Article Review

ORIGINAL PAPER

Initiation of Substance Use by Adolescents After One Year in Residential Youth Care

Karin Monshouwer • Annelies Kepper • Regina van den Eijnden •

Ina Koning • Wilma Vollebergh

Published online: 13 December 2014 � Springer Science+Business Media New York 2014

Abstract Background Several studies have shown that substance use levels among adolescents

living in residential youth care are high. However, it is not clear to what extent adolescents

initiate (heavy) substance during their stay and to what extent these rates are higher than

would be expected based on their risk profile.

Objective The aim of the present study is to examine the initiation of (heavy) substance

use among adolescents in residential care and to compare these initiation rates with a

reference group of non-institutionalized youth, while taking differences in the risk profiles

between both groups into account.

Methods Self-report questionnaires were completed by 241 adolescents in residential

care (42 % boys; mean age 15.4 years) and 359 adolescents attending mainstream edu-

cation (54 % boys; mean age 14.8 years).

Results A substantial proportion of adolescents first started to use substances (heavily)

during their stay in residential care (1 year incidence of daily tobacco use: 22.6 %,

drunkenness: 38.5 %, cannabis use: 27.3 %, hard drug use: 9.4 %. Except for drunkenness,

these rates were significantly higher compared to those in mainstream education. Adjusting

K. Monshouwer � A. Kepper � R. van den Eijnden � I. Koning � W. Vollebergh Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht, The Netherlands e-mail: [email protected]

R. van den Eijnden e-mail: [email protected]

I. Koning e-mail: [email protected]

W. Vollebergh e-mail: [email protected]

K. Monshouwer (&) Trimbos Institute (Netherlands Institute for Mental Health and Addiction), P.O Box 725, 3500 AS Utrecht, The Netherlands e-mail: [email protected]

123

Child Youth Care Forum (2015) 44:597–611 DOI 10.1007/s10566-014-9294-6

the analyses for the risk profile showed that the elevated risk for hard drug use remained

significant and substantial (IRR = 13.09).

Conclusion A substantial proportion of adolescents started using substances (heavily)

during their stay in residential care. Although rates may have been even higher if these

adolescents were not placed in residential care, these findings highlight the need for

effective preventive interventions and policies in these settings, especially with regard to

the use of hard drugs.

Keywords Residential youth care � Substance use onset � Longitudinal � Risk factors

Introduction

Residential youth care institutions provide intensive treatment and care (e.g., supervised

group treatment, emergency treatment) for adolescents who present severe emotional and

behavioural problems, often in co-occurrence with a history of abuse and neglect, and

troubled family relations (Frensch and Cameron 2002; Harder et al. 2006; Hurley et al.

2009; Trout et al. 2008). These are all identified risk factors for problematic use of alcohol,

tobacco and drugs (Aarons et al. 2001; Bacovic et al. 2006; Kepper et al. 2011; McCrystal

et al. 2008; Pilowsky and Wu 2006; Vaughn et al. 2007; Thompson Jr and Auslander

2007), which is reflected in the results of studies showing that compared to adolescents in

the general population, residential youth are three to ten times more likely to use tobacco,

alcohol and other drugs (Bacovic et al. 2006; Kepper et al. 2011; Pilowsky and Wu 2006).

Although it is established that substance use prevalence rates among youth in residential

care are high, what remains unclear is the impact of the institutional environment itself on

the onset of substance use for the young people who have not used substances when

entering the institution. Living in a residential institution for a prolonged period is likely to

have an effect on substance use onset, although theoretically, this effect could be either

protective or harmful. It seems plausible that the risk of substance use initiation might

decrease during residential care due to the higher level of monitoring and control over

drugs as well as the availability of preventive interventions (Bastiaanssen et al. 2012;

Morehouse and Tobler 2000). Moreover, several studies have shown that residential care

improves adolescents’ functioning (Bettmann and Jasperson 2009; Knorth et al. 2008; Lee

and Thompson 2008; Nijhof et al. 2011). For example, a review indicated that residential

treatment demonstrates positive behavioural changes as well as an increase in social and

familial functioning (Bettmann and Jasperson 2009). This illustrates that being in resi-

dential care has a positive effect on adolescent behaviour in general, and it may therefore

possibly reduce adolescents’ engagement in substance use. However, other studies provide

limited evidence for the effectiveness of residential care on behaviour (Frensch and

