A systematic review of school-based alcohol and other drug prevention programs facilitated by...
Transcript of A systematic review of school-based alcohol and other drug prevention programs facilitated by...
COMPREHENSIVE REVIEW
A systematic review of school-based alcohol and other drugprevention programs facilitated by computers or the Internet
KATRINA E. CHAMPION, NICOLA C. NEWTON, EMMA L. BARRETT & MAREE TEESSON
National Drug and Alcohol Research Centre, University of New SouthWales, Sydney, Australia
AbstractIssues. The use of alcohol and drugs amongst young people is a serious concern and the need for effective prevention is clear.This paper identifies and describes current school-based alcohol and other drug prevention programs facilitated by computersor the Internet. Approach. The Cochrane Library, PsycINFO and PubMed databases were searched in March 2012.Additional materials were obtained from reference lists of papers. Studies were included if they described an Internet- orcomputer-based prevention program for alcohol or other drugs delivered in schools. Key Findings.Twelve trials of 10 programswere identified. Seven trials evaluated Internet-based programs and five delivered an intervention via CD-ROM. Theinterventions targeted alcohol, cannabis and tobacco. Data to calculate effect size and odds ratios were unavailable for threeprograms. Of the seven programs with available data, six achieved reductions in alcohol, cannabis or tobacco use at postintervention and/or follow up.Two interventions were associated with decreased intentions to use tobacco, and two significantlyincreased alcohol and drug-related knowledge. Conclusion. This is the first study to review the efficacy of school-based drugand alcohol prevention programs delivered online or via computers. Findings indicate that existing computer- and Internet-based prevention programs in schools have the potential to reduce alcohol and other drug use as well as intentions to usesubstances in the future. These findings, together with the implementation advantages and high fidelity associated with newtechnology, suggest that programs facilitated by computers and the Internet offer a promising delivery method for school-basedprevention. [Champion KE, Newton NC, Barrett EL, Teesson M. A systematic review of school-based alcohol andother drug prevention programs facilitated by computers or the Internet. Drug Alcohol Rev 2013;32:115–123]
Key words: prevention, school, Internet, review, alcohol.
Introduction
The use of alcohol and other drugs by young people isa serious public health concern and the burden ofdisease, social costs and harms associated with this useare significant [1–5]. The most recent statistics in Aus-tralia show that approximately one-quarter of Austral-ian teenagers (between the ages of 14–19 years) havetried an illicit drug, two-thirds (65%) have consumed afull serve of alcohol in the past year and almost one-fifth(20%) have consumed alcohol at levels that put them atrisk of injury at least once in the past month (defined asmore than four drinks on a single occasion) [1]. Thesefigures are concerning, given that early initiation to
drug use (i.e. before the age of 18) is a risk factor fordeveloping substance use disorders and comorbidmental health problems in adulthood [6,7]. In light ofthis research the need for effective prevention is clear.
In recent years we have seen a substantial increase inthe development of school-based prevention programsfor alcohol and other drug use. Despite this, the major-ity of these programs have shown limited effects,particularly in terms of impacting on behaviour andreducing or preventing substance use [8,9].This is mostlikely due to the many obstacles that impact on suc-cessful program implementation [10,11].These includelimited resources in terms of teachers, money and timeallocated to deliver drug prevention, as well as the fact
Katrina E. Champion BA-Psych (Hons), Research Assistant, Nicola C. Newton BPsych (Hons), PhD, Senior Research Fellow, Emma L. BarrettBPsych (Hons), MPsych, PhD, Research Associate, MareeTeesson BA (Psych), PhD, Professor. Correspondence to Ms Katrina Champion, 22-32King Street, Randwick, NSW 2052, Australia. Tel: +61 2 9385 0175; Fax: +61 2 9385 0222; E-mail: [email protected]
Received 13 June 2012; accepted for publication 3 September 2012.
