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20190402035054nonmedical_prescription_drug_use_among_us_college_students_at_a_midwest_university.pdf
Substance Use & Misuse, 45:865–887 Copyright © 2010 Informa Healthcare USA, Inc. ISSN: 1082-6084 (print); 1532-2491 (online) DOI: 10.3109/10826080903443610
Original Article
Nonmedical Prescription Drug Use Among US College Students at a Midwest University: A Partial
Test of Social Learning Theory
ROBERT L. PERALTA AND JENNIFER L. STEELE
Department of Sociology, The University of Akron, Akron, Ohio, USA
We estimate the prevalence of nonmedical prescription drug (NMPD) use and test social learning theory as an explanation for NMPD use based upon data from a large pilot study. Data were collected from 465 college students at a Midwestern university in the USA using a self-administered questionnaire. The sample was predominantly white (88%), 43% were female and the mean age was 22. Most participants (80%) were not members of social fraternities or sororities. A majority of students did not report NMPD use: 39.4% of respondents reported lifetime NMPD use, 31% reported past- year use, and 14.4% reported past-month use. Multivariate regression results partially supported social learning theory as an explanation for lifetime NMPD use. Limitations and suggestions for future research are suggested.
Keywords social learning theory; nonmedical prescription drug use; NMPD use; pre- scription drug use and misuse; college students; deviance
Introduction
Relatively recently, calls for the use of social network theories (the equivalent of social learning theory) have been called for to better understand how drug use occurs from a socio- logical vantage point (see Valente, Gallaher, and Mouttapa, 2004 for a thorough overview). In response to this call for research, we test social learning theory as an explanation for nonmedical prescription drug (NMPD) use using data from a large pilot study collected at a Midwest university in the United States. In the past decade, NMPD use among college students has been steadily rising (McCabe, West, and Wechsler, 2007). According to a 2004 report by the National Survey on Drug Use and Health, the number of Americans initiating
The authors thank Dr.’s Keith Durkin (Ohio Northern University) and Michelle Brown (Ohio University) for early substantive contributions. We also thank Dr. Stan Einstein, editor in Chief, Sub- stance Use and Misuse, Dr. Cheryl Elman (The University of Akron), and the anonymous reviewers at Substance Use and Misuse for their suggestions and comments on initial drafts. Finally, we thank Dr. Christopher Eustis, Dr. Robert Jeantet, and Mr. Herman Jara-Droguett of the Modern Languages Department of The University of Akron for abstract translation.
Address correspondence to Dr. Robert L. Peralta, Olin Hall, Akron, OH 44325-1905, Department of Sociology, The University of Akron; E-mail: [email protected].
865
866 Peralta and Steele
(i.e., used at least once) the nonmedical use of prescription opioids over the age of 12 years (2.4 million) exceeded individuals initially beginning the use of marijuana (2.1 million) or cocaine (1.0 million) with young adults (18–25) having the highest rates of NMPD use (14.5%) than any other age group (SAMPSA, 2006a, 2006b).
Recent national survey data have found that college students may be more likely than their noncollege peers to report misuse of prescription drugs, specifically prescription stimulants (Herman-Stahl, Krebs, Kroutil, and Heller, 2007; Johnston, O’Malley, Bachman, and Schulenburg, 2004). Research on NMPD use has tended to focus on specific classes of drugs. The three most commonly recognized categories of prescription drugs examined in the current literature are opiates, stimulants, and depressants. There are only a handful of studies that have examined all classes concurrently. Table 1 below displays recent findings on NMPD use so that readers can make assessments about generalizability.
A possible theoretical explanation for NMPD use at the college level is social learning theory (Akers, 1994, 1998; Sutherland and Cressey, 1960). Social learning theory states that deviant and/or criminal behavior and the justifications for behavior are learned from intimate groups. Critical conditions for social learning theory to operate include exoge- nous (e.g., social concerns such as the impact of friends who use) as well as endogenous conditions (e.g., physiological or psychological precursors to substance use). The advan- tage of this perspective is that socio-structural conditions (e.g., exposure to social norms and socialization) are emphasized while limitations of social learning theory center on the problem of causal ordering and/or the ignoring of bio-psychological predispositions to substance misuse. Nevertheless, studies examining social learning theory have proved to be useful in explaining substance use and misuse. For example, Triplett and Payne (2004) and Ford (2008a) found that social learning theory was supported in studies on adolescent NMPD use and is a valuable criminological theory for explaining this particular type of drug use. Triplett and Payne (2004) also reported that social learning theory was useful in explaining NMPD use for a sample of adolescents. Other studies suggest most users obtain prescription drugs from friends: a key aspect of social learning (Hurwitz, 2005; McCabe, Knight, Teter, and Weschler, 2005; McCabe, Teter, and Boyd, 2005). Findings such as these infer that peer association with drug-using acquaintances or friends is predictive of NMPD use (Ford, 2008a). Given these established findings, we suggest that NMPD use among college students can at least partially be explained by elements of social learning theory.
Social learning theory is composed of four major components: differential association, definitions, imitation, and differential reinforcement (see Table 2). Differential association states that deviant and/or criminal behavior is learned; specifically, it is learned through intimate social interaction (e.g., friendship networks, peer socialization, and romantic re- lationships). Learning criminal and/or deviant behavior includes learning the techniques, motives, rationalizations, and attitudes needed for committing the violation (which is simi- lar to learning pro-social behavior). An individual becomes delinquent, for example, if he or she poses more favorable definitions of crime over definitions that are not favorable toward crime. Learning criminal behavior or deviance thus follows the same processes associated with learning other behaviors (Akers, 1994, 1998; Ford, 2008a; Sutherland and Cressey, 1960). Akers conducted a study examining drug use among teenagers and concluded that actual and anticipated rewards and punishments were significant predictors of frequency of drug use (Akers, 1998). Given the theory’s support in other areas of study, it is surprising that few studies have applied social learning theory to substance use and misuse treatment (Andes, 1994).