Cameron 2002; Hair 2005) or even show negative outcomes (Lyons et al. 2001). For

example, Lyons et al. (2001) studied youth over a 2-year period after placement in resi-

dential treatment and demonstrated that residential treatment may have unintended adverse

effects on anxiety and hyperactivity problems. Being in a residential institution may also

increase the risk of substance use onset, as residential settings typically group together

adolescents with severe behavioural and substance use problems. This results in a con-

centration of substance using models (Chartrand and Bargh 1999; Quigley and Collins

2012), stimulating peers to use various substances (Dinges and Oetting 1993; Harakeh and

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Vollebergh 2012) and facilitating access to alcohol and particularly drugs (Oetting and

Beauvais 1986). A report on substance use among incarcerated boys in the Netherlands

revealed that during their stay in a juvenile justice institution, cannabis and hard drugs

were readily available (Kepper et al. 2009). In less secured or open residential settings, the

availability of illegal substances is possibly even more pronounced. Consequently, the risk

of substance use initiation potentially increases when living in an institution. If this is

indeed the case, this would have major implications for the overseeing organizations whose

primary responsibility is the health and safety of its charges. Given the lack of longitudinal

studies on substance use initiation in residential care and the uncertainty with respect to the

possible effect of the residential care setting itself on behaviour, longitudinal research on

the initiation of substance use among youth in residential care is highly warranted.

Current Study

To our knowledge, no study so far has examined the initiation of substance use among

adolescents living in a residential youth care institution. Most studies had a cross-sectional

design, and the few longitudinal studies did not address initiation of substance use (Taussig

2002; Traube et al. 2012). This is an omission as information on initiation of substance use

is highly relevant for prevention and substance use policies within these institutions. The

aim of the present study is to examine the risk of initiation of substance use over a 1-year

period in a sample of youth living in a residential youth care institution. In order to assess

to what extent initiation rates differ from the ‘normal’ pattern (i.e. what can be expected

based on their risk profile) a comparison will be made with substance use initiation rates in

a general population sample, while accounting for differences between the groups in their

substance use risk profile.

Methods

Procedure

The study took place in 26 regional institutions in the Netherlands offering residential

treatment for 12–18 year old adolescents. The residential settings were located in both

rural and urban areas. The Dutch government funded all of the institutions, and govern-

ment inspectors supervised the quality of residential care. Adolescents were placed in a

residential youth care institution because of severe emotional and behavioural problems

(e.g., attention deficit hyperactivity disorder, oppositional defiant disorder, attachment

disorders, and pervasive developmental disorder) (Harder et al. 2006). Often, these ado-

lescents also had problems related to problematic family functioning, such as domestic

violence, parental psychiatric problems and parental substance abuse (Harder et al. 2006).

Placements included both voluntary and forced care, and varied from a short-term period

(crisis shelters) to long-term stays. The institutions offered living arrangements (i.e., group

homes) with room for 10–12 adolescents. In addition to living arrangements, the treatment

programs included education, recreational activities, and individual and family therapy.

The goals of the residential program of all institutions were to provide a safe and stable

living situation with daily activities (school or job) and opportunities for positive contacts

with family and peers. The description of the youth care institution is reported in accor-

dance with group care reporting guidelines, by Lee and Barth (Lee and Barth 2011; Weems

2011).

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In the Fall of 2008, trained research assistants administered anonymous questionnaires

in the living rooms of the institutions. In accordance with the Dutch ethical standards,

anonymity was assured, and adolescents were informed about the voluntary nature of

participation. Passive parental permission was obtained through a letter informing parents

about the purpose of the study and gave parents the opportunity to refuse the participation

of their child. Follow-up data were collected 12–15 months later (October–December

2009) by sending digital questionnaires to adolescents who had agreed to participate in the

follow-up and had provided their email address during the first data collection. Those who

failed to respond within 3 weeks received a reminder by email and non-responders were

contacted by telephone a week later. This process continued until the first week of

December 2009. Each participant received a (digital) gift voucher of €10 (baseline) and

€15 (follow-up).

The comparison group of adolescents in mainstream education was derived from the

‘Prevention of Alcohol use in Students (PAS)’ study, a randomized controlled trial on the

effectiveness of a school based prevention program (Koning et al. 2009). For the present

study, only data from respondents in the control condition (i.e., no intervention) were used.

