decisions were significantly
associated with compromised behavioral and emotional health. Interventions aimed at
improving the parent– child relationship may provide an avenue toward preventing h

ealth

risk behaviors in youth.
(Am

c
i
d
t
t
C
r
a

i
i
t
a
a
f
a
h
y
m
a
h
d

ntroduction

n one of the most significant works investigating
the relationship between several types of influential
environments (e.g., family and school) and health

isk behaviors among adolescents, Resnick et al.1 re-
orted that family connectedness was significantly and

nversely associated with emotional distress, suicidality,
lcohol use, marijuana use, and early age of sexual
ntercourse. Others have found significant direct asso-
iations between pathologic family environments and
ubstance use,2 depression,3–5 disordered eating,6

ower self-esteem,5 and suicidality.7–10

Although separation from parents is a normal devel-
pmental task for adolescents, it does not always culmi-
ate in a connected parent– child relationship. A 1-year

ongitudinal project evaluated the quality of the parent–

rom the private practice (Ackard), and Division of Epidemiology,
chool of Public Health, University of Minnesota (Neumark-Sztainer,
tory, Perry), Minneapolis, Minnesota
Address correspondence and reprint requests to: Diann M. Ackard,

a
hD, 5101 Olson Memorial Highway, Suite 4001, Golden Valley MN
5422. E-mail: Diann_Ackard@mindspring.com.

m J Prev Med 2006;30(1)
2006 American Journal of Preventive Medicine • Published by

hild relationship during the adolescent transition to
ncreased individuation.5 Parent–teen relationships
eemed as connected were associated with fewer symp-
oms of depression and anxiety, and greater self-worth
han relationships categorized as detached. Similarly,
alifornia teens were surveyed across 2 years, and

esults show an association between family connection
nd psychological and behavioral health.1

For youth, feeling connected to their families is an
mportant anchor, and many do turn to parents for
nformation and guidance. In a nationally representa-
ive study of the use of healthcare resources among
dolescents, mothers were identified by 41.7% of boys
nd 58.4% of girls as the first person they would consult
or healthcare concerns.12 More broadly, 60.3% of boys
nd 71.7% of girls identified parents as one source of
ealthcare information. However, of concern is that
outh who are at greatest need for adult intervention
ay not seek it. For example, results from a study of 879

dolescents indicated that only about half of youth who
ad attempted suicide had approached an adult to
iscuss their problems.10 Furthermore, those who had

ttempted suicide reported that they were less likely to

590749-3797/06/$–see front matter
Elsevier Inc. doi:10.1016/j.amepre.2005.09.013

d
f
s

e
g
m
p
c
n
g
h
o
t
h
v
w
a
w
t
w
c
a

M
S

P
s
g
s
p
w

E
a
s
m
M
C
p
r

i
c
7
(
(

T
d
n
E
n
t
w

w
i

O
h
c
P

P
t
m
y
(
a

h
w
i
f
u
s
a
c

m
s
s
e
u
“
c

S
d
l
c
f
c
m

S
o
d
b
c

B
e
m
g
v
q

S
c
R

iscuss their problems with a family member in the
uture compared to those who had not ever attempted
uicide.10

Previous studies have found significant associations
etween family connectedness and the behavioral and
motional health of youth, but are limited by investi-
ating only a few health risk behaviors or by a smaller,
ore homogeneous sample. This study expands on

revious research by exploring parent– child communi-
ation and caring in a large, ethnically and socioeco-
omically diverse population of youth, and by investi-
ating a broader range of behavioral and emotional
ealth indicators in order to better inform the devel-
pment of effective parent and adolescent interven-
ions and to identify populations at greatest risk. It was
ypothesized that both girls and boys who indicated
aluing their friends’ opinions more than their parents’
ould report higher odds for substance use, suicide
ttempts, and unhealthy weight-control behaviors, as
ell as higher odds of low self-esteem, body dissatisfac-

ion, and depression. Similar directional associations
ere also hypothesized between perceived parental
aring and ability to talk to parents about problems,
nd behavioral and emotional health outcomes.

ethod
tudy Population and Design

articipants in the current study included a total of 4746
tudents enrolled in 31 public middle and high schools in the
reater Minneapolis/St. Paul metropolitan area of Minne-
ota. Schools with diverse racial/ethnic and socioeconomic
rofiles were targeted for recruitment to increase diversity
ithin the sample.
In 2001, participants completed the confidential Project

AT (Eating Among Teens) survey in school classes and were
sked to have their height and weight measured in a private
creened area by trained staff using standardized anthropo-
etric procedures. The study complied with the University of
innesota’s Institutional Review Board and Human Subjects’
ommittee, and with each school district’s research board
rocess for obtaining student consent. The student response
ate was 81.5%.

The sample comprised 2357 girls and 2377 boys (1

ndividuals had missing data for gender and were not in-
luded in analyses). Participants were in the following grades:
th (28.2% girls, 27.4% boys); 8th (6.4% girls, 6.7% boys); 9th
0.9% girls, 1.0% boys); 10th (50.3% girls, 52.6% boys); 11th
10.1% girls, 8.6% boys); and 12th (4.1% girls, 3.8% boys).

easures

he Project EAT survey includes 221 self-report questions on
emographics, family and personal health attitudes, and
utritional and weight-related factors. Although the Project
AT survey has not been validated against other question-
aires or actual behavior, multidisciplinary professional

eams, youth focus groups, and pilot tests of the questions

ere conducted to provide guidance for the selection and s

0 American Journal of Preventive Medicine, Volume 30, Num

ording of questions.13–15 All questions listed below were
ncluded in the Project EAT survey.

arent–Child Connectedness

pinions valued. One question in the survey asked, “If you
ad a serious decision to make, like whether or not to
ontinue in school, whose opinions would you value most?”
ossible responses were “parent” or “friend.”

arent– child communication and caring. Two questions in
he survey were asked separately for each parent.16 (1) “How

uch do you feel you can talk to your mother (father) about
our problems?” (2) “How much do you feel your mother
father) cares about you?” Possible responses follow: “not at
ll,” “a little,” “somewhat,” “quite a bit,” or “very mu

ch.

”

ehavioral Health

eight-control behaviors. “Which of the following things
ave you done in order to lose weight or keep from gaining
eight during the past year?” Participants were requested to

ndicate “yes” or “no” to the following responses: exercise,
asted, ate very little food, took diet pills, made myself vomit,
sed laxatives, used diuretics, used food substitute (powder/
pecial drink), skipped meals, ate more fruits and vegetables,
te less high-fat foods, ate less sweets, and smoked more
igarettes.

Behaviors were grouped as follows: healthy (exercise, ate
ore fruits and vegetables, ate less high-fat foods, or ate less

weets); less extreme (fasted, ate very little food, used food
ubstitute, skipped meals, or smoked more cigarettes); or
xtreme (took diet pills, made myself vomit, used laxatives, or
sed diuretics). Participants were grouped by use (“yes” or
no”) of any less extreme or extreme unhealthy weight
ontrol behaviors in the past year.17

ubstance use. “How often have you used the following
uring the past year (12 months)? Liquor (beer, wine, hard

iquor), marijuana, or drugs other than marijuana (acid,
ocaine, crack, etc.).”16 Possible responses follow: “never,” “a
ew times,” “monthly,” “weekly,” or “daily”. Responses were
ollapsed into two categories: never versus a few times or
ore.

uicide attempts. “Have you ever tried to kill yourself?” The
riginal responses included a temporal component (“Yes,
uring the past year,” “Yes, more than a year ago,” or “No”),18

ut responses were dichotomized (“yes” or “no”) for the
urrent analyses.

motional Health

ody dissatisfaction. The dissatisfaction that one experi-
nces with his or her body appearance was assessed using a
odified version of Pingitore’s19 scale. Higher scores indicate

reater dissatisfaction. A binary score was created using the
alue separating the highest quartile from the lowest three
uartiles.

elf-esteem. The self-esteem instrument asked youth to indi-
ate their level of agreement with six sentences from the
osenberg Self-Esteem Scale.20 Higher scores reflect lower

elf-esteem. A binary variable was created using the value

ber 1 www.ajpm-online.net

s
q

D
s
s
n
“
i
s
w

P
m
“
p

R
i
A

S
e
f
k
h
f
f
m
c
w
p
S
v

F
s
c
i
m
w
c
a
l
g
w
g
a
t
u
f
p
a
q
e
w
s
v

R
D

P
5
b
L
g
s
(
m
c
1
m
g

M
e
d
A
t
m
s
2
c
a
t
m
2
b
c
8
b
t
b
l

P
H

G
t
t
t
r
c
p
a
r
g
p
p
t
v

eparating the lowest three quartiles from the highest
uartile.

epressive mood. Depressive mood was assessed using a
cale by Kandel and Davies21 asking the frequency of six
ymptoms of depression (dysthymic mood, tension/nervous-
ess, fatigue, worry, sleep disturbance, and hopelessness):
not at all,” “somewhat,” or “very much.” Higher values
ndicate more severe depressive moods. The summed score
eparating the lowest three quartiles from the highest quartile
as used as a cut-off to create a binary score.

emographics

arent marital status. Each student was asked to report the
arital status of his or her parents as “married,” “divorced,”

separated,” “parents never married,” or “one/both of my
arents is dead.”

ace/ethnicity. Students could choose as many of the follow-
ng as they wished: white, African American, Hispanic, Asian
merican, Native American, and mixed/other.

ocioeconomic status. One or both parents’ highest level of
ducation was used to establish socioeconomic status (SES)
or most youth. Due to the fact that some students did not
now their parent’s educational level (n �1058, 22.3%) or
ad missing data for items needed to calculate SES, other

actors (family eligibility for public assistance, eligibility for
ree or reduced-cost school meals, and employment status of

other and father) were combined in an algorithm using the
lassification and regression trees (CART) method,22 which
as found to be predictive of parent education among the
articipants who completed all questions needed to calculate
ES. By using this cartography, the number of missing SES
alues was reduced to 4.1% (n �196).

tatistical Analyses

requencies and percentages were used to describe the
ample by sociodemographic variables and by parent– child
ommunication and caring. Because the sample came from
ntact social clusters in schools, clustered logistic regression

odels, in which school was included as a random effect,
ere used to investigate the association between parent– child
onnectedness and behavioral and emotional health vari-
bles, adjusting for sociodemographic characteristics (grade
evel, race/ethnicity, SES, and parental marital status). Cate-
oric (grade level, race/ethnicity, and parental marital status,
ith “white” and “parents are married” serving as the referent
roups) and continuous (SES) sociodemographic “covari-
tes” were forced to enter in the first step. In the second step,
he parent– child connectedness variable was entered to eval-
ate the level of improvement of fit in the model. The
ollowing response sets served as the comparison: valuing
arents’ opinion, feeling able to talk to mother/father quite
bit or very much about, and feeling mother/father cares

uite a bit or very much. Adjusted probabilities, standard
rrors, and significance values were generated. The p values
ere not adjusted for multiple testing. All analyses were run

eparately in 2005 by gender using SAS/STAT software,

ersion 9.1 (SAS Institute Inc., Cary NC, 2004).23 t

anuary 2006

esults
escription of Sample

articipants’ race/ethnicity follows: white (45.6% girls,
1.3% boys); African American (20.1% girls, 17.9%
oys); Asian American (20.6% girls, 17.8% boys);
atina/Latino (5.2% girls, 6.5% boys); and other (8.6%
irls, 6.4% boys). They reported their parents’ marital
tatus as married (60.7% girls, 62.6% boys); divorced
18.1% girls, 18.5% boys); or other (separated, never
arried, or deceased; 21.2% girls, 18.9% boys). SES was

alculated and reported as follows: low (20.4% girls,
4.5% boys); low-middle (19.1% girls, 18.5% boys);
iddle (25.6% girls, 27.6% boys); high-middle (21.5%

irls, 25.3% boys); and high (13.4% girls, 14.1% boys).

escription of Parent–Child Connectedness

ost participants indicated that they valued their par-
nts’ opinions over their friends’ opinions for serious
ecisions (parents’ opinion: 75.5% girls; 82.2% boys).
pproximately half reported that they could talk to

heir mother about their problems “quite a bit” or “very
uch” (quite a bit/very much: 52.1% girls, 48.6% boys;

omewhat: 22% girls, 23.1% boys; not at all or a little:
5.9% girls, 28.3% boys). Fewer indicated that they
ould talk “quite a bit” or “very much” to their father
bout their problems, and in fact, the majority reported
hat they could not talk to their father (quite a bit/very

uch: 24.6% girls, 38.2% boys; somewhat: 20.0% girls,
5.2% boys; not at all or a little: 55.4% girls, 36.6%
oys). A majority of the girls and boys reported feeling
ared about by their mothers (quite a bit/very much:
8.6% girls, 90.8% boys; somewhat: 6.3% girls, 4.5%
oys; not at all or a little: 5.1% girls, 4.7% boys) and by
heir fathers (quite a bit/very much: 78.6% girls, 81.8%
oys; somewhat: 8.5% girls, 7.8% boys; not at all or a

ittle: 12.9% girls, 10.4% boys).

arent–Child Connectedness and Behavioral
ealth Indicators

irls who valued their friends’ opinions over those of
heir parents, and those who felt that they could not
alk (or talk very little) to their mother or father about
heir problems reported greater prevalence of health
isk behaviors than peers who reported higher parental
ommunication and caring (Table 1). Girls who re-
orted low paternal caring did not report higher prev-
lence of substance use compared to their peers who
eported high paternal caring. Of significant interest,
irls who reported low maternal caring, compared to
eers who reported high maternal caring, reported
articularly high prevalence of unhealthy weight con-
rol (63.49% vs 18.34%) and suicide attempts (33.51%
s 10.17%).

Among boys, valuing friends’ opinions over those of

heir parents, and feeling unable (or only slightly able)

Am J Prev Med 2006;30(1) 61

t
c
c
c
o
a
c
u
S
l
h
u
h

P
H

A
e
(
r
c
t
a
l
t
b
F

w
d

T
b
r
a
R
p
p
t
c
b
c
f
a
t
l
t
d
p
s
(
t

T
l

W
F
F
F
F
a
b

m
*
*
*
A

o talk to mother or father about problems was signifi-
antly and directly associated with unhealthy weight
ontrol behaviors, substance use, and suicide attempts
ompared to their peers who reported valuing parents’
pinions and feeling able to talk to mother or father
bout problems (Table 2). Perceptions of low paternal
aring were not significantly associated with substance
se compared to perceptions of high paternal caring.
imilar to their female counterparts, boys who reported
ow maternal caring, compared to peers who reported
igh maternal caring, were much more likely to report
nhealthy weight control (25.45% vs 3.63%) and to
ave attempted suicide (21.28% vs 3.97%).

arent–Child Connectedness and Emotional
ealth Indicators

ssociations between parent– child connectedness and
motional health indicators are shown in Table 3
girls) and Table 4 (boys). For all youth, parent– child
elationships characterized by valuing friends’ opinion
ompared to those of parents, and feeling unable to
alk to mother or father about problems were strongly
ssociated with scores indicating body dissatisfaction,
ow self-esteem, and depression. Among girls, percep-
ions of minimal parental caring were associated with
ody dissatisfaction, low self-esteem, and depression.

able 1. Girls: parent– child connectedness and behavioral h
evelsb

Unhealthy weight control

AP (SE) p value

hose opinion is valued for serious decisions?
Parents’ opinion 16.41 (1.34)
Friends’ opinion 37.95 (3.33) <0.001***

eel you can talk to mother about problems?
Quite a bit or very much 15.14 (1.50)
Somewhat 22.10 (2.79) 0.018*
Not at all or a little 35.48 (3.25) <0.001***

eel you can talk to father about problems?
Quite a bit or very much 15.02 (2.16)
Somewhat 17.68 (2.59) 0.422
Not at all or a little 25.72 (1.98) 0.001**

eel your mother cares about you?
Quite a bit or very much 18.34 (1.33)
Somewhat 31.18 (5.58) 0.001**
Not at all or a little 63.49 (7.35) <0.001***

eel your father cares about you?
Quite a bit or very much 18.78 (1.39)
Somewhat 35.73 (5.36) 0.001**
Not at all or a little 27.49 (4.06) 0.027*

p � 0.05;
*p � 0.01;
**p � 0.001 (all bolded).
P, adjusted probability; SE, standard error.

or boys, minimal parental caring was associated only p

2 American Journal of Preventive Medicine, Volume 30, Num

ith low self-esteem and depression, but not for body
issatisfaction.

iscussion

he aim of the present study was to explore associations
etween parent– child connectedness and a broad
ange of behavioral and emotional health indicators
mong a population-based sample of girls and boys.
esults from this large study of youth indicate that
arent– child relationships characterized by valuing
arent opinions for serious decisions, feeling able to
alk to parents about problems, and perceiving parental
aring were associated with more healthy indicators of
ehavioral and emotional health. These results are
onsistent with past research, which indicated that
amily connectedness was significantly and inversely
ssociated with several health risk behaviors and emo-
ional health indicators,1 depressive symptoms and
ower self-worth,5 substance use,2 and bulimic symp-
oms.6 Yet the current study adds to the literature by
emonstrating a significant relationship between
arent– child connectedness and a broad range of
erious behavioral and emotional health risk behaviors
substance use, unhealthy weight control, suicide at-
empts, body dissatisfaction, low self-esteem, and de-

: adjusted probabilities,a standard errors, and significance

Substance use Suicide attempts

P (SE) p value AP (SE) p value

3.06 (1.42) 10.44 (0.88)
5.39 (2.52) <0.001*** 18.13 (1.87) <0.001***

3.92 (1.68) 9.39 (0.98)
0.32 (2.56) 0.028* 11.49 (1.59) 0.227
6.81 (2.53 <0.001*** 19.31 (1.91) <0.001***

9.73 (2.30) 9.44 (1.40)
5.73 (2.68) 0.078 10.79 (1.64) 0.521
3.65 (1.77) <0.001*** 14.22 (1.19) 0.012*

7.29 (1.37) 10.17 (0.80)
9.95 (4.96) 0.012* 27.06 (4.13) <0.001*** 7.56 (5.58) 0.065 33.51 (4.95) <0.001***

6.87 (1.45) 10.21 (0.85)
9.74 (4.39) 0.004** 21.23 (3.32) <0.001*** 2.41 (3.67) 0.150 20.87 (2.88) <0.001***

city, and parent marital status, and were clustered for school.
ents’ opinion, feeling able to talk to mother/father quite a bit or very

ealth
A

3
5

3
4
4

2
3
4

3
4
4
3
4
4

ethni
g par

ch.

ression) in a diverse sample of both boys and girls.

ber 1 www.ajpm-online.net

y
s
i
y
t
i
e
p
t
H
w
t
t
a
o
s
t
t

o
a
I
f
s
r
a
o

t
a
t
a
r
n

e
w
s
i
s
i
m
r
t
t
c
t
v
t
t
e
g
c
l
a

T
l
W
F
F
F
F
a
b
m
*
*
*
A
J

A particularly interesting finding is the valuation that
outh place on their parents’ opinions when making
erious decisions, notably valuing their parents’ opin-
ons more than that of their peers. Although some
outh showed more interest in being with their friends
han spending time with family, parents may have more
nfluence on their teens’ behaviors than may be appar-
nt to them. Valuing parents’ opinions appears to be a
rotective factor against unhealthy behavioral and emo-
ional health indicators among both girls and boys.
ealthcare providers and school personnel working
ith teens may want to share study results with parents

o help them feel empowered by the knowledge that
heir opinions matter. In order to promote teens’
ttention to and respect for parents’ opinions, parents
f youth may wish to practice having discussions on
ensitive topics without lending judgment to their
een’s ideas until asked, and then strategizing solutions
o the problem in a collaborative manner.

