Upload
others
View
0
Download
0
Embed Size (px)
Citation preview
For peer review only
Social support as a mediator between gambling and
problem behavior among 14- to 16-year-old adolescents
Journal: BMJ Open
Manuscript ID bmjopen-2016-012468
Article Type: Research
Date Submitted by the Author: 30-Apr-2016
Complete List of Authors: Räsänen, Tiina; University of Tampere, School of Health Sciences Lintonen, Tomi; Finnish Foundation for Alcohol Studies Tolvanen, Asko; University of Jyväskylä, Department of Psychology Konu, Anne; University of Tampere, School of Health Sciences
<b>Primary Subject Heading</b>:
Addiction
Secondary Subject Heading: Public health
Keywords: Health policy < HEALTH SERVICES ADMINISTRATION & MANAGEMENT,
Substance misuse < PSYCHIATRY, PUBLIC HEALTH
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open on N
ovember 28, 2020 by guest. P
rotected by copyright.http://bm
jopen.bmj.com
/B
MJ O
pen: first published as 10.1136/bmjopen-2016-012468 on 22 D
ecember 2016. D
ownloaded from
For peer review only
1
Social support as a mediator between gambling and problem behavior among 14- to 16-year-old
adolescents
Tiina Räsänen, Tomi Lintonen, Asko Tolvanen & Anne Konu
Tiina Räsänen: School of Health Sciences, University of Tampere, Finland
Phone: +358 445368416
Email: [email protected]
Tomi Lintonen: Finnish Foundation for Alcohol Studies, Helsinki, Finland
Asko Tolvanen: Department of Psychology, University of Jyväskylä, Finland
Anne Konu: School of Health Sciences, University of Tampere, Finland
Word count: 2,965
What is already known on this subject?
Studies have shown that parents, friends, and school all play a crucial role in adolescents’ problem
behavior and gambling, but the role of social support in the association between problem behavior
and gambling frequency has not been investigated.
What this study adds?
Social support from parents, friend and school was associated with problem behavior, and problem
behavior and social support were significantly related to gambling. Social support also mediated the
relations between gambling and problem behavior among girls and boys. These mediation effects
have theoretical importance as well as significant implications for intervention.
Abstract: Background: During the adolescent period, risk-taking behavior increases. These behaviours can
compromise the successful transition from adolescence to adulthood The purpose of this study was to
examine social support as a mediator of the relation between problem behavior and gambling frequency
among Finnish adolescents. Methods: Data were obtained from the national School Health Promotion Study
(SHPS) from the years 2010 and 2011 (N = 102,545). Adolescents were classified in the most homogenous
groups based on their problem behavior via latent class analysis. Results: Path analysis indicated that social
support was associated with problem behavior, and problem behavior and social support were significantly
related to gambling. Social support also mediated the relations between gambling and problem behavior
among girls and boys. Conclusion: Problem behavior may affect gambling through social support from
school, friends, and parents. Thus prevention and intervention strategies should focus on strengthening
Page 1 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
2
adolescents’ social support. In addition, because of the clustering of different problem behaviors instead of
concentrating on a single form of problem behavior multiple-behavior interventions may have a much
greater impact on public health.
Keywords: gambling frequency, adolescents, social support, problem behaviour
Strengths and limitations of this study
• large scale, population-based study explored the relationship between gambling, problem behavior
and social support
• studies that have assessed gambling, problem behavior, and risk/protective factors concurrently, a
limited number of problem behaviors have been examined and studies have concentrated on parental
monitoring excluding social support
• temporal relationship between these factors remains unclear, because of the cross-sectional nature of
the study
• it may be that the final sample did not include the adolescents who were engaging in the highest
levels of gambling and the highest levels of problem behaviour
• since this study was based solely on adolescent self-reports, there is the possibility of over or under-
reporting
Introduction
During the adolescent period, risk-taking behavior increases. [1] Risk-taking includes behaviors that are done
under one’s own volition, have uncertain outcomes, and can compromise the successful transition from
adolescence to adulthood. [2,3] Risk-taking behaviors also manifest in the form of problem behaviors;
actions that are socially disapproved and result in social sanctions. These behaviors can co-occur; thus,
involvement in one problem behavior increases the risk of involvement in other problem behaviors, which is
known as problem behavior syndrome.[4,5] Gambling may be a component of problem behavior syndrome
as gambling is associated with conduct disorder, substance use, and delinquency.[6–9]
Page 2 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
3
According to problem behavior theory, it is the balance between protective and risk factors that determines
ones’ involvement in problem behavior. [5] On form of protective factor can be parents’ closeness and
caring, teachers’ interest in their students, and friends’ supportiveness [10]. Studies have shown that social
support from parents, friends, and school all play a crucial role in adolescents’ problem behaviour. [11–13]
There is also some evidence indicating that family characteristics influence adolescents’ gambling.[14]
Specifically, higher levels of parental attachment, monitoring, and supervision are linked to decreased
gambling, while lower levels of parental trust and communication are associated with increased
gambling.[15] Low levels of parental monitoring of adolescents is also associated with problem gambling
during young adulthood. [16] Additionally, adolescent problem gamblers tend to perceived lower levels of
familial and peer support.[17] While previous studies have examined the associations between gambling,
problem behaviors, and parenting concurrently, the findings of these studies do not provide evidence that
parental supervision or monitoring are related to gambling.[18,19] Moreover, friends’ approval of gambling,
associating with deviant peers, associating with friends who gamble, and having friends who have gambling
problems are associated with adolescent gambling.[8,20,21] However, school characteristics, such as
suspension rates, low school commitment, and schools’ rewards for prosocial involvement are either weakly
or not associated with gambling.[22,23]
In studies that assess gambling, problem behavior, and risk/protective factors concurrently, a limited number
of problem behaviors (e.g., gambling, substance use, and delinquency) are examined, and the focus is on
parental monitoring, individual factors (impulsivity, moral disengagement), and peer
delinquency[18,19,24,25], thereby excluding indicators of social support. As a result, the role of social
support in the association between problem behavior and gambling has not been investigated. Additionally,
the primary focus has been on boys’ gambling, thereby neglecting girls’ gambling.[19,25] Therefore, using a
population-based survey of 8th and 9th grade boys and girls, the aim of this study was to investigate the
relations between gambling frequency and problem behavior, and social support as a potential mediator of
this association (i.e., serve as a protective factor). It is assumed that higher social support would be
negatively associated with problem behavior and gambling.
Page 3 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
4
Method
Setting
In Finland, compulsory basic comprehensive school starts at age 7 (1st grade) and ends at the age of 16 (9th
grade). During the 8th and 9th grade boys and girls are between 14- to 16-years of age.
The Finnish gambling system is based on a state monopoly; the profits are returned to society and used for
common good. Thus, the general attitude about gambling among Finns are positive [26]. In addition, the
games are widely available in public places. The gambling age limit was set to 18 years in October 2010.
The limit was also applied to slot machines in July 2011, and prior to that the age limit was age 15. At the
time of survey completion, the age limit for gambling was 18 years, and 15 years for slot machines.
Data
Data were obtained from the national School Health Promotion Study (SHPS) in 2010 and 2011, which
included questions on adolescents’ gambling, problem behavior, and social support. In 2010, the study was
conducted in southern, eastern and northern Finland and in western and central Finland in 2011. Thus, the
2010 and 2011 surveys cover all of Finland. In 2010, 78% of Finnish 8th and 9
th graders were surveyed, and
in 2011 81% of Finnish 8th and 9th graders participated in the study. SHPS was approved by the ethical
committee of Tampere University Hospital. SHPS is a cross-sectional survey administered throughout the
school day in the 8th and 9
th grades of lower secondary schools. In total, 102,545 8
th (mean age = 14.9, SD =
0.4) and 9th (mean age = 15.9, SD = 0.4) grade students participated in the study. Forty-nine percent of
survey respondents were boys.
Measures
Problem behavior
Problem behavior was measured through 11 different forms of problem behaviors concerning adolescents’
truancy, bullying, delinquency, smoking, using snuff, alcohol drinking, drunkenness-related drinking, using
alcohol and medicine for intoxication, using medicine for intoxication, glue-sniffing and drug use. More
detailed information about questions regarding problem behavior can be found elsewhere (Räsänen,
Lintonen, & Konu, 2015). Because problem behavior indicator included measures with multiple behavior
Page 4 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
5
types and responses, which were not necessarily identically scaled, latent classes were estimated. Based on
latent class analysis (LCA) adolescents were divided into four groups. From these groups those who
participated in problem behavior the most and the least were selected from the data to study extremities of
the problem behavior phenomenon.
Social support from friends
Social support from friends were requested by question: Do you have at this moment any close friend whom
you can talk with confidentially almost everything? Alternatives were I do not have any friends, one close
friend, two close friends and several close friends.
Social support from school
Social support from school based on three statements and two questions about schools’ and teachers’
support. Statements were: teachers encourage me to impress my own opinions at classes, teachers are
interested about how I am doing and teachers are treating students fairly. The scale for these was totally
agree, agree, disagree and totally disagree. Students were also asked: do you have troubles getting along with
your teachers. Alternatives were not at all, fairly little, fairly much and very much. As well adolescents were
requested if they had troubles with school work, how often they got help from school. Alternatives were
always when I need it, most of the time, rarely and almost never. All of the statements and questions were
coded from one to four, four indicating good social support. From these five variables the sum variable was
created, which had one component structure with Cronbach’s alpha value of 0.7.
Social support from parents
Social support was examined by four questions. Students were asked do their parents know all of his/her
friends. This question had alternatives both parent do (coded as three), only mother/father knows (coded as
one) and neither of them do not know (coded as zero). Second question was, do your parent know where you
spent your Friday and Saturday evenings, which had alternatives they know always (coded as three), know
sometimes (coded as one) and most of the time do not know (coded as zero). Adolescents were also asked
can they talk with their parents: almost never (coded as zero), sometimes (coded as one), fairly often (coded
Page 5 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
6
as two) and often (coded as three). The last question was if adolescents had troubles with school work, how
often they got help from home. Alternatives were always when I need it (coded as three), most of the time
(coded as two), rarely (coded as one) and almost never (coded as zero). These four questions measuring the
social support from parents had one component structure, which had Cronbach’s alpha value of 0.6.
Gambling
Gambling was requested by one question: How often do you gamble? Alternatives were on 6–7 days per
week, on 3–5 days per week, on 1–2 days per week, less than once a week, less than once a month, I have
not gambled during previous year’.
Statistical analysis
Basic statistical analyses were conducted with IBM SPSS Statistics 22, and structural equation modelling
was conducted with Mplus 7.0.[28] Basic statistical analyses included a χ2-test (for categorical data) and
Mann–Whitney U test (for continuous data), which are used to detect statistically significant difference
between two or more groups. Latent class analysis (LCA) was used to identify groups of adolescents based
on their involvement in different problem behaviors. The purpose was to identify the most homogenous
groups that include extreme classes of problem behavior. LCA provides fit statistics and significance tests to
assess the number of classes that best fit the data.[29] To select the number of classes for the model, the
analysis was first run with one class, then with two and three classes, and so on. This procedure was
followed until to the highest possible number of classes were run (which was in this case 11). Model
solutions were assessed by examining the entropy values (near 1.0), the Lo–Mendell–Rubin test (a p value
that provides information about statistically significant improvement in fit for the inclusion of an additional
class) as well as the interpretation of the results.[30] For further analysis, all individuals were classified into
classes where class membership was based on the highest posterior probabilities.
Based on the LCA results, path analysis was conducted for those who participated in the most and the least
problem behaviors. The analysis was conducted to examine if social support mediates the association
between problem behavior and gambling. In this model, gambling frequency was regressed on the three
Page 6 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
7
forms of social support, and forms of social support were then regressed on problem behavior (Figure 1).
Analyses were run separately for 8th and 9th grade girls and boys given the possible differences in the relation
between gambling and problem behavior. All the models were saturated, so the model fits were necessarily
perfect.
Results
LCA
Adolescents who did not gamble during the previous year (37.3%) or had missing values on the main
outcome variable (1.3%) were excluded. This was done because we were only interested in adolescents who
were gambling. For the remaining 62,956 individuals, LCA was conducted separately for 8th and 9
th grade
girls and boys to identify groups of adolescents based on their problem behaviors. For all 8th and 9
th grade
girls and boys, the optimal model had four classes with entropy values ranging from 0.88 to 0.83. The
reasonably high entropies and the Lo–Mendell–Rubin test p values suggested a good model fit for the four
class model. However, among 8th grade girls and 9th grade boys, the p values were lower than 0.05,
indicating that the five or more class model was a better fit. However, after taking into account the entropies
and the interpretation of the results, the four class model was chosen for all participants (Table 1).
Class 1 included adolescents who participated regularly in all form of problem behaviors. Youths in class 2
also participated in problem behavior, but their participation was irregular. In addition, most of youths in
class 2 did not use alcohol with medicine for intoxication, use medicine for intoxication, and did not
participate in glue sniffing. In class 3, adolescents smoked tobacco less often than once a week and
consumed alcohol only a couple of times a month. The youths in class 4 did not participate in problem
behavior. From these groups, class 1 and class 4 were selected, which allowed for the study of the extremes
of problem behavior (N = 29,870).
Gambling, problem behavior and social support
The next set of analyses compared the adolescents who participated in the most problem behavior and the
adolescents that participated in the least problem behavior. Boys gambled more than girls did (χ2 (4) =
Page 7 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
8
3280.182, p < 0.001); however, participation in problem behavior was more common among girls (χ2 (1) =
1313.636, p < 0.001) (Table 2). Girls experienced more social support from friends (χ2 (4) = 553.19, p <
0.001), and boys received more support from school (U = 88080721, p < 0.001) and from parents (U =
84026360, p < 0.001) (Table 2). Among boys and girls, 9th graders gambled (boys: χ
2 (4) = 45.969, p <
0.001), (girls: χ2 (4) = 25.416, p < 0.001) and participated in problem behavior (boys: χ2 (1) = 126.024, p <
0.001), (girls: χ2 (1) = 367.030, p < 0.001) more often than 8th graders. Eighth grade boys also experienced
more social support from friends (χ2 (3) = 25.933), p < 0.001), school (U = 52467017.0, p < 0.01), and
parents (51780278.5, p < 0.001) than 9th grade boys. Eighth grade girls experienced more social support from
school (U = 9696512.5, p < 0.001) and parents (U = 9817557.0, p < 0.01), but there were no statistical
differences in social support from friends (Table 2). Of the 50% of 8th grade girls and 74% of 9
th grade girls
who gambled on a weekly basis also participated in problem behavior. Among the boys, the percentage was
14% for 8th graders and 22% for 9
th graders (Table 2).
Path analysis
The standardized parameter estimates (β) shown in Table 3 indicated that problem behavior was significantly
and positively related to adolescents’ gambling frequency (path c). The beta indices also showed that there
was a significant negative association between problem behavior and the different types of social support;
however, among 9th grade girls, social support from friends was not statistically significant (paths d–f).
Social support from parents and school were negatively related with gambling (paths g and i). Among boys,
social support from friends was significant and positively associated with gambling; however, among girls
social support from friends was significantly and negatively associated with gambling (path h) (Table 3; also
see Figure 1).
The statistically significant albeit very small indirect effects indicated that social support mediated the
relationship between problem behavior and gambling frequency, but social support from friends did not
mediate this association in 9th grade girls. The total effect of problem behavior on problem gambling
frequency consisted of a direct effect and an indirect effect through social support (Table 3). Forty-two
percent and 49% of the variance (R2) was explained by the association between gambling and social support
Page 8 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
9
for 8th grade and 9
th grade boys, respectively. For 8
th grade girls, 63% of the variance was explained and 69%
of the variance was explained for 9th graders.
Discussion
This large scale, population-based study explored the relationship between gambling, problem behavior and
social support among 14- to 16-year-old adolescents. The main purpose of the study was to examine whether
social support would mediate this association. Social support from parents, friends, and school mediated the
relations between gambling and problem behavior among girls and boys (except social support from friends
among 9th grade girls). Thus, the data suggest that the relation between problem behavior and gambling is
explained by the degree of social support received from school, friends, and parents.
Similar to the Mun et al. 2008 research, this study indicated that problem behavior did cluster at the both
ends of the lifestyle spectrum (i.e., “problem” or “non-problem” behavior patterns among adolescents).
Within these two classes, there were adolescents who participated regularly in all forms of problem
behaviors and those who did not participate in any problem behaviors. Additionally, this study found that
problem behavior and gambling were associated, with problem behavior increasing as the frequency of
gambling increased. This is similar to previous studies.[7,19,25] These results may indicate that involvement
in one problem behavior also increases the risk of involvement in other problem behaviors, as demonstrated
by problem behavior theory.[4,10]
To the best of our knowledge, this is the first study to examine whether social support from school is
associated with gambling frequency. Earlier studies have assessed school characteristics, such as suspension
rates, school commitment, and schools’ rewards for prosocial involvement.[22,23] In the current study,
social support from school was significantly related to gambling frequency, with lower support related to
higher gambling participation. In addition, low social support from parents and friends was related to
increased gambling, which is consistent with the findings of Hardoon et al. [17]. In their study, they reported
significant differences between gambling severity groups in their levels of family and peer support.
Specifically, their results indicated that non-gamblers and social gamblers experienced more social support
Page 9 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
10
than at-risk and pathological gamblers. However, in the current study, this pattern was found only for female
adolescent gamblers. For boys, social support from friends was positively related to gambling frequency. It
might be that gambling is social activity for boys, but for girls gambling may be an activity that substitutes
normal social contacts. There also can be differences between problem and social gambling[31] among boys
and girls. Problem gambling may occur in the absence of friends, whereas non-problematic gambling may be
part of a social pastime.[17] Gambling was more common among boys, which is consistent with previous
studies[6,20]; however, over 50% of 8th grade and 74% of 9
th grade girls who gambled on a weekly basis
participated in problem behavior. This indicates that active gambling among girls is a phenomenon that
should be studied more extensively.
Although the findings of this study indicated that social support mediated the association between problem
behavior and gambling frequency, the temporal relationship between these factors remains unclear. Thus,
additional research is needed using longitudinal data. Additionally, it is important to note that while social
support from friends, parents, and school were significantly associated with gambling, the path coefficients
were low among boys and girls. Furthermore, path coefficients for the indirect effects were low. This may
indicate that social support does not play a large in the association between problem behavior and gambling.