To match the two groups with regard to age, the study used the data from the fourth and

fifth follow-up measurements of the PAS study, described as baseline and follow-up data,

respectively. Baseline data were collected at the end of the third high school year (May/

June 2009) and follow-up data were collected 16 months later in October/November 2010.

Baseline data were collected by means of digital questionnaires administered in the

classroom by trained research assistants, and follow-up data were collected by means of

telephone interviews administered by trained research assistants. Parental questionnaires

were sent to parents’ home address along with a letter of consent at baseline. This letter

informed parents about the participation of the school in the project, and parents were

given the opportunity to refuse participation of their child (0.01 % refusal).

Participants

Overall, 673 adolescents in residential care (83 % of those invited) participated at baseline,

of whom 450 (67 % of all participants) also expressed willingness to participate in the

follow-up measurement and thus received an invitation. A final group of 241 adolescents

(54 % of those willing to participate) did in fact participate at the follow-up. Accordingly,

the present study included 241 adolescents who participated in both the baseline and

follow-up assessment (42 % male, mean age at baseline = 15.4 years, SD = 1.4). Of

those adolescents, 72 % were still living in a residential youth care institution at follow-up

while 28 % were living with their parents, foster parents or independently. Attrition

analysis showed that responders and non-responders (i.e., adolescents who did not agree to

participate in the follow-up as well as those who had originally agreed to participate but

did not actually participate in the follow-up) did not differ significantly on age, gender,

daily use of tobacco and life time drunkenness, cannabis use or hard drug use, p[ .05.

However, they differed significantly regarding ethnic background, with more non-

responders (30 %) having an ethnic minority background compared to responders (19 %),

V2(1) = 9.2, p = .003.

The comparison group consisted of 984 adolescents participating at baseline and 396

adolescents (39 %) participated at the follow-up. Hence, the present study included 396

adolescents attending mainstream education who participated in both the baseline and

follow-up assessment (53 % male; mean age at baseline = 15.3; SD = 0.4). Attrition

analyses of demographic variables (age and gender) and substance use indicated that the

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responders were slightly younger (t(984) = 6.07, p\ .001). No significant differences

between responders and non-responders were found regarding substance use (p[ .05). The

trial protocol (NTR649) was approved by the Medical Ethical Committee. More infor-

mation on the data collection of the PAS study is described in Koning et al. (2013).

Measures

Substance Use

Daily use of tobacco and life time prevalence of drunkenness, cannabis use, and hard drug

use were measured at baseline and follow-up. The measures were derived from national

(Monshouwer et al. 2008; Verdurmen et al. 2012) and European (Hibell et al. 2009, 2012)

school surveys on substance use. Daily use of cigarettes was measured by asking ‘Have

you ever smoked cigarettes, even one puff?’(den Exter Blokland et al. 2009; Engels et al.

2004). Answer categories were ‘I smoke every day’, ‘I smoke once in a while, but not

every day’, ‘I have smoked once or twice’, ‘I used to smoke, but I have quit smoking

completely’ or ‘I have never smoked’. In line with previous studies on student smoking

(Lynskey and Fergusson 1995; McGee et al. 2006), those answering ‘I smoke every day’

were classified as daily smokers (1) and those answering otherwise as no daily smoker (0).

Drunkenness or intoxication was measured by asking how many times adolescents had

been drunk or intoxicated by drinking alcohol during their life (Simons-Morton et al. 2010;

Kuntsche and Jordan 2006). Categories ranged from zero to forty or more times. Those

answering once or more were classified as ever having been drunk (1), those answering

zero were classified as never been drunk (0). Life time use of cannabis was measured by

asking: ‘How many times did you use cannabis in your life?’ Categories were zero to forty

or more (Monshouwer et al. 2005). Those answering one time or more were classified as

lifetime users of cannabis (1), those answering zero were classified as non-lifetime users of

cannabis (0). Lifetime use of hard drugs (i.e., ecstasy, cocaine, amphetamine, and heroin)

was measured by asking respondents whether they had ever used one of the listed hard

drugs (categories ‘yes’ or ‘no’. Those who had used at least one of the above-mentioned

hard drugs were categorized as lifetime users of hard drugs (1). Those who had not used

any of the hard drugs were classified as non-lifetime users of hard drugs (0).