One particular area of concern was the significance
f adolescents’ perceptions of maternal caring, and its
ssociation with both behavioral and emotional health.
nterventions can enhance mother– child caring. For
amilies in which the mother– child relationship is
trained, youth may benefit from developing positive
elationships with other adult female role models, such
s through Big Sister programs, other female relatives,

able 2. Boys: parent– child connectedness and behavioral h
evelsb

Unhealthy weight control
AP (SE) p value

hose opinion is valued for serious decisions?
Parents’ opinion 3.41 (0.65)
Friends’ opinion 9.31 (2.09) <0.001***

eel you can talk to mother about problems?
Quite a bit or very much 3.02 (0.68)
Somewhat 3.25 (1.00) 0.834
Not at all or a little 8.79 (1.76) <0.001***

eel you can talk to father about problems?
Quite a bit or very much 2.48 (0.67)
Somewhat 3.82 (1.08) 0.226
Not at all or a little 7.40 (1.43) <0.001***

eel your mother cares about you?
Quite a bit or very much 3.63 (0.63)
Somewhat 9.74 (3.89) 0.019*
Not at all or a little 25.45 (7.13) <0.001***

eel your father cares about you?
Quite a bit or very much 3.62 (0.66)
Somewhat 5.87 (2.14) 0.198
Not at all or a little 12.38 (3.25) <0.001***

p � 0.05;
*p � 0.01;
**p � 0.001 (all bolded).
P, adjusted probability; SE, standard error.

r community leaders, while continuing to ameliorate H

anuary 2006

he parent– child relationship. A longitudinal study of
dolescents found that youth who experience a rela-
ionship deficit in one source (e.g., the family) may be
ble to compensate for that void by forming a positive
elationship from another source (e.g., school,
eighborhood).23

Increased perceived communication and caring by
ither mother or father were consistently associated
ith adolescent well-being. These associations under-

core the importance of the parent– child relationship
n promoting overall health among youth, and empha-
ize that while it is valuable for either parent to be
nvolved in enhancing the parent–teen relationship, it

ay be ideal for both mother–teen and father–teen
elationships to be fostered through open communica-
ion and caring. Professionals working with youth and
heir families, such as family therapists and school
ounselors, should promote parent– child communica-
ion and find opportunities to enhance parental in-
olvement in addressing primary and tertiary preven-
ion of compromising behaviors among teens. One way
o promote parent– child connectedness may be to
ncourage parents and adolescents to spend time to-
ether, such as at family mealtimes, as higher frequen-
ies of family meals also have been associated with
ower substance use, depressive symptoms, and suicid-
lity, even after controlling for family connectedness.24

: adjusted probabilities,a standard errors, and significance
Substance use Suicide attempts
P (SE) p value AP (SE) p value

9.19 (1.45) 3.77 (0.57)
6.42 (2.90) <0.001*** 10.21 (1.81) <0.001***

5.73 (1.77) 2.80 (0.57)
0.10 (2.60) <0.001*** 4.85 (1.09) 0.052 7.45 (2.41) <0.001*** 8.83 (1.40) <0.001***

4.99 (1.97) 3.74 (0.76)
6.12 (2.46) <0.001*** 2.85 (0.79) 0.403 7.33 (2.14) <0.001*** 7.73 (1.18) 0.001***

1.66 (1.41) 3.97 (0.56)
8.72 (5.83) 0.229 11.29 (3.65) 0.003**
0.75 (6.35) 0.157 21.28 (4.92) <0.001***

1.20 (1.48) 4.00 (0.58)
0.73 (4.41) 0.036* 8.95 (2.40) 0.006**
5.29 (4.11) 0.340 10.11 (2.34) <0.001***

city, and parent marital status, and were clustered for school.
ents’ opinion, feeling able to talk to mother/father quite a bit or very
ealth
A
3
5

3
5
4

3
4
4

4
4
5

4
5
4

ethni
g par
ch.

ealthcare professionals should also assess the pres-

Am J Prev Med 2006;30(1) 63

e
a
h
m
i
r
I
b
a

P
s
s
o
a
s
b
c
e
e
y
p
p
p
c
p
s
s

c
i
b
h
w
b
f
t
n
m
f
b
s
a
r
n
t
a
s
a
m
y

u
c
g
p

T
l
W
F
F
F
F
a
b
m
*
*
*
A
6

nce of health problems in parents, as there are strong
ssociations between fathers’ and mothers’ mental
ealth and that of their offspring.25,26 For example,
ale and female adolescents of mothers with suicidal-

ty, compared to their peers whose mothers did not
eport suicidality, indicated greater suicide attempts.25

n addition, depression in a mother has been found to
e associated with depression recurrence, chronicity,
nd severity in young adult sons and daughters.26

Several practical implications result from this study.
rofessionals designing teen interventions may want to
pecifically target enhancing the parent– child relation-
hip. One parent-based intervention targeted the devel-
pment of communication skills and strengthening of
dult– child relationships through lessons such as re-
olving conflicts in a respectful manner by avoiding
lame and criticism, exploring mutual needs within
ommunication, solving problems constructively, and
ncouraging adolescent emancipation.27 Toward the
nd of educating parents on suicide risk factors among
outh, children of mothers who received the informal
rofessionally led intervention groups reported im-
roved perception of maternal caring and reduced
arent– child conflicts after the 3-month intervention,
ompared to youth in the control condition.27 These
romising results indicate that mother– child relation-
hips are malleable and able to be improved within a

able 3. Girls: parent– child connectedness and emotional h
evelsb

Body dissatisfaction

AP (SE) p value

hose opinion is valued for serious decisions?
Parents’ opinion 27.75 (2.40)
Friends’ opinion 43.40 (1.32) <0.001***

eel you can talk to mother about problems?
Quite a bit or very much 26.32 (1.49)
Somewhat 32.83 (2.35) 0.013*
Not at all or a little 41.98 (2.37) <0.001***

eel you can talk to father about problems?
Quite a bit or very much 28.10 (2.19)
Somewhat 24.49 (2.26) 0.237
Not at all or a little 35.95 (1.63) 0.004**

eel your mother cares about you?
Quite a bit or very much 29.18 (1.23)
Somewhat 48.05 (4.67) <0.001*** Not at all or a little 56.91 (5.19) <0.001***

eel your father cares about you?
Quite a bit or very much 28.64 (1.31)
Somewhat 46.40 (4.05) <0.001*** Not at all or a little 41.60 (3.48) <0.001***

Adjustments were made for grade level, socioeconomic status, race/
Significance levels are reported with the following comparison: valuin
uch about, and feeling mother/father cares quite a bit or very mu
p � 0.05;
*p � 0.01;
**p � 0.001 (all bolded).
P, adjusted probability; SE, standard error.

hort period of time. Interventions targeting parent– t

4 American Journal of Preventive Medicine, Volume 30, Num

hild connections and communication may be effective
n preventing and reducing the use of health risk
ehaviors, while at the same time enhancing emotional
ealth. Importantly, results from the current study, in
hich over one half of girls (55.4%) and one third of
oys (36.6%) did not feel that they could talk to their
ather about their problems, underscore the impor-
ance of including both parents in improving commu-
ication. It is possible that interventions that target
others form the foundation, and those targeting

athers construct the protective walls against health risk
ehaviors. Furthermore, although there were no con-
istent results across parent– child connectedness vari-
bles with respect to race/ethnicity, lower SES was
egularly associated with lower perceived family con-
ectedness (ability to talk to mother or father, percep-

ion of caring from mother or father). While a full
ssessment to identify at-risk youth is critical, profes-
ionals conducting broader outreach programs (such
s school based or as part of a community intervention)
ay choose to target interventions toward lower SES

outh, as low SES may be associated with greater need.
This study had several strengths that increase the

tility of study findings. The use of a diverse, nonclini-
al, population-based sample of girls and boys allows for
eneralization to larger populations, exploration of
atterns across race/ethnicities and socioeconomic sta-

: adjusted probabilities,a standard errors, and significance

Low self-esteem Depression

P (SE) p value AP (SE) p value

0.10 (2.18) 34.11 (1.38)
4.93 (0.98) <0.001*** 51.54 (2.41) <0.001***

2.44 (1.07) 31.55 (1.57)
1.12 (1.99) <0.001*** 40.46 (2.46) 0.001** 9.72 (2.14) <0.001*** 51.15 (2.39) <0.001***

2.68 (1.58) 30.77 (2.24)
4.64 (1.83) 0.407 29.82 (2.41) 0.765
2.87 (1.37) <0.001*** 45.07 (1.69) <0.001***

6.04 (0.93) 35.67 (.01)
4.88 (4.46) <0.001*** 58.21 (4.61) <0.001*** 7.15 (5.25) <0.001*** 63.52 (5.00) <0.001***

5.87 (0.99) 34.44 (1.37)
0.82 (3.79) <0.001*** 52.02 (4.11) <0.001*** 9.59 (3.29) <0.001*** 55.53 (3.51) <0.001***

city, and parent marital status, and were clustered for school.
ents’ opinion, feeling able to talk to mother/father quite a bit or very
ealth
A

3
1

1
2

1
1

1
3
4

1
3
2

ethni
g par
ch.

us, and identification of groups at potential high risk

ber 1 www.ajpm-online.net

f
t
a
b
c

s
c
u
p
a

c
T
b
l
a
t
c
a
p
r

c
b
p
t
n
t
i
t
y

T
B
a
a
i

T
l
W
F
F
F
F
a
b
m
*
*
*
A
J

or lower levels of parent– child connectedness. Fur-
hermore, the broad range of outcomes assessed yields

greater understanding of the diversity of health risk
ehaviors potentially associated with parent– child
onnectedness.

The present results need to be contextualized with
everal limitations. The questions assessing parent–
hild connectedness were brief (and thus cannot be
sed in an in-depth and qualitative exploration of the
arent– child relationship), and prone to source vari-
nce due to self-report by only one reporter (adoles-

able 4. Boys: parent– child connectedness and emotional h
evelsb

Body dissatisfaction
AP (SE) p value

hose opinion is valued for serious decisions?
Parents’ opinion 11.68 (0.85)
Friends’ opinion 18.07 (2.13) 0.002**

eel you can talk to mother about problems?
Quite a bit or very much 10.56 (1.02)
Somewhat 11.77 (1.54) 0.501
Not at all or a little 17.82 (1.70) <0.001***

eel you can talk to father about problems?
Quite a bit or very much 8.36 (1.02)
Somewhat 14.07 (1.60) 0.002**
Not at all or a little 16.84 (1.46) <0.001***

eel your mother cares about you?
Quite a bit or very much 12.31 (0.82)
Somewhat 15.61 (3.82) 0.354
Not at all or a little 21.99 (5.80) 0.016*

eel your father cares about you?
Quite a bit or very much 11.45 (0.83)
Somewhat 21.42 (3.33) <0.001*** Not at all or a little 17.84 (2.86) 0.014*

What This Study Adds . . .

The current study of a large, diverse population of
youth expands on previous research using
smaller, homogenous samples, and explores the
relationship between a broad range of behavioral
and emotional health indicators and specific char-
acteristics of parent– child communication and
caring.

Valuing parent opinions for serious decisions,
feeling able to discuss problems with parent(s),
and perceiving parent’s caring were related in-
versely to substance use, unhealthy weight con-
trol, suicide, body dissatisfaction, and depression,
and directly to self-esteem.

o
anuary 2006

ent). Some cells of interest yielded small sample sizes.
he cross-sectional design cannot address causation
etween variables. While parent– child connectedness

ikely has an impact on adolescent well-being, it may
lso be that the health-compromising behaviors among
eens lead to deterioration of family relations, per-
eived levels of parental communication and caring,
nd increased reliance on peers’ opinions. Future
rospective studies can address the direction of these
elationships.

In conclusion, adolescents’ perceptions of parent–
hild relationships were significantly associated with
ehavioral and emotional health indicators. Healthcare
rofessionals and school personnel should familiarize
hemselves with the perceived parent– child connected-
ess of youth. Interventions may target the mother–

een relationship as a foundation for change, but
deally should include both parents when possible for
he most comprehensive effort toward preventing
outh health risk behaviors.

his study was supported by the Maternal and Child Health
ureau (Title V, Social Security Act), Health Resources
nd Service Administration, U.S. Department of Health
nd Human Services (grant MCJ-270834, DN-S, principal
nvestigator).

No financial conflict of interest was reported by the authors

adjusted probabilities, standard errors, and significance

Low self-esteem Depression
P (SE) p value AP (SE) p value

7.47 (0.74) 17.83 (0.98)
4.18 (1.98) <0.001*** 30.80 (2.52) <0.001***

6.16 (0.82) 14.94 (1.17)
6.49 (1.20) 0.815 21.80 (1.96) 0.002**
5.16 (1.65) <0.001*** 28.19 (1.97) <0.001***

5.77 (0.88) 15.26 (1.34)
7.41 (1.24) 0.258 17.27 (1.73) 0.355
2.82 (1.38) <0.001*** 27.68 (1.74) <0.001***

7.50 (0.67) 18.79 (0.94)
9.58 (4.30) <0.001*** 38.21 (5.32) <0.001*** 4.56 (5.07) <0.001*** 33.35 (5.46) 0.002**

7.31 (0.71) 18.02 (0.98)
6.00 (3.06) <0.001*** 34.56 (3.91) <0.001*** 4.91 (2.73) <0.001*** 27.54 (3.39) 0.003**

city, and parent marital status and were clustered for school.
ents’ opinion, feeling able to talk to mother/father quite a bit or very

ealth;

A
1
1
1
1
2
1
1
ethni
g par
ch.

f this paper.

Am J Prev Med 2006;30(1) 65

R
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
6

eferences
1. Resnick MD, Bearman PS, Blum RW, et al. Protecting adolescents from

harm: findings from the National Longitudinal Study on Adolescent
Health. JAMA 1997;278:823–32.

2. Sale E, Sambrano S, Springer JF, Turner CW. Risk, protection, and
substance use in adolescents: a multi-site model. J Drug Educ
2003;33:91–105.

3. Allen JP, Hauser ST, Eickholt C, et al. Autonomy and relatedness in family
interactions as predictors of expressions of negative adolescent affect. J Res
Adolesc 1994;4:535–52.

4. Aydin B, Oztutuncu F. Examination of adolescents’ negative thoughts,
depressive mood, and family environment. Adolescence 2001;26:77– 83.

5. Delaney ME. Across the transition to adolescence: 1ualities of parent/
adolescent relationships and adjustment. J Early Adolesc 1996;16:274 –300.

6. Ackard DM, Neumark-Sztainer D. Family mealtime while growing up:
associations with symptoms of bulimia nervosa. Eat Disord 2001;9:239 – 49.

7. Fergusson DM, Woodward LJ, Horwood LJ. Risk factors and life processes
associated with the onset of suicidal behaviour during adolescence and
early adulthood. Psychol Med 2000;30:23–39.

8. Hollis C. Depression, family environment, and adolescent suicidal behav-
ior. J Am Acad Child Adolesc Psychiatry 1996;35:622–30.

9. King RA, Schwab-Stone M, Flisher AJ, et al. Psychosocial and risk behavior
correlates of youth suicide attempts and suicidal ideation. J Am Acad Child
Adolesc Psychiatry 2001;40:837– 46.

0. O’Donnell L, Stueve A, Wardlaw D, O’Donnell C. Adolescent suicidality
and adult support: the Reach for Health study of urban youth. Am J Health
Behav 2003;27:633– 44.

1. Herman MR, Dornbusch SM, Herron MC, Herting JR. The influence of
family regulation, connection, and psychological autonomy on six mea-
sures of adolescent functioning. J Adolesc Res 1997;12:34 – 67.

2. Ackard DM, Neumark-Sztainer D. Health care information sources for
adolescents: age and gender differences on use, concerns, and needs. J
Adolesc Health 2001;29:170 – 6.

3. Neumark-Sztainer D, Story M, Ackard D, et al. The “family meal”: views of

adolescents. J Nutr Educ 2000;32:329 –34.

6 American Journal of Preventive Medicine, Volume 30, Num

4. Neumark-Sztainer D, Story M, Ackard D, et al. Family meals among
adolescents: findings from a pilot study. J Nutr Educ 2000;32:335– 40.

5. Neumark-Sztainer D, Story M, Perry C, Casey M. Factors influencing food
choices of adolescents: findings from focus-group discussions with adoles-
cents. J Am Diet Assoc 1999;99:929 –37.

6. Resnick M, Harris LJ, Blum RW. The impact of caring and connectedness
on adolescent health and well-being. J Paediatr Child Health 1993;29:1–9.

7. Neumark-Sztainer D, Wall MM, Story M, Perry CL. Correlates of unhealthy
weight-control behaviors among adolescents: Implications for prevention
programs. Health Psychol 2003;22:88 –98.

8. Minnesota Department of Children, Families and Learning. Minnesota
Student Survey. Roseville: Minnesota Department of Human Services,
2001.

9. Pingitore R. Gender differences in body satisfaction. Obes Res
1997;5:402–9.

0. Rosenberg M. Society and the adolescent self-image. Princeton NJ:
Princeton University Press, 1965.

1. Kandel DB, Davies M. Epidemiology of depressive mood in adolescents; an
empirical study. Arch Gen Psychiatry 1982;35:1205–12.

2. Breiman L, Friedman JH, Olshen RA, Stone CJ. Classification and regres-
sion trees. Belmont CA: Wadsworth International Group, 1984.

3. Barber BK, Olsen JA. Socialization in context: connection, regulation, and
autonomy in the family, school, and neighborhood, and with peers. J
Adolesc Res 1997;12:287–315.

4. Eisenberg ME, Olson RE, Neumark-Sztainer D, et al. Correlations between
family meals and psychosocial well-being among adolescents. Arch Pediatr
Adolesc Med 2004;158:792– 6.

5. Lieb R, Bronisch T, Hofler M, Schreier A, Wittchen HU. Maternal
suicidality and risk of suicidality in offspring: findings from a community
study. Am J Psychiatry 2005;162:1665–71.

6. Rohde P, Lewinsohn PM, Klein DN, Seeley JR. Association of parental
depression with psychiatric course from adolescence to young adulthood
among formerly depressed individuals. J Abnorm Psychol 2005;114:
409 –20.

7. Toumbourou JW, Gregg ME. Impact of an empowerment-based parent

education program on the reduction of youth suicide factors. J Adolesc
Health 2002;31:277– 85.
ber 1 www.ajpm-online.net

Parent–Child Connectedness and Behavioral and Emotional Health Among Adolescents

Introduction
Method
Study Population and Design
Measures
Parent–Child Connectedness
Opinions valued
Parent–child communication and caring
Behavioral Health
Weight-control behaviors
Substance use
Suicide attempts
Emotional Health
Body dissatisfaction
Self-esteem
Depressive mood
Demographics
Parent marital status
Race/ethnicity
Socioeconomic status
Statistical Analyses
Results
Description of Sample
Description of Parent–Child Connectedness
Parent–Child Connectedness and Behavioral Health Indicators
Parent–Child Connectedness and Emotional Health Indicators
Discussion
References

Journ

l of Child and Family Studies, Vol. 15, No. 3, June 2006 ( C© 2006), pp. 255–270
DOI: 10.1007/s10826-006-9020-

Family Factors Predicting Categories
of Suicide Risk

Brooke P. Randell, D.N.Sc., C.S.,1,4 Wen-Ling Wang, Ph.D., R.N.,2

Jerald R. Herting, Ph.D.,1 and Leona L. Eggert, Ph.D., R.N. FAAN

Published online: 12 May 2006

We compared family risk and protective factors among potential high schoo

dropouts with and without suicide-risk behaviors (SRB) and examined the extent
to which these factors predict categories of SRB. Subjects were randomly selected
from among potential dropouts in 14 high schools. Based upon suicide-risk status,
1,083 potential high school dropouts were defined as belonging to one of four
groups; 573 non-suicide risk, 242 low suicide risk, 137 moderate suicide risk
and 131 high suicide risk. Results showed significant group differences in all
youth self-reported family risk and protective factors. Increased levels of suicid

risk were associated with perceived conflict with parents, unmet family goals, and
family depression; decreased levels of risk were associated with perceived parental
involvement and family support for school. Perceived conflict with parents, family
depression, family support satisfaction, and availability of family support for
school were the strongest predictors of adolescent SRB. Our findings suggest that
suicide vulnerable youth differ from their non-suicidal peers along the dimensions
of family risk and protective factors.

KEY WORDS: suicide risk; family support; prevention; family risk factors; adolescence.

Suicide is a leading cause of death among youth aged 15–19 years (Anderson,
2002). In a nationwide survey of high school students, Grunbaum et al. (2004)
reported that 16.9% of students had seriously considered attempting suicide,

1Research Associate Professor, Department of Psychosocial and Community Health, University of
Washington, Seattle, WA.

2Assistant Professor, Department of Nursing, College of Medicine, National Cheng-Kung University,
Tainan, Taiwan.

3Professor Emeritus, Department of Psychosocial and Community Health, University of Washington,
Seattle, WA.

4Correspondence should be directed to Brooke P. Randell, University of Washington, Seattle, WA,
98195-8732; e-mail: bpran@u.washington.edu.

255

256 Randell, Wang, Herting and Eggert

16.5% had made a specific plan to attempt suicide, and 8.5% had attempted
suicide during the 12 months preceding the survey. These findings are consistent
with those reported for high school samples (Allison, Pearce, Martin, Miller,
& Long, 1995, 1992; Fergusson, Woodward, & Horwood, 2000; Wichstrøm,
2000).

The family is an important environmental context related to adolescent suicide
and suicidal behaviors (Johnson et al., 2002; Resnick, et al., 1997; Wagner, 1997).
Studies employing community samples have begun to explore factors contributing
to suicide-risk behaviors among high school students (Fergusson et al., 2000;
Johnson et al., 2002; Perkins & Hartless, 2002; Wichstrøm, 2000). These studies
examined a variety of risk and protective factors which, increasingly, include
family factors. However, our knowledge of critical family risk and protective
factors remains somewhat limited.