There may be additional factors that play a more important role in this association, such as having friends or
parents who: gamble, have a gambling problem, or participate in other problem behaviors. These types of
factors have been examined in previous studies.[8,15,20,21]
Furthermore, gambling frequency was assessed by a single item, and there was not a validated problem
gambling screen used herein. However, the goal of the study was to study gambling involvement and its
associations with problem behaviors and social support, not to identify problem gamblers. The survey did not
collect additional information on gambling behavior (e.g., how much money is spent on gambling), nor was
information about gambling types.[27,32]
In addition, data were collected from 78% of Finnish 8th and 9th graders in 2010 and from 81% of Finnish
8th and 9th graders in 2011. However, it may be that the final sample did not include the adolescents who
were engaging in the highest levels of gambling and the highest levels of problem behavior. Moreover, since
this study was based solely on adolescent self-reports, there is the possibility of over or under-reporting.
Page 10 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
11
Despite the limitations, mediation effects were detected, which have theoretical importance as well as
significant implications for intervention. Specifically, prevention and intervention strategies should focus on
strengthening adolescents’ social support. In addition, because of the clustering of different problem
behaviors and the fact that problem behavior was linked to gambling, instead of concentrating on a single
form of problem behavior multiple-behavior interventions may have a much greater impact on public
health.[33]
Contributorship statemen: Study conception and design: Räsänen, Tolvanen, Lintonen, Konu; Analysis
and interpretation of data: Räsänen, Tolvanen, Lintonen, Konu; Drafting of manuscript: Räsänen; Critical
revision: Tolvanen, Lintonen, Konu
Competing interests: None declared.
Funding: This study was financially supported by the Finnish Foundation for Alcohol Studies. The Finnish
Foundation for Alcohol Studies had no involvement in the study design, data handling, writing or submission
of the manuscript. The grants awarded by the Finnish Foundation for Alcohol Studies for gambling research
are based on a government contract for studying gambling-related harm.
Data sharing statement: No additional data available.
1 Michael K, Ben-Zur H. Risk-taking among adolescents: associations with social and affective factors.
J Adolesc 2007;30:17–31.
2 Igra V, Irwin CE. Theories of Adolescent Risk-Taking Behavior. In: R. J. DiClemente, W. B. Hansen
&, Ponton LE, eds. Handbook of adolescent health risk behaviour. New York: : Plenum Press 1996.
35–51.
3 Leather NC. Risk-taking behaviour in adolescence: a literature review. J Child Health Care
2009;13:295–304.
4 Jessor R, Jessor SL. Problem behavior and psychosocial development: A longitudinal study of youth.
Page 11 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
12
New York: : Academic Press 1977.
5 Jessor R, Turbin MS. Parsing protection and risk for problem behavior versus pro-social behavior
among US and Chinese adolescents. J Youth Adolesc 2014;43:1037–51.
6 Barnes GM, Welte JW, Hoffman JH, et al. Gambling, alcohol, and other substance use among youth
in the United States. J Stud Alcohol Drugs 2009;70:134–42.
7 Cheung NWT. Low self-control and co-occurrence of gambling with substance use and delinquency
among Chinese adolescents. J Gambl Stud 2014;30:105–24.
8 Gori M, Potente R, Pitino A, et al. Relationship Between Gambling Severity and Attitudes in
Adolescents: Findings from a Population-Based Study. J Gambl Stud 2014;31:717–40.
9 Lau M, Kan M yue. Prevalence and correlates of problem behaviors among adolescents in Hong
Kong. Asia Pac J Public Health 2010;22:354–64.
10 Jessor R, Turbin MS, Costa FM, et al. Adolescent Problem Behavior in China and the United States:
A Cross-National Study of Psychosocial Protective Factors. J Res Adolesc 2003;13:329–60.
11 Deković M. Risk and Protective Factors in the Development of Problem Behavior During
Adolescence. J Youth Adolesc;28:667–85.
12 Fleming CB, Catalano RF, Haggerty KP, et al. Relationships between level and change in family,
school, and peer factors during two periods of adolescence and problem behavior at age 19. J Youth
Adolesc 2010;39:670–82.
13 Garnefski N, Diekstra RF. Perceived social support from family, school, and peers: relationship with
emotional and behavioral problems among adolescents. J Am Acad Child Adolesc Psychiatry
1996;35:1657–64.
14 McComb JL, Sabiston CM. Family influences on adolescent gambling behavior: a review of the
literature. J Gambl Stud 2010;26:503–20.
15 Magoon ME, Ingersoll GM. Parental Modeling, Attachment, and Supervision as Moderators of
Page 12 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
13
Adolescent Gambling. J Gambl Stud 2006;22:1–22.
16 Lee GP, Stuart EA, Ialongo NS, et al. Parental monitoring trajectories and gambling among a
longitudinal cohort of urban youth. Addiction 2014;109:977–85.
17 Hardoon KK, Gupta R, Derevensky JL. Psychosocial variables associated with adolescent gambling.
Psychol Addict Behav 2004;18:170–9.
18 Barnes GM, Welte JW, Hoffman JH, et al. Shared predictors of youthful gambling, substance use,
and delinquency. Psychol Addict Behav 2005;19:165–74.
19 Wanner B, Vitaro F, Carbonneau R, et al. Cross-lagged links among gambling, substance use, and
delinquency from midadolescence to young adulthood: additive and moderating effects of common
risk factors. Psychol Addict Behav 2009;23:91–104.
20 Castrén S, Grainger M, Lahti T, et al. At-risk and problem gambling among adolescents: a
convenience sample of first-year junior high school students in Finland. Subst Abuse Treat Prev
Policy 2015;10:1–10.
21 Hanss D, Mentzoni RA, Blaszczynski A, et al. Prevalence and Correlates of Problem Gambling in a
Representative Sample of Norwegian 17-Year-Olds. J Gambl Stud Published Online First: 12 March
2014. doi:10.1007/s10899-014-9455-4
22 Martins SS, Lee GP, Kim JH, et al. Gambling and sexual behaviors in African-American adolescents.
Addict Behav 2014;39:854–60.
23 Scholes-Balog KE, Hemphill SA, Dowling NA, et al. A prospective study of adolescent risk and
protective factors for problem gambling among young adults. J Adolesc 2014;37:215–24.
24 Barnes GM, Welte JW, Hoffman JH, et al. The co-occurrence of gambling with substance use and
conduct disorder among youth in the United States. Am J Addict 1999;20:166–73.
25 Vitaro F, Brendgen M, Ladouceur R, et al. Gambling, delinquency, and drug use during adolescence:
mutual influences and common risk factors. J Gambl Stud 2001;17:171–90.
Page 13 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
14
26 Salonen A, Raisamo S. Suomalaisten rahapelaaminen 2015 - Rahapelaaminen, rahapeliongelmat ja
rahapelaamiseen liittyvät asenteet ja mielipiteet 15-74-vuotiailla. 2015.
27 Räsänen T, Lintonen T, Konu A. Gambling and Problem Behavior Among 14- to 16-Year-Old Boys
and Girls in Finland. J Gambl Issues 2015;31:1–22.
28 Muthén LK, Muthén BO (1998-2015). Mplus User’s Guide. Seventh Edition. Los Angeles, CA: 2015.
29 Nylund KL, Asparouhov T, Muthén BO. Deciding on the number of classes in latent class analysis
and growth mixture modeling: A Monte Carlo simulation study. Struct Equ Model 2007;14:535–69.
30 Jung T, Wickrama KAS. An Introduction to Latent Class Growth Analysis and Growth Mixture
Modeling. Soc Personal Psychol Compass 2008;2:302–17.
31 Derewensky JL. Teen gambling: Understanding a growing epidemic. New York: : Rowman &
Littlefield Publishing 2012.
32 Räsänen T, Lintonen T, Joronen K, et al. Girls and boys gambling with health and well-being in
Finland. J Sch Health 2015;85:214–22.
33 Nigg CR, Allegrante JP, Ory M. Theory-comparison and multiple-behavior research: common themes
advancing health behavior research. Health Educ Res 2002;17:670–9.
Page 14 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
15
Table 1. Results for the latent class analysis (LCA).
8th grade boys 9
th grade boys 8
th grade girls 9
th grade girls
1 class model
n for classes 19,471 21,711 9,432 12,342
entropy na. na. na. na.
2 class model
n for classes (bolding for those
participating in
problem behavior
the most and the
least)
c1=6,805
c2=12,666 c1=25,768
c2=37,188 c1=3,591
c2=5,841
c1=5,445
c2=6,897
entropy 0.86 0.85 0.86 0.82
Lo-Mendell-Rubin
test 1vs2 class
0.00 0.00 0.00 0.00
3 class model
n for classes
(bolding for those
participating in
problem behavior
the most and the least)
c1=1,975
c2=6,813
c3=10,683
c1=9,482
c2=26,304
c3=27,170
c1=1,734
c2=3,706
c3=3,992
c1=2,645
c2=3,707
c3=5,990
entropy 0.90 0.89 0.88 0.88
Lo-Mendell-Rubin
test 2vs3 class
0.00 0.00 0.00 0.00
4 class model
n for classes
(bolding for those
participating in problem behavior
the most and the
least)
c1=586
c2=5,377
c3=3,065
c4=10,443
c1=911
c2=4,734
c3=7,233
c4=8,833
c1=513
c2=2,123
c3=3,240
c4=3,556
c1=1,473
c2=4,145
c3=3,169
c4=3,555
entropy 0.88 0.86 0.86 0.83
Lo-Mendell-Rubin
test 3vs4 class
0.04 0.00 0.00 0.00
5 class model
n for classes
(bolding for those
participating in problem behavior
the most and the
least)
c1=567
c2=2,829
c3=4,543 c4=2,956
c5=8,576
c1=503
c2=2,290
c3=6,086 c4=4,142
c5=8,690
c1=138
c2=1,165
c3=1,641 c4=3,013
c5=3,475
c1=159
c2=1,910
c3=2,865 c4=3,543
c5=3,865
entropy 0.81 0.85 0.86 0.84
Lo-Mendell-Rubin
test 4vs5 class
0.70 0.00 0.00 0.76
Page 15 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
16
Table 2. Adolescents’ involvement in gambling and problem behavior, and experiencing social support from
friends (SSF),
school (SSS)
and parents
(SSP) based
on their sex and
grade.
8th grade
boys
9th grade
boys
8th grade
girls
9th grade
girls %
Gambling
less than once
a month
38.4 34.1 73.7 69.9
less than once
a week
28.8 30.3 15.7 18.1
1–2 days per
week
18.7 19.6 5.0 6.2
3–5 days per
week
8.1 9.3 2.2 3.0
6–7 days per
week
6.1 6.8 3.4 2.8
Participating
in problem
behavior
5.3 9.3 12.6 29.3
SSF
do not have any friends
13.7 15.3 7.1 6.7
one close friend
24.1 26.0 20.7 21.6
two close
friends
20.5 19.1 27.5 27.2
several close
friends
40.9 39.0 44.5 44.3
missing values 0.8 0.7 0.2 0.3
x, (SD)
SSS 2.8 (0.5) 2.7 (0.6) 2.7 (0.5) 2.7 (0.6)
SSP 2.2 (0.6) 2.2 (1.2) 2.1 (0.7) 2.0 (0.7)
n 11,029 9,744 4,069 5,028
Page 16 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
17
Table 3.
Path model
of the direct
and indirect
effects
between the
social
support from
friends (ssf),
school (sss),
parents (ssp),
problem
behavior (pb)
and
gambling
frequency
(gb) among
8th and 9
th grade boys and girls.
** p<0.01, ***p<0.001
8
th grade boys 9
th grade boys 8
th grade girls 9
th grade girls
β β β β
Direct effect c (pb to gb) 0.35*** 0.36*** 0.34*** 0.36***
Path from pb to sss (path e) -0.30*** -0.36*** -0.43*** -0.46***
Path from pb to ssf (path d) -0.09*** -0.07*** -0.08*** -0.01
Path from pb to ssp (path f) -0.37*** -0.39*** -0.19*** -0.50***
Path from sss to gb (path h) -0.11*** -0.13*** -0.06** -0.11***
Path from ssf to gb (path g) 0.07*** 0.04*** -0.08*** -0.09***
Path from ssp to gb (path i) -0.09*** -0.08*** -0.10*** -0.06***
Total effect c’ (pb to gb) 0.41*** 0.43*** 0.42*** 0.44***
Total indirect effect c-c’ 0.06*** 0.07*** 0.08*** 0.08***
Path from pb to sss to gb 0.03*** 0.05*** 0.03** 0.05***
Path from pb to ssf to gb -0.01*** -0.00*** 0.01*** 0.00
Path from pb to ssp to gb 0.03*** 0.03*** 0.05*** 0.03***
Page 17 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
18
Figure 1. Path model of the associations between the social support from friends (SSF), school (SSS), parents
(SSP), problem behavior and gambling frequency among 8th and 9
th grade boys and girls.
d g
e h
f i
c
Problem
behavior
SSF
Gambling
frequency SSS
SSP
Page 18 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
1
STROBE Statement—checklist of items that should be included in reports of observational studies
Item
No Recommendation
Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract
page 1
(b) Provide in the abstract an informative and balanced summary of what was done
and what was found -page 1
Introduction
Background/rationale 2 Explain the scientific background and rationale for the investigation being reported
pages 2-3
Objectives 3 State specific objectives, including any prespecified hypotheses page 3
Methods
Study design 4 Present key elements of study design early in the paper pages 4-5
Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment,
exposure, follow-up, and data collection page 3
Participants 6 (a) Cohort study—Give the eligibility criteria, and the sources and methods of
selection of participants. Describe methods of follow-up
Case-control study—Give the eligibility criteria, and the sources and methods of
case ascertainment and control selection. Give the rationale for the choice of cases
and controls
Cross-sectional study—Give the eligibility criteria, and the sources and methods of
selection of participants pages 3-4
(b) Cohort study—For matched studies, give matching criteria and number of
exposed and unexposed
Case-control study—For matched studies, give matching criteria and the number of
controls per case
Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect
modifiers. Give diagnostic criteria, if applicable page 4, sup.material
Data sources/
measurement
8* For each variable of interest, give sources of data and details of methods of
assessment (measurement). Describe comparability of assessment methods if there
is more than one group sup. material
Bias 9 Describe any efforts to address potential sources of bias none
Study size 10 Explain how the study size was arrived at pages 3-4
Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable,
describe which groupings were chosen and why sup. material 4-5
Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding,
4-5
(b) Describe any methods used to examine subgroups and interactions
(c) Explain how missing data were addressed
(d) Cohort study—If applicable, explain how loss to follow-up was addressed
Case-control study—If applicable, explain how matching of cases and controls was
addressed
Cross-sectional study—If applicable, describe analytical methods taking account of
sampling strategy
(e) Describe any sensitivity analyses
Continued on next page
Page 19 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
2
Results
Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible,
examined for eligibility, confirmed eligible, included in the study, completing follow-up, and
analysed
(b) Give reasons for non-participation at each stage
(c) Consider use of a flow diagram
Descriptive
data
14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information
on exposures and potential confounders
(b) Indicate number of participants with missing data for each variable of interest
(c) Cohort study—Summarise follow-up time (eg, average and total amount)
Outcome data 15* Cohort study—Report numbers of outcome events or summary measures over time
Case-control study—Report numbers in each exposure category, or summary measures of
exposure
Cross-sectional study—Report numbers of outcome events or summary measures page 14
Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their
precision (eg, 95% confidence interval). Make clear which confounders were adjusted for and
why they were included
(b) Report category boundaries when continuous variables were categorized
(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful
time period
Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity
analyses 4-5
Discussion
Key results 18 Summarise key results with reference to study objectives 7-9
Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision.
Discuss both direction and magnitude of any potential bias 8-9
Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity
of analyses, results from similar studies, and other relevant evidence 8
Generalisability 21 Discuss the generalisability (external validity) of the study results 8
Other information
Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable,
for the original study on which the present article is based page 9
*
Page 20 of 20
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
Social support as a mediator between gambling and
problem behaviour – a cross-sectional study among 14- to
16-year-old Finnish adolescents
Journal: BMJ Open
Manuscript ID bmjopen-2016-012468.R1
Article Type: Research
Date Submitted by the Author: 28-Jul-2016
Complete List of Authors: Räsänen, Tiina; University of Tampere, School of Health Sciences Lintonen, Tomi; Finnish Foundation for Alcohol Studies Tolvanen, Asko; University of Jyväskylä, Department of Psychology
Konu, Anne; University of Tampere, School of Health Sciences
<b>Primary Subject Heading</b>:
Addiction
Secondary Subject Heading: Public health
Keywords: Health policy < HEALTH SERVICES ADMINISTRATION & MANAGEMENT, Substance misuse < PSYCHIATRY, PUBLIC HEALTH
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open on N
ovember 28, 2020 by guest. P
rotected by copyright.http://bm
jopen.bmj.com
/B
MJ O
pen: first published as 10.1136/bmjopen-2016-012468 on 22 D
ecember 2016. D
ownloaded from
For peer review only
1
Social support as a mediator between gambling and problem behaviour – a cross-sectional study
among 14- to 16-year-old Finnish adolescents
Tiina Räsänen, Tomi Lintonen, Asko Tolvanen & Anne Konu
Tiina Räsänen: School of Health Sciences, University of Tampere, Finland
Phone: +358 445368416
Email: [email protected]
Tomi Lintonen: Finnish Foundation for Alcohol Studies, Helsinki, Finland
Asko Tolvanen: Department of Psychology, University of Jyväskylä, Finland
Anne Konu: School of Health Sciences, University of Tampere, Finland
Word count:
Abstract: Background: During the adolescent period, risk-taking behaviour increases. These behaviours can
compromise the successful transition from adolescence to adulthood. The purpose of this study was to
examine social support as a mediator of the relation between problem behaviour and gambling frequency
among Finnish adolescents. Methods: Data were obtained from the national School Health Promotion Study
(SHPS) from the years 2010 and 2011 (N = 102,545). Adolescents were classified in the most homogenous
groups based on their problem behaviour via latent class analysis. Results: Path analysis indicated that social
support was negatively associated with problem behaviour, and problem behaviour and social support were
negatively related (except for social support from friends among boys) to gambling. Social support mediated,
albeit weakly, the relations between gambling and problem behaviour among girls and boys. Conclusion:
Problem behaviour may affect gambling through social support from school, friends, and parents. Thus
prevention and intervention strategies should focus on strengthening adolescents’ social support. In addition,
because of the clustering of different problem behaviours instead of concentrating on a single form of
problem behaviour multiple-behaviour interventions may have a much greater impact on public health.