Although researchers are beginning to document the epidemiological distribution of NMPD use, there has been little theoretical investigation into this particular form of
T ab
le 1
R ec
en t
re se
ar ch
on no
n- m
ed ic
al pr
es cr
ip ti
on dr
ug (N
M P
D )
us e:
a re
so ur
ce ta
bl e∗
A ut
ho r,
ye ar
C ou
nt ry
H yp
ot he
si s
/P ur
po se
C ri
ti ca
l co
nc ep
ts U
nd er
-p in
ni ng
P op
ul at
io n
N D
at a
so ur
ce /
in st
ru m
en ts
us ed
A na
ly si
s F
in di
ng s
L im
it at
io ns
C ri
ti ca
l un
re so
lv ed
is su
es
B oy
d, M
cC ab
e, an
d T
et er
,2 00
6 U
S A
D es
cr ip
ti ve
st ud
y P
ai n
m ed
ic at
io n
E vi
de nc
e- ba
se d
S tu
de nt
s ag
es 10
–1 8
in a
M id
w es
t pu
bl ic
sc ho
ol di
st ri
ct
10 17
U se
of qu
es ti
on s
ad ap
te d
fr om
M on
it or
in g
th e
F ut
ur e;
sp ec
ifi c
qu es
ti on
on no
np re
sc ri
be d
us e
of pa
in m
ed ic
at io
n
B iv
ar ia
te an
d lo
gi st
ic re
gr es
si on
; co
nt en
t an
al ys
is of
op en
en de
d su
rv ey
qu es
ti on
s
16 %
li fe
ti m
e us
e (i
.e .,
pa in
m ed
ic at
io n)
; 1%
us e
in pa
st ye
ar ;
gi rl
s re
po rt
ed hi
gh er
ra te
s of
us e;
no ra
ce di
ff er
en ce
s fo
un d;
le ad
in g
so ur
ce s
of pa
in m
ed ic
at io
n w
er e
fr ie
nd s
an d
fa m
il y
L im
it ed
op er
a- ti
on al
iz at
io n
of N
M P
D us
e (s
pe ci
fi c
to pa
in m
ed ic
at io
n) an
d no
sp ec
ifi ca
ti on
of dr
ug ty
pe ;c
ro ss
se ct
io na
l st
ud y,
se lf
-r ep
or t;
la ck
of qu
an ti
ty ,
fr eq
ue nc
y an
d ro
ut e
of ad
m in
is tr
at io
n m
ea su
re s
P ar
en ta
l aw
ar en
es s
of N
M P
D us
e; le
ve l
of ed
uc at
io n
an d
aw ar
en es
s ab
ou t
N M
P D
us e
in sc
ho ol
s
F or
d, 20
08 a
U S
A S
oc ia
l co
nt ro
l/ so
ci al
le ar
ni ng
pr ed
ic to
r of
N M
P D
us e
S ub
st an
ce ab
us e/
de li
nq ue
nc y
ne xu
s
E vi
de nc
e- ba
se d
N at
io na
l sa
m pl
e 12
an d
ol de
r 55
,9 05
N at
io na
l S
ur ve
y on
D ru
g U
se an
d H
ea lt
h 20
05
O L
S an
d lo
gi st
ic re
gr es
si on
8. 8%
pa st
ye ar
us e;
pa in
re li
ev er
us e
m os
t co
m m
on ;
N M
P D
us e
si gn
ifi ca
nt ly
as so
ci at
ed w
it h
se lf
-r ep
or te
d de
li nq
ue nc
y
S el
f- re
po rt
da ta
, no
ni ns
ti tu
ti on
- al
iz ed
sa m
pl e,
cr os
s se
ct io
na l
da ta
; li
m it
ed co
m pr
eh en
- si
ve ne
ss of
pr es
cr ip
ti on
dr ug
s in
su rv
ey
Id en
ti fy
m ot
iv es
fo r
us e,
th eo
re ti
ca l
pr ed
ic to
rs of
us e,
an d
ex pl
ai n
in cr
ea se
s in
us e
ov er
ti m
e
F or
d, an
d A
rr as
ti a,
20 08
U S
A S
oc ia
l co
nt ro
l; so
ci al
le ar
ni ng
pr ed
ic to
r of
N M
P D
us e
C or
re la
te s
of us
e E
vi de
nc e-
ba se
d N
at io
na l
co ll
eg e
st ud
en t
sa m
pl e
10 ,4
01 H
ar va
rd S
ch oo
l of
P ub
li c
H ea
lt h
C ol
le ge
A lc
oh ol
S ur
ve y
20 01
M ul
ti -
N om
ia l
lo gi
st ic
re gr
es si
on
11 %
li fe
ti m
e us
e (N
M P
D on
ly );
w hi
te s
m or
e li
ke ly
to re
po rt
N M
P D
us e;
il li
ci t
st re
et dr
ug us
e as
so ci
at ed
w it
h gr
ea te
r ri
sk -b
eh av
io r
th an
N M
P D
; su
pp or
t fo
r so
ci al
co nt
ro l
th eo
ry
D id
no t
ac co
un t
fo r
po ly
-s ub
st an
ce ab
us e;
se lf
-r ep
or t
da ta
; cr
os s-
se ct
io na
l; li
m it
ed co
m -
pr eh
en si
ve ne
ss of
pr es
cr ip
ti on
dr ug
s in
su rv
ey
S oc
ia l
an d
be ha
vi or
al co
ns eq
ue nc
es of
N M
P D
; pe
rc ei
ve d
sa fe
ty of
N M
P D
us e
co m
pa re
d to
“s tr
ee t
dr ug
s” ;
th eo
re ti
ca l
pr ed
ic to
rs of
us e
(C o
n ti
n u
ed o n
n ex
t p ag
e)
867
T ab
le 1
R ec
en t
re se
ar ch
on no
n- m
ed ic
al pr
es cr
ip ti
on dr
ug (N
M P
D )
us e:
a re
so ur
ce ta
bl e∗
(C on
ti nu
ed )
A ut
ho r,
ye ar
C ou
nt ry
H yp
ot he
si s
/P ur
po se
C ri
ti ca
l co
nc ep
ts U
nd er
-p in
ni ng
P op
ul at
io n
N D
at a
so ur
ce /
in st
ru m
en ts
us ed
A na
ly si
s F
in di
ng s
L im
it at
io ns
C ri
ti ca
l un
re so
lv ed
is su
es
F or
d an
d R
iv er
a, 20
08 U
S A
H is
pa ni
cs le
ss li
ke ly
to us