Family psychopathology and exposure to family suicide have been identified
in community samples as characteristics that increase a youth’s vulnerability
to suicide. Garber, Little, Hilsman, and Weaver (1998) found that adolescents
whose mothers had ever had a mood disorder diagnosis evidenced increased
risk for suicidal behaviors. Young people reporting suicidal behavior were more
likely to come from families characterized by a constellation of family risk
factors that include parental alcohol problems and illicit drug use (Fergusson
et al., 2000). Potential high school dropouts with suicide ideation reported
more problems related to parental alcohol and other drug (AOD) use when
compared to similar youth without suicidal ideation (Thompson, Moody, &
Eggert, 1994). Family suicidality is identified as a risk factor for adolescent
suicidal behavior (Rubenstein et al., 1989) and a predictor of adolescent suicide
risk (Resnick et al., 1997). However, in another sample of high school students,
exposure to a family member’s suicide-risk behavior was not significantly
associated with either past or future attempts (Lewinsohn, Rhode, & Seeley,
1994).

The terms family stress, family strain and family dysfunction seem to be
used similarly in studies of suicide-risk behaviors as a global indicator of family
problem behavior. Stressful relationships, with parents differentiated attempters
from both a depressed/ideator group and a comparison group (Wagner, Cole, &
Schwartzman, 1995). Suicide ideators were distinguished from their high-risk
peers as well as typical youth reporting higher levels on unmet family goals,
conflict with parents, unreasonable parental expectations, and thoughts of running
away from home (Thompson et al., 1994). In another study, family dysfunction
was found to make an independent contribution to adolescent depression, which
accounted for significant variance in suicide-risk behaviors (Martin, Rozanes,
Pearce, & Allison, 1995). Garber et al. (1998) reported that family functioning
mediated the relationship between maternal history of depression and adolescent
suicide symptoms measured over time.

Family Factors Predicting Suicide Risk 257

Family or parent-adolescent conflict is frequently associated with suicide-
risk behaviors; it is either considered as part of a broad indicator such as family
strain (Thompson et al., 1994) or family function (Garber et al., 1998), or ex-
amined as a separate construct (Lewinsohn et al., 1993). Suicidal behaviors were
said to increase steadily as numbers of unresolved conflicts with parents increased
(Toumbourou & Gregg, 2002). Allison et al. (1995) observed a higher rate of
reported maternal and paternal criticism when suicidal youth were compared to
their non-suicidal peers. Reports of suicidal behaviors increased when both par-
ents and adolescents reported parent-adolescent relationship difficulties (Breton,
Tousignant, Bergeron, & Berthiaume, 2002). Serious fights with family members
were significantly associated with increased risk for attempts in late adolescence
or early adulthood (Johnson et al., 2002). Yet it remains difficult to determine
the contribution of parent-adolescent conflict to adolescent suicide risk behavior
given the association of these conflicts with adolescent psychological problems
(Gould, Greenberg, Velting, & Shaffer, 2003).

A variety of scales have been used to measure family cohesion, family con-
nectedness and parental bonding. When parental care and protection were ex-
amined significant negative relationships were identified between low care/high
protection (affectionless control) and suicide-risk behavior (Allison et al., 1995).
An adolescent who described his/her family as highly cohesive was significantly
less likely to be suicidal than an adolescent who saw his/her family as non-cohesive
(Rubenstein et al., 1989). Conversely, the risk for suicide was increased among
young people reporting problematic family circumstances during childhood that
included less secure attachments to parents characterized by low levels of trust and
communication (Fergusson et al., 2000). Similarly, low levels of parental care and
over protection predicted both previous and subsequent attempts in a community
sample of over 12,000 Norwegian students (Wichstrøm, 2000).

Perceived family support was predictive of recent suicide attempts indepen-
dent of depression and attempters were differentiated from non-attempters on
family support in a native Hawaiian sample (Yuen et al., 1996). Low perceived
family support was associated with future attempts even after controlling for de-
pression (Lewinsohn et al., 1993; 1994). Dubow et al. (1989) reported non-ideators
were distinguishable from serious ideators on family support. When comparing
youth hospitalized for suicide attempts and a community sample composed of both
youth self-reporting attempts and “average” adolescents, hospitalized suicide at-
tempters sought support from parents significantly less often than youth in the
other groups; support from parents was found to protect from self-harm (Groholt
et al., 2000).

The purpose of our study was to compare the levels of perceived family risk
and protective factors among potential high school dropouts with and without
suicide-risk behaviors (SRB); and to examine the extent to which these family
factors predict categories of SRB.

258 Randell, Wang, Herting and Eggert

METHODS

Study Design and Sample

We used a two-stage, cross sectional survey design. Both survey and interview
data with youth were used to examine the relationships among perceived family
risk and protective factors relative to suicide-risk behaviors in a population of
potential high school dropouts. Participants included 1,083 potential high-school
dropouts in grades 9 to 12, from 14 high schools; 11 in the Pacific Northwest and
three in the Southwest.

Procedures

Case Identification and Invitation

A 2-step process was used to identify high-risk youth. First, a pool of poten-
tial high school dropouts was identified from each school district’s database using
indicators known to predict future dropout, including academic performance, at-
tendance, and prior dropout status (Eggert, Thompson, & Herting, 1994b). From
this population, youth were randomly sampled and personally invited to partic-
ipate in the study. IRB approved, informed assent was obtained from students
and informed consent was obtained from at least one parent/guardian. Students
completed a comprehensive survey, the High School Questionnaire: Profile of
Experiences (HSQ; Eggert, Herting, & Thompson, 1995), which tapped key study
variables and included the Screen for Suicide Risk (SRS) (Thompson & Eggert,
1999). Indicators included suicidal behaviors (thoughts, threats, and attempts),
depression, and drug involvement. Tests of the SRS case-finding model showed
it was reliable, and had concurrent and predictive validity (Eggert et al., 1994b;
Thompson & Eggert, 1999).

Comprehensive Assessment

Within a week of screening, all youth were assessed using a computer-assisted
interview, the Measure of Adolescent Potential for Suicide (MAPS) (Eggert et al.,
1994b). The content of the assessment taps three constructs of suicide potential:
direct suicide risk factors (suicide thoughts, planning/preparation, prior attempts,
threats and suicide exposure), related risk factors (stressors, depression, hopeless-
ness and anxiety), and protective factors (coping and social support resources). For
ethical reasons and as part of the MAPS assessment protocol, each youth, whether
at suicide risk or not, was personally introduced to a school “case manager” fol-
lowing the interview. In addition, each youth’s parent or guardian of choice was
contacted by telephone and advised of the youth’s suicide-risk status, strengths
and support needs.

Family Factors Predicting Suicide Risk 259

Subject Recruitment and Retention

The sample pool of potential high school dropouts represented 15–35% of
each school’s population. Of 1,494 youth randomly selected from the total pool,
83% or 1,240 accepted. Of those accepting, 91% or 1128 completed the HSQ and,
of these, 96% or 1,083 completed the MAPS interview.

Measurement

The Suicide Risk Screen (SRS)

The SRS, which is embedded in the High School Questionnaire (HSQ),
allows for incremental measurement of levels of suicide risk. These levels of risk
are defined by three sets of empirically-based criteria, including indicators of: (1)
suicidal behaviors (5 items tapping suicidal ideation, direct/indirect threats, prior
attempts; α = .88), (2) depression (5-item scale from the CES-D; α = .87); and
(3) drug involvement (a composite score of 10 items tapping AOD use, polydrug
use, drug use control problems; α = .90). Preliminary construct, discriminant and
predictive validity was established for the SRS with an independent sample;

confirmatory factor analysis resulted in a good-fitting three-dimensional SRS
measurement model (χ 2(22) = 26.85, AGFI = .96; n = 515) (Eggert, Herting, &
Nicholas, 1994a).

The suicide risk screen (SRS) criteria were used to categorize the level
of suicide risk among potential high school dropouts. Subjects were divided
into one non-suicide risk group and three suicide-risk groups (Low, Moderate
and High) based on the SRS criteria (Thompson & Eggert, 1999). Youth at
low risk evidenced any of the following behaviors: a) moderate suicide ideation
( ≥ 2), b) indirect/ direct threats of suicide ( ≥ 2), c) prior attempts ( ≥ 1), and/or
d) moderate depression (2–3.4). Youth at moderate risk evidenced two or more of
the behaviors listed above for low risk or may report drug involvement in addition
to one or more of the low risk criteria. Youth at high risk evidenced any of the
following: a) prior attempts ( ≥ 2), b) high suicide ideation ( ≥ 3), and/or high de-
pression ( ≥ 3.4). These levels of risk should not be seen as differentiating clinical
risk. That is, all youth, whether categorized as Low, Moderate or High, require
clinical assessment to determine their current need for support and/or referral.

Family Risk and Protective Factors

Measures of family risk and protective factors were taken from youth reports
on the HSQ and the MAPS. In combination, these instruments measure a broad
range of perceptions regarding risk and protective factors, including measures
of the family constructs of interest in this study. Table I provides a summary

260 Randell, Wang, Herting and Eggert

description of the key measures. Unless otherwise indicated, items were measured
using a seven-point, Likert-type scale, ranging from 0 (never) to 6 (always/many
times). The higher the scale value, the greater the level of the measured construct.
Cronbach’s alpha values reflecting internal consistency reliability for the current
sample were moderate to high, ranging from .61 to .89.

Analysis

Data analyses were conducted using the Statistical Package for the Social
Sciences for Windows, Release 8.0 (SPSS, 1998) and LIMDEP 7.0 (Greene,
1995). Graphic representations and appropriate descriptive statistics (including
kurtosis, skewness) were used to examine distributional properties of variables.
Due to non-normal distribution (extreme skews) three variables – family violence,
family AOD use, and family suicide exposure – were re-coded as dichotomous
variables (1 = presence, 0 = absence). Results were based on analysis of variance
(ANOVA) for group comparisons, Scheffé post-hoc tests for multiple comparisons,
Chi-square tests for nominal variables, and ordered logistic regression for tests of
the extent to which family factors predict suicide risk among potential high school
dropouts.

RESULTS

Sample and Subject Characteristics

Students participating in the study ranged in age from 14–19 years (M = 16
years); 53% were male. The ethnic composition was 59% minority (22% His-
panic/Latino, 18% African American, 12% Asian/Pacific Islander, 5% American
Indian/Alaska Native, 2% mixed ethnic background). Only 39% of the subjects
lived in a family unit where both natural parents were present; 34% lived in a
single parent family, and 16% lived with one natural and one stepparent. The
remainder of the youth (11%) lived with grandparents, other relatives, or alone.
Baseline differences on gender, age, grade, ethnic background, and family com-
position among the four suicide-risk groups (high, moderate, low and non-risk)
were examined. ANOVA and Chi-square tests detected no significant differences
at baseline on age, grade, ethnic background, and family composition.

Gender was the only significant difference among the four groups (χ 2 =
20.70; df = 3; N = 1083; p < .00). Specifically, there were more females (N = 275) than males (N = 235) in the suicide-risk group. Conversely, there were more males (N = 336) then females (N = 237) in the group identified as non-suicide risk. Fe- males at suicide-risk had significantly higher levels of suicidal behaviors, including prior suicide attempts, suicide ideation, and direct/indirect suicide threats, when compared to males at suicide-risk (M = 0.97 vs. 0.72, t = 2.67, p < .01). Females reported significantly more depression than males. This was true for all three

Family Factors Predicting Suicide Risk 26

T
ab

le
I.

D
es

cr
ip

ti
on

of
S

ca
le

C
on

te
nt

an
d

In
te

rn
al

C
on

si
st

en
cy

fo
r

F
am

il
y

R
is

k
&

P
ro

te
ct

iv
e

F
ac

o
rs

D
es
cr
ip
to
rs

D
im

en
si

on
\s

ca
le

It
em

#
α

N
=

10
83

(a
ll

)
α

N
=

57
1

(m
al

es
)

α
N

=
51

2
(f

em
al

es
)

F
a

m
il

y
R

is
k

F
a

ct
o
rs

C
on

fl
ic

t
w

it
h

pa
re

nt
C

on
fl

ic
t/

te
ns

io
n

w
it

h
pa

re
nt

s,
th

ou
gh

ts
ab

ou
t

ru
nn

in
g

w
ay

,u
nr

ea
so

na
bl

e
ex

pe
ct

at
io

ns
,e

xp
la

in
ru

le
s,

an
d

t
re

ss
ed

by
co

nfl
ic

s
at

ho
m

6
.7

4
.6

U
nm

et
fa

m
il

y
go

al
s

N
ot

ha
vi

ng
:

fa
ir

ru
le

s
at
ho
m

e,
a

fa
m

il
y

th
at

do
es

lo
ts

of
th

in
gs

to
ge

th
er

an
d
pa
re

nt
s

w
ho

th
e

te
en

a
n

ta
lk

to
ab

ou
t

an
yt

hi
ng

an
d
w
ho

kn
ow

th
at
th
e
te
en
ca
n

do
th

in
gs

w
el

4
.8

2
.8

6
F
am
il
y

vi
ol

en
ce

V
ic

ti
m

of
or

w
it

ne
ss

to
fa

m
il

y
m

em
be

r’
s

vi
ol
en
ce

3
.6

7
.6

1
.7

1
F
am
il
y

de
pr

es
si

on
F

am
il

y
m
em
be

r
de

pr
es

se
d

3
.7

1
.6

4
.7

6
F

am
il

y
su

ic
id

e
ex

po
su

re
S

ui
ci

de
at

te
m

pt
/c

om
pl

et
io

n
by

a
fa

m
il
y
m
em
be

r
2

n
a

n
a
n
a
F
am
il
y

A
O

D
U

se
U

se
of

al
co

ho
l

an
d

ot
he

r
dr

ug
s

by
pa

re
nt

s
or

si
bl

in
gs

,e
xp

er
ie

nc
ed

st
re

ss
re

la
te

d
to

fa
m
il
y

m
em

be
r

us
e

an
d/

or
tr

ea
tm

en
t

fo
r

us
e/

ab
us

e
4
.6

1
.5

7
.6
3
F
am
il
y
st
re

ss
or

s
S

um
of

al
l

ne
ga

ti
ve

fa
m
il
y

li
fe

ev
en

s
th

e
ad

ol
es

ce
nt

ev
er

ex
pe

ri
en

ce
d

9
n

a
n
a
n
a
F
a
m
il

y
P

ro
te

ct
iv

e
F

a
ct

o
rs

P
ar

en
t

in
vo

lv
em

en
t

K
no

w
in

g
an

d
ap

pr
ov

in
g
te
en

’s
fr

ie
nd

s,
kn

ow
in

g
w

he
re

to
fi

nd
te

en
,

pa
rt

ic
ip

at
in

g
in

sc
ho

ol
ev

en
ts

an
d

fr
ie

nd
s

sp
en

d
ti

m
e

w
it

h
te

en
at

ho
m
e

5
.7

3
.7

0
.7

6
F
am
il
y

su
pp

or
t

sa
ti

sf
ac

ti
on

S
at

is
fa

ct
io

n
w

it
h
th
e
w
ay
fa
m

il
y:

ta
lk
s
th
in
gs

ov
er

an
d

sh
ar

es
pr

ob
le

m
s,

sp
en

ds
ti

m
e
to
ge
th
er
,e
xp

re
ss

es
af

fe
ct

io
n,

ac
ce

pt
s/

su
pp

or
ts

m
y

ac
ti

vi
ti

es
,

an
d

is
av

ai
la

bl
e

to
he

5
.8

9
.8

7
.9

A
m

ou
nt

of
fa

m
il
y
su

pp
or

t
fo

r
sc

ho
ol

T
he

to
ta

l
su

pp
or
t
re

ce
iv

ed
fr

om
fa

th
er

,
m

ot
he

r,
&

si
bl
in
gs
fo
r
sc
ho

ol
4

n
a
n
a
n
a

S
up

po
rt

av
ai

la
bi

li
ty

fo
r
de
pr

es
se

d
fe

el
in

gs
&

S
I

T
he
su
pp
or
t
av
ai
la
bi
li
ty
of
fa
th
er

,m
ot

he
r,

&
si

bl
in

gs
fo

r
he

lp
w

it
h
de
pr
es
si

on
or

su
ic

id
e

th
ou

gh
ts

4
n

a
n
a
n
a

262 Randell, Wang, Herting and Eggert

Table II. Mean and Standard Deviation of Family Factors among Four Groups

Family factors
Non-risk
(N = 573)

Low-risk
(N = 131)

Mod-risk
(N = 137)

High-risk
(N = 242)

Significant
difference
by group∗

Risk Factors
Conflict with parent 1.53 (1.02) 1.99 (1.22) 2.41 (1.24) 2.69 (1.35) a, b, c, d, e
Unmet family goals 1.96 (1.41) 2.57 (1.44) 3.07 (1.47) 3.23 (1.60) a, b, c, d, e
Family violence 0.92 (1.09) 0.91 (1.25) 1.48 (1.44) 1.39 (1.44) b, c, d, e
Family depression 0.87 (1.03) 1.56 (1.46) 1.65 (1.48) 1.68 (1.54) a, b, c
Family suicide exposure 0.32(.73) 0.31(.69) 0.45(.85) 0.54(.88) c, e
Family AOD use 0.63 (0.88) 0.62 (0.88) 1.08 (1.19) 1.11 (1.21) b, c, d, e
Total family stressors 4.06 (1.97) 4.53 (2.20) 4.86 (2.09) 4.70 (1.92) b, c
Protective Factors
Parent involvement 3.55 (1.28) 3.40 (1.22) 3.01 (1.22) 2.89 (1.32) b, c, e
Family support satisfaction 3.73 (1.62) 3.00 (1.54) 2.50 (1.53) 2.13 (1.53) a, b, c, e
Amount of family support 5.74 (3.49) 5.19 (3.47) 4.28 (4.27) 2.55 (4.38) b, c, e, f
Support availability for

depressed feelings, and SI
4.31 (1.25) 3.67 (1.36) 3.85 (1.47) 3.29 (1.53) a, b, c, f

Note. a = Lo vs. Non; b = Mod vs. Non; c = Hi vs. Non; d = Lo vs. Mod; e = Lo vs. Hi; f = Mod vs.
Hi.

suicide-risk groups (High to Low) (M = 2.93 vs. 2.56, t = 3.30, p < .01) as well as the non-suicide risk group (M = 0.98 vs. 0.81, t = 3.50, p < .01).

While there were no significant differences among the groups on drug
involvement, males in the suicide risk group reported greater alcohol and poly
drug use than females. In the non-suicide risk group there was no difference
between males and females on either use or control problems.

Comparisons of Risk and Protective Factors across Suicide-Risk Groups

The mean score and standard deviation for all youth reported family factors
among the four suicide-risk groups are presented in Table II. ANOVAs were used
for testing gender (2) by group (4) differences. Results from ANOVAs revealed
significant group differences in all family risk and protective factors. Scheffé post-
hoc tests with multiple comparisons were used to test for differences between
the four groups. Despite the gender differences observed relative to suicide-risk
behaviors, only one gender difference was observed when within group differences
were examined. Females reported greater suicide exposure F (1, 1073) = 17.4
(p < .001).

Risk Factors by Suicide Risk Status

Perceived conflict with parents and unmet family goals revealed a signifi-
cant step down pattern among groups (i.e., the higher the level of suicide risk
demonstrated, the higher the level of conflict with parents and unmet family goals
experienced). Perceptions of family depression also differentiated the suicide-risk

Family Factors Predicting Suicide Risk 263

groups from the non-risk group. The three suicide-risk groups were significantly
higher on perceived family depression than the non-suicide risk group. Family vi-
olence, family AOD use, and number of family stressors were associated with the
highest levels of suicide risk. The two groups at highest suicide risk experienced
significantly higher levels of perceived family violence and AOD use compared to
the group at lowest suicide risk and the non-risk group. Similarly, the two groups
at highest suicide risk had a significantly higher number of stressors than the
non-risk group. Finally, on suicide exposure, the group at highest suicide risk was
significantly different from both the low and non-risk group.

Protective Factors by Suicide Risk Status

While the groups at moderate and low suicide risk reported no statistically
significant differences in any of the family protective factors, an interesting pattern
among the groups was observed. Perceived family support satisfaction and support
availability for depression and suicidal thoughts differentiated all youth at suicide
risk from their non-risk peers. Likewise, youth in the two groups at highest suicide
risk were differentiated from the non-suicide risk group on perceived parental
involvement and the amount of family support for school.