Keywords: gambling frequency, adolescents, social support, problem behaviour
Page 1 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
2
Strengths and limitations of this study
• large scale, population-based study explored the relationship between gambling, problem behaviour
and social support
• studies have examined pathways from social support to both gambling and other problem
behaviours, but research that tries to explain how adolescents’ access to social support accounts for
the association between gambling frequency and problem behaviour, is lacking
• temporal relationship between these factors remains unclear, because of the cross-sectional nature of
the study
• it may be that the final sample did not include the adolescents who were engaging in the highest
levels of gambling and the highest levels of problem behaviour
• since this study was based solely on adolescent self-reports, there is the possibility of over or under-
reporting
Introduction
During the adolescent period, risk-taking behaviour increases. [1] Risk-taking includes behaviours that are
done under one’s own volition, have uncertain outcomes, and can compromise the successful transition from
adolescence to adulthood. [2,3] Risk-taking behaviours also manifest in the form of problem behaviours;
actions that are socially disapproved and result in social sanctions. These behaviours can co-occur; thus,
involvement in one problem behaviour increases the risk of involvement in other problem behaviours, which
is known as problem behaviour syndrome.[4,5] Gambling may be a component of problem behaviour
syndrome as gambling is associated with conduct disorder, substance use, and delinquency.[6–9] However,
all gambling is not necessary seen as problem behaviour. In 2010 gambling was allowed for adolescents aged
15 and over (except Internet and casino gambling) and in 2011, 15 year olds could legally gamble at slot
machines (all other gambling games had age limit of 18), which are widely available in Finland. Adolescents
have also had positive attitudes towards gambling in Finland [10]. Likewise, studies have shown that parents
and teachers do not think that gambling is great concern among youth. [11,12]
Page 2 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
3
According to problem behaviour theory, it is the balance between protective and risk factors that determines
ones’ involvement in problem behaviour. [5] Social support provided by individuals and institutions can be
described as interpersonal relationships that influence an individual’s functioning. Social support is parents’
closeness, monitoring and caring, teachers’ interest in their students, and friends’ supportiveness [13].
Studies have shown that social support from parents, friends, and school all play a crucial role in
adolescents’ problem behaviour. [14–16] There is also some evidence indicating that family characteristics
influence adolescents’ gambling.[17] Specifically, higher levels of parental attachment, monitoring, and
supervision are linked to decreased gambling, while lower levels of parental trust and communication are
associated with increased gambling.[18] Low levels of parental monitoring of adolescents is also associated
with problem gambling during young adulthood. [19] Additionally, adolescent problem gamblers tend to
perceived lower levels of familial and peer support.[20] While previous studies have examined shared
predictors between gambling, problem behaviours, and parenting, the findings of these studies do not provide
evidence that parental supervision or monitoring are related to gambling as it is the case for other problem
behaviours.[21,22] Moreover, friends’ approval of gambling, associating with deviant peers, associating with
friends who gamble, and having friends who have gambling problems are associated with adolescent
gambling.[8,23,24] However, school characteristics, such as suspension rates, low school commitment, and
schools’ rewards for prosocial involvement are either weakly or not associated with gambling.[25,26]
Earlier studies have demonstrated that there are gender differences in gambling as well as problem
behaviour. For example, gambling is more common among males [27] and males also tend to start gambling
at a younger age. [28] Additionally, males have a higher risk for heavy alcohol use and smoking. [29,30]
However, little is known about gender differences in relation to co-occurrence of gambling frequency and
problem behaviours. It is also unclear if there are gender differences in associations between gambling,
problem behaviour and social support.
In studies that assess gambling, problem behaviour, and risk/protective factors, a limited number of problem
behaviours (e.g., gambling, substance use, and delinquency) are examined, and the focus is on parental
monitoring, individual factors (impulsivity, moral disengagement), and peer delinquency[21,22,31,32],
thereby excluding social support from important individuals and institutions, like friends and school.
Page 3 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
4
Previous studies have examined pathways from social support to both gambling and other problem
behaviours, but research that tries to explain how adolescents’ access to social support accounts for the
association between gambling frequency and problem behaviour, is lacking. Thus, the role of social support
in the association between problem behaviour and gambling has not been investigated. As earlier studies
have shown that gambling is associated with problem behaviour and the degree of social support that
adolescent receives is related to both gambling frequency and problem behaviour, it is reasonable to expect
that social support plays an important role in the extent to which problem behaviours are related to gambling
frequency. Therefore, using a population-based survey of 8th and 9th grade boys and girls, the aim of this
study was to investigate the relations between gambling frequency and problem behaviour, and social
support as a potential mediator of this association (i.e., serve as a protective factor). It is assumed that higher
social support would be negatively associated with problem behaviour and gambling.
Method
Setting
In Finland, compulsory basic comprehensive school starts at age 7 (1st grade) and ends at the age of 16 (9th
grade). During the 8th and 9th grade boys and girls are between 14- to 16-years of age.
The Finnish gambling system is based on a state monopoly; the profits are returned to society and used for
common good. In addition, the games are widely available in public places. The gambling age limit was set
to 18 years in October 2010. The limit was also applied to slot machines in July 2011, and prior to that the
age limit was age 15. At the time of survey completion, the age limit for gambling was 18 years, and 15
years for slot machines.
Data
Data were obtained from the national School Health Promotion Study (SHPS) in 2010 and 2011, which
included questions on adolescents’ gambling, problem behaviour, and social support. In 2010, the study was
conducted in southern, eastern and northern Finland and in western and central Finland in 2011. Thus, the
2010 and 2011 surveys cover all of Finland. In 2010, 78% of Finnish 8th and 9
th graders were surveyed, and
Page 4 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
5
in 2011 81% of Finnish 8th and 9
th graders participated in the study. SHPS was approved by the ethical
committee of Tampere University Hospital. SHPS is a cross-sectional survey administered throughout the
school day in the 8th and 9th grades of lower secondary schools. Answering was voluntary. Parental consent
was not required according to ethical guidelines in Finland; generally, surveys conducted during school days
do not need parental permission. In total, 102,545 8th (mean age = 14.9, SD = 0.4) and 9th (mean age = 15.9,
SD = 0.4) grade students participated in the study. Forty-nine percent of survey respondents were boys.
Measures
Problem behavior
Problem behavior was measured through 11 different forms of problem behaviors concerning adolescents’
truancy, bullying, delinquency, smoking, using snuff, alcohol drinking, drunkenness-related drinking, using
alcohol and medicine for intoxication, using medicine for intoxication, glue-sniffing and drug use. More
detailed information about questions regarding problem behavior can be found elsewhere. [33] Because
problem behavior indicator included measures with multiple behavior types and responses, which were not
necessarily identically scaled, latent classes were estimated. Based on latent class analysis (LCA) adolescents
were divided into four groups. From these groups those who participated in problem behavior the most and
the least were selected from the data to study extremities of the problem behavior phenomenon.
Social support from friends
Social support from friends were requested by question: Do you have at this moment any close friend whom
you can talk with confidentially almost everything? Alternatives were I do not have any friends, one close
friend, two close friends and several close friends.
Social support from school
Social support from school based on three statements and two questions about schools’ and teachers’
support. Statements were: teachers encourage me to impress my own opinions at classes, teachers are
interested about how I am doing and teachers are treating students fairly. The scale for these was totally
agree, agree, disagree and totally disagree. Students were also asked: do you have troubles getting along with
Page 5 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
6
your teachers. Alternatives were not at all, fairly little, fairly much and very much. As well adolescents were
requested if they had troubles with school work, how often they got help from school. Alternatives were
always when I need it, most of the time, rarely and almost never. All of the statements and questions were
coded from one to four, four indicating good social support. From these five variables the sum variable was
created, which had one component structure with Cronbach’s alpha value of 0.7.
Social support from parents
Social support was examined by four questions. Students were asked do their parents know all of his/her
friends. This question had alternatives both parent do (coded as three), only mother/father knows (coded as
one) and neither of them do not know (coded as zero). Second question was, do your parent know where you
spent your Friday and Saturday evenings, which had alternatives they know always (coded as three), know
sometimes (coded as one) and most of the time do not know (coded as zero). Adolescents were also asked
can they talk with their parents: almost never (coded as zero), sometimes (coded as one), fairly often (coded
as two) and often (coded as three). The last question was if adolescents had troubles with school work, how
often they got help from home. Alternatives were always when I need it (coded as three), most of the time
(coded as two), rarely (coded as one) and almost never (coded as zero). These four questions measuring the
social support from parents had one component structure, which had Cronbach’s alpha value of 0.6.
Gambling
Gambling was requested by one question: How often do you gamble? Alternatives were on 6–7 days per
week, on 3–5 days per week, on 1–2 days per week, less than once a week, less than once a month, I have
not gambled during previous year’.
Statistical analysis
Basic statistical analyses were conducted with IBM SPSS Statistics 22, and structural equation modelling
was conducted with Mplus 7.0.[34] Basic statistical analyses included a χ2-test (for categorical data) and
Mann–Whitney U test (for continuous data), which are used to detect statistically significant difference
between two or more groups. Latent class analysis (LCA) was used to identify groups of adolescents based
on their involvement in different problem behaviours. The purpose was to identify the most homogenous
Page 6 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
7
groups that include extreme classes of problem behaviour. LCA provides fit statistics and significance tests
to assess the number of classes that best fit the data.[35] To select the number of classes for the model, the
analysis was first run with one class, then with two and three classes, and so on. This procedure was
followed until to the highest possible number of classes were run (which was in this case 11). Model
solutions were assessed by examining the entropy values (near 1.0), the Lo–Mendell–Rubin test (a p value
that provides information about statistically significant improvement in fit for the inclusion of an additional
class) as well as the interpretation of the results.[36] For further analysis, all individuals were classified into
classes where class membership was based on the highest posterior probabilities.
Based on the LCA results, path analysis was conducted for those who participated in the most and the least
problem behaviours. The analysis was conducted to examine if social support mediates the association
between problem behaviour and gambling. In this model, gambling frequency was regressed on the three
forms of social support, and forms of social support were then regressed on problem behaviour (Figure 1).
Analyses were run separately for 8th and 9
th grade girls and boys given the possible differences in the relation
between gambling and problem behaviour. All the models were saturated, so the model fits were necessarily
perfect.
Results
LCA
Adolescents who did not gamble during the previous year (37.3%) or had missing values on the main
outcome variable (1.3%) were excluded. This was done because we were only interested in adolescents who
were gambling. For the remaining 62,956 individuals, LCA was conducted separately for 8th and 9th grade
girls and boys to identify groups of adolescents based on their problem behaviours. For all 8th and 9th grade
girls and boys, the optimal model had four classes with entropy values ranging from 0.88 to 0.83. The
reasonably high entropies and the Lo–Mendell–Rubin test p values suggested a good model fit for the four
class model. However, among 8th grade girls and 9
th grade boys, the p values were lower than 0.05,
indicating that the five or more class model was a better fit. However, after taking into account the entropies
and the interpretation of the results, the four class model was chosen for all participants (Table 1).
Page 7 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
8
Class 1 included adolescents who participated in all forms of problem behaviours at the highest frequency
[see 33]. For example, adolescent in class 1 smoked at least daily, drunk alcohol on a weekly basis and had
tried drugs at least once. Youths in class 2 also participated in problem behaviour, but their participation in
problem behaviours was more experimental. In addition, most of youths in class 2 did not use alcohol with
medicine for intoxication, use medicine for intoxication, and did not participate in glue sniffing. In class 3,
adolescents smoked tobacco less often than once a week and consumed alcohol only a couple of times a
month. The youths in class 4 did not participate in any form of problem behaviour. From these groups, class
1 and class 4 were selected, including adolescents participating regularly in all examined problem behaviours
and those not participating in any, which allowed for the study of the extremes of problem behaviour (N =
29,870).
Gambling, problem behaviour and social support
The next set of analyses compared the adolescents who participated in the most problem behaviour and the
adolescents that participated in the least problem behaviour. Boys gambled more than girls did (χ2 (4) =
3280.182, p < 0.001); however, participation in problem behaviour was more common among girls (χ2 (1) =
1313.636, p < 0.001) (Table 2). Girls experienced more social support from friends (χ2 (4) = 553.19, p <
0.001), and boys received more support from school (U = 88080721, p < 0.001) and from parents (U =
84026360, p < 0.001) (Table 2). Among boys and girls, 9th graders gambled (boys: χ
2 (4) = 45.969, p <
0.001), (girls: χ2 (4) = 25.416, p < 0.001) and participated in problem behaviour (boys: χ2 (1) = 126.024, p <
0.001), (girls: χ2 (1) = 367.030, p < 0.001) more often than 8
th graders. Eighth grade boys also experienced
more social support from friends (χ2 (3) = 25.933), p < 0.001), school (U = 52467017.0, p < 0.01), and
parents (51780278.5, p < 0.001) than 9th grade boys. Eighth grade girls experienced more social support from
school (U = 9696512.5, p < 0.001) and parents (U = 9817557.0, p < 0.01), but there were no statistical
differences in social support from friends (Table 2). Among girls who gambled on weekly basis, 50% of 8th
graders and 74% of 9th graders also participated in problem behaviour. Among the boys, the percentage was
14% for 8th graders and 22% for 9
th graders.
Path analysis
Page 8 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
9
The standardized parameter estimates (β) shown in Table 3 indicated that problem behaviour was
significantly and positively related to adolescents’ gambling frequency (path c). The beta indices also
showed that there was a significant negative association between problem behaviour and the different types
of social support; however, among 9th grade girls, social support from friends was not statistically significant
(paths d–f). Social support from parents and school were negatively related with gambling (paths g and i).
Among boys, social support from friends was significant and positively associated with gambling; however,
among girls social support from friends was significantly and negatively associated with gambling (path h)
(Table 3; also see Figure 1).
The statistically significant albeit very small indirect effects indicated that social support mediated the
relationship between problem behaviour and gambling frequency, but social support from friends did not
mediate this association. The total effect of problem behaviour on problem gambling frequency consisted of
a direct effect and an indirect effect through social support (Table 3). Forty-two percent and 49% of the
variance (R2) was explained by the association between gambling and social support for 8
th grade and 9
th
grade boys, respectively. For 8th grade girls, 63% of the variance was explained and 69% of the variance was
explained for 9th graders.
Discussion
This large scale, population-based study explored the relationship between gambling, problem behaviour and
social support among 14- to 16-year-old adolescents. The main purpose of the study was to examine whether
social support would mediate this association. Social support from parents and school mediated only weakly
the relations between gambling and problem behaviour among girls and boys. Thus, the data suggest that the
relation between problem behaviour and gambling is not explained by the degree of social support received
from school, friends, and parents and there might be some other variables, that could explain this association
more strongly.
In accordance with the Mun et al. [37] research, this study indicated that problem behaviour did cluster at the
both ends of the lifestyle spectrum (i.e., “problem” or “non-problem” behaviour patterns among adolescents).
Within these two classes, there were adolescents who participated regularly in all forms of problem
Page 9 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
10
behaviours and those who did not participate in any problem behaviours. Additionally, this study found that
problem behaviour and gambling were associated, with problem behaviour increasing as the frequency of
gambling increased. This is similar to previous studies.[7,22,32] These results may indicate that involvement
in one problem behaviour also increases the risk of involvement in other problem behaviours, as
demonstrated by problem behaviour theory.[4,13]
To the best of our knowledge, this is the first study to examine whether social support from school is
associated with gambling frequency. Earlier studies have assessed school characteristics, such as suspension
rates, school commitment, and schools’ rewards for prosocial involvement.[25,26] In the current study,
social support from school was significantly related to gambling frequency, with lower support related to
higher gambling participation. In addition, low social support from parents and friends was related to
increased gambling, which is consistent with the findings of Hardoon et al. [20] In their study, they reported
significant differences between gambling severity groups in their levels of family and peer support.
Specifically, their results indicated that non-gamblers and social gamblers experienced more social support
than at-risk and pathological gamblers. However, in the current study, this pattern was found only for female
adolescent gamblers. For boys, social support from friends was positively related to gambling frequency. It
might be that gambling is social activity for boys, but for girls gambling may be an activity that substitutes
normal social contacts. Problem gambling may occur in the absence of friends, whereas non-problematic
gambling may be part of a social pastime.[20] Gambling was more common among boys, which is consistent
with previous studies[6,23]; however, over 50% of 8th grade and 74% of 9
th grade girls who gambled on a
weekly basis participated in problem behaviour. This indicates that active gambling among girls is strongly
linked to problem behaviour and thus a phenomenon that should be studied more extensively.
Although the findings of this study indicated that social support mediated only weakly the association
between problem behaviour and gambling frequency, the temporal relationship between these factors
remains unclear. Thus, additional research is needed using longitudinal data. Additionally, it is important to
note that while social support from friends, parents, and school were significantly associated with gambling,
the path coefficients were low among boys and girls and may due to large sample size. Furthermore, path
coefficients for the indirect effects were low. This may indicate that social support does not play a large in
Page 10 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
11
the association between problem behaviour and gambling. There may be additional factors that play a more
important role in this association, such as having friends or parents who: gamble, have a gambling problem,
or participate in other problem behaviours or individual factors such as low self-control or conduct disorder.
These types of factors have been examined in previous studies.[7,8,18,21,23,24]
Furthermore, gambling frequency was assessed by a single item, and there was not a validated problem
gambling screen used herein. However, the goal of the study was to study gambling involvement and its
associations with problem behaviours and social support, not to identify problem gamblers. The survey did
not collect additional information on gambling behaviour (e.g., how much money is spent on gambling), nor
was information about gambling types. Additionally, the definition of gambling was not given in the
questionnaire, so adolescents could interpret gambling in many ways. [33,38] Also we did not use a validated
measure for social support.
In addition, data were collected from 78% of Finnish 8th and 9th graders in 2010 and from 81% of Finnish
8th and 9
th graders in 2011. However, it may be that the final sample did not include the adolescents who
were engaging in the highest levels of gambling and the highest levels of problem behaviour. Moreover,
since this study was based solely on adolescent self-reports, there is the possibility of over or under-
reporting.
Despite the limitations, mediation effects were detected, which have theoretical importance as well as
significant implications for intervention. Specifically, prevention and intervention strategies should focus on
strengthening adolescents’ social support. In addition, because of the clustering of different problem
behaviours and the fact that problem behaviour was linked to gambling, instead of concentrating on a single
form of problem behaviour multiple-behaviour interventions may have a much greater impact on public
health.[39]
Contributor ship statement: Study conception and design: Räsänen, Tolvanen, Lintonen, Konu; Analysis
and interpretation of data: Räsänen, Tolvanen, Lintonen, Konu; Drafting of manuscript: Räsänen; Critical
revision: Tolvanen, Lintonen, Konu
Competing interests: None declared.