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R E V I E W
Drug and Alcohol Review (March 2013), 32, 115–123DOI: 10.1111/j.1465-3362.2012.00517.x
© 2012 Australasian Professional Society on Alcohol and other Drugs
that programs are often adapted to the school/classenvironment thereby losing their effective ingredients.A study by Ennett and colleagues [12] found that only14% of programs delivered in schools have the correctcontent and modes of delivery identified in the litera-ture as being effective.
Computer- and Internet-based prevention programshave the potential to overcome these obstacles and offermany advantages over traditional drug preventionmethods. First, since professionals are not required todeliver the programs, they are less restrictive in theiravailability and offer increased feasibility of use in set-tings where professional and teaching time is limited.Even when combined with some direct contact or facili-tation from professionals, the burden on professionals isalleviated as it reduces the amount of time they need todedicate to individuals [13]. Second, once a program isdeveloped there is a reduction in implementation costs,ease of updating materials and increased potential toengage large numbers of individuals and overcome geo-graphical and socio-economic constraints. Third, theycan ensure a high degree of implementation fidelity asconsistent and complete delivery of materials can beguaranteed. Finally, specific to drug education, com-puters and the Internet have the potential to increaseself-disclosure and reduce stigmatisation about druguse, by enhancing perceptions of privacy and anonym-ity [14]. In a school environment however, althoughparticipants are likely to feel less vulnerable disclosinginformation online than in a face-to-face setting [15],some students may still have privacy concerns aboutwhether their personal information will be accessed byteachers or parents.
In recent years, a large number of reviews ofcomputer-based treatment programs have been con-ducted, with results indicating they can be effective interms of outcome and cost by addressing and reducingalcohol and tobacco use [16–33]. However, none ofthese existing reviews have specifically focussed on ado-lescents or on programs delivered in school-based set-tings. Moreover, these reviews have been limited totreatment and therapy interventions and no reviewshave reported specifically on Internet-based programsdesigned to prevent alcohol and drug use. This studywill address these gaps in the literature by reviewing theevidence on, and establishing whether school-basedprevention programs facilitated by the computer or theInternet have the potential to reduce and prevent theuse of alcohol and other drugs in adolescents.
Methods
Data sources
The Cochrane Library, PsycINFO and PubMed data-bases were searched in March 2012, using the following
keywords: ‘online OR web-based OR internet OR com-puter’, ‘drug OR alcohol OR cannabis OR ecstasy ORmarijuana OR substance OR amphetamine OR psychostimulant’, ‘school OR school-based’ and ‘interventionOR prevention OR program OR education’. The titlesand abstracts of the 2574 articles identified were inde-pendently reviewed and full copies of potentially rel-evant papers were obtained to determine if they met theinclusion criteria. Reference lists of individual paperswere manually searched for further publications. Pro-grams were included if they were an Internet- orcomputer-based prevention program for alcohol orother drugs, and if they were delivered at school. Pro-grams targeting school aged students that were imple-mented in the home or community were excluded, aswere those delivered to university or college students.Figure 1 displays a flow chart of the search strategy andstudy selection process.
Study quality
Study quality was evaluated using a validated tool forassessing the quality of randomised controlled trials[34].This instrument has been designed to measure thequality of trials across a broad range of subject areas[35], and has been used previously in reviews of school-based interventions for anxiety and depression [36] anddrug and alcohol use [37]. Studies were rated againstthree key criteria: randomisation, double-blinding, andwithdrawals and drop-outs, and given an overall scoreranging from 0 to 5. As reported previously [38],school-based interventions rarely receive scores above 3as double-blind conditions and full randomisation areoften not possible.
Outcome measures
The primary outcome evaluated was alcohol and drugconsumption, at immediate post-intervention and laterfollow-up occasions. Differences between control andintervention groups were also reported for a range ofsecondary outcome measures including drug-relatedknowledge, attitudes, harms and intentions to use.