Behavioural and Emotional Problems

Behavioural and emotional problems were measured by means of the Strengths and Dif-

ficulties Questionnaire (SDQ) (Goodman et al. 1998, 2000). Earlier studies have shown

that this measure represents a short and easy-to-understand alternative within a sample of

residential youth (Mason et al. 2012). The SDQ is a short questionnaire with 20 items

representing four scales of mental health problems, of which three were used in the present

study. The first scale, emotional problems, consists of five items (a = 0.73), for example ‘I

worry a lot’. The second scale, conduct problems, is based on five items (a = 0.50) such as

‘I get very angry and often lose my temper’. The third scale, hyperactivity, is characterized

by five items (a = 0.74), for example ‘I am easily distracted; I find it difficult to con-

centrate’. Students indicated whether the items were not true (0 points), a bit true (1 point),

or definitely true (2 points). For each of the problem types, scores were calculated as the

sum of the item scores. Negatively phrased items were recoded. The fourth scale, peer

relationship problems, was not used in the current study as it had a low reliability

(a = 0.40).

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Family Structure

Family structure was assessed by asking the respondents whether his or her parents were

divorced, whether a parent had passed away, or whether his or her parents were living

together (i.e., intact family).

Communication with Parents

Communication with parents was assessed by a measure derived from the international

Health Behaviour in School-aged Children study (Currie et al. 2008), developed by Lasky

et al. (1985). Respondents were asked how easy it is for them to communicate with their

father/mother. Answers were ‘easy’, ‘difficult’ or ‘do not have a father/mother or do not

communicate with father/mother’.

Background Factors

The following background factors were included: age, gender [i.e., boy (1) or girl (0)] and

ethnicity. Ethnicity was assessed by asking respondents to state their country of birth as

well as their parents’ country of birth. The respondents who reported that either they or

their father or mother were born in a non-western foreign country were classified as

belonging to an ethnic minority group (1), those reporting otherwise were classified as

being Dutch/Western (0).

Data Analysis Strategy

To test whether the risk on initiating substance use was significantly higher among

adolescents in residential care as compared to adolescents in mainstream education, we

used Poisson regression analysis. Odds ratios are often interpreted as relative risks, but

are in fact not the same. Particularly for common outcomes the odds ratio always

overstates the relative risk (McNutt et al. 2003). Poisson regression is an alternative

approach which can be used in a similar manner as logistic regression and can provide a

correct estimate of the adjusted relative risk (McNutt et al. 2003). These analyses were

performed for each of the four substances (i.e., daily tobacco use, drunkenness, cannabis

use, and hard drug use). In a first model, we examined the association between group

membership (i.e., being in residential care, with mainstream education being the refer-

ence group) and initiation of substance use, adjusting for gender, ethnic background, and

age. To test whether the elevated risk on substance use initiation among residential youth

is (partially) explained by their substance use risk profile, we added emotional, conduct,

hyperactivity problems, broken family, and difficult communication with parents to the

model.

All analyses considered the fact that our data are clustered (adolescents from the same

class or residential youth care group), and that the participants shared several character-

istics (having the same teacher or living in the same region); this influenced the standard

errors and p values. Therefore, robust standard errors were calculated using the Huber/

White/sandwich method in STATA Version 11 (Stata Corporation 2009).

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Results

Descriptive Statistics

Compared to adolescents in mainstream education, significantly more adolescents in res-

idential care reported substance use (i.e., daily tobacco use, and life time prevalence of

drunkenness, cannabis and hard drug use), behavioural and emotional problems, difficult or

no communication with their parents, and broken families at baseline (Table 1). They were

also slightly older and more often had an ethnic minority background.

Table 2 illustrates differences in rates of initiation at follow-up among adolescents who

were not substance users at baseline. With the exception of drunkenness, significantly more

adolescents in residential care initiated substance use compared to those in mainstream

education. For example, 9 % of the adolescents in residential care had onset of hard drug

use (ecstasy, cocaine, amphetamine and/or heroin) compared with 1 % among those in

mainstream education.

Risk on Initiating Substance Use at Follow-Up: Poisson Regression Analysis

The risk of initiating substance use was significantly higher for adolescents in residential

care compared to the reference group, with the exception of drunkenness (Model 1 of

Table 3). In the second model, associations between residential care and initiation of daily

tobacco use and cannabis use lost significance after adjusting for the behavioural and

emotional problems, family structure, and communication with father and mother. The

association between residential care and initiation of hard drug use remained significant

and substantial (Model 2 of Table 3).