Family Factors Predicting Suicide Risk

Ordered logistic regression in LIMDEP was used to assess the relationship
between perceived family risk and protective factors and suicide risk status. The
analysis allows for the determination of the independent effects of the specific fam-
ily factors of interest in the presence of the effects of other variables; included in
the regression were controls for the effects of demographic variables (age, gender,
ethnic background, and family composition). The analysis included initial multi-
nomial logistic regression and cumulative logistic regressions to examine whether
the parallel regression assumption of the ordered regression was reasonable, and
whether any of the categories of suicide risk could be collapsed. The results clearly
indicated the 4 categories of suicide risk could not be collapsed. The analysis of
the parallel regression assumption indicated few substantial departures. The only
substantial effects not evident in the ordered logistic regression was the significant
effect of perceived family violence and unmet family goals, which both increased
the odds of being in the medium category of suicide risk vs. no risk. In addition,
the ordered logistic regression suggests a constant effect of total family support
and gender which, in the multinominal logistic regression, the effects appear to be
significant for only the highest level of suicide risk. Therefore, we elect to present
the ordered regressions for the sake of simplicity.

The ordered logistic regression revealed that perceived conflict with parents,
family depression, family AOD use, family support satisfaction, family support

264 Randell, Wang, Herting and Eggert

Table III. Results of Ordered Logistic Regression of Suicide Risk (4 categories) on Family Risk
and Protective Factors

Coefficient Significant Lower bound Upper bound

Age .112 0.044 .002 .221
Gender (M = 1, F = 0) − .447 0.001 − .703 − .190
Female = referent
Ethnicity:
Native-Am .505 0.093 − .084 1.095
Asian-Am .171 0.431 − .254 .595
African-Am − .065 0.733 − .437 .307
Latino .094 0.579 − .238 .427
White = referent
Family status:
Single − .158 0.313 − .465 .149
Step .261 0.171 − .112 .635
Other − .144 0.523 − .584 .297
Intact = referent
Family factors:
Conflict with parent .243 0.000 .117 .369
Unmet family goals .055 0.204 − .054 .166
Family violence (1 = present) − .033 0.408 − .264 .199
Family depression .240 0.000 .155 .326
Exposure suicide .173 0.132 − .081 .425
Family ATOD use 1 = present) .243 0.044 .010 .476
Family stressors − .027 0.230 − .086 .033
Family support satisfaction − .199 0.001 − .306 − .091
Parental involvement .003 0.481 − .097 .103
Family support for school − .046 0.011 − .079 − .013
Support availability (for depress. & SI) − .122 0.011 − .210 − .034
Psuedo R2 = 0.115
Note. Upper and Lower bound is based on 90% confidence interval for family factors; significance
for all family factors is based on 1-tail test at .05.

for school, and support availability for feelings of depression and suicidal thoughts
were the significant family predictors of adolescent suicide-risk behaviors after
controlling for age, gender, ethnicity, and family composition (see Table III).
That is, the higher the level of perceived family conflict, family depression, and
family AOD use, the greater the level of suicide-risk behavior. Correspondingly,
the higher the perceived amount of support for school, support availability for
feelings of depression and suicidal thoughts, and general support satisfaction, the
lower the level of risk for suicide. Age and gender were also significantly related
in the regression; risk increased with age and being female.

To test for interaction effects, we added all two-way interactions of gender
with the eleven family variables, and compared the fit of this model to the model
without these interactions. The results suggested there were no strong interactions
present (χ 2 diff = 18, df = 11, p = ns). Only the perception of family support
satisfaction appeared to differ by gender (β = − 0.23. p ≤ .059), having a slightly
greater effect in reducing suicide risk among females.

Family Factors Predicting Suicide Risk 265

DISCUSSION

Within a multi-ethnic, community sample of potential high school dropouts,
47% of the participating youth were identified as at risk for suicide. As is
commonly observed (Garrison, Jackson, Addy, McKeown, & Waller, 1991;
Wichstrøm & Rossow, 2002), more females than males reported higher levels
of suicide-risk behaviors (e.g., prior attempts, suicide ideation) and depression.
Despite gender differences in suicide-risk behaviors, when comparing across
groups on self-reported family variables, the risk groups did not differ by gender;
the exposure to an attempt or suicide by a family member was the only exception.
Based on their own report, youth in the suicide risk groups were differentiated
from their non-suicide risk peers on perceptions of conflict with parents, unmet
family goals, family depression, support satisfaction, and support availability
for feelings of depression and suicide ideation. Youth at higher risk of suicide
(high and moderate groups) reported higher levels of perceived family violence,
family alcohol and other drug (AOD) use, and number of family stressors.
Perceived family conflict, family depression and family AOD use were predictive
of suicide-risk status; higher levels of risk were associated with higher perceived
levels of these three risk factors. Lower levels of suicide risk were predicted by
higher levels of general satisfaction with support, higher levels of support for
school, and support when feeling depressed and/or thinking about suicide.

Findings from our study confirm the significance of self-reported family char-
acteristics relative to youth suicide-risk status reported in previous studies (Garber
et al., 1998; Rubenstein et al., 1989). Perceived family depression, violence and
AOD use differentiated youth at risk for suicide from their non-suicide risk peers
in this sample of potential high school dropouts. Youth in the highest risk groups
(high and moderate) reported experiencing significantly higher levels of family vi-
olence and AOD use. All three suicide-risk groups reported perceptions of higher
levels of family depression than the non-risk group. Perceptions of family violence
did not predict suicide-risk status; however, the higher the levels of perceived fam-
ily AOD use and family depression, the higher the risk of suicide. These findings
support the need for selective, preventive interventions for youth from households
where they are exposed to family member depression and/or AOD use.

Family stress—variously defined as family dysfunction, family conflict
and parent-adolescent conflict—has been associated either directly or indirectly
with adolescent suicide-risk behavior. In this study, both perceptions of parent-
adolescent conflict and unmet family goals differentiated among various levels
of suicide risk. In addition, the number of family-related stressors a youth re-
ported experiencing differentiated youth at risk for suicide from those youth in
the non-risk group. Only youth perception of parent-adolescent conflict predicted
suicide risk; higher perceived levels of parent-adolescent conflict predicted higher
levels of suicide risk. Again, these findings were consistent with the literature on

266 Randell, Wang, Herting and Eggert

parent-adolescent conflict (Allison et al., 1995; Breton, et al., 2002; Kienhorst, de
Wilde, Diekstra, & Wolters, 1995; Toumbourou & Grett, 2002). Beyond conflict,
it is apparent that youth perceptions of family failures to meet traditional goals
such as having fair rules, open communication, doing things together, and valuing
the teen’s capabilities are associated with increasing suicide risk. Additionally,
teens reporting greater numbers of stressors, including perceived family conflict,
problematic parental behaviors, family member illness, job losses, and deaths,
comprise a group at greater suicide risk. Taken together, these findings speak
to the need to involve parents in suicide prevention programming. Specifically,
it seems critically important to focus on increasing communication competence
among family members and to enhance the provision of support teens experience
for increasing coping strategies and stress management techniques.

While support from parents is commonly associated with decreased risk
for suicide (Dubow et al., 1989; Lewinsohn et al., 1994; Perkins & Hartless,
2002; Yuen et al., 1996), explicit aspects of this support have not been previously
explored. In this sample of potential high school dropouts, teens perceptions of
support for school, having someone available to help with feelings of depression
and thoughts of suicide, as well as perceived parental involvement (i.e., knowing
and approving of teen’s friends, participating in school events) differentiated those
youth at highest risk (high and moderate risk groups) from the non-risk group.
Furthermore, youth reported feelings of specific support for school, availability
of family members to talk about depression and suicidal ideation, and support
satisfaction (i.e., satisfaction with time spent together, expression of affection,
and availability of help) predicted lower suicide-risk status. These findings
are consistent with studies that link adolescent psychological adjustment with
family support (Eccles, Early, Frasier, Belansky, & McCarthy, 1997; McFarlane,
Bellissimo, & Norman, 1995). Among potential high school dropouts, increasing
connections to school through parental collaboration with available school-based
support resources may be an important first step. Unique to this population is
helping parents communicate in ways their teens find supportive around feelings
of depression and thoughts about suicide. Parents frequently report being unaware
of their teen’s suicide risk (Breton et al., 2002; Garrison et al., 1991); thus,
programs need to focus on identifying the warning signs, available sources of help,
and provide opportunities to practice support strategies and asking about suicide.

Our study has several strengths and limitations that warrant discussion. Im-
portantly, we employed a large, ethnically diverse sample selected at random from
among potential high school dropouts. Suicide-risk status was identified using a
comprehensive, reliable and valid measure. The sample, albeit large and represen-
tative of this pool of high-risk youth, does not allow generalization to all youth.
Given that the sample included both those youth at risk for suicide and those not at
risk, there is increased confidence in the generalizability of study findings to this
high-risk population. In addition, the study included a comprehensive measure of

Family Factors Predicting Suicide Risk 267

multiple family constructs providing a detailed picture of the youths’ perception
of family characteristics, family stress and family support resources. Data reported
here were all self-report (questionnaire and interview) from participating teens,
not actual observation of family behavior, and while this represents a limitation,
individual participants remain the best source of information on internal states
such as depression and suicide thoughts as well as perceptions of their personal
experience. Neither the cross-sectional study design nor the statistical analysis em-
ployed provide sufficient evidence of causal relationships between predictors and
adolescent suicidal behaviors; thus, these findings must be interpreted as evidence
of associations present in the data and not explicitly as causal. Despite these limi-
tations, the study results provide important insights into the role of family risk and
protective factors relative to suicide risk among high-risk youth, laying the ground
work for future research and suggesting directions for prevention programming.

We believe the results have implications for designing interventions to ad-
dress suicide risk among high-risk adolescents. There are several implications that
can be drawn from this study. First, replication of this study using a longitudinal
design would allow for a more complete examination of the effects family char-
acteristics, family stress and family support on adolescent suicide-risk behaviors.
Additional replication studies with typical high school students and other high-
risk groups can potentially enhance the generalizability of these findings. Second,
research to test family-based prevention trials, using experimental designs, is in
its infancy. While the current findings are to be interpreted with care, they have
potential value for informing prevention efforts aimed at reducing adolescent
suicide and suicidal behaviors. Findings herein indicated that youth perceptions
of family characteristics, namely family depression and family AOD use, predict
suicide-risk behaviors in this population. Furthermore, perceived conflict with
parents predicts risk, while perceived support for school, support availability for
feelings of depression and suicidal thoughts, and general support satisfaction pre-
dict lower levels of risk for suicide. These findings suggest the importance of
designing and testing indicated prevention programs that target both youth and
parents. While it has been demonstrated that potential high school dropouts who
are at risk for suicide benefit from brief, school-based, indicated suicide pre-
ventive interventions we found no studies reporting on outcomes of programs
for parents and youth at risk for suicidal behaviors (Randell, Eggert, & Pike,
2001; Thompson, Eggert, Randell, & Pike, 2001). These findings, coupled with
those from previous studies (Garber et al., 1998; Martin et al., 1995; Wagner
et al., 1995), have implications for designing and testing preventive interventions:
(1) youth from households where family members experience depression, youth
witness or experience violence, are exposed to family substance use, and/or re-
port distress related to these family behaviors represent high-risk groups that
would likely benefit from selective preventive efforts; (2) programs designed to
decrease depression among family members and to decrease the occurrence of

268 Randell, Wang, Herting and Eggert

family violence and AOD use should also serve to decrease suicide-risk among
these high-risk youth; and (3) indicated prevention programs that include skills
training activities that assist both youth and parents to: (a) increase communication
and problem-solving skills, (b) establish fair rules, (c) increase the positive time
family members spend together, and (d) enhance the availability of support for
school and accessing help for feelings of depression and suicide ideation, warrant
efficacy testing.

ACKNOWLEGMENTS

This research was supported by grants R01 NR 03548 and R01 NR 03550
from the National Institute on Nursing Research (L. L. Eggert, principal inves-
tigator). We are indebted to the high school personnel and the young people
whose participation enhanced our understanding of factors contributing to and
protecting against suicide risk behaviors and to the dedicated efforts of the clini-
cal and research staff that comprise the Reconnecting Youth Prevention Research
team.

REFERENCES

Allison, S., Pearce, C., Martin, G., Miller, K., & Long, R. (1995). Parental influence, pessimism and
adolescent suicidality. Archives of Suicide Research, 1, 229–242.

Anderson, R. N. (2002). Deaths: Leading causes for 2000. National Vital Statistics Reports, 50(16).
Hyattsville, MD: National Center for Health Statistics.

Breton, J. J., Tousignant, M., Bergeron, L., & Berthiaume, C. (2002). Informant-specific correlates of
suicidal behavior in a community survey of 12- to 14-year olds. Journal of the American Academy
of Child & Adolescent Psychiatry, 41, 723–730.

Dubow, E. F., Kausch, D. F., Blum, M. C., Reed, J., & Bush, E. (1989). Correlates of suicidal ideation
and attempts in a community sample of junior high and high school students. Journal of Clinical
Child Psychology, 18, 158–66.

Eccles, J., Early, D., Fraiser, K., Belansky, E., & McCarthy, K. (1997). The relation of connection,
regulation, and support for autonomy to adolescents’ functioning. Journal of Adolescent Research,
12, 263–286.

Eggert, L. L., Herting, J. R., & Nicholas, L. J. (1994a). Prevention research program: Reconnecting
at-risk youth. Issues in Mental Health Nursing, 15, 107–135.

Eggert, L. L., Herting, J. R., & Thompson, E. A. (1995). High School Questionnaire: Profile of
experiences, University of Washington, Seattle, WA.

Eggert, L. L., Thompson, E. A., & Herting, J. R. (1994b). A measure of adolescent potential for
suicide (MAPS): Development and preliminary findings. Suicide & Life Threatening Behavior,
24, 359–381.

Fergusson, D. M., Woodward, L. J., & Horwood, L .J. (2000). Risk factors and life processes associated
with the onset of suicidal behaviour during adolescence and early adulthood. Psychological
Medicine, 30, 23–39.

Garber, J., Little, S., Hilsman, R., & Weaver, K. R. (1998). Family predictors of suicidal symptoms in
young adolescents. Journal of Adolescence, 21, 445–457.

Garrison, C. Z., Jackson, K. L., Addy, C. L., McKeown, R. E., & Waller, J. L. (1991). Suicidal behaviors
in young adolescents. American Journal of Epidemiology, 133, 1005–1014.

Family Factors Predicting Suicide Risk 269

Gould, M. S., Greenberg, T., Velting, D. M., & Shaffer, D. (2003). Youth suicide risk and preventive
interventions: A review of the past 10 years. Journal of the American Academy of Child and
Adolescent Psychiatry, 42, 386–405.

Greene, W. H. (1995). LIMDEP User’s Manual (Version 7). Bellport, NY: Econometric Software.
Grohølt, B., Ekeberg, Ø., Wichstrøm, L., & Haldorsen, T. (2000). Young suicide attempters: A com-

parison between a clinical and an epidemiological sample. Journal of the American Academy of
child and Adolescent Psychiatry, 39, 868–875.

Grunbaum, J. A., Kann, L., Kinchen, S., Ross, J., Hawkins, J., Lowry, R., Harris, W. A., McManus,
T., Chyen, D., & Collins, J. (2004). Youth Risk Behavior Surveillance – United States, 2003
(Abridqed). Jaurnal of School Health, 74, 307–324.

Johnson, J. G., Cohen, P., Gould, M. S., Kasen, S., Brown, J., & Brook, J. S. (2002). Childhood
adversities, interpersonal difficulties, and risk for suicide attempts during late adolescence and
early adulthood. Archives of General Psychiatry, 59, 741–749.

Kienhorst, C. W. M., de Wilde, E. J., Diekstra, F. W., & Wolters, W. (1995). Adolescents’ image of
their suicide attempt. Journal of the American Academy of Child and Adolescent Psychiatry, 34,
623–628.

Lewinsohn, P. M., Rohde, P., & Seeley, R. (1993). Psychosocial characteristics of adolescents with a
history of suicide attempt. Journal of the American Academy of Child and Adolescent Psychiatry,
32, 60–68.

Lewinsohn, P. M., Rohde, P., & Seeley, R. (1994). Psychosocial risk factors for future adolescent
suicide attempts. Journal of Consult & Clinical Psychology, 62, 297–305.

Martin, G., Rozanes, P., Pearce, C., & Allison, S. (1995). Adolescent suicide, depression and family
dysfunction. Acta Psychiatrica Scandinavica, 92, 336–344.

McFarlane, A. H., Bellissimo, A., & Norman, G. R. (1995). The role of family and peers in social
self-efficacy: Links to depression in adolescence. American Journal of Orthopsychiatry, 65,
402–410.

Perkins, D. F., & Hartless, G. (2002). An ecological risk-factor examination of suicide ideation and
behavior of adolescents. Journal of Adolescent Research, 17, 3–26.

Randell, B. P., Eggert, L. L., & Pike, K. C. (2001). Immediate post intervention effects of two brief
youth suicide prevention interventions. Suicide and Life-Threatening Behavior, 31, 41–61.

Resnick, M. D., Bearman, P. S., Blum, R. W., Bauman, K. E., Harris, K. M., Jones, J., et al. (1997).
Protecting adolescents from harm: Findings from the national longitudinal study on adolescent
health. Journal of the American Medical Association, 278, 823–865.

Rubenstein, J. L., Heeren, T., Housman, D., Rubin, C., & Stechler, G. (1989). Suicidal behavior in
“normal” adolescents: Risk and protective factors. American Journal of Orthopsychiatry, 59,
59–71.

SPSS. (1998). SPSS for Windows Release 8.0. Chicago, IL: Author.
Thompson, E. A., & Eggert, L. L. (1999). Using the Suicide Risk Screen to identify suicidal adolescents

among potential high school dropouts. Journal of the American Academy of Child & Adolescent
Psychiatry, 38, 1506–1514.

Thompson, E. A., Eggert, L. L., & Herting, J. R. (2000). Mediating effects of an indicated prevention
program for reducing youth depression and suicide risk behaviors. Suicide and Life-Threatening
Behavior, 30, 252–271

Thompson, E. A., Eggert, L. L., Randell, B. P., & Pike, K. C. (2001). Evaluation of indicated suicide-
risk prevention approaches for potential high school dropouts. American Journal of Public Health,
91, 742–752.

Thompson, E. A., Moody, K. A., & Eggert, L. L. (1994). Discriminating suicide ideation among
high-risk youth. Journal of School Health, 64, 361–367.

Toumbourou, J. W., & Gregg, M. E. (2002). Impact of an empowerment-based parent education
program on the reduction of youth suicide risk factors. Journal of Adolescent Health, 31, 277–
285.

Wagner, B. M. (1997). Family risk factors for child and adolescent suicidal behavior. Psychological
Bulletin, 121, 246–298.

Wagner, B. M., Cole, R. E., & Schwartzman, P. (1995). Psychosocial correlates of suicide attempts
among junior and senior high school youth. Suicide and Life-Threatening Behavior ,25, 358–
372.

270 Randell, Wang, Herting and Eggert

Wichstrøm, L. (2000). Predictors of adolescent suicide attempts: A nationally representative longitu-
dinal study of Norwegian adolescents. Journal of the American Academy of Child & Adolescent
Psychiatry, 39, 603–610.

Wichstrøm, L., & Rossow, I. (2002). Explaining the gender difference in self-reported suicide attempts:
A nationally representative study of Norwegian adolescents. Suicide and Life-Threatening Be-
havior, 32, 101–116.

Yuen, N., Andrade, N., Nahulu, L., Makini, G., McDermott, J. F., Danko, G., et al. (1996). The rate
and characteristics of suicide attempters in the native Hawaiian adolescent population. Suicide
and Life-Threatening Behavior, 26, 27–36.

SOC SCI 172AW
American Culture

Winter 2021
Short Literature Review

First Draft Due: Friday Februar 26th by 11:59PM on Canvas

Final Revision Due: Sunday March 14th by 11:59PM on Canvas

For the third and final assignment, students are individually responsible for writing a short literature
review on the topic of Youth Suicide. This review must be a minimum of 1,500 words, including a title
page, abstract, and reference page. APA formatted is required! This assignment is worth 35% of your
final grade.

Later in the quarter, each student will pick from one of six sub-topics. After the sub-topic has been
assigned, each student will write a literature review using three articles (all on the same sub-topic)
posted on the course website. You may not use any other articles or sources. The sub-topics are as
follows:

• LGBT Youth and Suicide
• Minority Youth and Suicide
• Family Factors and Youth Suicide
• Bullying and Youth Suicide
• Youth Offenders/Homeless Youth and Suicide
• Prevention of Youth Suicide

For this literature review, it is important for students to show their knowledge about the research topic.
This literature review is different from an annotated bibliography, which is a listing of articles with
descriptions. A critical review is not a string of summaries, it is a synthesized review. In other words,
students do not simply write a short review of each research study, but tie the research studies together
into a “story” or “conversation.”.

This process requires some insight and interpretation, not evaluation. Keep in mind that personal
opinions are not included in a literature review.

Report what is relevant to your study and ignore what is not. This means you need to read the abstract,
the introduction and conclusion of your articles. And, for long articles, focus on the parts that relate to
your topic.