Analysis
Effect sizes are reported for continuous outcomes andodds ratios are reported for dichotomous outcomes.Effect size was estimated using Cohen’s d [39], which iscalculated by subtracting the mean intervention scorefrom the mean control score, and dividing this by thepre-intervention pooled standard deviation. Whereavailable, effect sizes and odds ratios were extractedfrom papers, or were provided by the authors of thepaper on request. Due to the small number of studies
116 K. E. Champion et al.
© 2012 Australasian Professional Society on Alcohol and other Drugs
and the heterogeneity of study quality, outcome meas-ures and follow-up occasions, it was not possible tocombine the results into a meta-analysis. For thisreason we chose to report the results in a systematicreview.
Results
Overall, 12 trials of 10 programs were identified. Allprograms were universal, that is, they were deliveredto all students in a year group regardless of their levelof risk for alcohol or drug use. The programs tendedto be based on principles of social influence theory.The ‘social influence approach’ delineates that youngpeople initiate drug use as a result of external pressurefrom peers, family and the media, and that youngpeople are not adequately equipped to deal with suchpressure [40]. Therefore, the goal of this approach isto teach adolescents to resist drugs by providing themwith information, resistance skills and normative edu-cation [41,42]. Two programs were based on princi-ples of social cognitive theory, in which students aretaught skills to enhance self-efficacy and developnegative expectancies about alcohol and drug use
[43], and two interventions drew on the Transtheo-retical Model of Change, which posits that healthbehaviour change occurs through the progression ofsix stages of change [44].
Of the 12 trials, seven evaluated an Internet-basedprogram and five assessed interventions delivered viaCD-ROM. The majority of trials were conducted inAustralia and the USA. All trials were mixed genderand most targeted students in their first two years ofhigh school (13–15 years of age). Eight trials collecteddata post intervention and the follow-up period in thestudies ranged from 6 to 34 months. Most controlgroups received health education as usual, with theexception of the Drugs 4 Real trial, which included avideo component, the Smoking Zine trial whichincluded of a web evaluation control task, and controlsin the Head On trial, which received the Life SkillsTraining program. Overall, study quality was weak,with no studies scoring above 3 (Table 1).This is com-parable to other prevention reviews [37,38] and canlikely be explained by the difficulties achieving full ran-domisation and double-blind conditions in school-based interventions. Of the identified programs, onlythe CLIMATE Schools: Alcohol Module and the Consider
Records identified through database searching (n = 3085)
Scr
een
ing
Incl
uded
Eli
gib
ility
Iden
tifi
cati
on Additional records identified through other sources
(n = 5)
Records after duplicates removed (n = 2574)
Records screened (n = 2574)
Records excluded (n = 2542)
Full-text articles assessed for eligibility
(n = 32)
Full-text articles excluded (n = 20)
• Not school-based (10),
• Not prevention program (5),
• Not online or computer-based (5)
Studies included in qualitative synthesis
(n = 12)
Figure 1. Flow chart of search strategy and study selection.
Systematic review of Internet-based prevention 117
© 2012 Australasian Professional Society on Alcohol and other Drugs
Tab
le1.
Pri
mar
yan
dse
cond
ary
outc
ome
data
for
iden
tified
tria
ls
Pro
gram
Tri
alS
ubst
ance
Sam
ple
Inte
rven
tion
Ori
enta
tion
Con
trol
Sub
stan
ceus
epo
st-i
nter
vent
ion
ES
/OR
Sub
stan
ceus
efo
llow
-up
ES
/OR
Sec
onda
ryou
tcom
esE
S/O
RQ
ualit
yra
ting
Con
side
rT
his
Bul
ler
etal
.20
08[4
5]T
obac
coA
ustr
alia
,10
–16
yrs,
n=
2077
Onl
ine,
6le
sson
sS
ocia
lco
gnit
ive
prin
cipl
esS
tand
ard
heal
thed
ucat
ion
30-d
aysm
okin
gpr
eval
ence
(who
leci
gare
tte)
,E
S0.
05*
(low
erin
INT
than
CO
)
—F
utur
esm
okin
gin
tent
ions
PI,
OR
0.01
2
Tob
acco
US
A10
–14
yrs
n=
1234
Onl
ine,
6le
sson
sS
ocia
lco
gnit
ive
prin
cipl
esS
tand
ard
heal
thed
ucat
ion
30-d
aysm
okin
gpr
eval
ence
(who
leci
gare
tte)
,E
S0.