e N
M P
D co
m pa
re d
to w
hi te
s
E th
ni c
an d
ra ce
pr ed
ic to
rs of
N M
P D
us e
E vi
de nc
e- ba
se d
N at
io na
l sa
m pl
e 12
an d
ol de
r 55
,9 05
N at
io na
l S
ur ve
y on
D ru
g U
se an
d H
ea lt
h 20
05
B iv
ar ia
te an
d lo
gi st
ic re
gr es
si on
12 .1
% N
M P
D us
e in
pa st
ye ar
,t he
hi gh
es t
pr ev
al en
ce w
as op
ia te
us e
(1 0%
); H
is pa
ni cs
le ss
li ke
ly to
us e
co m
pa re
d to
w hi
te s
bu t
m or
e li
ke ly
to us
e th
an B
la ck
s an
d A
si an
s; ac
cu lt
ur at
io n
im po
rt an
t fo
r H
is pa
ni c
us e
S el
f re
po rt
da ta
; no
ni ns
ti tu
ti on
- al
iz ed
sa m
pl e,
de fi
ni ti
on of
N M
P D
us e;
li m
it ed
co m
- pr
eh en
si ve
ne ss
of pr
es cr
ip ti
on dr
ug s
in su
rv ey
C on
co -
m it
an t
so ci
al pr
ob le
m s
st em
m in
g fr
om N
M P
D us
e
H al
l, Ir
w in
, B
ow m
an ,
F ra
nk en
be rg
er ,
an d
Je w
et t,
20 05
U S
A D
es cr
ip ti
ve st
ud y
A D
H D
; pr
es cr
ib ed
st im
ul an
ts ,
co ll
eg e
st ud
en ts
E vi
de nc
e- ba
se d
M id
w es
t co
ll eg
e st
ud en
ts 38
1 L
ik er
t- ty
pe su
rv ey
on op
in io
ns an
d at
ti tu
de s
to w
ar d
st im
ul an
t us
e
A N
O V
A 13
.7 %
us ed
st im
ul an
ts th
at w
er e
no t
pr es
cr ib
ed ;
an ti
- de
pr es
sa nt
s m
os t
co m
m on
dr ug
ta ke
n (7
% );
m en
m or
e li
ke ly
to ha
ve re
po rt
ed ta
ki ng
st im
ul an
ts fo
r no
nm ed
ic al
pu rp
os es
In it
ia l
lo w
re sp
on se
ra te
fr om
m en
; es
ti m
at es
m ay
be co ns
er va
ti ve
; si
ng le
co ll
eg e
st ud
ie d;
lo w
ge ne
ra li
za ti
on
W ha
t is
th e
im pa
ct of
st im
ul an
t pr
es cr
ip ti
on fo
r ch
il dr
en on
th ei
r ad
ol se
ce nt
N M
P D
us e?
R eg
io na
l di
ff er
en ce
s, if
an y,
ne ed
to be
ex pl
or ed
868
H er
m an
-S ta
hl ,
K re
bs ,K
ro ut
il ,
an d
H el
le r,
20 07
U S
A D
es cr
ip ti
ve st
ud y
M et
ha m
- ph
et am
in e
E vi
de nc
e- ba
se d
Y ou
ng ad
ul ts
(1 8–
25 )
23 ,6
45 N
at io
na l
S ur
ve y
on D
ru g
U se
an d
H ea
lt h
20 02
M ul
ti va
ri at
e an
al ys
is 2.
1% us
ed N
M P
D (s
ti m
ul an
ts )
in pa
st ye
ar ;
w hi
te s
ha d
th e
hi gh
es t
ra te
; se
ll in
g an
d us
in g
il li
ci t
dr ug
s as
so ci
at ed
w it
h in
cr ea
se d
od ds
fo r
N M
P D
st im
ul an
t us
e; ps
yc ho
lo gi
ca l
di st
re ss
, se
ns at
io n-
se ek
in g,
bi ng
e dr
in ki
ng ,a
nd co
ll eg
e en
ro ll
m en
t as
so ci
at ed
w it
h in
cr ea
se d
ri sk
of N
M P
D st
im ul
an t
us e
N M
P D
su rv
ey m
ea su
re s
no t
op ti
m al
(l im
it ed
de sc
ri pt
io n
of ;
ch oi
ce s
fo r
pr es
cr ip
ti on
dr ug
us e)
; cr
os s-
se ct
io na
l; un
kn ow
n if
cu rr
en t
N M
P D
w as
th e
re su
lt of
pa st
pr es
cr ip
ti on
; li
ft im
e an
d pa
st m
on th
m ea
su re
s no
t us
ed
T he
di m
en si
on s
of ps
yc ho
lo gi
ca l
st re
ss as
th ey
pe rt
ai n
to ge
nd er
,r ac
e, et
hn ic
it y,
an d
ag e
ar e
im po
rt an
t fo
r fu
tu re
co ns
id er
at io
n
K ok
ke vi
,F ot
io u,
an d
R ic
ha rd
so n,
20 07
G re
ec e
D es
cr ip
ti ve
st ud
y P
re va
le nc
e an
d in
ci de
nc e
tr en
ds
E vi
de nc
e- ba
se d
N at
io na
l sa
m pl
e ag
es 12
–6 4,
ur ba
n, se
m i
ur br
an ,a
nd ru
ra l
4, 00
0 st
ru ct
ur ed
qu es
ti on
na ir
e, fa
ce to
fa ce
L og
is ti
c re
gr es
si on
9. 1%
en ga
ge d
in an
y N
M P
D us
e in
th e
pa st
ye ar
in 20
04 ;
an al
ge si
c us
e m
os t
co m
m on
; fe
m al
es ou
tn um
be r
m al
es in
N M
P D
us e
bu t
di ff
er en
ce de
cr ea
si ng
ov er
ti m
e
R es
po ns
e va
li di
ty an
d re
li ab
il it
y (l
ow pr
iv ac
y) ;
po ss
ib le
un de
r- es
ti m
at io
n; in
co ns
is te
nc ie
s ac
ro ss
su rv
ey s
P ea
ks an
d do
w nt
ur ns
in us
e ne
ed ex
pl an
at io
n; ef
fe ct
s of
tr ea
tm en
t de
m an
d an
d po
li ce
in te
rv en
ti on
s ne
ed ed
(C o
n ti
n u
ed o n
n ex
t p ag
e)
869
T ab
le 1
R ec
en t
re se
ar ch
on no
n- m
ed ic
al pr
es cr
ip ti
on dr
ug (N
M P
D )
us e:
a re
so ur
ce ta
bl e∗
(C on
ti nu
ed )
A ut
ho r,
ye ar
C ou