**At the end of the literature review, you will also need to write a two-paragraph summary of what
you have learned about the topic from the three articles. This includes critique and reflection about
the “story,” not the individual articles.**

Avoid long quotes in your review, and paraphrase whenever possible.
Maximum quotes = 2 short quotes (less than 40 words each).

Do not quote/cite secondary sources in the readings

Correct APA formatting is also required – double-spaced, 12 pt Times New Roman font, 1 inch margins

all around, APA in-text citations and a reference page. Run spelling and grammar checks and double-

check your APA formatting. Be sure to CITE your sources throughout the review.

Grading Rubric

Short Literature Reviews will be graded according to the following criteria:

1. Content and Development (Total points: 60)

a. Paper adequately synthesizes the key ideas and conclusions from the three articles and puts them in

conversation with one another: 60 Points

2. Mechanics and Style (Total points: 40)

a. APA rules of spelling, grammar, usage, and punctuation are followed: 30 Points

b. Sentences are complete, clear, and concise, and the tone is appropriate to the content and

assignment: 10 Points

100 points total

Contents lists available at ScienceDirect

Addictive Behaviors

journal homepage: www.elsevier.com/locate/addictbeh

Substance use and suicidal ideation among child welfare involved
adolescents: A longitudinal examination

Christina M. Sellersa,b,⁎, Ruth G. McRoyb, Kimberly H. McManama O’Briena,c,d

a Department of Psychiatry, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, USA
b Boston College, School of Social Work, 1

Commonwealth Avenue, Chestnut Hill, MA 02467, USA
c Department of Psychiatry, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA
d Department of Innovation in Practice and

echnology, Education Development Center,

Foundry Ave, Waltham, MA 02

3, USA

H I G H L I G H T S

• For child welfare involved youth, individual, family and peer factors predict alcohol and marijuana use, and suicide ideation
• For child welfare involved youth, there is evidence of a reciprocal relationship between alcohol use and suicide ideation
• Interventions for child welfare involved youth should focus on the relationship between alcohol use and suicide ideation

A R T I C L E I N F O

Keywords:
Alcohol
Marijuana
Suicidal ideation
Child-welfare involved adolescents

A B S T R A C T

Background: The purpose of this study was to investigate the longitudinal predictors of alcohol use, marijuana
use, and suicidal ideation among maltreated adolescents.
Methods: Longitudinal data from this study come from three waves of the National Survey of Child and
Adolescent Wellbeing II (NSCAW II). Participants included 1050 adolescents (Mage = 14.13) who were subjects
of child abuse or neglect investigations. Items from the Health Risk Behavior Questionnaire were used to
measure alcohol and marijuana use. Suicidal ideation was measured using an item from the Childhood
Depression Inventory. Data on deviant peer affiliation, caregiver health, maltreatment type, age, race, and
gender were also collected.
Results: Marijuana use, suicidal ideation, caregiver drug abuse, deviant peer affiliation, age, and race were
predictive of alcohol use. Alcohol use, deviant peer affiliation, age, and time were predictive of marijuana use.
Alcohol use, deviant peer affiliation, age, and gender predicted suicidal ideation.
Conclusions: Longitudinal evidence indicated that individual, family, and peer factors played an important role
in predicting alcohol use, marijuana use, and suicidal ideation among child welfare involved adolescents. In
addition, this study provides evidence of a potentially reciprocal relationship between alcohol use and suicidal
ideation among this population. Intervention efforts for reducing the public health problems of substance use
and suicide among child welfare involved adolescents should focus on the importance of peers in influencing
thoughts and behaviors, as well as the functional relationship between alcohol use and suicidal ideation.

1. Introduction

Approximately 3.6 million referrals alleging child maltreatment are
received in the United States (US) each year (U.S. Department of Health
& Human Services, Administration for Children and Families,
Administration on Children, 2016). Nearly two-thirds (61%) of these
referrals are screened for further investigation with a substantial pro-
portion eventually defined as substantiated child abuse and neglect

cases. In 2014, for example, 702,000 children and youth were identified
as child abuse and neglect victims (U.S. Department of Health & Human
Services, Administration for Children and Families, Administration on
Children, 2016). Since the circumstances and conditions in the child
welfare system are stressful and often traumatic, youth involved in this
system compared to other youth may be prone to engage in risky be-
haviors that can have life-threatening consequences. Although not all
maltreated youth are involved in risky behaviors, a large proportion use

https://doi.org/10.1016/j.addbeh.2019.01.021
Received 16 July 2018; Received in revised form 27 November 2018; Accepted 14 January 2019

⁎ Corresponding author at: Department of Psychiatry, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, USA.
E-mail addresses: Christina.sellers@childrens.harvard.edu (C.M. Sellers), Ruth.mcroy@bc.edu (R.G. McRoy),

KimberlyH.M.OBrien@childrens.harvard.edu (K.H.M. O’Brien).

Addictive Behaviors 93 (2019) 39–45

Available online 17 January 2019
0306-4603/ © 2019 Elsevier Ltd. All rights reserved.

http://www.sciencedirect.com/science/journal/03064603

https://www.elsevier.com/locate/addictbeh

https://doi.org/10.1016/j.addbeh.2019.01.021

mailto:Christina.sellers@childrens.harvard.edu

mailto:Ruth.mcroy@bc.edu

mailto:KimberlyH.M.OBrien@childrens.harvard.edu

https://doi.org/10.1016/j.addbeh.2019.01.021

http://crossmark.crossref.org/dialog/?doi=10.1016/j.addbeh.2019.01.021&domain=pdf

alcohol and other substances (Ireland et al., 2002) and endorse suicidal
ideation (Brown et al., 1999). Research has demonstrated that a history
of childhood abuse is a strong risk factor for suicidal ideation (Zapata
et al., 2013) and alcohol misuse and related problems (Widom & Hiller-
Sturmhöfel, 2001). Specifically, 29% of maltreated youth in the Na-
tional Survey of Child and Adolescent Wellbeing I (NSCAW I) engaged
in substance use, with 9% reporting moderate to high levels of use and
5% reporting risky suicidal behavior (Wall & Kohl, 2007). Another
study compared adolescents in a child welfare involved sample with
adolescents from public high schools and found that the child welfare
involved adolescents were approximately 1.5 times more likely to ex-
perience suicidal ideation, when compared to adolescents from the
public high schools (Heneghan et al., 2013).

Alcohol use increases the risk for suicide attempts among adoles-
cents with suicidal ideation (Schilling et al., 2009). Alcohol consump-
tion results in disinhibition of behavior that can enhance the odds of
acting on suicidal thoughts (Bagge et al., 2013; Bryan et al., 2016;
McManama O’Brien et al., 2014; Sher, 2006). Research has demon-
strated proximal and distal effects of alcohol use on suicide attempts, as
well as proximal and distal effects of suicide attempts on alcohol use
(Bagge & Sher, 2008). However, these relationships are complex and in
need of further research (Bagge & Sher, 2008), particularly among a
child welfare involved sample.

In addition, in a systematic review, Bridge, Goldstein, and Brent
(2006) noted that common risk factors for both suicidal thoughts and
behaviors and alcohol and marijuana use include parent/caregiver
variables as well as peer variables. Peer relationships are often a source
of influence for an adolescent’s substance using behavior, as well for
their suicidal thoughts and behaviors. One reason that peers are par-
ticularly influential is because the peer group often defines the beha-
vioral norms within adolescents’ social context. In addition, teens begin
to spend increasing time with their peers during adolescence14.
Previous school based research suggests that adolescents often affiliate
with peers who engage in similar behaviors as their own (Urberg et al.,
2003). Research has also demonstrated that peers also influence each
other’s behavior (Hartup, 2005). Bridge and colleagues (2006) suggest
that associating with a deviant peer group is a risk factor for suicidal
thoughts and behaviors as well as alcohol and marijuana use. Moreover,
research using structural equation modeling has found deviant peer
affiliation is related to suicidal ideation such that having a deviant peer
affiliation can increase substance use and depression, which ultimately
increases risk for suicidal ideation (Prinstein et al., 2000).

Caregivers (i.e., parents) are also influential in an adolescent’s
substance using behavior and suicidal thoughts and behaviors.
Caregiver health is one risk factor for substance use and suicidal
thoughts and behaviors. Specifically, having a caregiver with depres-
sion and/or a caregiver with alcohol or drug abuse has been identified
as risks for poorer outcomes among adolescents and maltreated youth
(Dubowitz & Bennett, 2007; Jaffee & Maikovich-Fong, 2011). More-
over, research suggests associations between suicidal ideation and at-
tempts and a poor family environment, parental psychiatric history, and
low parental monitoring (King et al., 2000).

Although prior studies provide a substantive foundation in sub-
stance use and suicidal ideation among maltreated youth, some sig-
nificant gaps remain in the research literature. First, studies examining
substance use and suicidal ideation among maltreated adolescents have
often relied on data collected before 2007 (Ireland et al., 2002; Brown
et al., 1999; Wall & Kohl, 2007). Older data limits our ability to gen-
eralize findings to the present, especially when terminology and po-
licies have changed (i.e., increased demands and decreased resources
for child welfare agencies; state budget cuts; and federal assessment
through Child and family Services Reviews aimed at higher account-
ability on agencies (Dolan et al., 2011). Second, past research has es-
tablished alcohol use as a risk factor for suicide ideation, but limited
research has examined the effects of marijuana. Third, the combination
of these problems has been understudied using a sample of maltreated

youth. This study intends to fill some gaps by using the NSCAW II, the
most recent (2008–2012) longitudinal national data set on maltreated
and other youth, focusing on both substance use and suicidal ideation.
Specifically, this study aims to investigate the longitudinal predictors of
alcohol and marijuana use and suicidal ideation among maltreated
youth. This study adds to the empirical literature by adding marijuana
as an additional variable, and examining an old research question
within a new population, that of child welfare involved youth. Based on
the empirical literature, the following research questions and hy-
potheses were developed in order to address study aims:

Research Question 1. After controlling for time, what factors predict
the odds of using substances among maltreated youth?

Hypothesis 1. Age, gender, suicidal ideation, deviant peer affiliation,
caregiver health, maltreatment type, and placement type will predict
substance use among child welfare involved youth over time.

Research Question 2. After controlling for time, what factors predict
the odds of endorsing suicidal ideation among maltreated youth?

Hypothesis 2. Age, gender, alcohol use, marijuana use, deviant peer
affiliation, caregiver health, maltreatment type, and placement type
will predict suicidal ideation.

2. Method

This study used the restricted data from the NSCAW II. The NSCAW
is a national, longitudinal survey of children and families who have had
child protective service investigations. The NSCAW collects data from
children, parents, and other caregivers. Reports from caseworkers,
teachers, and administrative records are also collected. To date, there
have been two rounds of NSCAW: NSCAW I (1996–2007, five waves)
and NSCAW II (2008–2012, three waves). This study utilized NSCAW II
data, as the landscape of the child welfare population and the policies
impacting the child welfare agencies have evolved since NSCAW I. The
study was approved under the exempt [Exempt 45 CFR 46. 101(b)]
status by the Institutional Review Board (IRB) at the overseeing uni-
versity.

2.1. Participants

Participants in this study included 1050 adolescents age 11–17.5
(Mage = 14.13) at W1, who were subjects of child abuse or neglect in-
vestigations conducted by Child Protective Services. In this sample,
55.43% of participants identified as female, 52.85% identified as White,
and 67.52% were in in-home care (i.e., living with their families).

3. Measures

Alcohol Use. Alcohol use was measured using the Health Risk
Behaviors Questionnaire, which is an adolescent self-report measure
developed from the Youth Risk Behavior Surveillance System (Kann
et al., 2000). A single item was used to measure the frequency of any
alcohol use over the past 30 days. Responses to this item were on a 7-
point Likert scale, with options ranging from “0 = zero days” to “6=all
30 days.” In this sample, alcohol use was severely skewed and lepto-
kurtic (skew = 3.01, kurtosis = 13.

; M = 0.36, SD = 0.86; range
[0,6]). No data transformations showed significant improvement. Ad-
ditional sensitivity analyses showed that using a dichotomous variable
was the best approach. Therefore, for this study, alcohol use was di-
chotomized into “1=past 30-day alcohol use”, or “0=no past 30-day
alcohol use”.

Marijuana Use. Marijuana use was measured using a single item
from the Health Risk Behaviors Questionnaire, measuring the frequency
of marijuana use over the past 30 days. Responses to this item were on a
6-point Likert scale, with options ranging from “0 = zero times” to
“5=50 or more times.” In this sample, marijuana use was severely

C.M. Sellers et al. Addictive Behaviors 93 (2019) 39–45

skewed and leptokurtic (skew = 3.37, kurtosis = 14.03; M = 0.33,
SD = 1.00; range [0,5]). No data transformations showed significant
improvement. Additional sensitivity analyses showed that using a di-
chotomous variable was the best approach. Therefore, for this study
marijuana use was dichotomized into “1=past 30-day marijuana use”,
or “0=no past 30-day marijuana use”.

Suicidal Ideation. Suicidal ideation (SI) was measured from a
single item from the Childhood Depression Inventory (CDI: Kovacs,
1992). The CDI measures symptom severity over the past 2 weeks.
Adolescents were asked, “Which of these best says how you have felt [in
the past 2 weeks]?” The first response (0 = I do not think about killing
myself) indicates an absence of SI, whereas the second (1 = I think
about killing myself but I wouldn’t do it) and third (2 = I want to kill
myself) represent SI and suicidal intent, respectively. For this study,
adolescents who responded with 1 or 2 were identified as having sui-
cidal ideation.

Deviant Peer Affiliation. Deviant peer affiliation was measured
using the Deviant Peer Affiliation scale (Capaldi & Patterson, 1989).
This 6 item scale measures involvement with peers who engage in risky
or deviant behaviors with questions regarding how many friends
cheated on school tests, how many friends suggested they broke the
law, and how many stole. In this sample, deviant peer affiliation use
skewed and leptokurtic (skew = 1.88, kurtosis = 6.89; M = 1.56,
SD = 0.74; range (U.S. Department of Health & Human Services,
Administration for Children and Families, Administration on Children,
2016; Widom & Hiller-Sturmhöfel, 2001). No data transformations
showed significant improvement. Additional sensitivity analyses
showed that using a dichotomous variable was the best approach.
Therefore, for this study, this variable was recoded into a dichotomous
variable. A score of 0 indicates the participants total score was below
the median, and a score of 1 indicates the total score was above the
median.

Caregiver Health. Four different measures were used to measure
caregiver health. Caregivers physical health was measured using the
standardized score from the Physical Health Summary, and caregivers
mental health was measured using the standardized score from the
Mental Health Summary, from the Short Form Health Survey (Ware
et al., 1996). These two composite scales were calculated from 12
questions with the composite score ranging from 0 to 100 with higher
scores indicating better health.

Caregiver alcohol dependence was measured using the total score
from the Alcohol Use Disorders Identification Test (AUDIT); (Babor
et al., 2001). The AUDIT consists of 10 questions with response options
ranging from 0 to 4. In this sample, AUDIT was severely skewed and
leptokurtic (skew = 4.43, kurtosis = 31.53; M = 1.77, SD = 3.32;
range (U.S. Department of Health & Human Services, Administration
for Children and Families, Administration on Children, 2016; 29 Legal
Medical Marijuana States and DC – Medical Marijuana, 2017)). No data
transformations showed significant improvement. Additional sensitivity
analyses showed that using a dichotomous variable was the best ap-
proach. Therefore, for this study, scores of 7 or below on the AUDIT
were recoded with a 0=“non hazardous drinking” and scores > 7 were
recoded to 1 = “hazardous drinking” mirroring clinical cut offs.

Caregiver drug abuse was measured using the Drug Abuse Screening
Test (DAST; (Skinner, 1982). The DSAT consists of 28 self-response
questions that measure the abuse of drugs other than alcohol. Each
question has a yes or no answer and a score of “1” was given for each
yes response, except for items 4,5, and 7, which are phrased in opposite
directions and thus, the no response was given a score of “1”. In this
sample, the DAST was severely skewed and leptokurtic (skew = 4.95,
kurtosis = 36.89; M = 0.74, SD = 1.63; range [0,18]). No data trans-
formations showed significant improvement. Additional sensitivity
analyses showed that using a dichotomous variable was the best ap-
proach. Therefore, for this study, the DSAT was recoded into a di-
chotomous variable, using clinical cut off scores where 0 represents “No
Drug Abuse” and 1 represents “Drug Abuse.”

Placement Type. Using administrative records, placement type was
measured using W1 data, and recoded to include, 0 = “In-Home”,
1 = “Kinship Care”, 2 = “Foster Care”, and 3=“Other out of home
arrangement, i.e., group home.”

Maltreatment Type. The most serious maltreatment type was
measured by caseworker report, using W1 data, and was recoded to
include: 0 = “Physical Maltreatment”, 1 = “Sexual Maltreatment”,
2 = “Emotional Maltreatment”, 3 = “Neglect”, and 4 = “Other.”

4. Data analysis

Data management and preliminary analyses were conducted using
STATA 14 SE. Next, panel data analysis using logistic models for di-
chotomous variables were run in order to investigate study hypotheses.
This type of analysis was chosen as conventional logistic regressions do
not account for dependency within each participant (Rabe-Hesketh &
Skrondal, 2012). Specifically, random effect models were utilized to
examine study aims, which invested the predictors for alcohol use,
marijuana use, and suicidal ideation.

In the alcohol use model, the Hausman test indicated that for
caregiver drug abuse, the between and within effects were different.
Consequently, these effects were estimated separately in the model. For
the marijuana use model, only within effects were estimated, as the
Hausman test indicated no difference in within and between effects.
Lastly, in the suicidal ideation model, the Hausman test indicated that
the between and within effects for caregiver mental health were dif-
ferent. Given these differences, the effects were estimated separately.

5. Results

Descriptive statistics of the sample are presented in Table 1, and Chi
square analyses are presented in Table 2. These results indicate cross-
sectional relationships between alcohol use and suicidal ideation at all
three waves.

6. Random effect models

Model One: Alcohol with Covariates. The results for the model
that tested the predictors of alcohol use among child welfare involved
youth are presented in Table 3. In this model, there were 1402 ob-
servations within 832 subjects. The model was statistically significant
(Wald Chi2 = 117.13, p < .001), suggesting that the odds of drinking alcohol in the past 30 days can be predicted from the independent variables. In this model, marijuana use, suicidal ideation, the between effect for caregiver drug abuse, deviant peer affiliation, age, and race were statistically significantly predictive of alcohol use.

In regards to individual thoughts and behaviors, when all other
variables were controlled for, the odds of drinking alcohol for those
who use marijuana increased 3662% when compared to those who did
not use marijuana. Similarly, when all other variables were controlled
for, those who presented with suicidal ideation were 113% more likely
to drink alcohol, than those who did not have suicidal ideation.

In regards to family and peer variables, the odds of past 30 day al-
cohol use for an individual who had a caregiver with drug dependence
was 67% less, when compared to an individual with a caregiver who
did not have drug dependence (between effect) and the odds of drinking
alcohol increased by 223% for adolescents whose deviant peer affilia-
tion score was above the median, compared to those whose deviant
peer affiliation score was below the median, when controlling for all
other variables.

Lastly, demographic characteristics, namely age and race, also
played a role in predicting the odds of drinking alcohol use. The odds of
past 30 day alcohol use for Black youth was 52% lower than for White
youth, when all other variables were controlled for. Additionally, for
each one-month increase in age, there was a 4% increase in the odds of
drinking alcohol when controlling for all other variables.

C.M. Sellers et al. Addictive Behaviors 93 (2019) 39–45
41

Model Two: Marijuana with Covariates. The results of testing the
predictors for marijuana use among child welfare involved youth are
presented in Table 4. There were 1360 observations within 821 parti-
cipants and the random effect model was statistically significant (Wald
Chi2 = 70.57, p < .001), suggesting that the odds of using marijuana in the past 30 days can be predicted from the independent variables. Alcohol use, deviant peer affiliation, age, and time were statistically significant predictors in this model. Furthermore, maltreatment type, and specifically sexual maltreatment approached significance.

Drinking alcohol in the past 30 days, compared with not drinking
alcohol in the past 30 days, presented a 4861% increase in the odds of
using marijuana, when controlling for all other variables. In addition,
youth whose deviant peer affiliation score was above the median had a

Table 1
Descriptive statistics for key variables: NSCAW II panel of adolescents with
child welfare involvement (Panel selected at W1, 2008–2009).

Variable Wave 1:
Baseline (N)

Wave 2: 18-
Months (N)

Wave 3:
36 Months (N)

Mean Age 14.13 (1050) 15.30 (854) 17.29 (768)
Gender
Male

.57% (468)
Female 55.