Page 11 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
12
Funding: This study was financially supported by the Finnish Foundation for Alcohol Studies. The Finnish
Foundation for Alcohol Studies had no involvement in the study design, data handling, writing or submission
of the manuscript. The grants awarded by the Finnish Foundation for Alcohol Studies for gambling research
are based on a government contract for studying gambling-related harm.
Data sharing statement: No additional data available.
1 Michael K, Ben-Zur H. Risk-taking among adolescents: associations with social and affective factors.
J Adolesc 2007;30:17–31.
2 Igra V, Irwin CE. Theories of Adolescent Risk-Taking Behavior. In: R. J. DiClemente, W. B. Hansen
&, Ponton LE, eds. Handbook of adolescent health risk behaviour. New York: : Plenum Press 1996.
35–51.
3 Leather NC. Risk-taking behaviour in adolescence: a literature review. J Child Health Care
2009;13:295–304.
4 Jessor R, Jessor SL. Problem behavior and psychosocial development: A longitudinal study of youth.
New York: : Academic Press 1977.
5 Jessor R, Turbin MS. Parsing protection and risk for problem behavior versus pro-social behavior
among US and Chinese adolescents. J Youth Adolesc 2014;43:1037–51.
6 Barnes GM, Welte JW, Hoffman JH, et al. Gambling, alcohol, and other substance use among youth
in the United States. J Stud Alcohol Drugs 2009;70:134–42.
7 Cheung NWT. Low self-control and co-occurrence of gambling with substance use and delinquency
among Chinese adolescents. J Gambl Stud 2014;30:105–24.
8 Gori M, Potente R, Pitino A, et al. Relationship Between Gambling Severity and Attitudes in
Adolescents: Findings from a Population-Based Study. J Gambl Stud 2014;31:717–40.
9 Lau M, Kan M yue. Prevalence and correlates of problem behaviors among adolescents in Hong
Kong. Asia Pac J Public Health 2010;22:354–64.
Page 12 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
13
10 Salonen A, Castren, S, Raisamo S, et al. Attitudes towards gambling in Finland: a cross-sectional
population study. BMC Public Health 2014. doi: 10.1186/1471-2458-14-982.
11 Shead WN, Derewensky, JL, Meerkamper E. Your Mother Should Know: A Comparison of Maternal
and Paternal Attitudes and Behaviors Related to Gambling among Their Adolescent Children. Int J
Ment Health Addiction 2011;9:264–75.
12 Derevensky JL, St-Pierre RA, Temcheff CE et al. Teacher Awareness and Attitudes Regarding
Adolescent Risky Behaviours: Is Adolescent Gambling Perceived to be a Problem? J Gambl Stud
2014;30: 435–51.
13 Jessor R, Turbin MS, Costa FM, et al. Adolescent Problem Behavior in China and the United States:
A Cross-National Study of Psychosocial Protective Factors. J Res Adolesc 2003;13:329–60.
14 Deković M. Risk and Protective Factors in the Development of Problem Behavior During
Adolescence. J Youth Adolesc 1999;28:667–85.
15 Fleming CB, Catalano RF, Haggerty KP, et al. Relationships between level and change in family,
school, and peer factors during two periods of adolescence and problem behavior at age 19. J Youth
Adolesc 2010;39:670–82.
16 Garnefski N, Diekstra RF. Perceived social support from family, school, and peers: relationship with
emotional and behavioral problems among adolescents. J Am Acad Child Adolesc Psychiatry
1996;35:1657–64.
17 McComb JL, Sabiston CM. Family influences on adolescent gambling behavior: a review of the
literature. J Gambl Stud 2010;26:503–20.
18 Magoon ME, Ingersoll GM. Parental Modeling, Attachment, and Supervision as Moderators of
Adolescent Gambling. J Gambl Stud 2006;22:1–22.
19 Lee GP, Stuart EA, Ialongo NS, et al. Parental monitoring trajectories and gambling among a
longitudinal cohort of urban youth. Addiction 2014;109:977–85.
20 Hardoon KK, Gupta R, Derevensky JL. Psychosocial variables associated with adolescent gambling.
Page 13 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
14
Psychol Addict Behav 2004;18:170–9.
21 Barnes GM, Welte JW, Hoffman JH, et al. Shared predictors of youthful gambling, substance use,
and delinquency. Psychol Addict Behav 2005;19:165–74.
22 Wanner B, Vitaro F, Carbonneau R, et al. Cross-lagged links among gambling, substance use, and
delinquency from midadolescence to young adulthood: additive and moderating effects of common
risk factors. Psychol Addict Behav 2009;23:91–104.
23 Castrén S, Grainger M, Lahti T, et al. At-risk and problem gambling among adolescents: a
convenience sample of first-year junior high school students in Finland. Subst Abuse Treat Prev
Policy 2015;10:1–10.
24 Hanss D, Mentzoni RA, Blaszczynski A, et al. Prevalence and Correlates of Problem Gambling in a
Representative Sample of Norwegian 17-Year-Olds. J Gambl Stud 2015;31:659–78.
25 Lee GP, Martins SS, Pas ET, et al. Examining potential school contextual influences on gambling
among high school youth. Am J Addict 2014;23:510-7.
26 Scholes-Balog KE, Hemphill SA, Dowling NA, et al. A prospective study of adolescent risk and
protective factors for problem gambling among young adults. J Adolesc 2014;37:215–24.
27 Kristiansen S, Jensen SM. Prevalence of gambling problems among adolescents in the Nordic
countries: an overview of national gambling surveys 1997–2009. Int J Soc Welfare 2011;20:75–86
28 Burge AN, Pietrzak RH, Molina CA et al. Age of gambling initiation and severity of gambling and
health problems among older adult problem gamblers. Psychiatric Services 2004;55:1437–39.
29 Schulte MT, Ramo D, Brown SA. Gender differences in factors influencing alcohol use and drinking
progression among adolescents. Clin Psychol Rev 2009;29:535–47.
30 Helldán, A., Helakorpi, S., Virtanen, S., & Uutela, A. (2013). Health behaviour and health among the
Finnish adult population. National Institute for Health and Welfare (THL), Report 15/2013. Retrieved
from: http://urn.fi/URN:ISBN:978-952-245-931-2
Page 14 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
15
31 Barnes GM, Welte JW, Hoffman JH, et al. The co-occurrence of gambling with substance use and
conduct disorder among youth in the United States. Am J Addict 1999;20:166–73.
32 Vitaro F, Brendgen M, Ladouceur R, et al. Gambling, delinquency, and drug use during adolescence:
mutual influences and common risk factors. J Gambl Stud 2001;17:171–90.
33 Räsänen T, Lintonen T, Konu A. Gambling and Problem Behavior Among 14- to 16-Year-Old Boys
and Girls in Finland. J Gambl Issues 2015;31:1–22.
34 Muthén LK, Muthén BO (1998-2015). Mplus User’s Guide. Seventh Edition. Los Angeles, CA: 2015.
35 Nylund KL, Asparouhov T, Muthén BO. Deciding on the number of classes in latent class analysis
and growth mixture modeling: A Monte Carlo simulation study. Struct Equ Model 2007;14:535–69.
36 Jung T, Wickrama KAS. An Introduction to Latent Class Growth Analysis and Growth Mixture
Modeling. Soc Personal Psychol Compass 2008;2:302–17.
37 Mun EY, Windle M, Schainker LM. A model-based cluster analysis approach to adolescent problem
behaviors and young adult outcomes. Dev Psychopathol 2008;20:291–318.
38 Räsänen T, Lintonen T, Joronen K, et al. Girls and boys gambling with health and well-being in
Finland. J Sch Health 2015;85:214–22.
39 Nigg CR, Allegrante JP, Ory M. Theory-comparison and multiple-behavior research: common themes
advancing health behavior research. Health Educ Res 2002;17:670–9.
Page 15 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
16
Table 1. Results for the latent class analysis (LCA). Bolding for those participating in problem behavior the most and the least.
8th grade boys 9
th grade boys 8
th grade girls 9
th grade girls
n for classes entropy Lo-
Mendell-
Rubin
n for classes entropy Lo-
Mendell-
Rubin
n for
classes
entropy Lo-
Mendell-
Rubin
n for
classes
entropy Lo-
Mendell-
Rubin
1 class
model
19,471 na. na. 21,711 na. na. 9,432 na. na. 12,342 na. na.
2 class
model
c1=6,805
c2=12,666
0.86 0.00 c1=25,768
c2=37,188
0.85 0.00 c1=3,591
c2=5,841
0.86 0.00 c1=5,445
c2=6,897
0.82 0.00
3 class
model
c1=1,975
c2=6,813
c3=10,683
0.90 0.00 c1=9,482
c2=26,304
c3=27,170
0.89 0.00 c1=1,734
c2=3,706
c3=3,992
0.88 0.00 c1=2,645
c2=3,707
c3=5,990
0.88 0.00
4 class
model
c1=586
c2=5,377
c3=3,065
c4=10,443
0.88 0.04 c1=911
c2=4,734
c3=7,233
c4=8,833
0.86 0.00 c1=513
c2=2,123
c3=3,240
c4=3,556
0.86 0.00 c1=1,473
c2=4,145
c3=3,169
c4=3,555
0.83 0.00
5 class
model
c1=567 c2=2,829
c3=4,543
c4=2,956
c5=8,576
0.81 0.70 c1=503 c2=2,290
c3=6,086
c4=4,142
c5=8,690
0.85 0.00 c1=138 c2=1,165
c3=1,641
c4=3,013
c5=3,475
0.86 0.00 c1=159 c2=1,910
c3=2,865
c4=3,543
c5=3,865
0.84 0.76
Page 16 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on November 28, 2020 by guest. Protected by copyright. http://bmjopen.bmj.com/ BMJ Open: first published as 10.1136/bmjopen-2016-012468 on 22 December 2016. Downloaded from
For peer review only
17
Table 2. Adolescents’ involvement in gambling and problem behavior, and experiencing social support from
friends (SSF), school (SSS) and parents (SSP) based on their sex and grade.
8th grade
boys
9th grade
boys
8th grade
girls
9th grade
girls %
Gambling
less than once
a month
38.4 34.1 73.7 69.9
less than once
a week
28.8 30.3 15.7 18.1
1–2 days per
week
18.7 19.6 5.0 6.2
3–5 days per
week
8.1 9.3 2.2 3.0
6–7 days per
week
6.1 6.8 3.4 2.8
Participating
in problem
behavior
5.3 9.3 12.6 29.3
SSF
do not have any friends
13.7 15.3 7.1 6.7
one close friend
24.1 26.0 20.7 21.6
two close
friends
20.5 19.1 27.5 27.2
several close
friends
40.9 39.0 44.5 44.3
missing values 0.8 0.7 0.2 0.3
x, (SD)
SSS 2.8 (0.5) 2.7 (0.6) 2.7 (0.5) 2.7 (0.6)
SSP 2.2 (0.6) 2.2 (1.2) 2.1 (0.7) 2.0 (0.7)
n 11,029 9,744 4,069 5,028
Page 17 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
18
Table 3. Path model of the direct and indirect effects between the social support from friends (ssf), school
(sss), parents (ssp), problem behaviour (pb) and gambling frequency (gb) among 8th and 9
th grade boys and
girls.
** p<0.01, ***p<0.001
8
th grade boys 9
th grade boys 8
th grade girls 9
th grade girls
β β β β
Direct effect c (pb to gb) 0.35*** 0.36*** 0.34*** 0.36***
Path from pb to sss (path e) -0.30*** -0.36*** -0.43*** -0.46***
Path from pb to ssf (path d) -0.09*** -0.07*** -0.08*** -0.01
Path from pb to ssp (path f) -0.37*** -0.39*** -0.19*** -0.50***
Path from sss to gb (path h) -0.11*** -0.13*** -0.06** -0.11***
Path from ssf to gb (path g) 0.07*** 0.04*** -0.08*** -0.09***
Path from ssp to gb (path i) -0.09*** -0.08*** -0.10*** -0.06***
Total effect c’ (pb to gb) 0.41*** 0.43*** 0.42*** 0.44***
Total indirect effect c-c’ 0.06*** 0.07*** 0.08*** 0.08***
Path from pb to sss to gb 0.03*** 0.05*** 0.03** 0.05***
Path from pb to ssf to gb -0.01*** -0.00*** 0.01*** 0.00
Path from pb to ssp to gb 0.03*** 0.03*** 0.05*** 0.03***
Page 18 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
108x60mm (300 x 300 DPI)
Page 19 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
1
STROBE Statement—checklist of items that should be included in reports of observational studies
Item
No Recommendation
Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract
page 1
(b) Provide in the abstract an informative and balanced summary of what was done
and what was found -page 1
Introduction
Background/rationale 2 Explain the scientific background and rationale for the investigation being reported
pages 2-3
Objectives 3 State specific objectives, including any prespecified hypotheses page 3
Methods
Study design 4 Present key elements of study design early in the paper pages 4-5
Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment,
exposure, follow-up, and data collection page 3
Participants 6 (a) Cohort study—Give the eligibility criteria, and the sources and methods of
selection of participants. Describe methods of follow-up
Case-control study—Give the eligibility criteria, and the sources and methods of
case ascertainment and control selection. Give the rationale for the choice of cases
and controls
Cross-sectional study—Give the eligibility criteria, and the sources and methods of
selection of participants pages 3-4
(b) Cohort study—For matched studies, give matching criteria and number of
exposed and unexposed
Case-control study—For matched studies, give matching criteria and the number of
controls per case
Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect
modifiers. Give diagnostic criteria, if applicable page 4, sup.material
Data sources/
measurement
8* For each variable of interest, give sources of data and details of methods of
assessment (measurement). Describe comparability of assessment methods if there
is more than one group sup. material
Bias 9 Describe any efforts to address potential sources of bias none
Study size 10 Explain how the study size was arrived at pages 3-4
Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable,
describe which groupings were chosen and why sup. material 4-5
Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding,
4-5
(b) Describe any methods used to examine subgroups and interactions
(c) Explain how missing data were addressed
(d) Cohort study—If applicable, explain how loss to follow-up was addressed
Case-control study—If applicable, explain how matching of cases and controls was
addressed
Cross-sectional study—If applicable, describe analytical methods taking account of
sampling strategy
(e) Describe any sensitivity analyses
Continued on next page
Page 20 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
2
Results
Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible,
examined for eligibility, confirmed eligible, included in the study, completing follow-up, and
analysed
(b) Give reasons for non-participation at each stage
(c) Consider use of a flow diagram
Descriptive
data
14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information
on exposures and potential confounders
(b) Indicate number of participants with missing data for each variable of interest
(c) Cohort study—Summarise follow-up time (eg, average and total amount)
Outcome data 15* Cohort study—Report numbers of outcome events or summary measures over time
Case-control study—Report numbers in each exposure category, or summary measures of
exposure
Cross-sectional study—Report numbers of outcome events or summary measures page 14
Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their
precision (eg, 95% confidence interval). Make clear which confounders were adjusted for and
why they were included
(b) Report category boundaries when continuous variables were categorized
(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful
time period
Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity
analyses 4-5
Discussion
Key results 18 Summarise key results with reference to study objectives 7-9
Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision.
Discuss both direction and magnitude of any potential bias 8-9
Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity
of analyses, results from similar studies, and other relevant evidence 8
Generalisability 21 Discuss the generalisability (external validity) of the study results 8
Other information
Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable,
for the original study on which the present article is based page 9
*
Page 21 of 21
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
Social support as a mediator between problem behaviour
and gambling – a cross-sectional study among 14- to 16-
year-old Finnish adolescents
Journal: BMJ Open
Manuscript ID bmjopen-2016-012468.R2
Article Type: Research
Date Submitted by the Author: 10-Oct-2016
Complete List of Authors: Räsänen, Tiina; University of Tampere, School of Health Sciences Lintonen, Tomi; Finnish Foundation for Alcohol Studies Tolvanen, Asko; University of Jyväskylä, Department of Psychology
Konu, Anne; University of Tampere, School of Health Sciences
<b>Primary Subject Heading</b>:
Addiction
Secondary Subject Heading: Public health
Keywords: Health policy < HEALTH SERVICES ADMINISTRATION & MANAGEMENT, Substance misuse < PSYCHIATRY, PUBLIC HEALTH
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open on N
ovember 28, 2020 by guest. P
rotected by copyright.http://bm
jopen.bmj.com
/B
MJ O
pen: first published as 10.1136/bmjopen-2016-012468 on 22 D
ecember 2016. D
ownloaded from
For peer review only
1
Social support as a mediator between problem behaviour and gambling – a cross-sectional study
among 14- to 16-year-old Finnish adolescents
Tiina Räsänen, Tomi Lintonen, Asko Tolvanen & Anne Konu
Tiina Räsänen: School of Health Sciences, University of Tampere, Finland
Phone: +358 445368416
Email: [email protected]
Tomi Lintonen: Finnish Foundation for Alcohol Studies, Helsinki, Finland
Asko Tolvanen: Department of Psychology, University of Jyväskylä, Finland
Anne Konu: School of Health Sciences, University of Tampere, Finland
Word count:
Abstract: Background: During the adolescent period, risk-taking behaviour increases. These behaviours can
compromise the successful transition from adolescence to adulthood. The purpose of this study was to
examine social support as a mediator of the relation between problem behaviour and gambling frequency
among Finnish adolescents. Methods: Data were obtained from the national School Health Promotion Study
(SHPS) from the years 2010 and 2011 (N = 102,545). Adolescents were classified in the most homogenous
groups based on their problem behaviour via latent class analysis. Results: Path analysis indicated that social
support was negatively associated with problem behaviour, and problem behaviour and social support were
negatively related (except for social support from friends among boys) to gambling. Social support from
parents and school mediated, albeit weakly, the relations between problem behaviour and gambling among
girls and boys. Conclusion: Problem behaviour may affect gambling through social support from school and
parents. Thus prevention and intervention strategies should focus on strengthening adolescents’ social
support. In addition, because of the clustering of different problem behaviours instead of concentrating on a
single form of problem behaviour multiple-behaviour interventions may have a much greater impact on
public health.