nt ry
H yp
ot he
si s
/P ur
po se
C ri
ti ca
l co
nc ep
ts U
nd er
-p in
ni ng
P op
ul at
io n
N D
at a
so ur
ce /
in st
ru m
en ts
us ed
A na
ly si
s F
in di
ng s
L im
it at
io ns
C ri
ti ca
l un
re so
lv ed
is su
es
K ok
ke vi
,F ot
io u,
A ra
pa ki
,a nd
R ic
ha rd
so n,
20 08
E ur
op e
D es
cr ip
ti ve
st ud
y P
re va
le nc
e, co
rr el
at es
E vi
de nc
e- ba
se d
A do
le sc
en ts
fr om
31 E
ur op
ea n
co un
tr ie
s
85 ,0
00 S
ta nd
a- rd
iz ed
su rv
ey s
L og
is ti
c re
gr es
si on
5. 6%
li fe
ti m
e no
nm ed
ic al
tr an
qu il
iz er
or se
da ti
ve us
e; N
M P
D us
e as
so ci
at ed
w it
h to
ba cc
o, al
co ho
l, an
d il
li ci
t dr
ug s;
fi nd
in gs
co m
pa ra
bl e
to U
S ;
L it
hu an
ia ha
d th
e hi
gh es
t ra
te of
N M
P D
an d
U kr
ai ne
ha d
th e
lo w
es t
T he
us e
of tr
an qu
il iz
er s
an d
se da
ti ve
s co
m bi
ne d
in a
si ng
le qu
es ti
on ;
li m
it ed
op er
a- ti
on al
iz at
io n
of N
M P
D ;
cr os
s- se
ct io
na l;
se lf
-r ep
or t
C ro
ss va
- li
da ti
on th
ro ug
h co
nt ex
tu al
in fo
rm at
io n
on pr
es cr
ip ti
on pr
ac ti
ce s
an d
co nt
ro ls
in di
ff er
en t
co un
tr ie
s or
re ta
il sa
le s
ne ed
ed
L eu
ke fe
ld ,
M cD
on al
d, M
at ey
ok e-
S cr
iv en
er ,
R ob
er to
, W
al ke
r, W
eb st
er ,a
nd G
ar ri
ty ,2
00 5
U S
A O
xy C
on ti
n us
er s
w il
l be
m or
e dr
ug in
vo lv
ed ,
us e
m or
e he
al th
se rv
ic es
,a nd
co m
m it
m or
e cr
im es
th an
no nu
se rs
O xy
C on
ti n
(n ar
co ti
c an
al ge
si c)
us er
s ve
rs us
no nu
se rs
; dr
ug us
e cr
im in
al it
y ne
xu s
ev id
en ce
-b as
ed P
ur po
si ve
sa m
pl e
of ru
ra l
M id
w es
t pr
ob at
io ne
rs
29 5
A dd
ic ti
on se
ve ri
ty in
de x;
M ia
m i
H ea
lt h
S er
vi ce
s U
ti li
za ti
on Q
ue st
io nn
ai re
U ni
va ri
at e,
ch i
sq ua
re s;
t- te
st s
O xy
C on
ti n
us er
s si
gn ifi
ca nt
ly yo
un ge
r, ex
hi bi
te d
hi gh
er le
ve ls
of ot
he r
il li
ci t
dr ug
us e,
us ed
m or
e de
to xi
fi ca
ti on
se rv
ic es
, re
po rt
ed hi
gh er
le ve
ls of
m en
ta l
il ln
es s
an d
cr im
in al
be ha
vi or
th an
no nu
se rs
P re
do m
i- na
nt ly
w hi
te m
al e
sa m
pl e;
di d
no t
co nt
ro l
fo r
ag e;
di vi
si on
be tw
ee n
O xy
C on
ti n
us e
an d
no nu
se ;
no nr
ep re
se nt
a- ti
ve sa
m pl
e; se
lf -r
ep or
t
T ar
ge ti
ng N
M P
D ab
us er
s fo
r tr
ea tm
en t
fo r
ru ra
l ar
ea s;
N M
P D
tr ea
tm en
t an
d ru
ra l
N M
P D
tr ea
tm en
t ef
fe ct
iv en
es s;
pa tt
er ns
of in
it ia
l us
e an
d co
nt in
ue d
us e
L eu
ke fe
ld ,
W al
ke r,
H av
en s,
an d
T al
be rt
,2 00
7
U S
A pe
rc ep
ti on
s an
d op
ti on
s w
il l
va ry
ac ro
ss ty
pe s
of in
to rm
an t
gr ou
p
pe rc
ep ti
on s
of ru
ra l
N M
P D
us e
th eo
ry ba
se d
ke y
in fo
rm an
ts fr
om A
pp al
ac hi
an co
un ti
es in
K en
tu ck
y (e
.g .,
el ec
te d
of fi
ci al
s, bu
si ne
ss le
ad er
s)
70 fa
ce -t
o- fa
ce st
ru ct
ur ed
in te
rv ie
w s
qu al
it at
iv e
an al
ys is
de ri
ve d
fr om
sn ow
ba ll
sa m
pl in
g
N M
P D
us e
is no
t ne
w ph
ys ic
al pa
in ,
re cr
ea ti
on al
us e
an d
cu lt
ur al
ac ce
pt an
ce ar
e pa
th w
ay s
to pr
ob le
m us
ed ar
ti cl
es an
d op
ti on
s di
d no
t ve
ry by
gr ou
p ex
tr em
ly hi
gh ra
te of
N M
P D
us e
N on
ra nd
om sa
m pl
in g
of re
sp on
de nt
s se
lf re
po rt
ed da
ta cr
os s-
se ct
io na
l de
si gn
V ie
w s
fr om
la w
en fo
rc em
en t
an d
ju di
ci al
sy st
em ne
ed ed
re se
ar ch
on tr
ea tm
en t
an d
pr ev
en ti
on pe
rt in
an t
to ru
ra l
co m
m un
it ie
s in
ge ne
ra l
al so
in ne
ed
870
L an
ke na
u, S
an de
rs ,
B lo
om ,
H at
ha zi
, B
la rc
on ,T
or tu
, an
d C
la tt
s 20
07
U S
A E
xp lo
ra to
ry ex
am in
at io
n of
co nt
ex t
an d
pa tt
er ns
as so
ci at
ed w
it h
N M
P D
us e
am on
g in
je ct
io n
dr ug
us er
s (I
D U
s)
P ol
yd ru
g us
e; ID
U s
T he
or y-
ba se
d Y
ou th
an d
yo un
g ID
U s
fr om
3 U
S ci
ti es
21 3
F ac
e- to
-f ac
e st
ru ct
ur ed
in te