% (582)
Race
American Indian 12.30% (125)
Asian/Hawiian/Pacific

Islander
4.72% (48)

Black 30.12% (306)
White 52.85% (537)
Substantiated maltreatment 52.94% (541)
Placement
In-Home 67.52% (709)
Kinship Care 14.00% (147)
Foster Care 12.38% (130)
Other OOH Placement 6.10% (64)
Lifetime history of Alc. Use

(Yes)
43.24%%
(435)

47.35% (393) 55.77% (401)

P30 Day Alc days used (Yes)⁎ 16.22% (165) 20.22% (168) 28.47% (209)
Lifetime history of MJ Use

(Yes)
23.01% (231) 30.53% (254) 38.69% (277)

P30 Day MJ used (Yes)⁎ 10.13% (103) 13.82% (115) 16.64% (122)
P2 week SI (Yes)⁎ 19.56% (194) 17.00% (126) 12.80% (53)
Deviant Peer Affiliation

(Above the Mean)
54.29% (570) 61.62% (647) 22.48% (236)

Caregiver Alcohol Use
(Hazardous Drinking)

32.86% (345) 43.43% (456) 65.81% (691)

Caregiver Substance
Dependence (Drug
Abuse)

32.57% (342) 44.95% (472) 67.33% (707)

Caregiver Physical Healtha 46.44 (1008) 45.83 (789) 45.36 (462)
Caregiver Mental Healtha 48.65 (1008) 50.10 (789) 49.18 (462)

Notes: unbalanced panel
⁎ P = Past
a Caregiver Physical and Mental Health each ranged from 0 to 100 with

higher scores indicating better health, thus the sample was on average, of
average health.

Table 2
Chi Square values for suicidal ideation related to alcohol use and marijuana use
at all three waves.

Variable Chi Square p

Wave 1
Alcohol use 16.83 0.000
Marijuana use 6.81 0.009
Wave 2
Alcohol use 6.97 0.008
Marijuana use 0.20 0.652
Wave 3
Alcohol use 9.54 0.002
Marijuana use 3.54 0.060

Table 3
Random effect model of alcohol use on marijuana use; suicidal ideation; care-
giver alcohol dependence, drug dependence, mental health, and physical
health; age, race, gender, maltreatment type, placement type, and time.

Variable Coefficient Odds Ratio

Marijuana Use 3.63 (0.39)*** 37.62
Suicidal Ideation 0.76 (0.25)** 2.13
Caregiver Alcohol Dependence 0.15 (0.37) 1.16
Caregiver Drug Abuse (Between) −1.10 (0.54)*** 0.33
Caregiver Drug Abuse (Within) −0.19 (0.42) 0.83
Caregiver Mental Health −0.00 (0.01) 1.00
Caregiver Physical Health 0.00 (0.01) 1.00
Deviant Peer Affiliation 1.17 (0.23)*** 3.23
Age 0.04 (0.01)*** 1.04
Race
American Indian 0.09 (0.34) 1.10
Asian/Hawaiian/Pacific Islander 0.08 (0.52) 1.08
Black −0.73 (0.23)** 0.48
Gender 0.15 (0.23) 1.16
Maltreatment Type
Sexual Maltreatment −0.78 (0.56) 0.46
Emotional Maltreatment −0.89 (0.63) 0.41
Neglect Maltreatment −0.52 (0.42) 0.59
Other Maltreatment −0.26 (0.34) 0.77
Placement
In-Home Care 0.09 (0.34) 1.10
Foster Care −0.05 (0.47) 0.95
Kinship Care −0.35 (0.60) 0.70
Time 0.29 (0.21) 1.34
Goodness of Fit
Wald Chi2 117.13, p < .001 AIC 887.20 BIC 1007.854

*p < .05; **p < .01, ***p < .001 Note: Standard Errors in parenthesis

Table 4
Random effect model of marijuana use on alcohol use; suicidal ideation; care-
giver alcohol dependence, drug dependence, mental health, and physical
health; age, race, gender, maltreatment type, placement type, and time.

Variable Coefficient Odds ratio

Random Effect
Alcohol Use 3.90 (0.49)*** 49.61
Suicidal Ideation 0.08 (0.35) 1.08
Caregiver Alcohol Dependence 0.42 (0.50) 1.51
Caregiver Drug Abuse −0.86 (0.56) 0.42
Caregiver Mental Health 0.00 (0.01) 1.00
Caregiver Physical Health −0.02 (0.01) 0.99
Deviant Peer Affiliation 0.53 (0.18)** 1.70
Age 0.03 (0.01)** 1.03
Race
American Indian 0.33 (0.45) 1.39
Asian/Hawaiian/Pacific Islander −0.28 (0.80) 0.76
Black 0.17 (0.36) 1.19
Gender −0.13 (0.32) 0.88
Maltreatment Type
Sexual Maltreatment 1.21 (0.63) 3.36
Emotional Maltreatment 0.78 (0.73) 2.19
Neglect Maltreatment 0.25 (0.53) 1.29
Other Maltreatment −0.39 (0.48) 0.68
Placement
In-Home Care 0.32 (0.45) 1.38
Foster Care 0.67 (0.58) 1.96
Kinship Care 0.66 (0.74) 1.94
Time 0.58 (0.28)* 1.79
Goodness of Fit
Wald Chi2 70.57, p < .001 AIC 627.13 BIC 741.86

*p < .05; **p < .01, ***p < .001 Note: Standard Errors in parenthesis C.M. Sellers et al. Addictive Behaviors 93 (2019) 39–45 42

70% increase in the odds of using marijuana when compared to their
peers who had lower deviant peer affiliation scores. Increases in age
and time also increased the odds of using marijuana. Specifically, for
each additional month in age, there was a 3% increase in the odds of
using marijuana, and for each additional wave of data collection
(18 months), there was a 79% increase in the odds of using marijuana,
when all other variables were controlled for. Lastly, although mal-
treatment type did not statistically significantly predict marijuana use
with > 95% confidence, it did predict marijuana use at 94.5% con-
fidence (p = .055), indicating that, we are 94.5% confident that for
youth who have a history of sexual maltreatment, compared to other
types of maltreatment, the odds for using marijuana increase by 235%.

Model Three: Suicidal Ideation with Covariates. The results
testing the predictors for suicidal ideation among child welfare in-
volved youth are presented in Table 5. There were 1360 observations
within 821 participants. The random effect model for suicidal ideation
was statistically significant (Wald Chi2 = 47.45, p < .001), suggesting that the odds of endorsing suicidal ideation in the past week can be predicted from the independent variables.

In this model, alcohol use, deviant peer affiliation, age, and gender
were statistically significant predictors of suicidal ideation and the
between effect for caregiver mental health was approaching sig-
nificance. Child welfare involved youth who drank alcohol had a 134%
increase in the odds for suicidal ideation, compared to their peers who
did not drink alcohol, when controlling for all other variables.
Similarly, when all other variables were controlled, youth whose de-
viant peer affiliation score was above the median, had a 97% increase
in the odds of having suicidal ideation when compared to their peers
whose deviant peer affiliation score was below the median. For each
month increase in age, there was a 1% decrease in the odds of having
suicidal ideation. Lastly, compared to males, females had a 71% in-
creased odds of having suicidal ideation.

7. Discussion

Bivariate results indicated significant differences in suicidal ideation
based on alcohol use (at all three waves) and marijuana use (at W1
only). The random effect models demonstrated how individual, family,
and peer factors affect alcohol use, marijuana use, and suicidal ideation
among youth involved in the child welfare system. Specifically, mar-
ijuana use, suicidal ideation, caregiver drug abuse, deviant peer af-
filiation, age, and race were predictive of alcohol use over time; alcohol
use, deviant peer affiliation, age, and time were predictive of marijuana
use over time; and alcohol use, deviant peer affiliation, age, and gender
predicted suicidal ideation over time.

Consistent with other studies of child welfare involved youth
(Heneghan et al., 2013), our study also found higher rates of alcohol
use, marijuana use, and suicide ideation when compare to youth not
involved with the child welfare system. In this study, marijuana use,
suicidal ideation, caregiver drug abuse, deviant peer affiliation, age,
and race were significant predictors of alcohol use over time. As ex-
pected, marijuana use, suicidal ideation, and deviant peer affiliation
were particularly potent risk factors for alcohol use. When youth use
marijuana, experience suicidal ideation, and/or spend time with de-
viant peers, they are at an increased risk of using alcohol. In this
sample, however, having a caregiver with drug abuse (other than al-
cohol) served as a protective factor. Specifically, when comparing in-
dividuals with caregivers with drug abuse to individuals with caregivers
without drug abuse, those who had a caregiver with drug abuse were at
a decreased risk of using alcohol. These results are contrary to other
studies, which suggest caregiver drug abuse is a risk factor for alcohol
use among adolescents (Hawkins et al., 1992; Kilpatrick et al., 2000).
One potential explanation for this finding is that given the sample of
participants, these families are closely monitored which may result in
additional supports and services. Over the past two decades, re-
searchers and clinicians have developed and identified effective stra-
tegies and services to support child welfare involved parents and their
children when a parent has a substance use problem1. Social Cognitive
Theory31 may also help explain this finding. In order to identify the
probabilistic nature of a behavior, social cognitive theory suggests that
there are five basic cognitive capabilities common to individuals
(symbolizing, forethought, vicarious, self-regulatory, and self-re-
flective) (Bandura, 1986). The degree to which individuals utilize these
capabilities can help to predict how probable it is that the individual
will engage in any given behavior31. Given that more and more youth
are being removed from their families and/or gaining child welfare
involvement as a result of parental substance use, it is possible that
youth in this sample utilized the cognitive capabilities of forethought
and vicarious learning in order to predict major consequences of their
own drinking from the consequences of their parents substance use. As
a result, it is possible that through these predictions, youth are less
likely to engage in underage drinking given the expectancies they de-
veloped around consequences of substance use.

Alcohol use, deviant peer affiliation, age, and time predicted mar-
ijuana use over time in this study. Surprisingly, caregiver health (i.e.,
physical health, mental health, alcohol dependence, or substance
abuse) had no significant effect on the odds of using marijuana. These
findings may be related to adolescents spending more time with peers
and less time with caregivers, as they transition from childhood to
adolescence (Steinberg, 2014). Similarly, recent research has demon-
strated that peer influences may be stronger than parent influences,
particularly when it comes to alcohol and other drug use (Sellers et al.,
2018). Specifically, research has suggested that peer factors are one
potential mechanism through which alcohol use occurs in adolescence,
over and above parental factors such as parental monitoring (Sellers
et al., 2018). This may be particularly important for child welfare in-
volved youth who may be placed in out of home settings resulting in
less family involvement than their same aged peers. At the same time,
adolescence is a time of exploration and experimentation and many

Table 5
Random effect model of suicidal ideation on alcohol use; marijuana use; care-
giver alcohol dependence, drug dependence, mental health, and physical
health; age, race, gender, maltreatment type, placement type, and time.

Variable Coefficient Odds ratio

Alcohol Use 0.85 (0.33)* 2.34
Marijuana Use −0.04 (0.39) 0.96
Caregiver Alcohol Dependence 0.40 (0.38) 1.49
Caregiver Drug Abuse 0.14 (0.37) 1.15
Caregiver Mental Health (Between) −0.03 (0.01) 0.97
Caregiver Mental Health (Within) 0.01 (0.02) 1.01
Caregiver Physical Health −0.01 (0.01) 0.99
Deviant Peer Affiliation 0.68 (0.16)*** 1.97
Age −0.01 (0.01)* 0.99
Race
American Indian 0.39 (0.39) 1.47
Asian/Hawaiian/Pacific Islander 0.41 (0.56) 1.51
Black −0.08 (0.29) 0.92
Gender 0.54 (0.25)* 1.71
Maltreatment Type
Sexual Maltreatment 0.42 (0.56) 1.52
Emotional Maltreatment −0.50 (0.64) 0.61
Neglect Maltreatment −0.39 (0.44) 0.68
Other Maltreatment −0.26 (0.36) 0.77
Placement
In-Home Care −0.41 (0.39) 0.66
Foster Care −0.19 (0.50) 0.83
Kinship Care 0.11 (0.62) 1.11
Time −0.30 (0.19) 0.74
Goodness of Fit
Wald Chi2 47.45 p < .001 AIC 1232.69 BIC 1352.64

*p < .05; **p < .01, ***p < .001 Note: Standard Errors in parenthesis C.M. Sellers et al. Addictive Behaviors 93 (2019) 39–45 43

youth begin to experiment with alcohol during their adolescence
(Steinberg, 2014), which may be a gateway into the use of marijuana.

Results from this study indicated that alcohol use, deviant peer af-
filiation, age, and gender predict suicidal ideation over time. Both al-
cohol use and deviant peer affiliation are risk factors for suicidal
ideation among child welfare involved youth. When youth use alcohol
or affiliate with deviant peers, they are at an increased risk for suicidal
ideation. Being surrounded by a deviant peer group can amplify suicide
risk, including increasing suicidal thoughts (Winterrowd & Canetto,
2013). One mechanism through which this may occur is through the
proliferation of low emotional and behavioral regulation skills that
ultimately contribute to increased suicidal ideation (He et al., 2015).
Similarly, Cognitive Behavioral Theory posits that cognition plays a
large role in the development and maintenance of emotional and be-
havioral responses to a variety of experiences, with thoughts, behaviors,
and emotions being intricately tied together (Sowers et al., 2008).
Consequently, it is possible that youth who are involved with deviant
peers are more likely to engage in deviant behaviors that lead to a
negative self-schema and poor self-esteem, contributing to increased
suicidal ideation.

The longitudinal analyses indicated a relationship between alcohol
use and suicidal ideation among child welfare involved youth, such that
alcohol use predicted suicidal ideation and suicidal ideation predicted
alcohol use. These results are consistent with previous literature sup-
porting the relationship between alcohol use and suicidal ideation
among clinical populations (Bagge & Sher, 2008; Nock et al., 2013).
Youth in the child welfare system may use alcohol to cope with distress
(Khantzian, 1997), and at the same time, alcohol use may exacerbate
distress (Marschall-Lévesque et al., 2017), suggesting a potential bi-
directional relationship. For youth in the child welfare system, the
circumstances and conditions of their child welfare involvement are
often stressful and/or traumatic, leading to increased distress. Without
the emotion regulation skills to cope with this stress and trauma, youth
may use alcohol as one way of coping. Despite this attempt to cope,
alcohol use may unintentionally exacerbate that distress as the con-
sequences of drinking may be heightened for child-welfare involved
youth.

Although this study contributes to the knowledge base on substance
use and suicidal ideation among child welfare involved youth, it has
several limitations. First, although the NSCAW II is the most recent
national level study with data on suicidal ideation and substance use
specific to the child welfare population, the data are approximately
10 years old. This study did not find a relationship between marijuana
use and suicidal ideation. However, marijuana policies and potency
continue to change. In 2008, 12 states had legalized medical marijuana
and no states had legalized recreational marijuana. In 2017, 29 states
had legalized medical marijuana and 8 states had legalized recreational
marijuana (29 Legal Medical Marijuana States and DC – Medical
Marijuana, 2017). In addition, there has been, and continues to be, an
increase in the strength of marijuana (ElSohly et al., 2016). Specifically,
the potency of marijuana has increased from approximately 4% in 1995
to approximately 12% in 2014 (ElSohly et al., 2016). Given the change
in marijuana policies and potency over the past ten years, it is possible
that the effect marijuana has on suicidal ideation has changed.

Lastly, the NSCAW II collects limited data on suicidal thoughts and
behaviors. Understanding all elements of suicidal thoughts and beha-
vior are important in understanding the relationship between substance
use and suicide, as well as in identifying implications for policy, prac-
tice, and research. Only measuring suicidal ideation (as opposed to also
including suicide attempts, suicide plans, and non-suicidal self-injury)
limits our ability to further understand these nuanced relationships. In
addition, measuring gender as a binary construct without allowing for
other gender presentations limits our ability to understand the effects of
gender on suicide, especially when research has demonstrated that
transgender youth are at an increased risk for suicide (Veale et al.,
2017).

Despite these limitations, the findings of this study demonstrate that
the proportion of youth experiencing substance use and suicidal
thoughts is substantially higher among youth involved with the child
welfare system, indicating the need for programming and interventions
in this area. In addition, results indicated the potency with which peers
play a role in both substance use and suicidal thoughts among child
welfare involved youth. Consequently, clinicians should be aware of the
developmental trajectories of youth and the role peers play in these
problems. In order to utilize peers in a positive way, adults should train
peers to recognize warning signs of problematic substance use and
suicidal thoughts. Lastly, results provide evidence of a bidirectional
relationship between alcohol use and suicidal ideation among this sub-
population of youth. Research and theory have posited a complex re-
lationship between thoughts and behaviors, with changes in one area
leading to changes in another (Hollon & Beck, 1994). In addition, the
standard of care is that youth receiving treatment for alcohol use or
suicidal ideation often do so separately, despite the strong connection.
As such, clinicians should consider developing accessible interventions
for youth in care by either integrating substance use and suicidal
ideation treatment, or targeting a reduction in underage alcohol use as
a way to indirectly target suicidal thoughts for this population.

Declarations of interest

None.

Role of funding sources

This research did not receive any specific grant from funding
agencies in the public, commercial, or not-for-profit sectors.

Contributions

Christina M. Sellers conducted the literature search and developed
the research questions. She conducted the analyses and wrote the
manuscript. Ruth G. McRoy and Kimberly H. McManama O’Brien as-
sisted with research conception, interpretation of results, and revisions
of the manuscript. All authors contributed to and have approved the
final manuscript.

References

29 Legal Medical Marijuana States and DC – Medical Marijuana. ProCon.org. https://
medicalmarijuana.procon.org/view.resource.php?resourceID=000881 Published
2017. Accessed December 30, 2017.

Babor, T. F., Higgins-Biddle, J. C., Saunders, J. B., & Monteiro, M. G. (2001). The alcohol
use disorders identification test guidelines for use in primary care.

Bagge, C. L., Lee, H.-J., Schumacher, J. A., Gratz, K. L., Krull, J. L., & Holloman, G. (2013).
Alcohol as an acute risk factor for recent suicide attempts: A case-crossover analysis.
Journal of Studies on Alcohol and Drugs, 74(4), 552–558 (http://www.ncbi.nlm.-
nih.gov/pubmed/23739018. Accessed June 8, 2016).

Bagge, C. L., & Sher, K. J. (2008). Adolescent alcohol involvement and suicide attempts:
Toward the development of a conceptual framework. Clinical Psychology Review,
28(8), 1283–1296. https://doi.org/10.1016/j.cpr.2008.06.002.

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory
(Prentice-Hall, ed.). Engldwood Cliffs, N.J.

Brown, J., Cohen, P., Johnson, J. G., & Smailes, E. M. (1999). Childhood abuse and ne-
glect: Specificity of effects on adolescent and young adult depression and suicidality.
Journal of the American Academy of Child and Adolescent Psychiatry, 38(12),
1490–1496. https://doi.org/10.1097/00004583-199912000-00009.

Bryan, C. J., Garland, E. L., Rudd, M. D., et al. (2016). From impulse to action among
military personnel hospitalized for suicide risk: Alcohol consumption and the re-
ported transition from suicidal thought to behavior. General Hospital Psychiatry, 41,
13–19. https://doi.org/10.1016/j.genhosppsych.2016.05.001.

Capaldi, D. M., & Patterson, G. R. (1989). Psychometric properties of fourteen latent con-
structs from the Oregon youth study. New York, NY: Springer New Yorkhttps://doi.org/
10.1007/978-1-4612-3562-0.

Dolan, M., Smith, K., Casanueva, C., Ringeisen, H., & Webb, M. B. (2011). Introduction to
NSCAW II NSCAW II BASELINE REPORT: INTRODUCTION TO NSCAW II FINAL
REPORT. (http://www.acf.hhs.gov/programs/opre/index.html. Accessed November
24, 2018).

Dubowitz, H., & Bennett, S. (2007). Physical abuse and neglect of children. Lancet,
369(9576), 1891–1899. https://doi.org/10.1016/S0140-6736(07)60856-3.

C.M. Sellers et al. Addictive Behaviors 93 (2019) 39–45
44

http://refhub.elsevier.com/S0306-4603(18)30781-0/rf0005

http://refhub.elsevier.com/S0306-4603(18)30781-0/rf0010

https://doi.org/10.1016/j.cpr.2008.06.002

http://refhub.elsevier.com/S0306-4603(18)30781-0/rf0020

https://doi.org/10.1097/00004583-199912000-00009

https://doi.org/10.1016/j.genhosppsych.2016.05.001

https://doi.org/10.1007/978-1-4612-3562-0

http://refhub.elsevier.com/S0306-4603(18)30781-0/rf0040

https://doi.org/10.1016/S0140-6736(07)60856-3

ElSohly, M. A., Mehmedic, Z., Foster, S., Gon, C., Chandra, S., & Church, J. C. (2016).
Changes in Cannabis potency over the last 2 decades (1995–2014): Analysis of cur-
rent data in the United States. Biological Psychiatry, 79, 613–619. https://doi.org/10.
1016/j.biopsych.2016.01.004.