23
—F
utur
esm
okin
gin
tent
ions
PI,
OR
0.13
*(I
NT
low
erth
anC
O)
2
Sm
okin
gZ
ine
Nor
man
etal
.20
08[4
6]T
obac
coC
anad
a14
–16
yrs
n=
1402
Onl
ine,
5st
ages
Soc
ial
cogn
itiv
epr
inci
ples
,L
AI,
TT
M
Web
eval
uati
onta
sk—
Cig
aret
teus
e,O
R1.
27;
Cig
aret
teus
eam
ong
non-
smok
ers,
OR
0.79
*(l
ower
inIN
Tth
anC
O)
Res
ista
nce
(who
lesa
mpl
e),
OR
1.03
and
resi
stan
ceam
ong
base
line
smok
ers,
OR
1.22
*(h
ighe
rin
INT
than
CO
);B
ehav
iour
alin
tent
ions
tosm
oke,
OR
1.04
and
beha
viou
ral
inte
ntio
nsam
ong
base
line
smok
ers,
OR
0.82
*(l
ower
inIN
Tth
anC
O)
3
AS
PIR
EP
rokh
orov
etal
.20
08[4
7]T
obac
coU
SA
15–1
6yr
sn
=15
74
CD
-RO
M,
5le
sson
s+
boos
ter
TT
MS
tand
ard
heal
thed
ucat
ion
—S
mok
ing
init
iati
onat
18-m
onth
F/U
,O
R2.
87*
(low
erin
INT
than
CO
);C
igar
ette
smok
ing
beha
viou
rat
18-m
onth
F/U
,E
S0.
12*
(low
erin
INT
than
CO
)
Dec
isio
nal
bala
nce,
ES
0.25
*(I
NT
high
erth
anC
O);
Tem
ptat
ion
tosm
oke,
ES
0.20
*(I
NT
low
erth
anC
O);
Sel
f-ef
ficac
y,E
S0.
02;
Res
ista
nce
skill
s,E
S0.
26,
all
at18
-mon
thF
/U
2
CL
IMA
TE
Sch
ools
:Alc
ohol
Vog
let
al.
2009
[48]
Alc
ohol
Aus
tral
ia13
yrs
n=
1466
CD
-RO
M,
6le
sson
sH
arm
-min
imis
atio
n;so
cial
lear
ning
prin
cipl
es
Sta
ndar
dhe
alth
educ
atio
nA
vera
geal
coho
lco
nsum
ptio
n,E
S0.
25;
Bin
gedr
inki
ng,
ES
0.11
Ave
rage
alco
hol
cons
umpt
ion
at6-
mon
thF
/U,
ES
0.24
*an
d12
-mon
thF
/U,
ES
0.23
*(l
ower
inIN
Tth
anC
Ofo
rfe
mal
eson
ly);
Bin
gedr
inki
ngat
6-m
onth
F/U
,E
S0.
20*
and
12-m
onth
F/U
,E
S0.
20*
(low
erin
INT
than
CO
for
fem
ales
only
).
Alc
ohol
know
ledg
eat
6-m
onth
F/U
,E
S0.
73an
d12
-mon
thF
/U,
ES
0.52
;Alc
ohol
harm
sat
6-m
onth
F/U
,E
S0.
08an
d12
-mon
thF
/U,
ES
0.20
*(I
NT
low
erth
anC
Ofo
rfe
mal
eson
ly);
Alc
ohol
expe
ctan
cies
at6-
mon
thF
/U,
ES
0.27
and
12-m
onth
F/U
,fe
mal
es,
ES
0.41
*,an
dm
ales
,E
S0.
30*,
(IN
Tlo
wer
than
CO
).