Keywords: gambling frequency, adolescents, social support, problem behaviour
Page 1 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
2
Strengths and limitations of this study
• large scale, population-based study explored the relationship between gambling, problem behaviour
and social support
• studies have examined pathways from social support to both gambling and other problem
behaviours, but research that tries to explain how adolescents’ access to social support accounts for
the association between gambling frequency and problem behaviour, is lacking
• temporal relationship between these factors remains unclear, because of the cross-sectional nature of
the study
• it may be that the final sample did not include the adolescents who were engaging in the highest
levels of gambling and the highest levels of problem behaviour
• since this study was based solely on adolescent self-reports, there is the possibility of over or under-
reporting
Introduction
During the adolescent period, risk-taking behaviour increases. [1] Risk-taking includes behaviours that are
done under one’s own volition, have uncertain outcomes, and can compromise the successful transition from
adolescence to adulthood. [2,3] Risk-taking behaviours also manifest in the form of problem behaviours;
actions that are socially disapproved and result in social sanctions. These behaviours can co-occur; thus,
involvement in one problem behaviour increases the risk of involvement in other problem behaviours, which
is known as problem behaviour syndrome.[4,5] Gambling may be a component of the problem behaviour
syndrome: problem gambling and active gambling (at least once a week) are associated with conduct
disorder, substance use, and delinquency [6–9]. However, it is not known if gambling which is not
necessarily problematic per se is related to the problem behaviour syndrome. In Finland in 2010 gambling
was allowed for adolescents aged 15 and over (except Internet and casino gambling) and in 2011, 15 year
olds could legally gamble at slot machines (all other gambling games had age limit of 18), which are widely
available in Finland. Adolescents have also had positive attitudes towards gambling in Finland [10].
Page 2 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
3
Likewise, studies have shown that parents and teachers do not think that gambling is great concern among
youth. [11,12]
According to problem behaviour theory, it is the balance between protective and risk factors that determines
ones’ involvement in problem behaviour. [5] Social support provided by individuals and institutions can be
described as interpersonal relationships that influence an individual’s functioning. Social support is parents’
closeness, monitoring and caring, teachers’ interest in their students, and friends’ supportiveness [13].
Studies have shown that social support from parents, friends, and school all play a crucial role in
adolescents’ problem behaviour. [14–16] There is also some evidence indicating that family characteristics
influence adolescents’ gambling.[17] Specifically, higher levels of parental attachment, monitoring, and
supervision are linked to decreased gambling, while lower levels of parental trust and communication are
associated with increased gambling.[18] Low levels of parental monitoring of adolescents is also associated
with problem gambling during young adulthood. [19] Additionally, adolescent problem gamblers tend to
perceived lower levels of familial and peer support.[20] While previous studies have examined shared
predictors between gambling, problem behaviours, and parenting, the findings of these studies do not provide
evidence that parental supervision or monitoring are related to gambling as it is the case for other problem
behaviours.[21,22] Moreover, friends’ approval of gambling, associating with deviant peers, associating with
friends who gamble, and having friends who have gambling problems are associated with adolescent
gambling.[8,23,24] However, the only school characteristics that have been studied in the context of
gambling are suspension rates, low school commitment, and schools’ rewards for prosocial involvement.
These were either weakly or not at all associated with gambling. [25,26] Studies examining the associations
between schools’ social support and gambling, are lacking.
Earlier studies have demonstrated that there are gender differences in gambling as well as problem
behaviour. For example, gambling is more common among males [27] and males also tend to start gambling
at a younger age. [28] Additionally, males have a higher risk for heavy alcohol use and smoking. [29,30]
However, little is known about gender differences in relation to co-occurrence of gambling frequency and
problem behaviours. It is also unclear if there are gender differences in associations between gambling,
problem behaviour and social support.
Page 3 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
4
In studies that assess gambling, problem behaviour, and risk/protective factors, a limited number of problem
behaviours (e.g., gambling, substance use, and delinquency) are examined, and the focus is on parental
monitoring, individual factors (impulsivity, moral disengagement), and peer delinquency[21,22,31,32],
thereby excluding social support from important individuals and institutions, like friends and school.
Previous studies have examined pathways from social support to both gambling and other problem
behaviours, but research that tries to explain how adolescents’ access to social support accounts for the
association between gambling frequency and problem behaviour, is lacking. Thus, the role of social support
in the association between problem behaviour and gambling has not been investigated. As earlier studies
have shown that gambling is associated with problem behaviour and the degree of social support that
adolescent receives is related to both gambling frequency and problem behaviour, it is reasonable to expect
that social support plays an important role in the extent to which problem behaviours are related to gambling
frequency. Therefore, using a population-based survey of 8th and 9
th grade boys and girls, the aim of this
study was to investigate the relations between problem behaviour and gambling frequency, and social
support as a potential mediator of this association (i.e., serve as a protective factor). It is assumed that higher
social support would be negatively associated with problem behaviour and gambling.
Method
Setting
In Finland, compulsory basic comprehensive school starts at age 7 (1st grade) and ends at the age of 16 (9th
grade). During the 8th and 9th grade boys and girls are between 14- to 16-years of age.
The Finnish gambling system is based on a state monopoly; the profits are returned to society and used for
common good. In addition, the games are widely available in public places. The gambling age limit was set
to 18 years in October 2010. The limit was also applied to slot machines in July 2011, and prior to that the
age limit was age 15. At the time of survey completion, the age limit for gambling was 18 years, and 15
years for slot machines.
Page 4 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
5
Data
Data were obtained from the national School Health Promotion Study (SHPS) in 2010 and 2011, which
included questions on adolescents’ gambling, problem behaviour, and social support. In 2010, the study was
conducted in southern, eastern and northern Finland and in western and central Finland in 2011. Thus, the
2010 and 2011 surveys cover all of Finland, and in each year only a few municipalities refuse to participate
[33]. The municipalities that did not participate do not differ from the others and this part of the drop-out is
not likely to pose a threat to generalizability. In 2010, 78% of Finnish 8th and 9
th graders were surveyed, and
in 2011 81% of Finnish 8th and 9th graders participated in the study. Respondents who had not answered
over half of the questions, or had not expressed their sex or grade, were removed. Also those who were not
school when survey was conducted or could not answer independently did not participate. [33] SHPS was
approved by the ethical committee of Tampere University Hospital. SHPS is a cross-sectional survey
administered throughout the school day in the 8th and 9
th grades of lower secondary schools. Answering was
voluntary. Parental consent was not required according to ethical guidelines in Finland; generally, surveys
conducted during school days do not need parental permission. In total, 102,545 8th (mean age = 14.9, SD =
0.4) and 9th (mean age = 15.9, SD = 0.4) grade students participated in the study. Forty-nine percent of
survey respondents were boys.
Measures
Problem behavior
Problem behavior was measured through 11 different forms of problem behaviors concerning adolescents’
truancy, bullying, delinquency, smoking, using snuff, alcohol drinking, drunkenness-related drinking, using
alcohol and medicine for intoxication, using medicine for intoxication, glue-sniffing and drug use. More
detailed information about questions regarding problem behavior can be found elsewhere. [34] Because
problem behavior indicator included measures with multiple behavior types and responses, which were not
necessarily identically scaled, latent classes were estimated. Based on latent class analysis (LCA) adolescents
were divided into four groups. From these groups those who participated in problem behavior the most and
the least were selected from the data to study extremities of the problem behavior phenomenon.
Page 5 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
6
Social support from friends
Social support from friends were requested by question: Do you have at this moment any close friend whom
you can talk with confidentially almost everything? Alternatives were I do not have any friends, one close
friend, two close friends and several close friends.
Social support from school
Social support from school based on three statements and two questions about schools’ and teachers’
support. Statements were: teachers encourage me to impress my own opinions at classes, teachers are
interested about how I am doing and teachers are treating students fairly. The scale for these was totally
agree, agree, disagree and totally disagree. Students were also asked: do you have troubles getting along with
your teachers. Alternatives were not at all, fairly little, fairly much and very much. As well adolescents were
requested if they had troubles with school work, how often they got help from school. Alternatives were
always when I need it, most of the time, rarely and almost never. All of the statements and questions were
coded from one to four, four indicating good social support. From these five variables the sum variable was
created, which had one component structure with Cronbach’s alpha value of 0.7.
Social support from parents
Social support was examined by four questions. Students were asked do their parents know all of his/her
friends. This question had alternatives both parent do (coded as three), only mother/father knows (coded as
one) and neither of them do not know (coded as zero). Second question was, do your parent know where you
spent your Friday and Saturday evenings, which had alternatives they know always (coded as three), know
sometimes (coded as one) and most of the time do not know (coded as zero). Adolescents were also asked
can they talk with their parents: almost never (coded as zero), sometimes (coded as one), fairly often (coded
as two) and often (coded as three). The last question was if adolescents had troubles with school work, how
often they got help from home. Alternatives were always when I need it (coded as three), most of the time
Page 6 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
7
(coded as two), rarely (coded as one) and almost never (coded as zero). These four questions measuring the
social support from parents had one component structure, which had Cronbach’s alpha value of 0.6.
Gambling
Gambling was requested by one question: How often do you gamble? Alternatives were on 6–7 days per
week, on 3–5 days per week, on 1–2 days per week, less than once a week, less than once a month, I have
not gambled during previous year’.
Statistical analysis
Basic statistical analyses were conducted with IBM SPSS Statistics 22, and structural equation modelling
was conducted with Mplus 7.0.[35] Basic statistical analyses included a χ2-test (for categorical data) and
Mann–Whitney U test (for continuous data), which are used to detect statistically significant difference
between two or more groups. Latent class analysis (LCA) was used to identify groups of adolescents based
on their involvement in different problem behaviours. The purpose was to identify the most homogenous
groups that include extreme classes of problem behaviour. LCA provides fit statistics and significance tests
to assess the number of classes that best fit the data.[36] To select the number of classes for the model, the
analysis was first run with one class, then with two and three classes, and so on. This procedure was
followed until to the highest possible number of classes were run (which was in this case 11). Model
solutions were assessed by examining the entropy values (near 1.0), the Lo–Mendell–Rubin test (a p value
that provides information about statistically significant improvement in fit for the inclusion of an additional
class) as well as the interpretation of the results.[37] For further analysis, all individuals were classified into
classes where class membership was based on the highest posterior probabilities.
Based on the LCA results, path analysis was conducted for those who participated in the most and the least
problem behaviours. The analysis was conducted to examine if social support mediates the association
between problem behaviour and gambling. In this model, gambling frequency was regressed on the three
forms of social support, and forms of social support were then regressed on problem behaviour (Figure 1).
Analyses were run separately for 8th and 9
th grade girls and boys given the possible differences in the relation
Page 7 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
8
between gambling and problem behaviour. All the models were saturated, so the model fits were necessarily
perfect.
Results
LCA
Adolescents who did not gamble during the previous year (37.3%) or had missing values on the main
outcome variable (1.3%) were excluded. This was done because we were only interested in adolescents who
were gambling. For the remaining 62,956 individuals, LCA was conducted separately for 8th and 9
th grade
girls and boys to identify groups of adolescents based on their problem behaviours. For all 8th and 9th grade
girls and boys, the optimal model had four classes with entropy values ranging from 0.88 to 0.83. The
reasonably high entropies and the Lo–Mendell–Rubin test p values suggested a good model fit for the four
class model. However, among 8th grade girls and 9th grade boys, the p values were lower than 0.05,
indicating that the five or more class model was a better fit. However, after taking into account the entropies
and the interpretation of the results, the four class model was chosen for all participants (Table 1).
Class 1 included adolescents who participated in all forms of problem behaviours at the highest frequency
[see 33]. For example, adolescent in class 1 smoked at least daily, drunk alcohol on a weekly basis and had
tried drugs at least once. Youths in class 2 also participated in problem behaviour, but their participation in
problem behaviours was more experimental. In addition, most of youths in class 2 did not use alcohol with
medicine for intoxication, use medicine for intoxication, and did not participate in glue sniffing. In class 3,
adolescents smoked tobacco less often than once a week and consumed alcohol only a couple of times a
month. The youths in class 4 did not participate in any form of problem behaviour. From these groups, class
1 and class 4 were selected, including adolescents participating regularly in all examined problem behaviours
and those not participating in any, which allowed for the study of the extremes of problem behaviour (N =
29,870).
Page 8 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
9
Gambling, problem behaviour and social support
The next set of analyses compared the adolescents who participated in the most problem behaviour and the
adolescents that participated in the least problem behaviour. Boys gambled more than girls did (χ2 (4) =
3280.182, p < 0.001); however, participation in problem behaviour was more common among girls (χ2 (1) =
1313.636, p < 0.001) (Table 2). Girls experienced more social support from friends (χ2 (4) = 553.19, p <
0.001), and boys received more support from school (U = 88080721, p < 0.001) and from parents (U =
84026360, p < 0.001) (Table 2). 9th graders gambled (boys: χ2 (4) = 11,395 p=0,022), (girls: χ2 (4) = 25.416,
p < 0.001) and participated in problem behaviour (boys: χ2 (1) = 126.024, p < 0.001), (girls: χ
2 (1) = 367.030,
p < 0.001) more often than 8th graders. Eighth grade boys also experienced more social support from friends
(χ2 (3) = 25.933), p < 0.001), school (U = 52467017.0, p < 0.01), and parents (51780278.5, p < 0.001) than
9th grade boys. Eighth grade girls experienced more social support from school (U = 9696512.5, p < 0.001)
and parents (U = 9817557.0, p < 0.01), but there were no statistical differences in social support from friends
(Table 2). Among girls who gambled on weekly basis, 50% of 8th graders and 74% of 9th graders also
participated in problem behaviour. Among the boys, the percentage was 14% for 8th graders and 22% for 9
th
graders.
Path analysis
The standardized parameter estimates (β) shown in Table 3 indicated that problem behaviour was
significantly and positively related to adolescents’ gambling frequency (path c). The beta indices also
showed that there was a significant negative association between problem behaviour and the different types
of social support; however, among 9th grade girls, social support from friends was not statistically significant
(paths d–f). Social support from parents and school were negatively related with gambling (paths g and i).
Among boys, social support from friends was significant and positively associated with gambling; however,
among girls social support from friends was significantly and negatively associated with gambling (path h)
(Table 3; also see Figure 1).
The statistically significant albeit very small indirect effects indicated that social support mediated the
relationship between problem behaviour and gambling frequency, but social support from friends did not
mediate this association. The total effect of problem behaviour on problem gambling frequency consisted of
Page 9 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
10
a direct effect and an indirect effect through social support (Table 3). Forty-two percent and 49% of the
variance (R2) was explained by the association between gambling and social support for 8th grade and 9th
grade boys, respectively. For 8th grade girls, 63% of the variance was explained and 69% of the variance was
explained for 9th graders.
Discussion
This large scale, population-based study explored the relationship between problem behaviour, gambling and
social support among 14- to 16-year-old adolescents. The main purpose of the study was to examine whether
social support would mediate this association. Social support from parents and school mediated weakly the
relations between problem behaviour and gambling among girls and boys. Social support from friends did
not mediate this association. Thus, the data suggest that the relation between problem behaviour and
gambling can be explained only by the degree of social support received from school and parents; there may
be other issues or phenomena that are more important in mediating this association.
In accordance with the Mun et al. [38] research, this study indicated that problem behaviour did cluster at the
both ends of the lifestyle spectrum (i.e., “problem” or “non-problem” behaviour patterns among adolescents).
Within these two classes, there were adolescents who participated regularly in all forms of problem
behaviours and those who did not participate in any problem behaviours. Additionally, this study found that
problem behaviour and gambling were associated, with problem behaviour increasing as the frequency of
gambling increased. This is similar to previous studies.[7,22,32] These results may indicate that involvement
in one problem behaviour also increases the risk of involvement in other problem behaviours, as
demonstrated by problem behaviour theory.[4,13]
To the best of our knowledge, this is the first study to examine whether social support from school is
associated with gambling frequency. Earlier studies have assessed school characteristics, such as suspension
rates, school commitment, and schools’ rewards for prosocial involvement.[25,26] In the current study,
social support from school was significantly related to gambling frequency, with lower support related to
higher gambling participation. In addition, low social support from parents and friends was related to
increased gambling, which is consistent with the findings of Hardoon et al. [20] In their study, they reported
Page 10 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
11
significant differences between gambling severity groups in their levels of family and peer support.
Specifically, their results indicated that non-gamblers and social gamblers experienced more social support
than at-risk and pathological gamblers. However, in the current study, this pattern was found only for female
adolescent gamblers. For boys, social support from friends was positively related to gambling frequency. It
might be that gambling is social activity for boys, but for girls gambling may be an activity that substitutes
normal social contacts. Problem gambling may occur in the absence of friends, whereas non-problematic
gambling may be part of a social pastime.[20] Gambling was more common among boys, which is consistent
with previous studies[6,23]; however, over 50% of 8th grade and 74% of 9th grade girls who gambled on a
weekly basis participated in problem behaviour. This indicates that active gambling among girls is strongly
linked to problem behaviour and thus a phenomenon that should be studied more extensively.
Although the findings of this study indicated that social support mediated the association between problem
behaviour and gambling frequency, the temporal relationship between these factors remains unclear. Thus,
additional research is needed using longitudinal data. Additionally, it is important to note that while social
support from friends, parents, and school were significantly associated with gambling, the path coefficients
were low among boys and girls and may due to large sample size. Furthermore, path coefficients for the
indirect effects were low. This may indicate that social support does not play a large in the association
between problem behaviour and gambling. There may be additional factors that play a more important role in
this association, such as having friends or parents who: gamble, have a gambling problem, or participate in
other problem behaviours or individual factors such as low self-control or conduct disorder. These types of
factors have been examined in previous studies.[7,8,18,21,23,24]
Furthermore, gambling frequency was assessed by a single item, and there was not a validated problem
gambling screen used herein. However, the goal of the study was to study gambling involvement and its
associations with problem behaviours and social support, not to identify problem gamblers. The survey did
not collect additional information on gambling behaviour (e.g., how much money is spent on gambling), nor
was information about gambling types. Additionally, the definition of gambling was not given in the
questionnaire, so adolescents could interpret gambling in many ways. [34,39] Also we did not use a validated
measure for social support. The internal consistency for the scale of “social support from parents” was not
Page 11 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
12
optimal as indicated by the low value of Cronbach's alpha. However, validity is supported by the fact that the
principal component analysis indicated one component structure.
In addition, data were collected from 78% of Finnish 8th and 9th graders in 2010 and from 81% of Finnish
8th and 9
th graders in 2011. However, it may be that the final sample did not include the adolescents who
were engaging in the highest levels of gambling and the highest levels of problem behaviour. Moreover,
since this study was based solely on adolescent self-reports, there is the possibility of over or under-
reporting.