Additional analyses included only adolescents still living in a residential youth care

institution during follow-up (n = 173). The results were similar to the results illustrated in

Table 3 (which considered both adolescents still living in an institution as well as those

who were no longer living there during follow-up measurement). In the first model, the risk

of initiating daily use of tobacco, IRR = 2.84, p\ .05, 95 % CI [1.21–6.72], cannabis use

IRR = 3.16, p\ . 01, 95 % CI [1.64–6.09], and hard drug use IRR = 11.57, p\ .01,

95 % CI [3.14–140.98] was significantly higher for adolescents living in residential care

compared to adolescents in mainstream education. No significant risk for first time

drunkenness was found (p[ . 05). In the second model, associations between being in

residential care and initiating daily tobacco use and cannabis use were no longer significant

when adjusting for risk factors, p[ .05. The association between being in residential care

and initiating hard drugs remained significant and substantial, IRR = 20.27, p\ .01, 95 %

CI [2.63–156.28]. A table including all results is available from the first author upon

request.

Discussion

The results of this longitudinal study show that a substantial group of adolescents start

using substances (heavily) for the first time, while living in a residential care institute. The

1-year initiation rates of daily smoking and the use of cannabis and hard drugs, were

considerably higher among residential youth as compared to their counterparts in regular

education. We found no differences between the groups with respect to the initiation rates

of drunkenness.

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Table 1 Descriptive statistics of adolescents at baseline, divided by residential youth and youth in mainstream education

Background factors Residential youth n = 241

Mainstream education youth n = 359

%/M (SD) 95 % CI %/M (SD) 95 % CI

Boys (%) 41.9 [34.5, 49.7] 53.5 [44.6, 62.1]

Ethnic minority background (%) 18.8* [13.8, 25.2] 3.7* [2.2, 6.1]

Age in years (M) 15.4* (1.43) [15.2, 15.6] 14.8* (.52) [14.8, 14.9]

Emotional problems 0–10 (M) 4.19* (2.62) [3.85, 4.52] 2.09 (1.98) [1.88, 2.29]

Conduct disorder 0–8 (M) 2.86* (1.80) [2.63, 3.09] 1.97 (1.59) [1.81, 2.14]

Hyperactivity 0–10 (M) 4.97* (2.49) [4.66, 5.29] 3.91 (2.19) [3.69, 4.15]

Family structure (%)

Intact family 23.1* [17.2, 30.4] 84.6* [81.0, 87.8]

Divorced parents 68.1* [60.7, 74.6] 13.4* [10.4, 17.1]

Parent has passed away 8.8* [6.1, 12.5] 2.0* [1.0, 3.8]

Communication with father (%)

Easy 36.6* [30.9, 42.7] 77.2* [72.6, 81.1]

Difficult 31.1* [25.5, 37.2] 17.8* [14.3, 22.1]

No contact 32.3* [26.7, 38.6] 5.0* [3.1, 8.0]

Communication with mother (%)

Easy 59.2* [51.3, 66.5] 86.6* [82.9, 89.6]

Difficult 30.2* [23.9, 37.4] 12.0* [9.1, 15.7]

No contact 10.6* [7.2, 15.4] 1.4* [0.6, 3.3]

Substance use (%)

Daily tobacco use 55.7* [49.1, 62.0] 8.1* [5.4, 11.9]

Life time prevalence of drunkenness 74.0* [67.8, 79.3] 36.3* [30.2, 42.9]

Life time prevalence of cannabis use 62.2* [56.0, 68.0] 19.2* [14.6, 24.9]

Life time prevalence of hard drug usea 22.4* [17.6, 27.9] 3.9* [2.2, 6.9]

CI confidence interval a Ever used at least one of the following substances: ecstasy, cocaine, amphetamine or heroin

* Differences between the two groups are statistically significant (p\ .001)

Table 2 Initiation of substance use at follow-up for youth in residential care and in mainstream education

Residential youth Mainstream education youth

(na) % 95 % CI (na) % 95 % CI

Initiation of daily tobacco use (106) 22.6* [15.1, 32.5] (330) 8.4* [5.0, 13.8]

Initiation of drunkenness (65) 38.5 [25.4, 53.4] (183) 34.7 [27.3, 43.0]

Initiation of cannabis use (90) 27.3* [19.5, 36.8] (290) 9.7* [5.5, 16.3]