3
New
ton
etal
.20
09[4
9]A
lcoh
olA
ustr
alia
13yr
sn
=76
4
Onl
ine,
6le
sson
sH
arm
-min
imis
atio
n;so
cial
lear
ning
prin
cipl
es
Sta
ndar
dhe
alth
educ
atio
nA
vera
geal
coho
lco
nsum
ptio
n,E
S0.
09*
(low
erin
INT
than
CO
);B
inge
drin
king
,E
S0.
06
Ave
rage
alco
hol
cons
umpt
ion
at6-
mon
thF
/U,
0.09
;B
inge
drin
king
at6-
mon
thF
/U,
ES
0.05
Alc
ohol
know
ledg
e,E
S0.
69*
(IN
Thi
gher
than
CO
);A
lcoh
olha
rms,
ES
0.08
;A
lcoh
olex
pect
anci
es,
ES
0.20
,al
lat
6-m
onth
F/U
2
118 K. E. Champion et al.
© 2012 Australasian Professional Society on Alcohol and other Drugs
CL
IMA
TE
Sch
ools
:Alc
ohol
&C
anna
bis
New
ton
etal
.20
09[5
0]N
ewto
net
al.
2010
[51]
Alc
ohol
,ca
nnab
isA
ustr
alia
13yr
sn
=76
4
Onl
ine,
12le
sson
s(i
ncl.
2bo
oste
rle
sson
s)
Har
m-m
inim
isat
ion;
soci
alle
arni
ngpr
inci
ples
Sta
ndar
dhe
alth
educ
atio
nA
vera
geal
coho
lco
nsum
ptio
n,E
S0.
18;
Bin
gedr
inki
ng,
ES
0.90
;F
requ
ency
ofca
nnab
isus
e,E
S0.
18
Ave
rage
alco
hol
cons
umpt
ion
at6-
mon
thF
/U,
ES
0.16
*an
d12
-mon
thF
/U,
ES
0.38
*(l
ower
inIN
Tth
anC
O);
Bin
gedr
inki
ngat
6-m
onth
F/U
,E
S0.
05an
d12
-mon
thF
/U,
ES
0.17
*(l
ower
inIN
Tth
anC
O);
Fre
quen
cyof
cann
abis
use
at6-
mon
thF
/U,
ES
0.19
*lo
wer
inIN
Tth
anC
O)
and
12-m
onth
F/U
,E
S0.
31
Alc
ohol
know
ledg
eat
6-m
onth
F/U
,E
S0.
75*
and
12-m
onth
F/U
,E
S0.
76*
(IN
Thi
gher
than
CO
);C
anna
bis
know
ledg
eat
6-m
onth
F/U
,E
S0.
56*
and
12-m
onth
F/U
,E
S0.
61*
(IN
Thi
gher
than
CO
);A
lcoh
olha
rms
at6-
mon
thF
/U,
ES
0.04
and
12-m
onth
F/U
,E
S0.
26;
Can
nabi
sha
rms
at6-
mon
thF
/U,
ES
0.04
and
12-m
onth
F/U
,E
S0.
12;A
lcoh
olex
pect
anci
esat
6-m
onth
F/U
,E
S0.
16an
d12
-mon
thF
/U,
ES
0.3;
Can
nabi
sat
titu
des
at6-
mon
thF
/U,
ES
0.03
and
12-m
onth
F/U
,E
S0.
21.
3
Com
bine
dPA
SIn
terv
enti
onK
onin
get
al.
2009
[52]
Kon
ing
etal
.20
11[4
3]
Alc
ohol
Net
herl
ands
12–1
3yr
sn
=33
68
Onl
ine,
4le
sson
san
d/or
pare
nted
ucat
ion
+bo
oste
r
Soc
ial
lear
ning
prin
cipl
esS
tand
ard
heal
thed
ucat
ion
—O
nset
ofhe
avy
wee
kly
alco
hol
use
at10
-mon
thF
/U,
OR
0.36
*,22
-mon
thF
/U,
OR
0.80
and
34-m
onth
F/U
,O
R0.