rv ie
w s
M ix
es d
m et
ho ds
(d es
cr ip
ti ve
un iv
ar ia
te an
d qu
al it
at iv
e an
al ys
is )
95 .8
% N
M P
D us
e; op
io id
s m
os t
co m
m on
; N
M P
D an
in te
gr al
pa rt
of dr
ug us
e am
on g
ID U
s
P ri
m ar
il y
m al
e, w
hi te
, he
te ro
se xu
al sa
m pl
e
R es
ea rc
h on
in it
ia ti
on ,u
se ,
su pp
ly ,a
nd co
nt ex
ts am
on g
ID U
s ne
ed ed
M cC
ab e,
W es
t, M
or al
es ,
C ra
nf or
d, an
d B
oy d,
20 07
U S
A D
es cr
ip ti
ve st
ud y
E ar
ly on
se t,
de pe
nd en
ce E
vi de
nc e-
ba se
d N
at io
na l
sa m
pl e
of ad
ul ts
18 an
d ov
er
43 ,0
93 N
at io
na l
E pi
de m
io lo
gi c
S ur
ve y
on al
co ho
l- re
la te
d co
nd it
io ns
20 01
–2 00
2
R es
ul ts
fr om
st ru
ct ur
ed di
ag no
st ic
in te
rv ie
w s
an al
yz ed
vi a
bi va
ri at
e, ch
i sq
ua re
,a nd
lo gi
st ic
re gr
es si
on
9. 1%
of ad
ul ts
li fe
ti m
e N
M P
D us
e; ea
rl y
ye ar
of N
M P
D on
se t
pr ed
ic ti
ve of
ad ul
t N
M P
D ab
us e
an d
de pe
nd en
ce ;
po ly
dr ug
us e
co m
m on
N M
P D
su rv
ey m
ea su
re s
no t
op ti
m al
(i .e
., co
m pr
eh en
si ve
li st
no t
of fe
re d
to pa
rt ic
ip an
ts )
th us
es ti
m at
es li
ke ly
co ns
er va
ti ve
; ba
se d
on se
co nd
ar y
an al
ys is
; w
or d
ch oi
ce di
ff er
en ce
s co
m pa
re d
to ot
he r
su rv
ey s;
fa il
ur e
to id
en ti
fy th
e m
is us
e of
on e’
s ow
n m
ed ic
at io
n ve
rs us
th e
m is
us e
of ot
he r’
s m
ed ic
at io
ns ;
re su
lt s
m ay
no t
ge ne
ra li
ze ou
ts id
e th
e U
S A
C on
te xt
of ea
rl y
on se
t im
po rt
an t
to st
ud y;
so ci
al ,
ps yc
ho lo
gi ca
l, an
d ph
ys io
lo gi
ca l
vu ln
er ab
il it
ie s
to ea
rl y
us e
im po
rt an
t to
co ns
id er
; ro
le of
fa m
il y
hi st
or ie
s of
al co
ho li
sm im
po rt
an t
to co
ns id
er
(C o
n ti
n u
ed o n
n ex
t p ag
e)
871
T ab
le 1
R ec
en t
re se
ar ch
on no
n- m
ed ic
al pr
es cr
ip ti
on dr
ug (N
M P
D )
us e:
a re
so ur
ce ta
bl e∗
(C on
ti nu
ed )
A ut
ho r,
ye ar
C ou
nt ry
H yp
ot he
si s
/P ur
po se
C ri
ti ca
l co
nc ep
ts U
nd er
-p in
ni ng
P op
ul at
io n
N D
at a
so ur
ce /
in st
ru m
en ts
us ed
A na
ly si
s F
in di
ng s
L im
it at
io ns
C ri
ti ca
l un
re so
lv ed
is su
es
M cC
ab e
an d
T et
er ,2
00 7
U S
A D
es cr
ip ti
ve st
ud y
P re
sc ri
pt io
n st
im ul
an ts
E vi
de nc
e- ba
se d
W eb
-b as
ed M
id w
es t
sa m
pl e
3, 63
9 M
od ifi
ed us
e of
th e
D ru
g A
bu se
S cr
ee ni
ng T
es t
(D A
S T
)
B iv
ar ia
te ,A
N O
V A
8. 5%
li fe
ti m
e N
M P
D us
e, w
hi le
pa st
ye ar
us e
w as
6% ;
N M
P D
us er
s m
or e
li ke
ly to
re po
rt po
ly dr
ug us
e (9
0% );
m od
e of
N M
P D
in ge
st io
n si
gn ifi
ca nt
N M
P D
su rv
ey m
ea su
re s
no t
op ti
m al
(l im
it ed
de sc
ri pt
io n
of /c
ho ic
es fo
r pr
es cr
ip ti
on dr
ug us
e) ;
D A
S T
no t
te st
ed in
W eb
-b as
ed ve
rs io
ns ;
no nr
es po
ns e
ra te
co ul
d be
pr ob
le m
at ic
F ut
ur e
st ud
ie s
sh ou
ld ex
am in
e m
ul ti
pl e
co ll
eg es
fr om
a ra
ng e
of ge
og ra
ph ic
lo ca
ti on
s fo
r co
m pa
ri so
n pu
rp os
es an
d to
as se
ss ge
ne ra
li za
ti on
; la
rg er
,m or
e di
ve rs
e sa
m pl
es ar
e ne
ed ed
; se
xu al
it y,
ra ce
, an
d et
hn ic
it y
di ff
er en
ce s
ar e
in ne
ed of
st ud
y M
cC ab
e W
es t,
an d
W ec
hs le
s, 20
07
U S
A D
es cr
ip ti
ve st
ud y
T re
nd s
an d
co ll
eg e
le ve
l ch
ar ac
te ri
st ic
s
E vi
de nc
e- ba
se d
N at
io na
l sa
m pl
e of
co ll
eg e
st ud
en ts
19 93
–2 00
1
15 ,2
82 14
,4 28
13 ,9
53 10
,9 04
C ol
le ge
A lc
oh ol
S tu
dy H
L M
,m ul
ti pl
e pa
ir w
is e
co m
pa ri
so ns
, ch
i sq
ua re
te st
s,
4. 4%
pa st
ye ar
N M
P D
us e
in 19
93 an
d ro
se to
9. 97
% in
20 01
; li
fe ti
m e
N M
P D
us e
w as
16 .3
4% st
ud en
ts fr
om H
is to
ri ca
ll y
B la
ck sc
ho ol
s le
ss li
ke ly
to us
e; H
L M
su gg
es ts
a st
ea dy
, si
gn ifi
ca nt
ly in
cr ea
si ng
tr en
d in
us e
F in
di ng
s ba
se d
on se
co nd
ar y
an al
ys is
; N
M P
D us
e su