Initiation of hard drug useb (184) 9.4* [5.4, 15.8] (345) 1.0* [0.3, 3.0]

CI confidence interval a n of participants not using at baseline b Used at least one of the following substances: ecstasy, cocaine, amphetamine or heroin

* Differences between the two groups are statistically significant (p\ .001)

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T a b le

3 R is k o f in it ia ti o n o f su b st an ce

u se

at fo ll o w -u p , p re d ic te d b y re si d en ti al

y o u th

ca re

an d in d iv id u al

an d fa m il y fa ct o rs

V ar ia b le

In it ia ti o n o f d ai ly

to b ac co

u se

In it ia ti o n o f d ru n k en n es s

In it ia ti o n o f ca n n ab is u se

In it ia ti o n o f h ar d d ru g u se

a

IR R

9 5 %

C I

IR R

9 5 %

C I

IR R

9 5 %

C I

IR R

9 5 %

C I

M o d el

1

R es id en ti al

y o u th

1 3 .0 2 * *

[1 .3 6 – 6 .7 1 ]

1 .1 2

[. 7 2 – 1 .7 5 ]

3 .0 3 * *

[1 .6 2 – 5 .7 0 ]

1 2 .5 1 * *

[3 .0 8 , 5 0 .7 4 ]

M o d el

2

R es id en ti al

y o u th

1 1 .6 6

[. 6 7 – 4 .0 9 ]

.8 4

[. 4 4 – 1 .6 0 ]

1 .6 6

[. 8 2 – 3 .3 6 ]

1 3 .0 9 * *

[2 .9 0 , 5 9 .1 6 ]

E m o ti o n al

p ro b le m s

1 .0 1

[. 9 0 – 1 .1 3 ]

.9 7

[. 8 8 – 1 .0 8 ]

1 .1 2

[1 .0 0 – 1 .2 6 ]

.8 2

[. 6 4 , 1 .0 5 ]

C o n d u ct

d is o rd er s

1 .0 2

[. 8 2 – 1 .2 6 ]

.9 1

[. 7 9 – 1 .0 6 ]

.9 4

[. 7 8 – 1 .1 3 ]

1 .1 8

[. 9 2 , 1 .5 3 ]

H y p er ac ti v it y

1 .0 8

[. 9 4 – 1 .2 4 ]

1 .0 8

[. 9 9 – 1 .1 9 ]

1 .0 8

[. 9 6 – 1 .2 3 ]

.9 8

[. 8 3 , 1 .1 7 ]

F am

il y st ru ct u re

D iv o rc ed

p ar en ts 2

2 .5 2 *

[1 .2 0 – 5 .3 2 ]

1 .6 5 *

[1 .0 3 – 2 .6 4 ]

1 .8 2 *

[1 .0 3 – 3 .2 1 ]

1 .1 4

[. 4 2 , 3 .1 1 ]

P ar en t h as

p as se d aw

ay 2

1 .6 0

[. 2 1 – 1 2 .0 3 ]

.7 0

[. 0 8 – 6 .5 0 ]

1 .1 9

[. 3 7 – 3 .8 1 ]

2 .8 0

[. 2 2 , 3 5 .1 0 ]

C o m m u n ic at io n w it h fa th er

D if fi cu lt 3

1 .2 8

[. 5 3 – 3 .0 7 ]

.8 6

[. 3 9 – 1 .8 7 ]

.7 1

[. 3 6 – 1 .4 1 ]

.9 1

[. 3 8 , 2 .1 8 ]

N o co n ta ct 3

.6 9

[. 3 0 – 1 .5 9 ]

1 .0 1

[. 4 8 – 2 .1 2 ]

.6 7

[. 3 3 – 1 .3 8 ]

.5 5

[. 1 9 , 1 .5 7 ]

C o m m u n ic at io n w it h m o th er

D if fi cu lt 3

.6 0

[. 2 3 – 1 .5 7 ]

1 .2 1

[. 6 1 – 2 .4 1 ]

1 .5 8

[. 7 6 – 3 .3 0 ]

2 .2 1

[. 7 4 , 6 .5 6 ]

N o co n ta ct 3

1 .9 0

[. 8 0 – 4 .5 1 ]

1 .3 7

[. 4 4 – 4 .2 8 ]

1 .3 8

[. 5 9 – 3 .2 5 ]

.6 0

[. 0 2 , 1 4 .8 9 ]