Hartup, W. W. (2005). Peer interaction: What causes what? Journal of Abnormal Child
Psychology, 33(3), 387–394. https://doi.org/10.1007/s10802-005-3578-0.

Hawkins, J. D., Catalano, R. F., & Miller, J. Y. (1992). Risk and protective factors for
alcohol and other drug problems in adolescence and early adulthood: Implications for
substance abuse prevention. Psychological Bulletin, 112(1), 64–105. https://doi.org/
10.1037/0033-2909.112.1.64.

He, A. S., Fulginiti, A., & Finno-Velasquez, M. (2015). Connectedness and suicidal idea-
tion among adolescents involved with child welfare: A national survey. Child Abuse &
Neglect, 42, 54–62. https://doi.org/10.1016/J.CHIABU.2015.02.016.

Heneghan, A., Stein, R. E. K., Hurlburt, M. S., et al. (2013). Mental health problems in
teens investigated by U.S. child welfare agencies. Journal of Adolescent Health, 52,
634–640. https://doi.org/10.1016/j.jadohealth.2012.10.269.

Hollon, S. D., & Beck, A. T. (1994). Cognitive and cognitive-behavioral therapies. In A. E.
Bergin, & S. L. Garfield (Eds.). Handbook of psychotherapy and behavior change (pp.
428–466). Oxford, England: John Wiley http://psycnet.apa.org/record/1994-97069-
009Accessed December 30, 2017.

Ireland, T. O., Smith, C. A., & Thornberry, T. P. (2002). Developmental issues in the
impact of child maltreatment on later delinquency and drug use. Criminology, 40(2),
359–400. https://doi.org/10.1111/j.1745-9125.2002.tb00960.x.

Jaffee, S. R., & Maikovich-Fong, A. K. (2011). Effects of chronic maltreatment and mal-
treatment timing on children’s behavior and cognitive abilities. Journal of Child
Psychology and Psychiatry, 52(2), 184–194. https://doi.org/10.1111/j.1469-7610.
2010.02304.x.

Kann, L., Kinchen, S. A., Williams, B. I., et al. (2000). Youth risk behavior surveillance –
United States, 1999. The Journal of School Health, 70(7), 271–285. https://doi.org/10.
1111/j.1746-1561.2000.tb07252.x.

Khantzian, E. J. (1997). The self-medication hypothesis of substance use disorders: A
reconsideration and recent applications. Harvard Review of Psychiatry, 4(5), 231–244.
https://doi.org/10.3109/10673229709030550.

Kilpatrick, D. G., Acierno, R., Saunders, B., Resnick, H. S., Best, C. L., & Schnurr, P. P.
(2000). Risk factors for adolescent substance abuse and dependence: Data from a
national sample. Journal of Consulting and Clinical Psychology, 68(1), 19–30. https://
doi.org/10.1037/0022-006X.68.1.19.

King, R. D., Gaines, L. S., Lambert, E. W., Summerfelt, W. T., & Bickman, L. (2000). The
co-occurrence of psychiatric and substance use diagnoses in adolescents in different
service systems: Frequency, recognition, cost, and outcomes. The Journal of Behavioral
Health Services & Research, 27(4), 417–430. https://doi.org/10.1007/BF02287823.

Kovacs, M. (1992). Childrens depression inventory manual.
Marschall-Lévesque, S., Castellanos-Ryan, N., Parent, S., et al. (2017). Victimization, sui-

cidal ideation, and alcohol use from age 13 to 15 years: Support for the self-medication
model. https://doi.org/10.1016/j.jadohealth.2016.09.019.

McManama O’Brien, K. H., Becker, S. J., Spirito, A., Simon, V., & Prinstein, M. J. (2014).
Differentiating adolescent suicide attempters from ideators: Examining the interac-
tion between depression severity and alcohol use. Suicide & Life-Threatening Behavior,
44(1), 23–33. https://doi.org/10.1111/sltb.12050.

Nock, M. K., Green, J. G., Hwang, I., et al. (2013). Prevalence, correlates, and treatment of
lifetime suicidal behavior among adolescents: Results from the National Comorbidity

Survey Replication Adolescent Supplement. JAMA Psychiatry. 70(3), 300–310.
https://doi.org/10.1001/2013.jamapsychiatry.55.

Prinstein, M. J., Boergers, J., Spirito, A., Little, T. D., & Grapentine, W. L. (2000). Peer
functioning, family dysfunction, and psychological symptoms in a risk factor Model
for adolescent inpatients’ suicidal ideation severity. Journal of Clinical Child
Psychology, 29(3), 392–405. https://doi.org/10.1207/S15374424JCCP2903_10.

Rabe-Hesketh, S., & Skrondal, A. (2012). Multilevel and longirudinal modeling using stata,
Volume II: Categorical responses, counts, and survival (3). College Station, TX: Stata
Press.

Schilling, E. A., Aseltine, R. H., Glanovsky, J. L., James, A., & Jacobs, D. (2009).
Adolescent alcohol use, suicidal ideation, and suicide attempts. Journal of Adolescent
Health, 44(4), 335–341. https://doi.org/10.1016/j.jadohealth.2008.08.006.

Sellers, C. M., O’Brien, K. H. M., Hernandez, L., & Spirito, A. (2018). Adolescent alcohol
use: The effects of parental knowledge, peer substance use, and peer tolerance of use.
Journal Soc Social Work Res. 9(1), https://doi.org/10.1086/695809.

Sher, L. (2006). Alcohol consumption and suicide. QJM, 99(1), 57–61. https://doi.org/10.
1093/qjmed/hci146.

Skinner, H. A. (1982). The drug abuse screening test. Addictive Behaviors, 7(4), 363–371.
https://doi.org/10.1016/0306-4603(82)90005-3.

Sowers, K. M., Karen, M., & Dulmus, C. N. (2008). Comprehensive handbook of social work
and social welfare. John Wiley & Sons (https://books.google.com/books?hl=en&lr=
&id=Z_o3LkQgk2YC&oi=fnd&pg=PA101&dq=cognitive+behavioral+theory&
ots=BCGDNDSSKv&sig=0sYvkwm0NCOqGAkpP8EWy1g5K94#v=onepage&
q=cognitive behavioral theory&f=false. Accessed November 27, 2018).

Steinberg, L. (2014). Adolescence (10). Boston, MA: McGraw Hill.
U.S. Department of Health & Human Services, Administration for Children and Families,

Administration on Children (2016). Youth and families CB. Child Maltreatment 2014
(http://www.acf.hhs.gov/programs/cb/research-data-technology/statistics-re-
search/child-maltreatment).

Urberg, K. A., Luo, Q., Pilgrim, C., & Degirmencioglu, S. M. (2003). A two-stage model of
peer influence in adolescent substance use: Individual and relationship-specific dif-
ferences in susceptibility to influence. Addictive Behaviors, 28, 1243–1256. https://
doi.org/10.1016/S0306-4603(02)00256-3.

Veale, J. F., Watson, R. J., Peter, T., & Saewyc, E. M. (2017). Mental health disparities
among Canadian transgender youth. The Journal of Adolescent Health, 60(1), 44–49.
https://doi.org/10.1016/j.jadohealth.2016.09.014.

Wall, A. E., & Kohl, P. L. (2007). Substance use in maltreated youth: Findings from the
national survey of child and adolescent well-being. Child Maltreatment, 12(1), 20–30.
https://doi.org/10.1177/1077559506296316.

Ware, J., Kosinski, M., & Keller, S. D. (1996). A 12-item short-form health survey:
Construction of scales and preliminary tests of reliability and validity. Medical Care,
34(3), 220–233 (http://www.ncbi.nlm.nih.gov/pubmed/8628042 Accessed
November 14, 2017).

Widom, C. S., & Hiller-Sturmhöfel, S. (2001). Alcohol abuse as a risk factor for and
consequence of child abuse. Alcohol Res Heal. 25(1), 52–57.

Winterrowd, E., & Canetto, S. S. (2013). The long-lasting impact of adolescents’ deviant
friends on suicidality: A 3-year follow-up perspective. Social Psychiatry and Psychiatric
Epidemiology, 48(2), 245–255. https://doi.org/10.1007/s00127-012-0529-2.

Zapata, L. B., Kissin, D. M., Bogoliubova, O., et al. (2013). Orphaned and abused youth
are vulnerable to pregnancy and suicide risk. Child Abuse & Neglect, 37(5), 310–319.
https://doi.org/10.1016/j.chiabu.2012.10.005.

C.M. Sellers et al. Addictive Behaviors 93 (2019) 39–45
45

https://doi.org/10.1016/j.biopsych.2016.01.004

https://doi.org/10.1007/s10802-005-3578-0

https://doi.org/10.1037/0033-2909.112.1.64

https://doi.org/10.1016/J.CHIABU.2015.02.016

https://doi.org/10.1016/j.jadohealth.2012.10.269

http://refhub.elsevier.com/S0306-4603(18)30781-0/rf0075

https://doi.org/10.1111/j.1745-9125.2002.tb00960.x

https://doi.org/10.1111/j.1469-7610.2010.02304.x

https://doi.org/10.1111/j.1746-1561.2000.tb07252.x

https://doi.org/10.3109/10673229709030550

https://doi.org/10.1037/0022-006X.68.1.19

https://doi.org/10.1007/BF02287823

http://refhub.elsevier.com/S0306-4603(18)30781-0/rf0110

https://doi.org/10.1016/j.jadohealth.2016.09.019

https://doi.org/10.1111/sltb.12050

https://doi.org/10.1001/2013.jamapsychiatry.55

https://doi.org/10.1207/S15374424JCCP2903_10

http://refhub.elsevier.com/S0306-4603(18)30781-0/rf0135

https://doi.org/10.1016/j.jadohealth.2008.08.006

https://doi.org/10.1086/695809

https://doi.org/10.1093/qjmed/hci146

https://doi.org/10.1016/0306-4603(82)90005-3

http://refhub.elsevier.com/S0306-4603(18)30781-0/rf0160

http://refhub.elsevier.com/S0306-4603(18)30781-0/rf0165

http://refhub.elsevier.com/S0306-4603(18)30781-0/rf0170

https://doi.org/10.1016/S0306-4603(02)00256-3

https://doi.org/10.1016/j.jadohealth.2016.09.014

https://doi.org/10.1177/1077559506296316

http://refhub.elsevier.com/S0306-4603(18)30781-0/rf0190

http://refhub.elsevier.com/S0306-4603(18)30781-0/rf0195

https://doi.org/10.1007/s00127-012-0529-2

https://doi.org/10.1016/j.chiabu.2012.10.005

Substance use and suicidal ideation among child welfare involved adolescents: A longitudinal examination

Introduction
Method
Participants
Measures
Data analysis
Results
Random effect models
Discussion
Declarations of interest
Role of funding sources
Contributions
References

Running head:

SUBTOPIC TITLE

Subtopic Title

Peter T. Anteater

University of California, Irvine

Author Note

Peter T. Anteater, Department of Criminology, Law and Society/Earth System Science/East Asian Studies/Economics/Global and International Studies/Mathematics/Psychology, University of California, Irvine.

This short literature review is being submitted in initial/final draft form on August 29, 2020/September 9, 2020 in order to fulfill the final grading requirements of the School of Social Science’s 172AW course titled “American Culture: Media and Social Problems” (70180) instructed by Dr. William J. Dewan and assisted by Michelle Kim Gardner in Summer Session II. My student identification number is 123456.

Correspondence concerning this short literature review should be addressed to peteranteater@uci.edu.

Abstract

Don’t indent this paragraph. Here you should write a short, 150 to 250 word summary of the literature review ensuring that it is presenting the problems at stake in these studies (i.e. the ideas, objectives, research questions and/or hypotheses) and what was done in order to solve these problems (i.e. which methods). Do not make citations in the abstract, since in order for it to be a good abstract, it should be able to stand on its own without any citations. Then, summarize the key findings and conclusions. Most importantly, provide a quick gloss of what these studies implicate (i.e. what the the authors discuss and recommend in order to solve these problems). Finally, you will want to choose some keywords that best represent your topic. I have literally put all of the possible keywords down below; so now all you have to do is delete the ones that do not apply to your literature review. You will have
exactly
three keywords, except for those with the subtopic Youth Offenders/Homeless Youth and Suicide, you will have four. Ident the keywords and “keywords” should be italicized, as follows.

Keywords: youth, suicide, LGBT, minority, family factors, bullying, offenders, homeless, prevention

Subtopic Title

It is completely inappropriate to give a heading for your introduction, since we all know that the first paragraph is going to be the introduction of your paper. It does, after all, come first! However, you should start off your paper with a punchy introduction line that really brings the reader in and makes them interested to keep reading your paper. Ensure that there is a topic sentence and a thesis. Please, please include a thesis, or else your paper will have no direction and will look like a string of summaries. I suggest

this link

for tips on how to write a good thesis statement for the introduction. Following the thesis, state the parameters of the literature that you will include. Basically, what is included in these studies and what is not included. The next part of the introduction should highlight the major themes that you are fixing to discuss and analyze. Finally, provide reasons why this research is important, but do not give your personal opinion why or be melodramatic. But be specific, concrete and use only scientific language. There are no word minimums for each section, but introductions of this sort are usually about a page double-spaced, or approximately 250 words.

For the rest of the content in this template, I will borrow from other APA guides I’ve found online (which will be linked) and Dr. Dewan’s instructions. I implore you to use this Word Document template alongside the provided Easy APA guide so that there are no hiccups in your final grades for the short literature reviews! If you have any questions about how to type out numbers or dates or any little thing that might come up, the answer is likely already there in the guide. However, if you must, reach out to me and I can certainly help you find the information you need. I wish very much to give you all perfect scores on your APA formatting (and elsewhere) on your final grades. Also, for the sake of everything that we find dear, please read Dr. Dewan’s instructions carefully.

Main Body Heading 1

How you arrange your main bodies is completely up to you. Just remember, synthesize, don’t summarize.

Subheading 1. Neither of us would recommend subheadings (at all) for a short literature review such as this. In fact, we strongly recommend against it. However, if you seriously insist, for whatever reason, then you should at least do it right. Anyway, this is how it should look.

Subheading 2. A second subheading, just in case! Again, none of us recommend that you do this. It is really so unnecessary for this assignment. But hey, if you want it, you do you. Again, not recommended. Not at all. Not one single bit.

Main Body Heading 2

There is no minimum or maximum amount of headings to include. Simply include as many as you feel necessary in order to get your point across, or don’t use any at all! Free will is so amazing after all isn’t it? I checked and there’s not any philosophers enrolled in this class, so I’m hoping there won’t be much pushback on that statement. Any who, as long as you have a solid thesis statement, write a strong synthesis of the three journal articles, and address all aspects of the rubric, you will do just fine with or without headings. I would highly suggest at least having a heading that separates the introduction from the main body, and then separate headings for the conclusion and reflection, which you will see goes as follows.

Main Body Heading 3

What the heck, let’s toss another main body in the mix! Three articles, three main bodies right? Sure, well, not necessarily! Like I’ve said, the amount of main bodies that you have and how your literature review is organized is entirely up to you, however, the most successful reviews are usually ordered thematically. If you want to be rebellious (and I encourage you to be if so desired) then there are examples of other ways to organize your literature review at this link.

Conclusion

Quickly review what has been said in this short literature review, restate how your thesis was corroborated along the way, and end with some suggestions for research possibilities that your topic might take in the future. This should be about half a page, or approximately 150 words.

Reflection

Don’t forget about this final little piece! This needs to be two paragraphs, and no, unfortunately, it does not count toward your 1,500 words. Remember, two whole paragraphs! And none of those baby paragraphs (like this one) that only have five sentences or less. I like me at least a good, solid, hunky seven sentence paragraph.

After this will come the references. At the end of this paragraph, insert a page break, and center the heading. Write “References” in bold, press enter, align left again, and list your three references (note: you should ONLY have three) in alphabetical order. I know we usually ignore the references at the bottom but pay attention to the ones I’ve put below. I’ve put some clues inside there to help you better understand how to format them. The one tricky part is the indentation that comes beginning with the second line of a reference, which you can do by pressing the enter key, and then tab. Look for the Microsoft guide in the course files on the Canvas page if you are having an issue. I also want to note that you should not have any links at all anywhere in your document! Not even for your email address or the DOI numbers. NOWHERE! If Word wants to link it, don’t give into the pressure, click backspace and undo it! I know that I have included links in this document, but I am not turning this in for a grade, I am just doing this to help all of you my dear students. Speaking of links,

click here

for help with composing the references for your three journal articles, and click here for help with doing in-text citations. Happy writing!

References

Dewan, W.J. (2010). The article title doesn’t get any special formatting: But if there’s a colon

capitalize that in sentence case like I just did here. Journal Name and Volume Number is Always in Italics, 17(1), 36-55. doi:10.1080/15567030802462911

Doe, J.D., Figgins, J.A., & Smith, J. (1999). But we don’t italicize the journal issue number:

Don’t ask us why. Journal Issue Goes Inside Parentheses, 22(5), 183-205. doi:10.1080/15567030802462911

Gardner, M.K. & Anteater, P.T. (2000). The author names don’t always have to be alphabetical:

Follow the way they are listed on the article itself. Journal Name is Always Capitalized, 9(3), 23-39. doi:10.1080/10723030802533853

Running Head: Review on Family Factors and Youth Suicide 1

Review on Family Factors and Youth Suicide

Jiaqiao Fan

University of California Irvine

William Dewan

SOC SCI 172AW

February 20, 2021

Yiwen Huang
44070000000321729
Too long. At most three words.

Review on Family Factors and Youth Suicide 2

Abstract:

Behind every suicide, there is a unique reason that is not known until someone kills

himself. Suicide cases have reached a very alarming level nowadays. Especially a spike in the

trend of attempting suicide among youth is seen in the last decade. Suicidal attempts can be

based on a lot of reasons depending upon a person’s insights, thought process, and the strength of

someone’s personality, along with the environmental effects and behaviors on the person.

Reasons like LGBT bullying, youth depression due to bullying because of their body features,

family problems and disconnection with the parents, and homelessness and poverty are mostly

behind the suicide attempts. Studies have shown that family problems are one of the main causes

of producing suicidal peers, and we studied different experimentations, surveys and findings to

conclude that lack of parental affection and caring can be the main reason behind suicide

ideation.

Literature Review:

Family problems and the absence of parental caring affiliated with the chance of youth

attempting suicide is the topic of discussion. Family problems are the most common reasons for

suicidal behavior among youth today. Youth is facing difficulty in talking to their parents, and

that is the most highlighting problem causing the absence of parental caring leading to body

dissatisfaction, low self-esteem, depression and unhealthy weight control behaviors. Studies have

shown that almost half of the suicide attempters do not approach anyone or any adult, including

their parents, to talk about their problems and the other half mostly prioritizes their friends’

opinions more than their parents’ opinions, which leads to the building of weak personalities

causing suicidal thoughts. Researchers have studied in a lot of different environments like high

Yiwen Huang
44070000000321729
Abstract should have its own page, followed by keywords (see APA Template for Short Literature Review).

Yiwen Huang
44070000000321729
delete colon

Yiwen Huang
44070000000321729
students, peers, caregivers, etc. are not “environments” though

Yiwen Huang
44070000000321729
?

Review on Family Factors and Youth Suicide 3

school students, deviant peers, alcoholic caregivers, and dropouts from high school. Results have

shown a lot of different factors that are responsible for producing suicidal ideation (SI). A lot of

different random effect models were proposed to measure suicidal ideation (SI). EAT survey was

conducted to ask high school students some questions to analyze the potential suicidal peers.

Results showed that individuals lacking parental caring were most distant from their parents and

were closer to other distractions like friends, alcohol, marijuana, substance use, unhealthy eating

patterns and some more unhealthy obsessions, resulting in suicidal thoughts because of the

rejection they felt from others since childhood till rejecting themselves in their youth.

Emotional health has a lot to do with the person’s physical health. This means that

emotional and mental problems are most likely to lead to a physical health imbalance. Parental

caring is the only way to keep a young adult sane enough to be physically fit. Father-child and

mother-child connectedness help in molding the teen perceptions about valuing the parental

opinions and perceptions about how parental communication and caring affect the teens’

behavior and emotional health. These family closeness problems predict the patterns of teens

either to be normal and healthy or to be drug addicts and suicidal. Studies were done to predict

the alcohol and marijuana addicts in response to suicidal thoughts. Suicidal ideation (SI) can be

measured by CDI that is a childhood depression inventory. These factors depend upon age, type,

race, gender, maltreatment, and bullying and childhood lifestyle and findings suggest that

suicidal peers are different from non-suicidal peers. EAT (eating among teen) survey was

conducted in 2001, whose population-based sample was 4746 high school students from

Minnesota. The sample included 2357 girls and 2377 boys. The EAT survey included 221

questions that were focused on a person’s ideas and beliefs as in, there were questions about the

value of opinions among students, questions about parent-child communication, about their

Review on Family Factors and Youth Suicide 4

weight control behaviors and use of the substance, questions about thoughts on attempting

suicide, about accepting their appearances and self-esteem, about depression, and also questions

related to their parents marital status, their ethnicity and socioeconomic status. All of the data

collected was then analyzed by statistical soft wares like STATA, and the data was interpreted by

charts and graphs produced. The result showed most of the students depends on their parental

opinions to solve their problems. Some boys and girls valued their friend’s opinions over

parent’s opinions for different reasons. Girls that lacked parental caring had a high prevalence of

unhealthy weight control and suicide attempts. While boys, along with these thoughts, also

showed the prevalence of substance use, depression and low self-esteem. (Diann M. Ackard,

2006). This experiment showed that suicidal ideation is directly linked with problematic family

or parental connectedness and the individuals having better bonding with their parents showed

less or no suicidal ideation.