Despite the limitations, mediation effects were detected, which have theoretical importance as well as
significant implications for intervention. Specifically, prevention and intervention strategies should focus on
strengthening adolescents’ social support from parents and school. In addition, because of the clustering of
different problem behaviours and the fact that problem behaviour was linked to gambling, instead of
concentrating on a single form of problem behaviour multiple-behaviour interventions may have a much
greater impact on public health.[40]
Contributor ship statement: Study conception and design: Räsänen, Tolvanen, Lintonen, Konu; Analysis
and interpretation of data: Räsänen, Tolvanen, Lintonen, Konu; Drafting of manuscript: Räsänen; Critical
revision: Tolvanen, Lintonen, Konu
Competing interests: None declared.
Funding: This study was financially supported by the Finnish Foundation for Alcohol Studies. The Finnish
Foundation for Alcohol Studies had no involvement in the study design, data handling, writing or submission
of the manuscript. The grants awarded by the Finnish Foundation for Alcohol Studies for gambling research
are based on a government contract for studying gambling-related harm.
Data sharing statement: No additional data available.
1 Michael K, Ben-Zur H. Risk-taking among adolescents: associations with social and affective factors.
J Adolesc 2007;30:17–31.
2 Igra V, Irwin CE. Theories of Adolescent Risk-Taking Behavior. In: R. J. DiClemente, W. B. Hansen
Page 12 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
13
&, Ponton LE, eds. Handbook of adolescent health risk behaviour. New York: : Plenum Press 1996.
35–51.
3 Leather NC. Risk-taking behaviour in adolescence: a literature review. J Child Health Care
2009;13:295–304.
4 Jessor R, Jessor SL. Problem behavior and psychosocial development: A longitudinal study of youth.
New York: : Academic Press 1977.
5 Jessor R, Turbin MS. Parsing protection and risk for problem behavior versus pro-social behavior
among US and Chinese adolescents. J Youth Adolesc 2014;43:1037–51.
6 Barnes GM, Welte JW, Hoffman JH, et al. Gambling, alcohol, and other substance use among youth
in the United States. J Stud Alcohol Drugs 2009;70:134–42.
7 Welte JW, Barnes GM, Tidwell MC, et al. Association between problem gambling and conduct
disorder in a national survey of adolescents and young adults in the United States. J Adolesc Health
2009;45:396-401.
8 Gori M, Potente R, Pitino A, et al. Relationship Between Gambling Severity and Attitudes in
Adolescents: Findings from a Population-Based Study. J Gambl Stud 2014;31:717–40.
9 Yip SW, Desai RA, Steinberg MA, et al. Health/functioning characteristics, gambling behaviors, and
gambling-related motivations in adolescents stratified by gambling problem severity: findings from a
high school survey. Am J Addict 2011;20(6):495-508.
10 Salonen A, Castren, S, Raisamo S, et al. Attitudes towards gambling in Finland: a cross-sectional
population study. BMC Public Health 2014. doi: 10.1186/1471-2458-14-982.
11 Shead WN, Derewensky, JL, Meerkamper E. Your Mother Should Know: A Comparison of Maternal
and Paternal Attitudes and Behaviors Related to Gambling among Their Adolescent Children. Int J
Ment Health Addiction 2011;9:264–75.
12 Derevensky JL, St-Pierre RA, Temcheff CE et al. Teacher Awareness and Attitudes Regarding
Adolescent Risky Behaviours: Is Adolescent Gambling Perceived to be a Problem? J Gambl Stud
Page 13 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
14
2014;30: 435–51.
13 Jessor R, Turbin MS, Costa FM, et al. Adolescent Problem Behavior in China and the United States:
A Cross-National Study of Psychosocial Protective Factors. J Res Adolesc 2003;13:329–60.
14 Deković M. Risk and Protective Factors in the Development of Problem Behavior During
Adolescence. J Youth Adolesc 1999;28:667–85.
15 Fleming CB, Catalano RF, Haggerty KP, et al. Relationships between level and change in family,
school, and peer factors during two periods of adolescence and problem behavior at age 19. J Youth
Adolesc 2010;39:670–82.
16 Garnefski N, Diekstra RF. Perceived social support from family, school, and peers: relationship with
emotional and behavioral problems among adolescents. J Am Acad Child Adolesc Psychiatry
1996;35:1657–64.
17 McComb JL, Sabiston CM. Family influences on adolescent gambling behavior: a review of the
literature. J Gambl Stud 2010;26:503–20.
18 Magoon ME, Ingersoll GM. Parental Modeling, Attachment, and Supervision as Moderators of
Adolescent Gambling. J Gambl Stud 2006;22:1–22.
19 Lee GP, Stuart EA, Ialongo NS, et al. Parental monitoring trajectories and gambling among a
longitudinal cohort of urban youth. Addiction 2014;109:977–85.
20 Hardoon KK, Gupta R, Derevensky JL. Psychosocial variables associated with adolescent gambling.
Psychol Addict Behav 2004;18:170–9.
21 Barnes GM, Welte JW, Hoffman JH, et al. Shared predictors of youthful gambling, substance use,
and delinquency. Psychol Addict Behav 2005;19:165–74.
22 Wanner B, Vitaro F, Carbonneau R, et al. Cross-lagged links among gambling, substance use, and
delinquency from midadolescence to young adulthood: additive and moderating effects of common
risk factors. Psychol Addict Behav 2009;23:91–104.
Page 14 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
15
23 Castrén S, Grainger M, Lahti T, et al. At-risk and problem gambling among adolescents: a
convenience sample of first-year junior high school students in Finland. Subst Abuse Treat Prev
Policy 2015;10:1–10.
24 Hanss D, Mentzoni RA, Blaszczynski A, et al. Prevalence and Correlates of Problem Gambling in a
Representative Sample of Norwegian 17-Year-Olds. J Gambl Stud 2015;31:659–78.
25 Lee GP, Martins SS, Pas ET, et al. Examining potential school contextual influences on gambling
among high school youth. Am J Addict 2014;23:510-7.
26 Scholes-Balog KE, Hemphill SA, Dowling NA, et al. A prospective study of adolescent risk and
protective factors for problem gambling among young adults. J Adolesc 2014;37:215–24.
27 Kristiansen S, Jensen SM. Prevalence of gambling problems among adolescents in the Nordic
countries: an overview of national gambling surveys 1997–2009. Int J Soc Welfare 2011;20:75–86
28 Burge AN, Pietrzak RH, Molina CA et al. Age of gambling initiation and severity of gambling and
health problems among older adult problem gamblers. Psychiatric Services 2004;55:1437–39.
29 Schulte MT, Ramo D, Brown SA. Gender differences in factors influencing alcohol use and drinking
progression among adolescents. Clin Psychol Rev 2009;29:535–47.
30 Helldán, A., Helakorpi, S., Virtanen, S., & Uutela, A. (2013). Health behaviour and health among the
Finnish adult population. National Institute for Health and Welfare (THL), Report 15/2013. Retrieved
from: http://urn.fi/URN:ISBN:978-952-245-931-2
31 Barnes GM, Welte JW, Hoffman JH, et al. The co-occurrence of gambling with substance use and
conduct disorder among youth in the United States. Am J Addict 1999;20:166–73.
32 Vitaro F, Brendgen M, Ladouceur R, et al. Gambling, delinquency, and drug use during adolescence:
mutual influences and common risk factors. J Gambl Stud 2001;17:171–90.
33 Luopa, P, Kivimäki H, Matikka, A, et al. Nuorten hyvinvointi Suomessa 2000-2013 -
Kouluterveyskyselyn tulokset. [Wellbeing of adolescents in Finland 2000–2013.The Results of the
Page 15 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
16
School Health Promotion study]. National Institute for Health and Welfare (THL). Report 25/2014
34 Räsänen T, Lintonen T, Konu A. Gambling and Problem Behavior Among 14- to 16-Year-Old Boys
and Girls in Finland. J Gambl Issues 2015;31:1–22.
35 Muthén LK, Muthén BO (1998-2015). Mplus User’s Guide. Seventh Edition. Los Angeles, CA: 2015.
36 Nylund KL, Asparouhov T, Muthén BO. Deciding on the number of classes in latent class analysis
and growth mixture modeling: A Monte Carlo simulation study. Struct Equ Model 2007;14:535–69.
37 Jung T, Wickrama KAS. An Introduction to Latent Class Growth Analysis and Growth Mixture
Modeling. Soc Personal Psychol Compass 2008;2:302–17.
38 Mun EY, Windle M, Schainker LM. A model-based cluster analysis approach to adolescent problem
behaviors and young adult outcomes. Dev Psychopathol 2008;20:291–318.
39 Räsänen T, Lintonen T, Joronen K, et al. Girls and boys gambling with health and well-being in
Finland. J Sch Health 2015;85:214–22.
40 Nigg CR, Allegrante JP, Ory M. Theory-comparison and multiple-behavior research: common themes
advancing health behavior research. Health Educ Res 2002;17:670–9.
Page 16 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
17
Table 1. Results for the latent class analysis (LCA). Bolding for those participating in problem behavior the most and the least.
8th grade boys 9
th grade boys 8
th grade girls 9
th grade girls
n for classes entropy Lo-
Mendell-
Rubin
n for classes entropy Lo-
Mendell-
Rubin
n for
classes
entropy Lo-
Mendell-
Rubin
n for
classes
entropy Lo-
Mendell-
Rubin
1 class
model
19,471 na. na. 21,711 na. na. 9,432 na. na. 12,342 na. na.
2 class
model
c1=6,805
c2=12,666
0.86 0.00 c1=25,768
c2=37,188
0.85 0.00 c1=3,591
c2=5,841
0.86 0.00 c1=5,445
c2=6,897
0.82 0.00
3 class
model
c1=1,975
c2=6,813
c3=10,683
0.90 0.00 c1=9,482
c2=26,304
c3=27,170
0.89 0.00 c1=1,734
c2=3,706
c3=3,992
0.88 0.00 c1=2,645
c2=3,707
c3=5,990
0.88 0.00
4 class
model
c1=586
c2=5,377
c3=3,065
c4=10,443
0.88 0.04 c1=911
c2=4,734
c3=7,233
c4=8,833
0.86 0.00 c1=513
c2=2,123
c3=3,240
c4=3,556
0.86 0.00 c1=1,473
c2=4,145
c3=3,169
c4=3,555
0.83 0.00
5 class
model
c1=567 c2=2,829
c3=4,543
c4=2,956
c5=8,576
0.81 0.70 c1=503 c2=2,290
c3=6,086
c4=4,142
c5=8,690
0.85 0.00 c1=138 c2=1,165
c3=1,641
c4=3,013
c5=3,475
0.86 0.00 c1=159 c2=1,910
c3=2,865
c4=3,543
c5=3,865
0.84 0.76
Page 17 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on November 28, 2020 by guest. Protected by copyright. http://bmjopen.bmj.com/ BMJ Open: first published as 10.1136/bmjopen-2016-012468 on 22 December 2016. Downloaded from
For peer review only
18
Table 2. Adolescents’ involvement in gambling and problem behavior, and experiencing social support from
friends (SSF), school (SSS) and parents (SSP) based on their sex and grade.
Eta values indicate the strength of associations
8th grade
boys
9th grade
boys
8th grade
girls
9th grade
girls
Boys vs.
girls
8 vs. 9
grade %
Gambling p < 0.001 eta:0.278
p=0,022 eta:0.01
less than once a month
38.4 34.1 73.7 69.9
less than once a week
28.8 30.3 15.7 18.1
1–2 days per
week
18.7 19.6 5.0 6.2
3–5 days per
week
8.1 9.3 2.2 3.0
6–7 days per
week
6.1 6.8 3.4 2.8
Participating
in problem
behavior
5.3 9.3 12.6 29.3 p < 0.001
eta: 0.210
p < 0.001
eta: 0,14
SSF p < 0.001
eta: 0.101
p=0.029
eta:0.015
do not have
any friends
13.7 15.3 7.1 6.7
one close
friend
24.1 26.0 20.7 21.6
two close
friends
20.5 19.1 27.5 27.2
several close
friends
40.9 39.0 44.5 44.3
missing values 0.8 0.7 0.2 0.3
x, (SD)
SSS 2.8 (0.5) 2.7 (0.6) 2.7 (0.5) 2.7 (0.6) p < 0.001
eta: 0.003
p < 0.001
eta: 0.002
SSP 2.2 (0.6) 2.2 (1.2) 2.1 (0.7) 2.0 (0.7) p < 0.001
eta: 0.005
p < 0.001
eta: 0.001
n 11,029 9,744 4,069 5,028 29,870 29,870
Page 18 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
19
Table 3. Path model of the direct and indirect effects between the social support from friends (ssf), school
(sss), parents (ssp), problem behaviour (pb) and gambling frequency (gb) among 8th and 9th grade boys and
girls.
** p<0.01, ***p<0.001
Direct effect c (pb to gb) 8th grade boys 9
th grade boys 8
th grade girls 9
th grade girls
Path from pb to sss (path e) β β β β
Path from pb to ssf (path d) 0.35*** 0.36*** 0.34*** 0.36***
Path from pb to ssp (path f) -0.30*** -0.36*** -0.43*** -0.46***
Path from sss to gb (path h) -0.09*** -0.07*** -0.08*** -0.01
Path from ssf to gb (path g) -0.37*** -0.39*** -0.19*** -0.50***
Path from ssp to gb (path i) -0.11*** -0.13*** -0.06** -0.11***
Total effect c’ (pb to gb) 0.07*** 0.04*** -0.08*** -0.09***
Total indirect effect c-c’ -0.09*** -0.08*** -0.10*** -0.06***
Path from pb to sss to gb 0.41*** 0.43*** 0.42*** 0.44***
Path from pb to ssf to gb 0.06*** 0.07*** 0.08*** 0.08***
Path from pb to ssp to gb 0.03*** 0.05*** 0.03** 0.05***
Direct effect c (pb to gb) -0.01*** -0.00*** 0.01*** 0.00
Path from pb to sss (path e) 0.03*** 0.03*** 0.05*** 0.03***
Page 19 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
20
Page 20 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
106x59mm (300 x 300 DPI)
Page 21 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
1
STROBE Statement—checklist of items that should be included in reports of observational studies
Item
No Recommendation
Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract
page 1
(b) Provide in the abstract an informative and balanced summary of what was done
and what was found -page 1
Introduction
Background/rationale 2 Explain the scientific background and rationale for the investigation being reported
pages 2-3
Objectives 3 State specific objectives, including any prespecified hypotheses page 3
Methods
Study design 4 Present key elements of study design early in the paper pages 4-5
Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment,
exposure, follow-up, and data collection page 3
Participants 6 (a) Cohort study—Give the eligibility criteria, and the sources and methods of
selection of participants. Describe methods of follow-up
Case-control study—Give the eligibility criteria, and the sources and methods of
case ascertainment and control selection. Give the rationale for the choice of cases
and controls
Cross-sectional study—Give the eligibility criteria, and the sources and methods of
selection of participants pages 3-4
(b) Cohort study—For matched studies, give matching criteria and number of
exposed and unexposed
Case-control study—For matched studies, give matching criteria and the number of
controls per case
Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect
modifiers. Give diagnostic criteria, if applicable page 4, sup.material
Data sources/
measurement
8* For each variable of interest, give sources of data and details of methods of
assessment (measurement). Describe comparability of assessment methods if there
is more than one group sup. material
Bias 9 Describe any efforts to address potential sources of bias none
Study size 10 Explain how the study size was arrived at pages 3-4
Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable,
describe which groupings were chosen and why sup. material 4-5
Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding,
4-5
(b) Describe any methods used to examine subgroups and interactions
(c) Explain how missing data were addressed
(d) Cohort study—If applicable, explain how loss to follow-up was addressed
Case-control study—If applicable, explain how matching of cases and controls was
addressed
Cross-sectional study—If applicable, describe analytical methods taking account of
sampling strategy
(e) Describe any sensitivity analyses
Continued on next page
Page 22 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
2
Results
Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible,
examined for eligibility, confirmed eligible, included in the study, completing follow-up, and
analysed
(b) Give reasons for non-participation at each stage
(c) Consider use of a flow diagram
Descriptive
data
14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information
on exposures and potential confounders
(b) Indicate number of participants with missing data for each variable of interest
(c) Cohort study—Summarise follow-up time (eg, average and total amount)
Outcome data 15* Cohort study—Report numbers of outcome events or summary measures over time
Case-control study—Report numbers in each exposure category, or summary measures of
exposure
Cross-sectional study—Report numbers of outcome events or summary measures page 14
Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their
precision (eg, 95% confidence interval). Make clear which confounders were adjusted for and
why they were included
(b) Report category boundaries when continuous variables were categorized
(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful
time period
Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity
analyses 4-5
Discussion
Key results 18 Summarise key results with reference to study objectives 7-9
Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision.
Discuss both direction and magnitude of any potential bias 8-9
Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity
of analyses, results from similar studies, and other relevant evidence 8
Generalisability 21 Discuss the generalisability (external validity) of the study results 8
Other information
Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable,
for the original study on which the present article is based page 9
*
Page 23 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
Social support as a mediator between problem behaviour
and gambling – a cross-sectional study among 14- to 16-
year-old Finnish adolescents
Journal: BMJ Open
Manuscript ID bmjopen-2016-012468.R3
Article Type: Research
Date Submitted by the Author: 03-Nov-2016
Complete List of Authors: Räsänen, Tiina; University of Tampere, School of Health Sciences Lintonen, Tomi; Finnish Foundation for Alcohol Studies Tolvanen, Asko; University of Jyväskylä, Department of Psychology
Konu, Anne; University of Tampere, School of Health Sciences
<b>Primary Subject Heading</b>:
Addiction
Secondary Subject Heading: Public health
Keywords: Health policy < HEALTH SERVICES ADMINISTRATION & MANAGEMENT, Substance misuse < PSYCHIATRY, PUBLIC HEALTH
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open on N
ovember 28, 2020 by guest. P
rotected by copyright.http://bm
jopen.bmj.com
/B
MJ O
pen: first published as 10.1136/bmjopen-2016-012468 on 22 D
ecember 2016. D
ownloaded from
For peer review only
1
Social support as a mediator between problem behaviour and gambling – a cross-sectional study
among 14- to 16-year-old Finnish adolescents
Tiina Räsänen, Tomi Lintonen, Asko Tolvanen & Anne Konu
Tiina Räsänen: School of Health Sciences, University of Tampere, Finland
Phone: +358 445368416
Email: [email protected]
Tomi Lintonen: Finnish Foundation for Alcohol Studies, Helsinki, Finland
Asko Tolvanen: Department of Psychology, University of Jyväskylä, Finland
Anne Konu: School of Health Sciences, University of Tampere, Finland
Word count:
Abstract: Background: During the adolescent period, risk-taking behaviour increases. These behaviours can
compromise the successful transition from adolescence to adulthood. The purpose of this study was to
examine social support as a mediator of the relation between problem behaviour and gambling frequency
among Finnish adolescents. Methods: Data were obtained from the national School Health Promotion Study
(SHPS) from the years 2010 and 2011 (N = 102,545). Adolescents were classified in the most homogenous
groups based on their problem behaviour via latent class analysis. Results: Path analysis indicated that social
support was negatively associated with problem behaviour, and problem behaviour and social support were
negatively related (except for social support from friends among boys) to gambling. Social support from
parents and school mediated, albeit weakly, the relations between problem behaviour and gambling among
girls and boys. Conclusion: Problem behaviour may affect gambling through social support from school and
parents. Thus prevention and intervention strategies should focus on strengthening adolescents’ social
support. In addition, because of the clustering of different problem behaviours instead of concentrating on a
single form of problem behaviour multiple-behaviour interventions may have a much greater impact on
public health.