rv ey
m ea
su re
s no
t op
ti m
al ;
da ta
ar e
cr os
s se
ct io
na l
an d
no t
lo ng
it ud
in al
; se
lf -r
ep or
t; va
ri at
io ns
in re
sp on
se ra
te s
fr om
di ff
er en
t in
st it
ut io
ns
R es
ea rc
h on
w ha
t ha
s fa
ci li
ta te
d in
cr ea
se s
in N
M P
D ac
ro ss
ti m
e w
ou ld
be us
ef ul
as w
ou ld
re se
ar ch
on th
e so
ci o-
st ru
ct ur
al pr
oc es
se s
as so
ci at
ed w
it h
re gi
on al
an d
hi st
or ic
al ly
bl ac
k st
at us
di ff
er en
ce s
872
M cC
ab e,
C ra
nf or
d, an
d B
oy d,
20 06
U S
A D
es cr
ip ti
ve st
ud y
A lc
oh ol
us e
co -o
cc ur
re nc
e E
vi de
nc e-
ba se
d N
at io
na l
sa m
pl e
43 ,0
93 N
at io
na l
E pi
de m
io lo
gi c
S ur
ve y
on A
lc oh
ol R
el at
ed co
nd it
io ns
20 01
–2 00
2
R es
ul ts
fr om
st ru
ct ur
ed di
ag no
st ic
in te
rv ie
w s
A na
ly ze
d w
it h
bi va
ri at
e, ch
i sq
ua re
,a nd
lo gi
st ic
re gr
es si
on
3. 17
% pa
st ye
ar N
M P
D us
e ov
er al
l sa
m pl
e; 18
–2 4
ye ar
s ha
d hi
gh es
t pa
st ye
ar R
at e
at 7.
51 %
; dr
in ki
ng se
ve ri
ty si
gn ifi
ca nt
ly as
so ci
at ed
w it
h N
M P
D (a
lc oh
ol -
de pe
nd en
t 18
X m
or e
li ke
ly to
re po
rt an
y N
M P
D us
e)
N M
P D
su rv
ey m
ea su
re s
no t
op ti
m al
(i .e
. co
m pr
eh en
si ve
li st
no t
of fe
re d
to pa
rt ic
ip an
ts th
us es
ti m
at es
li ke
ly co
ns er
va ti
ve ;
ba se
d on
se co
nd ar
y an
al ys
is ;
w or
d ch
oi ce
di ff
er en
ce s
co m
pa re
d to
ot he
r su
rv ey
s; fa
il ur
e to
id en
ti fy
th e
m is
us e
of on
e’ s
ow n
m ed
ic at
io n
ve rs
us th
e m
is us
e of
ot he
r’ s
m ed
ic at
io ns
; re
su lt
s m
ay no
t ge
ne ra
li ze
ou ts
id e
th e
U S
A
R es
ea rc
h in
to w
hy co
-o cc
ur re
nc e
of al
co ho
l an
d N
M P
D us
e is
so pr
ev al
en t
is ne
ed ed
; re
se ar
ch on
ed uc
at io
n ab
ou t
th e
po te
nt ia
l fo
r in
te ra
ct io
n ef
fe ct
s ar
e ne
ed ed
(C o
n ti
n u
ed o n
n ex
t p ag
e)
873
T ab
le 1
R ec
en t
re se
ar ch
on no
n- m
ed ic
al pr
es cr
ip ti
on dr
ug (N
M P
D )
us e:
a re
so ur
ce ta
bl e∗
(C on
ti nu
ed )
A ut
ho r,
ye ar
C ou
nt ry
H yp
ot he
si s
/P ur
po se
C ri
ti ca
l co
nc ep
ts U
nd er
-p in
ni ng
P op
ul at
io n
N D
at a
so ur
ce /
in st
ru m
en ts
us ed
A na
ly si
s F
in di
ng s
L im
it at
io ns
C ri
ti ca
l un
re so
lv ed
is su
es
Q ui
nt er
o, P
et er
so n,
an d
Y ou
ng ,2
00 6
U S
A E
xp lo
ra to
ry ex
am in
at io
n of
ty pe
s an
d so
ur ce
of N
M P
D us
e, th
e ve
nu e
in w
hi ch
us e
ta ke
s pl
ac e,
an d
ty pe
s of
us e
S oc
io -c
ul tu
ra l
fa ct
or s
T he
or y-
ba se
d C
ol le
ge st
ud en
ts in
a so
ut hw
es t
un iv
er si
ty w
ho m
is us
ed pr
es cr
ip ti
on dr
ug s
52 2-
st ag
e se
qu en
ti al
it er
at iv
e se
m i-
st ru
ct ur
ed in
te rv
ie w
s
Q ua
li ta
ti ve
an al
ys e
de ri
ve d
fr om
sn ow
ba ll
sa m
pl in
g an
d ad
ve rt
is em
en ts
N ar
co ti
c an
al ge
si cs
an d
be nz
od i-
az ep
in es
m os
t co
m m
on N
M P
D us
ed fo
r se
lf -
m ed
ic at
io n,
so ci
o- re
cr ea
ti on
an d
ac ad
em ic
fu nc
ti on
in g;
N M
P D
ex pe
ri -
m en
ta ti
on is
so ci
al ly
ac ce
pt ab
le an
d av
ai la
bi li
ty is
w id
es pr
ea d,
w hi
ch co
nt ri
bu te
to N
M P
D at
tr ac
ti ve
ne ss
S m
al l
sa m
pl e/
no n
re pr
es en
ta ti
ve ;
re li
ab il
it y;
in te
rv ie
w ef
fe ct
s (i
.e .,
so ci
al de
si ra
bi li
ty );
fe w
sa m
pl es
fr om
hi gh
-r is
k se
tt in
gs (i
.e .,
do rm
s)
R es
ea rc
h on
re la
ti on
sh ip
be tw
ee n
N M
P D
an d
ad he
re nc
e to
le gi
ti m
at e
pr es
cr ip
ti on
dr ug
us e;
th e
ro le
of st
re ss
in N
M P
D us
e an
d N
M P
D us
e to
en ha
nc e
sc ho
la st
ic pe
rf or
m an
ce
S im
on i-
W as
ti la
an d
S tr
ic kl
er ,
20 04
U S
A D
es cr
ip ti
ve st
ud y
P ro
bl em
us e
E vi
de nc
e- ba
se d
N at
io na
l sa
m pl
e of
pa st
ye ar
N M
P D
us e
40 49
N at
io na
l H
ou se
ho ld
S ur
ve y
on D
ru g
A bu
se 19
91 –1
99 3
L og
is ti
c re
gr es
si on
4% us
e of
an y
N M
P D