69*
(les
sus
ein
INT
than
CO
);O
nset
ofw
eekl
yal
coho
lus
eat
10-m
onth
F/U
,O
R,
0.67
*,22
-mon
thF
/UO
R0.
71*
and
34-m
onth
F/U
,O
R0.
69*
(les
sus
ein
INT
than
CO
);F
requ
ency
ofm
onth
lydr
inki
ngat
10an
d22
-mon
thF
/Ua
—3
TT
MIn
terv
enti
onA
veya
rdet
al.
2001
[53]
Tob
acco
UK
13–1
4yr
sn
=83
52
CD
-RO
M,
3le
sson
sT
TM
AO
—W
eekl
ysm
okin
gat
24-m
onth
F/U
,O
R1.
06;
Pos
itiv
ech
ange
ofst
age
at24
-mon
thF
/U,
OR
1.25
—2
Hea
dO
nM
arsc
het
al.
2007
[54]
Tob
acco
,al
coho
l,ca
nnab
is
US
A12
yrs
n=
272
CD
-RO
M,
15le
sson
sS
ocia
lle
arni
ngpr
inci
ples
Lif
eS
kills
Tra
inin
gpr
ogra
m
Fre
quen
cyof
smok
ing*
a
(IN
Thi
gher
than
CO
);F
requ
ency
ofdr
inki
nga ;
Fre
quen
cyof
mar
ijuan
aus
ea
—D
rug-
rela
ted
know
ledg
e*a
(IN
Thi
gher
than
CO
);In
tent
ions
tous
eal
coho
l,ci
gare
ttes
and
mar
ijuan
aa ;A
ttit
udes
tow
ards
drug
usea ;
Lik
elih
ood
ofre
fusa
la
0
Ref
use
toU
seD
unca
net
al.
2000
[55]
Can
nabi
sU
SA
,15
yrs,
n=
65
CD
-RO
M,
1le
sson
Soc
ial
lear
ning
prin
cipl
esS
tand
ard
Hea
lth
Edu
cati
on
——
Effi
cacy
tore
fuse
mar
ijuan
a*a
(IN
Thi
gher
than
CO
);In
tent
ion
tore
fuse
*a(I
NT
high
erth
anC
O)
3
Dru
gs4
Rea
lL
ord
&D
’Am
ante
[56]
Alc
ohol
,C
anna
bis,
Tob
acco
US
A,
12–1
4yr
s,n
=29
5
Onl
ine,
6vi
sits
Soc
ial
lear
ning
prin
cipl
esA
O;V
ideo
cont
rol
Dru
g-re
late
dkn
owle
dge*
a
(IN
Thi
gher
than
CO
);In
tent
ions
tous
eal
coho
l,ci
gare
ttes
and
mar
ijuan
aa ;A
ttit
udes
tow
ards
drug
usea ;
Lik
elih
ood
ofre
fusa
la
——
1
*Sig
nific
ant
diff
eren
ceat
P<
0.05
betw
een
inte
rven
tion
and
cont
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Systematic review of Internet-based prevention 119
© 2012 Australasian Professional Society on Alcohol and other Drugs
This program had been evaluated more than once.Effect size or odds ratios were unable to be calculatedfor three trials [54–56], and therefore are not includedin the results below (but are described in Table 1).
Primary outcomes
Table 1 presents outcome data relating to alcohol ordrug use for each trial. Five trials targeted tobacco andthree were associated with some reduction in smoking.In one trial [45], there was only a small effect at postintervention and in another [46] the intervention wasonly effective at reducing cigarette use among non-smokers at baseline. A third trial [47] was associatedwith a medium effect at the 18-month follow up. Allfour trials that measured alcohol consumption wereassociated with some reduction in alcohol use at postintervention and/or follow up. Effect size (ES) wassmall at post intervention (ES 0.09) and similarlymodest at follow up (ES 0.16–0.38 and odds ratio0.36–0.71). Two trials [48,51] were associated withpositive outcomes relating to the frequency of bingedrinking. Of the seven programs, only one targetedcannabis. This program was associated with a signifi-cant reduction in the frequency of cannabis use at6-month follow up with a small effect size (0.19).