Keywords: gambling frequency, adolescents, social support, problem behaviour
Page 1 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
2
Strengths and limitations of this study
• large scale, population-based study explored the relationship between gambling, problem behaviour
and social support
• studies have examined pathways from social support to both gambling and other problem
behaviours, but research that tries to explain how adolescents’ access to social support accounts for
the association between gambling frequency and problem behaviour, is lacking
• temporal relationship between these factors remains unclear, because of the cross-sectional nature of
the study
• it may be that the final sample did not include the adolescents who were engaging in the highest
levels of gambling and the highest levels of problem behaviour
• since this study was based solely on adolescent self-reports, there is the possibility of over or under-
reporting
Introduction
During the adolescent period, risk-taking behaviour increases. [1] Risk-taking includes behaviours that are
done under one’s own volition, have uncertain outcomes, and can compromise the successful transition from
adolescence to adulthood. [2,3] Risk-taking behaviours also manifest in the form of problem behaviours;
actions that are socially disapproved and result in social sanctions. These behaviours can co-occur; thus,
involvement in one problem behaviour increases the risk of involvement in other problem behaviours, which
is known as problem behaviour syndrome.[4,5] Gambling may be a component of the problem behaviour
syndrome: problem gambling and regular gambling (at least once a week) are associated with conduct
disorder, substance use, and delinquency [6–9]. However, it is not known if non-problem gambling and
gambling that is not necessary regular is related to the problem behaviour syndrome. In Finland in 2010
gambling was allowed for adolescents aged 15 and over (except Internet and casino gambling) and in 2011,
15 year olds could legally gamble at slot machines (all other gambling games had age limit of 18), which are
widely available in Finland. Adolescents have also had positive attitudes towards gambling in Finland [10].
Page 2 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
3
Likewise, studies have shown that parents and teachers do not think that gambling is great concern among
youth. [11,12]
According to problem behaviour theory, it is the balance between protective and risk factors that determines
ones’ involvement in problem behaviour. [5] Social support provided by individuals and institutions can be
described as interpersonal relationships that influence an individual’s functioning. Social support is parents’
closeness, monitoring and caring, teachers’ interest in their students, and friends’ supportiveness [13].
Studies have shown that social support from parents, friends, and school all play a crucial role in
adolescents’ problem behaviour. [14–16] There is also some evidence indicating that family characteristics
influence adolescents’ gambling.[17] Specifically, higher levels of parental attachment, monitoring, and
supervision are linked to decreased gambling, while lower levels of parental trust and communication are
associated with increased gambling.[18] Low levels of parental monitoring of adolescents is also associated
with problem gambling during young adulthood. [19] Additionally, adolescent problem gamblers tend to
perceived lower levels of familial and peer support.[20] While previous studies have examined shared
predictors between gambling, problem behaviours, and parenting, the findings of these studies do not provide
evidence that parental supervision or monitoring are related to gambling as it is the case for other problem
behaviours.[21,22] Moreover, friends’ approval of gambling, associating with deviant peers, associating with
friends who gamble, and having friends who have gambling problems are associated with adolescent
gambling.[8,23,24] However, the only school characteristics that have been studied in the context of
gambling are suspension rates, low school commitment, and schools’ rewards for prosocial involvement.
These were either weakly or not at all associated with gambling. [25,26] Studies examining the associations
between schools’ social support and gambling, are lacking.
Earlier studies have demonstrated that there are gender differences in gambling as well as problem
behaviour. For example, gambling is more common among males [27] and males also tend to start gambling
at a younger age. [28] Additionally, males have a higher risk for heavy alcohol use and smoking. [29,30]
However, little is known about gender differences in relation to co-occurrence of gambling frequency and
problem behaviours. It is also unclear if there are gender differences in associations between gambling,
problem behaviour and social support.
Page 3 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
4
In studies that assess gambling, problem behaviour, and risk/protective factors, a limited number of problem
behaviours (e.g., gambling, substance use, and delinquency) are examined, and the focus is on parental
monitoring, individual factors (impulsivity, moral disengagement), and peer delinquency[21,22,31,32],
thereby excluding social support from important individuals and institutions, like friends and school.
Previous studies have examined pathways from social support to both gambling and other problem
behaviours, but research that tries to explain how adolescents’ access to social support accounts for the
association between gambling frequency and problem behaviour, is lacking. Thus, the role of social support
in the association between problem behaviour and gambling has not been investigated. As earlier studies
have shown that gambling is associated with problem behaviour and the degree of social support that
adolescent receives is related to both gambling frequency and problem behaviour, it is reasonable to expect
that social support plays an important role in the extent to which problem behaviours are related to gambling
frequency. Therefore, using a population-based survey of 8th and 9
th grade boys and girls, the aim of this
study was to investigate the relations between problem behaviour and gambling frequency, and social
support as a potential mediator of this association (i.e., serve as a protective factor). It is assumed that higher
social support would be negatively associated with problem behaviour and gambling.
Method
Setting
In Finland, compulsory basic comprehensive school starts at age 7 (1st grade) and ends at the age of 16 (9th
grade). During the 8th and 9th grade boys and girls are between 14- to 16-years of age.
The Finnish gambling system is based on a state monopoly; the profits are returned to society and used for
common good. In addition, the games are widely available in public places. The gambling age limit was set
to 18 years in October 2010. The limit was also applied to slot machines in July 2011, and prior to that the
age limit was age 15. At the time of survey completion, the age limit for gambling was 18 years, and 15
years for slot machines.
Page 4 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
5
Data
Data were obtained from the national School Health Promotion Study (SHPS) in 2010 and 2011, which
included questions on adolescents’ gambling, problem behaviour, and social support. In 2010, the study was
conducted in southern, eastern and northern Finland and in western and central Finland in 2011. Thus, the
2010 and 2011 surveys cover all of Finland, and in each year only a few municipalities refuse to participate
[33]. The municipalities that did not participate do not differ from the others and this part of the drop-out is
not likely to pose a threat to generalizability. In 2010, 78% of Finnish 8th and 9
th graders were surveyed, and
in 2011 81% of Finnish 8th and 9th graders participated in the study. Respondents who had not answered
over half of the questions, or had not expressed their sex or grade, were removed. Also those who were not
school when survey was conducted or could not answer independently did not participate. [33] SHPS was
approved by the ethical committee of Tampere University Hospital. SHPS is a cross-sectional survey
administered throughout the school day in the 8th and 9
th grades of lower secondary schools. Answering was
voluntary. Parental consent was not required according to ethical guidelines in Finland; generally, surveys
conducted during school days do not need parental permission. In total, 102,545 8th (mean age = 14.9, SD =
0.4) and 9th (mean age = 15.9, SD = 0.4) grade students participated in the study. Forty-nine percent of
survey respondents were boys.
Measures
Problem behavior
Problem behavior was measured through 11 different forms of problem behaviors concerning adolescents’
truancy, bullying, delinquency, smoking, using snuff, alcohol drinking, drunkenness-related drinking, using
alcohol and medicine for intoxication, using medicine for intoxication, glue-sniffing and drug use. More
detailed information about questions regarding problem behavior can be found elsewhere. [34] Because
problem behavior indicator included measures with multiple behavior types and responses, which were not
necessarily identically scaled, latent classes were estimated. Based on latent class analysis (LCA) adolescents
were divided into four groups. From these groups those who participated in problem behavior the most and
the least were selected from the data to study extremities of the problem behavior phenomenon.
Page 5 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
6
Social support from friends
Social support from friends were requested by question: Do you have at this moment any close friend whom
you can talk with confidentially almost everything? Alternatives were I do not have any friends, one close
friend, two close friends and several close friends.
Social support from school
Social support from school based on three statements and two questions about schools’ and teachers’
support. Statements were: teachers encourage me to impress my own opinions at classes, teachers are
interested about how I am doing and teachers are treating students fairly. The scale for these was totally
agree, agree, disagree and totally disagree. Students were also asked: do you have troubles getting along with
your teachers. Alternatives were not at all, fairly little, fairly much and very much. As well adolescents were
requested if they had troubles with school work, how often they got help from school. Alternatives were
always when I need it, most of the time, rarely and almost never. All of the statements and questions were
coded from one to four, four indicating good social support. From these five variables the sum variable was
created, which had one component structure with Cronbach’s alpha value of 0.7.
Social support from parents
Social support was examined by four questions. Students were asked do their parents know all of his/her
friends. This question had alternatives both parent do (coded as three), only mother/father knows (coded as
one) and neither of them do not know (coded as zero). Second question was, do your parent know where you
spent your Friday and Saturday evenings, which had alternatives they know always (coded as three), know
sometimes (coded as one) and most of the time do not know (coded as zero). Adolescents were also asked
can they talk with their parents: almost never (coded as zero), sometimes (coded as one), fairly often (coded
as two) and often (coded as three). The last question was if adolescents had troubles with school work, how
often they got help from home. Alternatives were always when I need it (coded as three), most of the time
Page 6 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
7
(coded as two), rarely (coded as one) and almost never (coded as zero). These four questions measuring the
social support from parents had one component structure, which had Cronbach’s alpha value of 0.6.
Gambling
Gambling was requested by one question: How often do you gamble? Alternatives were on 6–7 days per
week, on 3–5 days per week, on 1–2 days per week, less than once a week, less than once a month, I have
not gambled during previous year’.
Statistical analysis
Basic statistical analyses were conducted with IBM SPSS Statistics 22, and structural equation modelling
was conducted with Mplus 7.0.[35] Basic statistical analyses included a χ2-test (for categorical data) and
Mann–Whitney U test (for continuous data), which are used to detect statistically significant difference
between two or more groups. Latent class analysis (LCA) was used to identify groups of adolescents based
on their involvement in different problem behaviours. The purpose was to identify the most homogenous
groups that include extreme classes of problem behaviour. LCA provides fit statistics and significance tests
to assess the number of classes that best fit the data.[36] To select the number of classes for the model, the
analysis was first run with one class, then with two and three classes, and so on. This procedure was
followed until to the highest possible number of classes were run (which was in this case 11). Model
solutions were assessed by examining the entropy values (near 1.0), the Lo–Mendell–Rubin test (a p value
that provides information about statistically significant improvement in fit for the inclusion of an additional
class) as well as the interpretation of the results.[37] For further analysis, all individuals were classified into
classes where class membership was based on the highest posterior probabilities.
Based on the LCA results, path analysis was conducted for those who participated in the most and the least
problem behaviours. The analysis was conducted to examine if social support mediates the association
between problem behaviour and gambling. In this model, gambling frequency was regressed on the three
forms of social support, and forms of social support were then regressed on problem behaviour (Figure 1).
Analyses were run separately for 8th and 9
th grade girls and boys given the possible differences in the relation
Page 7 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
8
between gambling and problem behaviour. All the models were saturated, so the model fits were necessarily
perfect.
Results
LCA
Adolescents who did not gamble during the previous year (37.3%) or had missing values on the main
outcome variable (1.3%) were excluded. This was done because we were only interested in adolescents who
were gambling. For the remaining 62,956 individuals, LCA was conducted separately for 8th and 9
th grade
girls and boys to identify groups of adolescents based on their problem behaviours. For all 8th and 9th grade
girls and boys, the optimal model had four classes with entropy values ranging from 0.88 to 0.83. The
reasonably high entropies and the Lo–Mendell–Rubin test p values suggested a good model fit for the four
class model. However, among 8th grade girls and 9th grade boys, the p values were lower than 0.05,
indicating that the five or more class model was a better fit. However, after taking into account the entropies
and the interpretation of the results, the four class model was chosen for all participants (Table 1).
Class 1 included adolescents who participated in all forms of problem behaviours at the highest frequency
[see 33]. For example, adolescent in class 1 smoked at least daily, drunk alcohol on a weekly basis and had
tried drugs at least once. Youths in class 2 also participated in problem behaviour, but their participation in
problem behaviours was more experimental. In addition, most of youths in class 2 did not use alcohol with
medicine for intoxication, use medicine for intoxication, and did not participate in glue sniffing. In class 3,
adolescents smoked tobacco less often than once a week and consumed alcohol only a couple of times a
month. The youths in class 4 did not participate in any form of problem behaviour. From these groups, class
1 and class 4 were selected, including adolescents participating regularly in all examined problem behaviours
and those not participating in any, which allowed for the study of the extremes of problem behaviour (N =
29,870).
Page 8 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
9
Gambling, problem behaviour and social support
The next set of analyses compared the adolescents who participated in the most problem behaviour and the
adolescents that participated in the least problem behaviour. Boys gambled more than girls did (χ2 (4) =
3280.182, p < 0.001); however, participation in problem behaviour was more common among girls (χ2 (1) =
1313.636, p < 0.001) (Table 2). Girls experienced more social support from friends (χ2 (4) = 553.19, p <
0.001), and boys received more support from school (U = 88080721, p < 0.001) and from parents (U =
84026360, p < 0.001) (Table 2). 9th graders gambled (boys: χ
2 (4) = 11,395 p=0,022), (girls: χ
2 (4) = 25.416,
p < 0.001) and participated in problem behaviour (boys: χ2 (1) = 126.024, p < 0.001), (girls: χ2 (1) = 367.030,
p < 0.001) more often than 8th graders. Eighth grade boys also experienced more social support from friends
(χ2 (3) = 25.933), p < 0.001), school (U = 52467017.0, p < 0.01), and parents (51780278.5, p < 0.001) than
9th grade boys. Eighth grade girls experienced more social support from school (U = 9696512.5, p < 0.001)
and parents (U = 9817557.0, p < 0.01), but there were no statistical differences in social support from friends
(Table 2). Among girls who gambled on weekly basis, 50% of 8th graders and 74% of 9
th graders also
participated in problem behaviour. Among the boys, the percentage was 14% for 8th graders and 22% for 9th
graders.
Path analysis
The standardized parameter estimates (β) shown in Table 3 indicated that problem behaviour was
significantly and positively related to adolescents’ gambling frequency (path c). The beta indices also
showed that there was a significant negative association between problem behaviour and the different types
of social support; however, among 9th grade girls, social support from friends was not statistically significant
(paths d–f). Social support from parents and school were negatively related with gambling (paths g and i).
Among boys, social support from friends was significant and positively associated with gambling; however,
among girls social support from friends was significantly and negatively associated with gambling (path h)
(Table 3; also see Figure 1).
The statistically significant albeit very small indirect effects indicated that social support mediated the
relationship between problem behaviour and gambling frequency, but social support from friends did not
mediate this association. The total effect of problem behaviour on problem gambling frequency consisted of
Page 9 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
10
a direct effect and an indirect effect through social support (Table 3). Forty-two percent and 49% of the
variance (R2) was explained by the association between gambling and social support for 8th grade and 9th
grade boys, respectively. For 8th grade girls, 63% of the variance was explained and 69% of the variance was
explained for 9th graders.
Discussion
This large scale, population-based study explored the relationship between problem behaviour, gambling and
social support among 14- to 16-year-old adolescents. The main purpose of the study was to examine whether
social support would mediate this association. Social support from parents and school mediated weakly the
relations between problem behaviour and gambling among girls and boys. Social support from friends did
not mediate this association. Thus, the data suggest that the relation between problem behaviour and
gambling can be explained only by the degree of social support received from school and parents; there may
be other issues or phenomena that are more important in mediating this association.
In accordance with the Mun et al. [38] research, this study indicated that problem behaviour did cluster at the
both ends of the lifestyle spectrum (i.e., “problem” or “non-problem” behaviour patterns among adolescents).
Within these two classes, there were adolescents who participated regularly in all forms of problem
behaviours and those who did not participate in any problem behaviours. Additionally, this study found that
problem behaviour and gambling were associated, with problem behaviour increasing as the frequency of
gambling increased. This is similar to previous studies.[7,22,32] These results may indicate that involvement
in one problem behaviour also increases the risk of involvement in other problem behaviours, as
demonstrated by problem behaviour theory.[4,13]
To the best of our knowledge, this is the first study to examine whether social support from school is
associated with gambling frequency. Earlier studies have assessed school characteristics, such as suspension
rates, school commitment, and schools’ rewards for prosocial involvement.[25,26] In the current study,
social support from school was significantly related to gambling frequency, with lower support related to
higher gambling participation. In addition, low social support from parents and friends was related to
increased gambling, which is consistent with the findings of Hardoon et al. [20] In their study, they reported
Page 10 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
11
significant differences between gambling severity groups in their levels of family and peer support.
Specifically, their results indicated that non-gamblers and social gamblers experienced more social support
than at-risk and pathological gamblers. However, in the current study, this pattern was found only for female
adolescent gamblers. For boys, social support from friends was positively related to gambling frequency. It
might be that gambling is social activity for boys, but for girls gambling may be an activity that substitutes
normal social contacts. Problem gambling may occur in the absence of friends, whereas non-problematic
gambling may be part of a social pastime.[20] Gambling was more common among boys, which is consistent
with previous studies[6,23]; however, over 50% of 8th grade and 74% of 9th grade girls who gambled on a
weekly basis participated in problem behaviour. This indicates that active gambling among girls is strongly
linked to problem behaviour and thus a phenomenon that should be studied more extensively.