M o d el

1 : ad ju st ed

fo r ag e,

g en d er , et h n ic

b ac k g ro u n d ; m o d el

2 : ad d s to

m o d el

1 co n tr o ls

fo r al l o th er

fa ct o rs

in th e m o d el

IR R in ci d en ce

ra te

ra ti o s, C I co n fi d en ce

in te rv al

1 R ef er en ce

g ro u p is m ai n st re am

ed u ca ti o n

2 R ef er en ce

g ro u p is in ta ct

fa m il y

3 R ef er en ce

g ro u p is ea sy

co m m u n ic at io n

a E v er

u se d at

le as t o n e o f th e fo ll o w in g su b st an ce s:

ec st as y , co ca in e,

am p h et am

in e o r h er o in

* p \

.0 5 , * * p \

.0 1

Child Youth Care Forum (2015) 44:597–611 605

123

When differences between the groups with respect to individual and family risk factors

were taken into account, only the elevated risk of starting to use hard drugs remained

significant. This increased risk was substantial; adolescents in residential youth care were

thirteen times more likely to start using hard drugs compared to mainstream youth, after

controlling for their risk profile. The risk profile consisted of a limited set of variables, and

it is likely that the inclusion of omitted individual and family variables would have further

attenuated the strength of the relationships. In particular parental abuse is a well-estab-

lished confounder of psychosocial and mental health problems among adolescents,

including substance use (Wu et al. 2010; Gil et al. 1998). As parental substance abuse and

parental psychopathology have been identified as important factors in relation to contact

with (residential) youth care (Besinger et al. 1999; Dore et al. 1995; Forrester and Harwin

2006; Havnen et al. 2009), future studies need to asses such factors when examining onset

of drug use among these youngsters. In addition, the findings could also indicate that risk

factors related to the setting itself, e.g., peer group processes (Dishion et al. 1999), explain

part of the increased risk for the use of hard drugs among youth in residential care. For

example, a residential setting puts adolescents with problematic risk profiles together

thereby generating a deviant-peer-environment. In such environment, adolescents who

originally did not use drugs might feel the pressure to start using hard drugs in order to be

accepted by their drug using peers (Santor et al. 2000). The presence of drug using peers is

also likely to increase the availability of and access to drugs (Oetting and Beauvais 1986).

Peer processes labelled deviancy training, in which rule-breaking discussions and deviant

talk are reinforced by contingent positive reactions (Cécile and Born 2009; Dishion et al.

1999; Rhule 2005), may also play a significant role. Such deviant-peer-environment might

also affect chances of starting tobacco and cannabis use. However, as the use of ecstasy,

cocaine, amphetamine and heroin is much more in conflict with the prevailing standard of

normative substance use behaviour than the use of cannabis and tobacco, it is likely that

deviant peers particularly have an influence on hard drug use. Based on our study we

cannot draw definite conclusions on the possible contribution of other factors on the

individual domain and/or the setting itself. Given the high risk of initiating drug use while

being in residential care, further studies are warranted.

The risk of onset of cannabis use and daily smoking was three times higher among

adolescents in residential care compared to their counterparts in mainstream education.

This increased risk was fully explained by the risk profile of these adolescents, particularly

having divorced parents. Initiating both smoking and cannabis can therefore be seen as an

effect of the selection of adolescents with behavioural, emotional and family problems in

the residential setting. The finding that particularly family structure contributed to the risk

of smoking and cannabis use initiation is in accordance with several studies, which found

that parental divorce predicts substance use, abuse or dependence among adolescents

(Flewelling and Bauman 1990; Hayatbakhsh et al. 2006; Needle et al. 1990). Potentially,

parental divorce or separation is associated with other risk factors of adolescent substance

use. For example, marital disruption can lead to a decline in socio-economic status, which

in turn can negatively affect adolescents’ development (Amato and Sobolewski 2001), and

undermine the parent–child relationship, thereby enhancing adolescents’ sensitivity to

(deviant) peer influences (Hoffmann 1993). Furthermore, adolescents raised in broken

families or in families characterised by marital conflict exhibit poorer school performance

and lower psychosocial wellbeing in comparison to their peers (Amato and Sobolewski

2001; Sun and Li 2002). This could in turn predict engagement in substance use (Hoffmann

1993; Rey et al. 2002).