Secondary outcomes
Table 1 displays data for the secondary outcomes meas-ured in each trial. Three trials measured future inten-tions to use tobacco. Of these, one was associated witha small reduction in intentions to smoke post interven-tion, and another found a larger effect, but only amongsmokers at baseline. All three trials that assessed drug-related knowledge demonstrated a significant increasein knowledge in the intervention groups compared withcontrols. Effect size for positive results ranged frommodest to large (0.69–1.33). Of the three trials thatassessed attitudes towards cannabis and alcohol, onefound a reduction in positive expectancies and atti-tudes, with the strongest effects occurring at 12-monthfollow up (ES 0.4 females, ES 0.3 males). One trial wasassociated with a reduction in alcohol-related harms,however only for females and only at 12-month followup [48], and another was associated with an increase inresistance skills, but only among baseline smokers [46].Finally, one study found a small, yet significant increasein decisional balance relating to tobacco use, as well asa reduction in temptations to smoke.
Discussion
Overall, we identified 10 computer- or Internet-basedprograms that have been trialled for the prevention of
alcohol and drug use in schools, and obtained effect sizeand/or odds ratios for seven of these programs. Six ofthe seven programs achieved a reduction in alcohol ordrug use at post intervention and/or follow up, two wereassociated with decreased intentions to smoke in thefuture and two programs significantly increasedalcohol- and drug-related knowledge.The results of thepresent review indicate that existing computer- andInternet-based programs in schools are a potentiallyefficacious method of delivering drug and alcohol pre-vention to adolescents.
Effect size and odds ratios for drug and alcohol usewere small. Of the 6 trials that assessed drug andalcohol consumption at follow up, 5 showed lastingeffects, ranging from 6 months to 34 months. Althougheffects were modest, this is comparable to effect sizereported in a recent review of Internet-based interven-tions for the treatment of substance use in young adults[20].The effect sizes were also similar to those reportedfor Internet-based interventions for anxiety and depres-sion in adolescents, with the exception of those thatinvolved an additional motivational interviewing orinformational component, which showed greater effects[57]. Results from the present review also comparefavourably with traditional, non-computerised pro-grams such as those reported in a recent review ofAustralian school-based prevention programs [37].This suggests that computer- and Internet-based inter-ventions can be as effective, if not more effective, asschool-based programs delivered without computers.
Overall, effect size and odds ratios for secondaryoutcomes were similarly modest. The greatest effectswere achieved in relation to drug- and alcohol-relatedknowledge, with effectiveness persisting at 6- and12-month follow ups for three trials. Previous system-atic reviews of school-based programs and Internet-based interventions have tended to exclude secondaryoutcomes such as knowledge, intentions to use andattitudes.Therefore, a clear strength of this review is theinclusion of a wide range of secondary outcomes, ena-bling a more comprehensive review, and providing amore complete picture of the impact of school-basedonline prevention programs.
This is also the first review to focus specifically oncomputer- and Internet-based programs for the preven-tion of alcohol and drugs in schools. Other trials haveevaluated Internet-based programs among universityand college students, and others have assessed the effi-cacy of implementing computer- and Internet-basedprograms in the home or community, and among olderpopulations. However, given the link between the earlyonset of drug use and later substance use disorders inadulthood [7], it is important to implement and evaluateonline programs that are delivered to adolescents whilethey are still at high school, before they initiate drug use.
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© 2012 Australasian Professional Society on Alcohol and other Drugs
Although the number of trials identified in thisreview is small, the results have implications for thedelivery of alcohol and drug prevention in schools.Theresults of this review support the use of the Internet asa potentially efficacious means of overcoming theobstacles associated with the implementation of tradi-tional prevention programs. Specifically, Internet- andcomputer-based programs offer increased accessibilityand feasibility of use and high implementation fidelity.When considering these advantages in conjunction withthe present results, Internet-based program deliveryappears to be a promising framework for the provisionof school-based education and prevention in the future.
