bmj open€¦ · relations between gambling and problem behavior among girls and boys. these...

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

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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

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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]

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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.

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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

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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

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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

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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) =

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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

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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

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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.

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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.

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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.

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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.

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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

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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

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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***

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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

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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

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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

*

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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


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


Addiction


Keywords: Health policy < HEALTH SERVICES ADMINISTRATION & MANAGEMENT, Substance misuse < PSYCHIATRY, PUBLIC HEALTH


BMJ Open on N



jopen.bmj.com

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Social support as a mediator between gambling and problem behaviour – a cross-sectional study

among 14- to 16-year-old Finnish adolescents



Phone: +358 445368416





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



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.


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• 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


the study




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]

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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.

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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




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


included questions on adolescents’ gambling, problem behaviour, and social support. In 2010, the study was


2010 and 2011 surveys cover all of Finland. In 2010, 78% of Finnish 8th and 9


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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




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.










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Gambling









on their involvement in different problem behaviours. The purpose was to identify the most homogenous

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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








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



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



class model. However, among 8th grade girls and 9

th grade boys, the p values were lower than 0.05,



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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) =



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

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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).


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 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).


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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


in one problem behaviour also increases the risk of involvement in other problem behaviours, as

demonstrated by problem behaviour theory.[4,13]






increased gambling, which is consistent with the findings of Hardoon et al. [20] In their study, they reported






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

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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]



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.


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.



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




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J Adolesc 2007;30:17–31.



35–51.


2009;13:295–304.







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.



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.

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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.




Adolescence. J Youth Adolesc 1999;28:667–85.



Adolesc 2010;39:670–82.



1996;35:1657–64.








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Policy 2015;10:1–10.


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.



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

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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.





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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


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

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17


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


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

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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 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***

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108x60mm (300 x 300 DPI)

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Item

No Recommendation


page 1



Introduction


pages 2-3


Methods








and controls






controls per case



Data sources/

measurement









4-5





addressed


sampling strategy



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Results



analysed



Descriptive

data







exposure







time period


analyses 4-5

Discussion







Other information



*

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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



Date Submitted by the Author: 10-Oct-2016




Addiction




BMJ Open on N



jopen.bmj.com

/B

MJ O


ecember 2016. D

ownloaded from



1

Social support as a mediator between problem behaviour and gambling – a cross-sectional study




Phone: +358 445368416





Word count:








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.


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and social support





the study




reporting

Introduction






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].

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Likewise, studies have shown that parents and teachers do not think that gambling is great concern among

youth. [11,12]
















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.







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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



Method

Setting








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Data




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


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 =



Measures

Problem behavior









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Gambling
























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perfect.

Results

LCA




th grade
















29,870).

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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












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variance (R2) was explained by the association between gambling and social support for 8th grade and 9th



Discussion

This large scale, population-based study explored the relationship between problem behaviour, gambling and


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.















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with previous studies[6,23]; however, over 50% of 8th grade and 74% of 9th grade girls who gambled on a




behaviour and gambling frequency, the temporal relationship between these factors remains unclear. Thus,



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]







measure for social support. The internal consistency for the scale of “social support from parents” was not

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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.


8th and 9




reporting.



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]











J Adolesc 2007;30:17–31.


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35–51.


2009;13:295–304.







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.



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.








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2014;30: 435–51.







Adolesc 2010;39:670–82.



1996;35:1657–64.














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Policy 2015;10:1–10.




















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

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School Health Promotion study]. National Institute for Health and Welfare (THL). Report 25/2014














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8th grade boys 9

th grade boys 8

th grade girls 9

th grade girls


Mendell-

Rubin


Mendell-

Rubin

n for

classes

entropy Lo-

Mendell-

Rubin

n for

classes

entropy Lo-

Mendell-

Rubin

1 class

model


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

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18



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


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

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(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 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***

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106x59mm (300 x 300 DPI)

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Item

No Recommendation


page 1



Introduction


pages 2-3


Methods








and controls






controls per case



Data sources/

measurement









4-5





addressed


sampling strategy



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Results



analysed



Descriptive

data







exposure







time period


analyses 4-5

Discussion







Other information



*

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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



Date Submitted by the Author: 03-Nov-2016




Addiction




BMJ Open on N



jopen.bmj.com

/B

MJ O


ecember 2016. D

ownloaded from



1

Social support as a mediator between problem behaviour and gambling – a cross-sectional study




Phone: +358 445368416





Word count:








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.


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and social support





the study




reporting

Introduction






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].

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3

Likewise, studies have shown that parents and teachers do not think that gambling is great concern among

youth. [11,12]
















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.







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4












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



Method

Setting








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5

Data




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


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 =



Measures

Problem behavior









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Gambling
























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perfect.

Results

LCA




th grade
















29,870).

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9







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












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