in pa
st ye
ar of
w hi
ch 15
% w
er e
ca te
go ri
ze d
as pr
ob le
m us
er s;
na rc
ot ic
an al
ge si
c w
as th
e m
os t
co m
m on
; be
in g
fe m
al e,
in po
or /f
ai r
he al
th ,a
nd da
il y
al co
ho l
us er
s in
cr ea
se d
th e
pr ob
ab il
it y
of us
e; fe
m al
e st
at us
pr ed
ic te
d na
rc ot
ic an
al ge
si c
an d
tr an
qu il
iz er
pr ob
le m
us e
N on
in st
it -
ut io
na li
ze d
sa m
pl e
an d
se lf
-r ep
or t
da ta
li ke
ly pr
od uc
ed co
ns er
va ti
ve es
ti m
at es
; op
er -
at io
na li
za ti
on of
N M
P D
ne ed
s to
be va
li da
te d
an d
re fi
ne d
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Nonmedical Prescription Drug Use Among College Students 877
substance misuse among college students. Studies on stimulant use have shown that most college students get their drugs from other students but fail to make the connection as to why certain individuals will choose to engage in drug use, while others refrain from this particular form of substance misuse. Meanwhile, research on social deviance in general and social learning theory specifically continues to reveal that peer association is an important predictor of drug use. Thus social learning theory appears to be a useful theory for the explanation of both use and nonuse of drugs among college populations. As such, we attempt to advance knowledge of the epidemiological distribution of prescription drug use among college students and advance deviance and criminological theory by testing social learning theory.
Method and Hypothesis
A self-administered questionnaire was developed and distributed with the approval of the research site’s Institutional Review Board. Questionnaires were pre-tested with graduate students. During the study, those taking the survey were informed verbally by the second author and in writing that “. . .non-medical prescription drug use is defined as the use of prescription drugs for non-prescription purposes, specifically recreational use (which includes drug use in order to aid in studying, test taking, and getting high or buzzed).” Thirteen classes were selected from the College of Arts and Sciences at a university (25,000 students) situated in a rural area and medium-sized town of the Midwest in spring 2006. Classes were randomly selected. Upon permission from instructors, the study was announced in classes and students over the age of 18 were invited to participate.
Careful and appropriate steps were taken to protect respondent’s rights. Potential respondents were informed that the survey was completely voluntary and participation did not affect class performance. Respondents were instructed not to put any identifying information on the survey. Participants were informed that they could discontinue the survey at any time or skip any questions. A cover page was added to ensure the privacy of their answers and serve as a reminder that the survey was confidential. The cover page also reminded participants that they had to be 18 years of age or older to participate and that by completing the questionnaire they were providing consent to have the data analyzed and prepared for publication consideration. Survey responses were analyzed using Statistical Package for the Social Sciences (SPSS). It is important to note the ethical implications of using collected data from individuals–minors and adults–in terms of if and how participants benefit from study participation (see Kleinig and Einstein, 2006). As we were not able to compensate participants directly because our pilot study was unfunded, in asking about NMPD use, the prompting of students to consider NMPD use as potentially problematic may have occurred. Future research should consider providing students with treatment literature and other benefits to offset the “using” of participants for scientific advancement.