As well as establishing whether Internet-based pro-grams are efficacious in preventing alcohol and druguse, it is critical to gauge why these programs might behaving an effect. One factor that may be associated withprogram success is the number of sessions included inthe intervention. All programs in this review that pro-duced significant results were comprised of between 4and 12 lessons. In comparison, the TranstheoreticalModel of Change Intervention [53], which only con-sisted of three lessons, failed to produce effects. Anadditional factor that has been cited previously as con-tributing to program success, is the inclusion of boostersessions [41]. In the present review, all three programsthat included booster lessons [43,47,50–52] showedsignificant effects. Program orientation may also havehad an impact on the efficacy of trials in terms ofalcohol and drug use. Five of the six programs thatfound significant reductions in substance use wereorientated around social learning or social cognitiveprinciples. This suggests that some of the effectiveingredients in Internet-based prevention programs arenormative education, resistance skills training andreducing positive expectancies [41,42]. However, it isimportant to note there may be reasons why youngpeople use alcohol and drugs, other than peer pressureand poor resistance skills. For example, it is possiblethat teenagers may have realistic positive expectanciesabout alcohol or drug use, and may actively desire toalter their conscious state [58]. Therefore, future pre-vention programs that address these potential motiva-tions, in addition to social influence factors, mayproduce larger intervention effects for adolescents. Afinal factor possibly associated with program efficacy inthe present review is the inclusion of a parenting com-ponent. Although only one program included a parentintervention [43,52], program effects for this trial per-sisted at 34-month follow up. In recent years, researchhas suggested that adding a parental component touniversal prevention programs can strengthen programeffects [53,59]. Therefore, future trials may benefitfrom adding a parental component to existing Internet-based programs for drug and alcohol prevention.
A potential limitation of the present study is that thetrials included in the review relied solely on studentself-report. However, studies have found the self-reportof behaviours such as substance use among adolescentsis highly consistent with behavioural observations, aslong as confidentiality and anonymity is assured [60]. Afurther limitation is the small number of studiesincluded in the review, differences in outcome measuresassessed and the unavailability of data to calculate effectsizes for three of the identified programs. Additionally,only two of the 10 programs had been evaluated morethan once. This highlights a clear need for cross-validation and replication studies of these existing pro-grams, to provide further support for the effectivenessof Internet-based prevention for alcohol and otherdrugs, delivered in schools. Finally, of the 12 trialsincluded in this review, only two [48,55] analysedresults separately for males and females, and only oneof these [48] had available data to calculate effect size.The importance of distinguishing between males andfemales has been noted in the literature [58], and issupported by the differential effect these interventionshad by gender.Therefore, where sample size and powerare adequate to do so, future evaluations shouldattempt to consider results for males and females sepa-rately, especially in countries where the recommendeddrinking guidelines differ for males and females.
Conclusion
Despite the significant harms associated with alcoholand other drug use and the need for effective and prac-tical prevention programs, there are relatively few trialsof school-based alcohol and other drug prevention pro-grams facilitated by computers or the Internet. Amongthose that do exist, it appears that the use of computersand the Internet can be effective in overcoming tradi-tional obstacles to implementation and have the poten-tial to reduce the uptake and use of alcohol and druguse in adolescents. These promising results, togetherwith the numerous implementation advantages andhigh fidelity associated with new technology, suggestthat Internet-facilitated programs offer a promisingdelivery method for school-based prevention.
Acknowledgements
Funding for this paper was supported by an NHMRCproject grant APP1004744. Dr Nicola Newton is aUNSW Vice Chancellor Post-Doctoral ResearchFellow and Professor Maree Teesson is funded on Aus-tralia National Health and Medical Research CouncilResearch Fellowship.
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© 2012 Australasian Professional Society on Alcohol and other Drugs
Competing interests
Dr Nicola Newton and Professor MareeTeesson led thedevelopment and evaluation of the Climate Schoolsprograms. They derive no financial income from theClimate Schools website.
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