Although the findings of this study indicated that social support mediated the association between problem
behaviour and gambling frequency, the temporal relationship between these factors remains unclear. Thus,
additional research is needed using longitudinal data. Additionally, it is important to note that while social
support from friends, parents, and school were significantly associated with gambling, the path coefficients
were low among boys and girls and may due to large sample size. Furthermore, path coefficients for the
indirect effects were low. This may indicate that social support does not play a large in the association
between problem behaviour and gambling. There may be additional factors that play a more important role in
this association, such as having friends or parents who: gamble, have a gambling problem, or participate in
other problem behaviours or individual factors such as low self-control or conduct disorder. These types of
factors have been examined in previous studies.[7,8,18,21,23,24]
Furthermore, gambling frequency was assessed by a single item, and there was not a validated problem
gambling screen used herein. However, the goal of the study was to study gambling involvement and its
associations with problem behaviours and social support, not to identify problem gamblers. The survey did
not collect additional information on gambling behaviour (e.g., how much money is spent on gambling), nor
was information about gambling types. Additionally, the definition of gambling was not given in the
questionnaire, so adolescents could interpret gambling in many ways. [34,39] Also we did not use a validated
measure for social support. The internal consistency for the scale of “social support from parents” was not
Page 11 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
12
optimal as indicated by the low value of Cronbach's alpha. However, validity is supported by the fact that the
principal component analysis indicated one component structure.
In addition, data were collected from 78% of Finnish 8th and 9th graders in 2010 and from 81% of Finnish
8th and 9
th graders in 2011. However, it may be that the final sample did not include the adolescents who
were engaging in the highest levels of gambling and the highest levels of problem behaviour. Moreover,
since this study was based solely on adolescent self-reports, there is the possibility of over or under-
reporting.
Despite the limitations, mediation effects were detected, which have theoretical importance as well as
significant implications for intervention. Specifically, prevention and intervention strategies should focus on
strengthening adolescents’ social support from parents and school. In addition, because of the clustering of
different problem behaviours and the fact that problem behaviour was linked to gambling, instead of
concentrating on a single form of problem behaviour multiple-behaviour interventions may have a much
greater impact on public health.[40]
Contributor ship statement: Study conception and design: Räsänen, Tolvanen, Lintonen, Konu; Analysis
and interpretation of data: Räsänen, Tolvanen, Lintonen, Konu; Drafting of manuscript: Räsänen; Critical
revision: Tolvanen, Lintonen, Konu
Competing interests: None declared.
Funding: This study was financially supported by the Finnish Foundation for Alcohol Studies. The Finnish
Foundation for Alcohol Studies had no involvement in the study design, data handling, writing or submission
of the manuscript. The grants awarded by the Finnish Foundation for Alcohol Studies for gambling research
are based on a government contract for studying gambling-related harm.
Data sharing statement: No additional data available.
1 Michael K, Ben-Zur H. Risk-taking among adolescents: associations with social and affective factors.
J Adolesc 2007;30:17–31.
2 Igra V, Irwin CE. Theories of Adolescent Risk-Taking Behavior. In: R. J. DiClemente, W. B. Hansen
Page 12 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
13
&, Ponton LE, eds. Handbook of adolescent health risk behaviour. New York: : Plenum Press 1996.
35–51.
3 Leather NC. Risk-taking behaviour in adolescence: a literature review. J Child Health Care
2009;13:295–304.
4 Jessor R, Jessor SL. Problem behavior and psychosocial development: A longitudinal study of youth.
New York: : Academic Press 1977.
5 Jessor R, Turbin MS. Parsing protection and risk for problem behavior versus pro-social behavior
among US and Chinese adolescents. J Youth Adolesc 2014;43:1037–51.
6 Barnes GM, Welte JW, Hoffman JH, et al. Gambling, alcohol, and other substance use among youth
in the United States. J Stud Alcohol Drugs 2009;70:134–42.
7 Welte JW, Barnes GM, Tidwell MC, et al. Association between problem gambling and conduct
disorder in a national survey of adolescents and young adults in the United States. J Adolesc Health
2009;45:396-401.
8 Gori M, Potente R, Pitino A, et al. Relationship Between Gambling Severity and Attitudes in
Adolescents: Findings from a Population-Based Study. J Gambl Stud 2014;31:717–40.
9 Yip SW, Desai RA, Steinberg MA, et al. Health/functioning characteristics, gambling behaviors, and
gambling-related motivations in adolescents stratified by gambling problem severity: findings from a
high school survey. Am J Addict 2011;20(6):495-508.
10 Salonen A, Castren, S, Raisamo S, et al. Attitudes towards gambling in Finland: a cross-sectional
population study. BMC Public Health 2014. doi: 10.1186/1471-2458-14-982.
11 Shead WN, Derewensky, JL, Meerkamper E. Your Mother Should Know: A Comparison of Maternal
and Paternal Attitudes and Behaviors Related to Gambling among Their Adolescent Children. Int J
Ment Health Addiction 2011;9:264–75.
12 Derevensky JL, St-Pierre RA, Temcheff CE et al. Teacher Awareness and Attitudes Regarding
Adolescent Risky Behaviours: Is Adolescent Gambling Perceived to be a Problem? J Gambl Stud
Page 13 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
14
2014;30: 435–51.
13 Jessor R, Turbin MS, Costa FM, et al. Adolescent Problem Behavior in China and the United States:
A Cross-National Study of Psychosocial Protective Factors. J Res Adolesc 2003;13:329–60.
14 Deković M. Risk and Protective Factors in the Development of Problem Behavior During
Adolescence. J Youth Adolesc 1999;28:667–85.
15 Fleming CB, Catalano RF, Haggerty KP, et al. Relationships between level and change in family,
school, and peer factors during two periods of adolescence and problem behavior at age 19. J Youth
Adolesc 2010;39:670–82.
16 Garnefski N, Diekstra RF. Perceived social support from family, school, and peers: relationship with
emotional and behavioral problems among adolescents. J Am Acad Child Adolesc Psychiatry
1996;35:1657–64.
17 McComb JL, Sabiston CM. Family influences on adolescent gambling behavior: a review of the
literature. J Gambl Stud 2010;26:503–20.
18 Magoon ME, Ingersoll GM. Parental Modeling, Attachment, and Supervision as Moderators of
Adolescent Gambling. J Gambl Stud 2006;22:1–22.
19 Lee GP, Stuart EA, Ialongo NS, et al. Parental monitoring trajectories and gambling among a
longitudinal cohort of urban youth. Addiction 2014;109:977–85.
20 Hardoon KK, Gupta R, Derevensky JL. Psychosocial variables associated with adolescent gambling.
Psychol Addict Behav 2004;18:170–9.
21 Barnes GM, Welte JW, Hoffman JH, et al. Shared predictors of youthful gambling, substance use,
and delinquency. Psychol Addict Behav 2005;19:165–74.
22 Wanner B, Vitaro F, Carbonneau R, et al. Cross-lagged links among gambling, substance use, and
delinquency from midadolescence to young adulthood: additive and moderating effects of common
risk factors. Psychol Addict Behav 2009;23:91–104.
Page 14 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
15
23 Castrén S, Grainger M, Lahti T, et al. At-risk and problem gambling among adolescents: a
convenience sample of first-year junior high school students in Finland. Subst Abuse Treat Prev
Policy 2015;10:1–10.
24 Hanss D, Mentzoni RA, Blaszczynski A, et al. Prevalence and Correlates of Problem Gambling in a
Representative Sample of Norwegian 17-Year-Olds. J Gambl Stud 2015;31:659–78.
25 Lee GP, Martins SS, Pas ET, et al. Examining potential school contextual influences on gambling
among high school youth. Am J Addict 2014;23:510-7.
26 Scholes-Balog KE, Hemphill SA, Dowling NA, et al. A prospective study of adolescent risk and
protective factors for problem gambling among young adults. J Adolesc 2014;37:215–24.
27 Kristiansen S, Jensen SM. Prevalence of gambling problems among adolescents in the Nordic
countries: an overview of national gambling surveys 1997–2009. Int J Soc Welfare 2011;20:75–86
28 Burge AN, Pietrzak RH, Molina CA et al. Age of gambling initiation and severity of gambling and
health problems among older adult problem gamblers. Psychiatric Services 2004;55:1437–39.
29 Schulte MT, Ramo D, Brown SA. Gender differences in factors influencing alcohol use and drinking
progression among adolescents. Clin Psychol Rev 2009;29:535–47.
30 Helldán, A., Helakorpi, S., Virtanen, S., & Uutela, A. (2013). Health behaviour and health among the
Finnish adult population. National Institute for Health and Welfare (THL), Report 15/2013. Retrieved
from: http://urn.fi/URN:ISBN:978-952-245-931-2
31 Barnes GM, Welte JW, Hoffman JH, et al. The co-occurrence of gambling with substance use and
conduct disorder among youth in the United States. Am J Addict 1999;20:166–73.
32 Vitaro F, Brendgen M, Ladouceur R, et al. Gambling, delinquency, and drug use during adolescence:
mutual influences and common risk factors. J Gambl Stud 2001;17:171–90.
33 Luopa, P, Kivimäki H, Matikka, A, et al. Nuorten hyvinvointi Suomessa 2000-2013 -
Kouluterveyskyselyn tulokset. [Wellbeing of adolescents in Finland 2000–2013.The Results of the
Page 15 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
16
School Health Promotion study]. National Institute for Health and Welfare (THL). Report 25/2014
34 Räsänen T, Lintonen T, Konu A. Gambling and Problem Behavior Among 14- to 16-Year-Old Boys
and Girls in Finland. J Gambl Issues 2015;31:1–22.
35 Muthén LK, Muthén BO (1998-2015). Mplus User’s Guide. Seventh Edition. Los Angeles, CA: 2015.
36 Nylund KL, Asparouhov T, Muthén BO. Deciding on the number of classes in latent class analysis
and growth mixture modeling: A Monte Carlo simulation study. Struct Equ Model 2007;14:535–69.
37 Jung T, Wickrama KAS. An Introduction to Latent Class Growth Analysis and Growth Mixture
Modeling. Soc Personal Psychol Compass 2008;2:302–17.
38 Mun EY, Windle M, Schainker LM. A model-based cluster analysis approach to adolescent problem
behaviors and young adult outcomes. Dev Psychopathol 2008;20:291–318.
39 Räsänen T, Lintonen T, Joronen K, et al. Girls and boys gambling with health and well-being in
Finland. J Sch Health 2015;85:214–22.
40 Nigg CR, Allegrante JP, Ory M. Theory-comparison and multiple-behavior research: common themes
advancing health behavior research. Health Educ Res 2002;17:670–9.
Page 16 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
17
Table 1. Results for the latent class analysis (LCA). Bolding for those participating in problem behavior the most and the least.
8th grade boys 9
th grade boys 8
th grade girls 9
th grade girls
n for classes entropy Lo-
Mendell-
Rubin
n for classes entropy Lo-
Mendell-
Rubin
n for
classes
entropy Lo-
Mendell-
Rubin
n for
classes
entropy Lo-
Mendell-
Rubin
1 class
model
19,471 na. na. 21,711 na. na. 9,432 na. na. 12,342 na. na.
2 class
model
c1=6,805
c2=12,666
0.86 0.00 c1=25,768
c2=37,188
0.85 0.00 c1=3,591
c2=5,841
0.86 0.00 c1=5,445
c2=6,897
0.82 0.00
3 class
model
c1=1,975
c2=6,813
c3=10,683
0.90 0.00 c1=9,482
c2=26,304
c3=27,170
0.89 0.00 c1=1,734
c2=3,706
c3=3,992
0.88 0.00 c1=2,645
c2=3,707
c3=5,990
0.88 0.00
4 class
model
c1=586
c2=5,377
c3=3,065
c4=10,443
0.88 0.04 c1=911
c2=4,734
c3=7,233
c4=8,833
0.86 0.00 c1=513
c2=2,123
c3=3,240
c4=3,556
0.86 0.00 c1=1,473
c2=4,145
c3=3,169
c4=3,555
0.83 0.00
5 class
model
c1=567 c2=2,829
c3=4,543
c4=2,956
c5=8,576
0.81 0.70 c1=503 c2=2,290
c3=6,086
c4=4,142
c5=8,690
0.85 0.00 c1=138 c2=1,165
c3=1,641
c4=3,013
c5=3,475
0.86 0.00 c1=159 c2=1,910
c3=2,865
c4=3,543
c5=3,865
0.84 0.76
Page 17 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on November 28, 2020 by guest. Protected by copyright. http://bmjopen.bmj.com/ BMJ Open: first published as 10.1136/bmjopen-2016-012468 on 22 December 2016. Downloaded from
For peer review only
18
Table 2. Adolescents’ involvement in gambling and problem behavior, and experiencing social support from
friends (SSF), school (SSS) and parents (SSP) based on their sex and grade.
Eta values indicate the strength of associations
8th grade
boys
9th grade
boys
8th grade
girls
9th grade
girls
Boys vs.
girls
8 vs. 9
grade %
Gambling p < 0.001 eta:0.278
p=0,022 eta:0.01
less than once a month
38.4 34.1 73.7 69.9
less than once a week
28.8 30.3 15.7 18.1
1–2 days per
week
18.7 19.6 5.0 6.2
3–5 days per
week
8.1 9.3 2.2 3.0
6–7 days per
week
6.1 6.8 3.4 2.8
Participating
in problem
behavior
5.3 9.3 12.6 29.3 p < 0.001
eta: 0.210
p < 0.001
eta: 0,14
SSF p < 0.001
eta: 0.101
p=0.029
eta:0.015
do not have
any friends
13.7 15.3 7.1 6.7
one close
friend
24.1 26.0 20.7 21.6
two close
friends
20.5 19.1 27.5 27.2
several close
friends
40.9 39.0 44.5 44.3
missing values 0.8 0.7 0.2 0.3
x, (SD)
SSS 2.8 (0.5) 2.7 (0.6) 2.7 (0.5) 2.7 (0.6) p < 0.001
eta: 0.003
p < 0.001
eta: 0.002
SSP 2.2 (0.6) 2.2 (1.2) 2.1 (0.7) 2.0 (0.7) p < 0.001
eta: 0.005
p < 0.001
eta: 0.001
n 11,029 9,744 4,069 5,028 29,870 29,870
Page 18 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
19
Table 3. Path model of the direct and indirect effects between the social support from friends (ssf), school
(sss), parents (ssp), problem behaviour (pb) and gambling frequency (gb) among 8th and 9th grade boys and
girls.
** p<0.01, ***p<0.001
Direct effect c (pb to gb) 8th grade boys 9
th grade boys 8
th grade girls 9
th grade girls
Path from pb to sss (path e) β β β β
Path from pb to ssf (path d) 0.35*** 0.36*** 0.34*** 0.36***
Path from pb to ssp (path f) -0.30*** -0.36*** -0.43*** -0.46***
Path from sss to gb (path h) -0.09*** -0.07*** -0.08*** -0.01
Path from ssf to gb (path g) -0.37*** -0.39*** -0.19*** -0.50***
Path from ssp to gb (path i) -0.11*** -0.13*** -0.06** -0.11***
Total effect c’ (pb to gb) 0.07*** 0.04*** -0.08*** -0.09***
Total indirect effect c-c’ -0.09*** -0.08*** -0.10*** -0.06***
Path from pb to sss to gb 0.41*** 0.43*** 0.42*** 0.44***
Path from pb to ssf to gb 0.06*** 0.07*** 0.08*** 0.08***
Path from pb to ssp to gb 0.03*** 0.05*** 0.03** 0.05***
Direct effect c (pb to gb) -0.01*** -0.00*** 0.01*** 0.00
Path from pb to sss (path e) 0.03*** 0.03*** 0.05*** 0.03***
Page 19 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
20
Page 20 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
106x59mm (300 x 300 DPI)
Page 21 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
1
STROBE Statement—checklist of items that should be included in reports of observational studies
Item
No Recommendation
Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract
page 1
(b) Provide in the abstract an informative and balanced summary of what was done
and what was found -page 1
Introduction
Background/rationale 2 Explain the scientific background and rationale for the investigation being reported
pages 2-3
Objectives 3 State specific objectives, including any prespecified hypotheses page 3
Methods
Study design 4 Present key elements of study design early in the paper pages 4-5
Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment,
exposure, follow-up, and data collection page 3
Participants 6 (a) Cohort study—Give the eligibility criteria, and the sources and methods of
selection of participants. Describe methods of follow-up
Case-control study—Give the eligibility criteria, and the sources and methods of
case ascertainment and control selection. Give the rationale for the choice of cases
and controls
Cross-sectional study—Give the eligibility criteria, and the sources and methods of
selection of participants pages 3-4
(b) Cohort study—For matched studies, give matching criteria and number of
exposed and unexposed
Case-control study—For matched studies, give matching criteria and the number of
controls per case
Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect
modifiers. Give diagnostic criteria, if applicable page 4, sup.material
Data sources/
measurement
8* For each variable of interest, give sources of data and details of methods of
assessment (measurement). Describe comparability of assessment methods if there
is more than one group sup. material
Bias 9 Describe any efforts to address potential sources of bias none
Study size 10 Explain how the study size was arrived at pages 3-4
Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable,
describe which groupings were chosen and why sup. material 4-5
Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding,
4-5
(b) Describe any methods used to examine subgroups and interactions
(c) Explain how missing data were addressed
(d) Cohort study—If applicable, explain how loss to follow-up was addressed
Case-control study—If applicable, explain how matching of cases and controls was
addressed
Cross-sectional study—If applicable, describe analytical methods taking account of
sampling strategy
(e) Describe any sensitivity analyses
Continued on next page
Page 22 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from
For peer review only
2
Results
Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible,
examined for eligibility, confirmed eligible, included in the study, completing follow-up, and
analysed
(b) Give reasons for non-participation at each stage
(c) Consider use of a flow diagram
Descriptive
data
14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information
on exposures and potential confounders
(b) Indicate number of participants with missing data for each variable of interest
(c) Cohort study—Summarise follow-up time (eg, average and total amount)
Outcome data 15* Cohort study—Report numbers of outcome events or summary measures over time
Case-control study—Report numbers in each exposure category, or summary measures of
exposure
Cross-sectional study—Report numbers of outcome events or summary measures page 14
Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their
precision (eg, 95% confidence interval). Make clear which confounders were adjusted for and
why they were included
(b) Report category boundaries when continuous variables were categorized
(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful
time period
Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity
analyses 4-5
Discussion
Key results 18 Summarise key results with reference to study objectives 7-9
Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision.
Discuss both direction and magnitude of any potential bias 8-9
Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity
of analyses, results from similar studies, and other relevant evidence 8
Generalisability 21 Discuss the generalisability (external validity) of the study results 8
Other information
Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable,
for the original study on which the present article is based page 9
*
Page 23 of 23
For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
BMJ Open
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960
on Novem
ber 28, 2020 by guest. Protected by copyright.
http://bmjopen.bm
j.com/
BM
J Open: first published as 10.1136/bm
jopen-2016-012468 on 22 Decem
ber 2016. Dow
nloaded from