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Finally, this study found no elevated risk for the onset of drunkenness. This is perhaps

partly explained by the fact that ethnic minority groups are overrepresented in residential

care. In the Netherlands, ethnic minority groups are predominantly Muslims, who have

strong rules concerning the use of alcohol, which is reflected in low alcohol use prevalence

rates (Monshouwer et al. 2007; van Tubergen and Poortman 2010). Moreover, there are

possibly fewer opportunities to acquire alcohol in a supervised environment, such as a

residential youth care institution, whereas drugs can be hidden more easily (i.e., alcoholic

beverages are take up more space (bottles) than for example marijuana, ecstasy or cocaine).

This is supported by a study conducted in youth prisons in which the use of cannabis and

hard drugs was found to be particularly high while the use of alcohol was relatively rare

(Kepper et al. 2009). Incarcerated youth also indicated that it would be easy for them to

acquire the drugs even within the youth prison while this was not the case with respect to

alcohol (Kepper et al. 2009).

Implications for Practice

Several implications arise from the results of the current study. The results suggest a need

for increased awareness of the substantial risk of initiating daily tobacco, and the first use

of cannabis and hard drugs for youth living in a residential care setting. Adolescents often

receive residential treatment through interaction with group care workers (Knorth et al.

2010) and daily interventions; hence, group care workers have an important influence on

the treatment of adolescents in residential youth care (Bastiaanssen et al. 2012). During

these interventions, group care workers are advised to pay attention to adolescents who are

already using alcohol, tobacco or drugs, but also to those who are not using substances yet.

Moreover, in working with these adolescents, possible negative peer processes (e.g.,

deviancy training) need to be considered and the accessibility of drugs in institutions needs

to be controlled.

Limitations of the Study

This study has a number of limitations to consider when interpreting the results. First, the

analyses were based on self-reported data, which could result in over- or under-reporting of

substance use. However, self-reported measures have been found to be reliable (Del Boca

and Darkes 2003; Koning et al. 2010), and they are often used in studies with larger sample

sizes. Second, this study was performed in a specific group of adolescents, who on average

have poor reading and concentration skills. Therefore, the questionnaire had to be short and

easy-to-understand. As a consequence, the number of variables included in the risk profile

was limited, and for several measures we had to rely on single items and brief scales. In

order to have more detailed knowledge on factors related to substance use, other ways of

data collection are more appropriate, e.g., interviews. However, data collection by means

of self-report questionnaires allowed us to study a relatively large sample size, which is

generally not possible in case of qualitative studies. Third, we used different measurement

methods at the baseline and follow-up basements. At baseline, research assistants

administered self-report questionnaires and at follow-up, online self-report questionnaires

and telephone surveys were used to collect data from adolescents in residential care and

mainstream education, respectively. Since substance use has been found to be more easily

reported in (adult) self-report questionnaires than in telephone interviews (Kraus and

Augustin 2001), we may have overestimated the differences in substance use initiation

between residential care and mainstream education. The change from face-to-face

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assessment to the assessment of online surveys among residential youth, may have influ-

enced the results as well, although studies have indicated that online surveys and face-to-

face interviews with regard to substance use lead to similar results (Khadjesari et al. 2009;

Raghupathy and Hahn-Smith 2011). Fourth, attrition occurred in both the residential youth

care and the reference group. More than half of the respondents did not participate in the

follow-up. Although the attrition analysis showed no significant differences between

responders and non-responders on age, gender and substance use measures, we cannot

exclude the possibility that selective drop-out on other variables has affected the results of

the study. Fifth, the period between the two measurement waves was somewhat longer for

mainstream education (16 months) than for residential youth care (around 13.5 months).

Since there was less time for the adolescents in residential care to initiate substance use

compared to adolescents in mainstream education, this may have led to conservative

estimates of the differences in substance use between adolescents in residential care and

mainstream education, which actually strengthens our conclusions.

Conclusion

Although residential youth care institutions aim to provide a safe environment for ado-

lescents who are not able to live with their parents, the results of the current study suggest

that this setting does not prevent the initiation of daily tobacco use and cannabis use, and

may even elevate the risk for the initiation of hard drug use. These findings suggest a need

for more effective preventive measures and an increased awareness among staff for sub-

stance use among youth living in the institutions.

Conflict of interest There is no conflict of interest that might present a potential conflict in the form of grants, employment by, consultancy for, shared ownership in, or any close relationship with, an organization whose interests, financial or otherwise, may be affected by the publication of the paper.

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