Another study was focused on high school dropouts to predict if they can be suicidal or

not. Participants were 1083 potential dropouts (Randell, June 2006). Among these, there were

different groups who showed different behaviors ranging from not suicidal to less suicidal to

extreme suicidal cases. Ones, who were at high suicide risk, had failed family goals, conflicts

with parents, and family depression showed by the SRB (suicide risk behavior), HSQ, and

MAPS. Results from this study showed that males and females having this background were

almost equally involved in drug addiction with a difference of use of alcohol which was more in

males as well as females. At the same time, females showed more suicide exposure than males.

This study also showed that teens are more likely to use AOD if their family is using it, as

children who lose their parents by suicide are more likely to die in the same way because of the

physiological disorders in response to the trauma. Individuals having suicidal ideation are more

Yiwen Huang
44070000000321729
format

Yiwen Huang
44070000000321729
You need to specify the meanings of all abbreviations that are not widely known.

Yiwen Huang
44070000000321729
format mistake

Yiwen Huang
44070000000321729
were

Review on Family Factors and Youth Suicide 5

likely to have an addiction to alcohol and marijuana, and other drugs. To study this relationship,

1050 adults who were subject to child abuse in child welfare were investigated as children at

child welfare are often abused and are more likely to be suicidal and substance addicts because

they are always looking for distractions (Christina M. Sellersa, 2019). Random effect models for

alcohol, marijuana, and suicide ideation were used to analyze the data. Results showed how one

thing led to another as family problems, and disconnection with parents led peers to child welfare

where they were abused, and finally, they started using drugs and became addicts, which led to

rejection and suicide ideation.

Reflection:

Suicide is a very sensitive issue in today’s world. It is the leading cause of death today for

the age 15-24, as recorded by CDC. Suicide ideation mostly hits the youth because of a lot of

different reasons, like bullying mostly. People are maltreated or bullied, and that makes them

suicidal. Here we discussed how family problems can make peers suicidal and how problematic

relationships can cause suicide ideation and provoke peers to kill themselves. When a peer is

facing problems in connecting with their parents or consulting them with any of the problems

they are facing or having problems with general communication with their parents, it leads to the

distancing of the peer from their parents. Afterward, peers do not consult their parents for any

consultation rather, they consult their friends. This practice has shown a very important role in

the peers showing attraction towards suicidal ideas and attempting suicide. As they are away

from their parents, they grow up into teens having a drug addiction, self-esteem problems, basic

self-rejection problems, unhealthy weight control problems, body dissatisfaction, and depression

which are leading causes of attempting suicide.

Yiwen Huang
44070000000321729
Note that Shellers et al. made a more nuanced argument on page 43: “when comparing individuals with caregivers with drug abuse to individuals with caregivers without drug abuse, those who had a caregiver with drug abuse were at a decreased risk of using alcohol”. This is relevant because alcohol use is positively correlated with suicidality.

Review on Family Factors and Youth Suicide 6

Suicide might be provoked because of a peer thinking of himself as a failure, and the

stress and depression from feeling this way might not let him or her life, and that’s how suicide

ideation occurs. Parents nowadays must keep an eye on their children to prevent them from

becoming deviant peers, and they should provide them with all the attention and care in order to

save their children. Also, we should look out for the problematic peers or traumatic teens that

talk about suicide or death a lot and drop hints of what is going on in their subconscious. Single

trauma or abuse can lead a teen to become a drug addict or become a potential suicidal peer

because traumatic experiences give rise to post-traumatic mental sickness, and lack of parental

care can leave a peer in distress and rejection and suicidal thoughts all together leading to suicide

ideation. Studies show that parental displacement can disrupt the adolescent’s interpersonal

environment, leading to decreased feelings of belonging and increased feelings of wanting to die.

Loneliness causes low self-esteem and decreases the desire to live, provoking suicidal thoughts.

Looking at the trend of suicide ideation, we can see how gender, maltreatment type, race, and the

community around the peer can mold the prevalence of a peer towards suicidal thoughts. For

example, females are most likely to attempt suicide than males. A lot of suicide prevention

programs are running, but they need to improve their working and promote parental education so

that parents can actually prevent producing suicidal peers by providing basic support to their

children, and for this, interpersonal communication skills teaching programs must be launched

for all family members.

Review on Family Factors and Youth Suicide 7

References

Christina M. Sellersa, R. G. (2019). Substance use and suicidal ideation among child welfare

involved adolescents. elsevier.

Diann M. Ackard, P. D.-S. (2006). Parent–Child Connectedness and Behavioral and Emotional

Health Among Adolescents. American Journal of Preventive Medicine.

Randell, W. H. (june 2006). Family Factors Predicting Categories of Suicide Risk. Journal of

Child and Family Studies, Vol. 15.

Running Head: YOUTH SUICIDE 1

YOUTH SUICIDE 8

Review on Family Factors and Youth Suicide

Jiaqiao Fan

University of California Irvine

William Dewan

SOC SCI 172AW

January 29, 2021

Abstract

Behind every suicide, there is a unique reason that is not known until someone kills himself. Suicide cases have reached a very alarming level nowadays. Especially a spike in the trend of attempting suicide among youth is seen in the last decade. Suicidal attempts can be based on a lot of reasons depending upon a person’s insights, thought process, and the strength of someone’s personality, along with the environmental effects and behaviors on the person. Reasons like LGBT bullying, youth depression due to bullying because of their body features, family problems and disconnection with the parents, and homelessness and poverty are mostly behind the suicide attempts. Studies have shown that family problems are one of the main causes of producing suicidal peers, and we studied different experimentations, surveys and findings to conclude that lack of parental affection and caring can be the main reason behind suicide ideation.

Keywords: youth, suicide, LGBT, minority, family factors, bullying, offenders.

Literature Review

Family problems and the absence of parental caring affiliated with the chance of youth attempting suicide is the topic of discussion. Family problems are the most common reasons for suicidal behavior among youth today. Youth is facing difficulty in talking to their parents, causing the absence of parental caring leading to body dissatisfaction, low self-esteem, depression, and unhealthy weight control behaviors (Ackard, 2006, p.1). All of this is linked to the verbal and physical abuse that youth is facing today from the society. Studies have shown that almost half of the suicide attempters do not approach anyone or any adult, including their parents, to talk about their problems and the other half mostly prioritizes their friends’ opinions more than their parents’ opinions, which leads to the building of weak personalities causing suicidal thoughts. Researchers have studied in a lot of different objects like high school students, deviant peers, alcoholic caregivers, and dropouts from high school. This happens when youth faces this kind of problems from the society but lack of parenting and sincerity from their parents stop them from discussing their problems with them. Results have shown a lot of different factors that are responsible for producing suicidal ideation (SI), A lot of different random effect models were proposed to measure suicidal ideation (SI). EAT survey was conducted to ask high school students some questions to analyze the potential suicidal peers. Results also revealed that individuals lacking parental caring were most distant from their parents and were closer to other distractions like friends, alcohol, marijuana, substance use, unhealthy eating patterns and some more unhealthy obsessions, resulting in suicidal thoughts because of the rejection they felt from others since childhood till rejecting themselves in their youth.

Emotional health has a lot to do with the person’s physical health. This means that emotional and mental problems are most likely to lead to a physical health imbalance. As we have discussed earlier, Parental caring is the only way to keep a young adult sane enough to be physically fit. Father-child and mother-child connectedness help in molding the teen perceptions about valuing the parental opinions and perceptions about how parental communication and caring affect the teens’ behavior and emotional health. These family closeness problems predict the patterns of teens either to be normal and healthy or to be drug addicts and suicidal. Studies were done to predict the alcohol and marijuana addicts in response to suicidal thoughts. Suicidal ideation (SI) can be measured by CDI that is a childhood depression inventory. These factors depend upon age, type, race, gender, maltreatment, and bullying and childhood lifestyle and findings suggest that suicidal peers are different from non-suicidal peers. EAT (eating among teen) survey was conducted in 2001, whose population-based sample was 4746 high school students from Minnesota. The sample included 2357 girls and 2377 boys. The EAT survey included 221 questions that were focused on a person’s ideas and beliefs as in, there were questions about the value of opinions among students, questions about parent-child communication, about their weight control behaviors and use of the substance, questions about thoughts on attempting suicide, about accepting their appearances and self-esteem, about depression, and also questions related to their parents marital status, their ethnicity and socioeconomic status. All of the data collected was then analyzed by statistical soft wares like STATA, and the data was interpreted by charts and graphs produced. The result showed most of the students depends on their parental opinions to solve their problems. Some boys and girls valued their friend’s opinions over parent’s opinions for different reasons. Girls that lacked parental caring had a high prevalence of unhealthy weight control and suicide attempts. While boys, along with these thoughts, also showed the prevalence of substance use, depression, and low self-esteem (Ackard, 2006, p.1). This experiment showed that suicidal ideation is directly linked with problematic family or parental connectedness and the individuals having better bonding with their parents showed less or no suicidal ideation.

Besides, suicidal ideation is found also connected with school dropouts. Another study was focused on high school dropouts to predict if they were suicidal or not. Participants were 1,083 potential dropouts (Randell, 2006, p.260). Among these, there were different groups who showed different behaviors ranging from not suicidal to less suicidal to extreme suicidal cases. Ones who were at high suicide risk had failed family goals, conflicts with parents, and family depression showed by the SRB (suicide risk behavior), which is a measure of behavior at risk of suicide, HSQ, and MAPS, which are more tests to check the risk of suicide. Results from this study showed that males and females having this background were almost equally involved in drug addiction with a difference of use of alcohol which was more in males as well as females. At the same time, females showed more suicide exposure than males. This study also showed that teens are more likely to use alcohol and other drug if their family is using it, as children who lose their parents by suicide are more likely to die in the same way because of the physiological disorders in response to the trauma. Individuals having suicidal ideation are more likely to have an addiction to alcohol and marijuana, and other drugs. To study this relationship, 1,050 adults who were subject to child abuse in child welfare, because they had no family so they had to live in the child welfare, were investigated as children at child welfare are often abused and are more likely to be suicidal and substance addicts because they are always looking for distractions. Child welfare have many kinds of people as workers. It is possible that the drug dealers might be working there and selling drugs to children as well as abusers who abuse children because they know their weak spots (Sellers, 2019, p.7). Random effect models for alcohol, marijuana, and suicide ideation were used to analyze the data. Results showed how one thing led to another as family problems, and disconnection with parents led peers to child welfare where they were abused, and finally, they started using drugs and became addicts, which led to rejection and suicide ideation.

Conclusion

In conclusion, we can say that the abuse and the family problems are the sole reason for the suicidal ideation among youth. If a peer is lacking the parental care he or she is most likely to develop suicide ideation as well. Because besides all the troubles that youth is facing, parental care is something that makes youth less likely to feel lonely as they know that their parents are there to understand them and take care of them. This importance of parental care needs to be learned by the parents and needs to be teach by the social service providers. In this way, we can avoid a big number of suicides and development of suicidal peers having deviant thoughts. Therapy regarding this problem must be promoted at all costs among the communities.

Reflection

Suicide is a very sensitive issue in today’s world. It is the leading cause of death today for the age 15-24, as recorded by CDC. Suicide ideation mostly hits the youth because of a lot of different reasons, like bullying mostly. People are maltreated or bullied, and that makes them suicidal. Here we discussed how family problems can make peers suicidal and how problematic relationships can cause suicide ideation and provoke peers to kill themselves. When a peer is facing problems in connecting with their parents or consulting them with any of the problems they are facing or having problems with general communication with their parents, it leads to the distancing of the peer from their parents. Afterward, peers do not consult their parents for any consultation rather, they consult their friends. This practice has shown a very important role in the peers showing attraction towards suicidal ideas and attempting suicide. As they are away from their parents, they grow up into teens having a drug addiction, self-esteem problems, basic self-rejection problems, unhealthy weight control problems, body dissatisfaction, and depression which are leading causes of attempting suicide.

Suicide might be provoked because of a peer thinking of himself as a failure, and the stress and depression from feeling this way might not let him or her life, and that’s how suicide ideation occurs. Parents nowadays must keep an eye on their children to prevent them from becoming deviant peers, and they should provide them with all the attention and care in order to save their children. Also, we should look out for the problematic peers or traumatic teens that talk about suicide or death a lot and drop hints of what is going on in their subconscious. Single trauma or abuse can lead a teen to become a drug addict or become a potential suicidal peer because traumatic experiences give rise to post-traumatic mental sickness, and lack of parental care can leave a peer in distress and rejection and suicidal thoughts all together leading to suicide ideation. Studies show that parental displacement can disrupt the adolescent’s interpersonal environment, leading to decreased feelings of belonging and increased feelings of wanting to die. Loneliness causes low self-esteem and decreases the desire to live, provoking suicidal thoughts. Looking at the trend of suicide ideation, we can see how gender, maltreatment type, race, and the community around the peer can mold the prevalence of a peer towards suicidal thoughts. For example, females are most likely to attempt suicide than males. A lot of suicide prevention programs are running, but they need to improve their working and promote parental education so that parents can actually prevent producing suicidal peers by providing basic support to their children, and for this, interpersonal communication skills teaching programs must be launched for all family members.

References
Christina M. Sellers, R. G. (2019). Substance use and suicidal ideation among child welfare involved adolescents. elsevier.
Diann M. Ackard, P. D.-S. (2006). Parent–Child Connectedness and Behavioral and Emotional Health Among Adolescents. American Journal of Preventive Medicine.
Holly C. Wilcox, P. (2010). Children Who Lose a Parent to Suicide More Likely to Die the Same Way. Journal of the American Academy of Child & Adolescent Psychiatry.
Katherine A. Timmons, E. A. (2012). Parental Displacement and Adolescent Suicidality: Exploring the Role of Failed Belonging. NCBI.
Randell, W. H. (june 2006). Family Factors Predicting Categories of Suicide Risk. Journal of Child and Family Studies, Vol. 15.

What Will You Get?

We provide professional writing services to help you score straight A’s by submitting custom written assignments that mirror your guidelines.

Premium Quality

Get result-oriented writing and never worry about grades anymore. We follow the highest quality standards to make sure that you get perfect assignments.

Experienced Writers

Our writers have experience in dealing with papers of every educational level. You can surely rely on the expertise of our qualified professionals.

On-Time Delivery

Your deadline is our threshold for success and we take it very seriously. We make sure you receive your papers before your predefined time.

24/7 Customer Support

Someone from our customer support team is always here to respond to your questions. So, hit us up if you have got any ambiguity or concern.

Complete Confidentiality

Sit back and relax while we help you out with writing your papers. We have an ultimate policy for keeping your personal and order-related details a secret.

Authentic Sources

We assure you that your document will be thoroughly checked for plagiarism and grammatical errors as we use highly authentic and licit sources.

Moneyback Guarantee

Still reluctant about placing an order? Our 100% Moneyback Guarantee backs you up on rare occasions where you aren’t satisfied with the writing.

Order Tracking

You don’t have to wait for an update for hours; you can track the progress of your order any time you want. We share the status after each step.

Order Now Talk to Us

Areas of Expertise

Although you can leverage our expertise for any writing task, we have a knack for creating flawless papers for the following document types.

Essay

Thesis

Presentation

Dissertation

Term Paper

Research Paper

Book Review

Assignment

Report

Case Study

Letter

Article

Coursework

Speech

Q & A

Critical Thinking

Areas of Expertise

Although you can leverage our expertise for any writing task, we have a knack for creating flawless papers for the following document types.

Essay

Thesis

Presentation

Dissertation

Term Paper

Research Paper

Book Review

Assignment

Report

Case Study

Letter

Article

Coursework

Speech

Q & A

Critical Thinking

Trusted Partner of 9650+ Students for Writing

From brainstorming your paper's outline to perfecting its grammar, we perform every step carefully to make your paper worthy of A grade.

Preferred Writer

Hire your preferred writer anytime. Simply specify if you want your preferred expert to write your paper and we’ll make that happen.

Grammar Check Report

Get an elaborate and authentic grammar check report with your work to have the grammar goodness sealed in your document.

One Page Summary

You can purchase this feature if you want our writers to sum up your paper in the form of a concise and well-articulated summary.

Plagiarism Report

You don’t have to worry about plagiarism anymore. Get a plagiarism report to certify the uniqueness of your work.

Free Features $66FREE

Most Qualified Writer $10FREE
Plagiarism Scan Report $10FREE
Unlimited Revisions $08FREE
Paper Formatting $05FREE
Cover Page $05FREE
Referencing & Bibliography $10FREE
Dedicated User Area $08FREE
24/7 Order Tracking $05FREE
Periodic Email Alerts $05FREE

Our Services

Join us for the best experience while seeking writing assistance in your college life. A good grade is all you need to boost up your academic excellence and we are all about it.

On-time Delivery
24/7 Order Tracking
Access to Authentic Sources

Academic Writing

We create perfect papers according to the guidelines.

Professional Editing

We seamlessly edit out errors from your papers.

Thorough Proofreading

We thoroughly read your final draft to identify errors.

Thorough Proofreading

We thoroughly read your final draft to identify errors.

Delegate Your Challenging Writing Tasks to Experienced Professionals

Work with ultimate peace of mind because we ensure that your academic work is our responsibility and your grades are a top concern for us!

Check Out Our Sample Work

Dedication. Quality. Commitment. Punctuality

It May Not Be Much, but It’s Honest Work!

Here is what we have achieved so far. These numbers are evidence that we go the extra mile to make your college journey successful.

0+

Happy Clients

0+

Words Written This Week

0+

Ongoing Orders

0%

Customer Satisfaction Rate

Process as Fine as Brewed Coffee

We have the most intuitive and minimalistic process so that you can easily place an order. Just follow a few steps to unlock success.

Call Us +1 (877) 657-8180 Discuss Order Details Now

See How We Helped 9000+ Students Achieve Success

We Analyze Your Problem and Offer Customized Writing

We understand your guidelines first before delivering any writing service. You can discuss your writing needs and we will have them evaluated by our dedicated team.

Clear elicitation of your requirements.
Customized writing as per your needs.

We Mirror Your Guidelines to Deliver Quality Services

We write your papers in a standardized way. We complete your work in such a way that it turns out to be a perfect description of your guidelines.

Proactive analysis of your writing.
Active communication to understand requirements.

We Handle Your Writing Tasks to Ensure Excellent Grades

We promise you excellent grades and academic excellence that you always longed for. Our writers stay in touch with you via email.

Thorough research and analysis for every order.
Deliverance of reliable writing service to improve your grades.

Place an Order Start Chat Now

Short Literature Review (READ 3 articles and write a summary)

Subtopic Title

Author Note

What Will You Get?

Premium Quality

Experienced Writers

On-Time Delivery

24/7 Customer Support

Complete Confidentiality

Authentic Sources

Moneyback Guarantee

Order Tracking

Areas of Expertise

Essay

Thesis

Presentation

Dissertation

Term Paper

Research Paper

Book Review

Assignment

Report

Case Study

Letter

Article

Coursework

Speech

Q & A

Critical Thinking

Areas of Expertise

Essay

Thesis

Presentation

Dissertation

Term Paper

Research Paper

Book Review

Assignment

Report

Case Study

Letter

Article

Coursework

Speech

Q & A

Critical Thinking

Trusted Partner of 9650+ Students for Writing

Preferred Writer

Grammar Check Report

One Page Summary

Plagiarism Report

Free Features $66FREE

Our Services

Academic Writing

Professional Editing

Thorough Proofreading

Thorough Proofreading

Delegate Your Challenging Writing Tasks to Experienced Professionals

Check Out Our Sample Work

It May Not Be Much, but It’s Honest Work!

0+

Happy Clients

0+

Words Written This Week

0+

Ongoing Orders

0%

Customer Satisfaction Rate

Process as Fine as Brewed Coffee

Share Your Requirements

Place Order & Deposit Funds

Release Payment to Your Writer

See How We Helped 9000+ Students Achieve Success

We Analyze Your Problem and Offer Customized Writing

We Mirror Your Guidelines to Deliver Quality Services

We Handle Your Writing Tasks to Ensure Excellent Grades