We hypothesize that the probability for self-reports of NMPD lifetime use will increase in relation to the four aspects of social learning theory (see Table 3): (1) differential association; (2) definitions; (3) imitation; and (4) differential reinforcement. In other words, if a participant has friends who engage in NMPD use, he or she will also be more likely to engage in NMPD use. NMPD use will be greater among those whose behavior is reinforced either socially or nonsocially (i.e., the more rewards and fewer punishments perceived, the more likely the behavior will occur). Peers who participate in NMPD use will have more neutral or positive definitions of this behavior. By determining the applicability of social learning theory, we directly test social learning theory as a predictor of NMPD use.
878 Peralta and Steele
Table 3 Social learning instrument
Range Alpha
1. Differential Association 0.62 la. What proportion of your close friends (or friends you
associated with most frequently) take prescription drugs for recreational purposes?
(1-5)
1b. Have any of your friends ever pressured you to take prescription drugs for recreational purposes?
(1-5)
2. Definitions 2a. College students should not be held responsible for using
prescription drugs without a prescription, such as Ritalin, to get ahead in schoolbecause
(1-6) 0.80
2b. Older adults have no right to condemn students for taking prescription drugs since they take pills for their problems everyday
(1-6)
2c. Using prescription drugs without a prescription is not really that dangerous
(1-6)
2d. Taking prescription drugs without a prescription does not hurt anyone
(1-6)
2e. Using prescription drugs is not as bad as using illegal drugs such as cocaine, heroin, etc.
(1-6)
2f. Prescription drugs are less addictive than other illegal drugs such as cocaine, heroin, etc.
(1-6)
3. Imitation 0.83 3a1. How would most of your friends react if they discovered
that you were using or had used illicit prescription drugs? (1-5)
3a2. How would your best friends react if they discovered that you were using or had used illicit prescription drugs?
(1-5)
3a. How do you feel your friends view illicit prescription drug use?
(1-5) N/A
4. Differential Reinforcement 0.73 4a. Costs and benefits (scale 2-reinforcement) (1-4) 4b. Willbecome sick (1-4) 4c. Get arrested (1-4) 4d. If arrested, severely punished (1-4) 4e. Develop an addiction (1-4) 4f. Fit into the group better (1-4) 4g. Relief fromboredom (1-4) 4h. Have a good time (1-4) 4i. Achieve better grades (1-4) 4j. Feel buzz or high (1-4) 4k. Suffer a serious physical side-effect that can affect one’s
health (1-4)
4l. Suffer from a serious mental-side effect that can affect one’s mental health
(1-4)
4m. Lose weight or look more attractive (1-4) 4n. Improve focus (1-4)
Nonmedical Prescription Drug Use Among College Students 879
The Instrument
The instrument was 13 pages long and consisted of 45 questions and a prescription drug checklist, which had 32 prescription drug choices. NMPD use was assessed by asking respondents to choose from a list of 30 of the most common names of opiates, stimulants, and depressants (i.e., tranquilizers), which were acquired from the National Institute on Drug Abuse (see Appendix A). An open-ended question was provided to allow students to list additional drugs. We asked about lifetime use and current use. The question phrasing was as follows: How many occasions in (a) your lifetime, (b) the last 30 days, (c) the last 3 months, (d) the last year have you used illicit prescription drugs? This scale was similar to scales used in national research on NMPD use. The response options were: (1) never; (2) 1–2 occasions; (3) 3–5 occasions; (4) 6–9 occasions; (5) 10–19 occasions; (6) 20–30 occasions; (7) more than 30 occasions (Boyd et al., 2006; McCabe, Teter, and Boyd, 2006; Teter, McCabe, Boyd, and Guthrie, 2003; Teter, McCabe, Cranford, Boyd, and Guthrie, 2005). Two changes were adopted to improve the precision of the instrument. Use in last 3 months was included in the present study to sharpen epidemiological precision of prescription drug misuse. Next, participants were asked to identify from a provided list of specific prescription drugs used (instead of drug categories) in the past (lifetime, past year, and past month) for increased accuracy. Other questions, not analyzed here, included questions on coingestion, where or whom the drug was obtained from, and questions on alcohol use and other illicit drug use (e.g., heroine).
The survey was designed to include a series of indicators consistent with components of social learning theory (see Table 3). A number of questions relevant to social learning theory were drawn from previous studies on social learning theory (e.g. Akers et al., 1979; Durkin, Wolfe, and Clark, 2005). The four main components of social learning theory examined were differential association, definitions, imitation, and differential reinforcement. While family influence certainly is an important component of socialization, for the purposes of this study, we were concerned with the effects of peer associations. Also, family members are not considered a primary socialization group for young adults. The impact of secondary socialization factors were beyond the scope of the present study.
Differential association was measured using a two-part scale that asked (a) what proportion of your close friends (or friends you associated with most frequently) take prescription drugs for recreational purposes? and (b) have any of your friends ever pressured you to take prescription drugs for recreational purposes? Response options ranged from 1 (none or almost none) to 5 (all or almost all) (Cronbach’s α = .62). Definitions were measured using a six-question scale designed to assess the presence of techniques of neutralization. Rationalizations for use were provided (e.g., “College students should not be held responsible for using prescription drugs without a prescription, such as Ritalin, to get ahead in school because they are under so much pressure”). Respondents were asked the degree to which they agreed or disagreed with each rationalization by choosing from a range of 1 (strongly disagree) to 6 (strongly agree) (Cronbach’s α = .80). Next, respondents were asked how they thought their friends viewed NMPD use in order to assess imitation based on friend’s positive outlook on NMPD use. We also inquired about friends reactions to NMPD use by the participant–both ‘best’ friend and ‘most of your friends’ reaction were used to approximate imitation. Response options ranged from 1 (very negatively) to 5 (very positively) (Cronbach’s α = .83). Finally, for differential reinforcement, a scale was composed of 13 items and was designed to measure student’s perceived cost (e.g., getting sick) and benefits (e.g., achieving better grades) associated using NMPD. Responses ranged from 1 (very unlikely) to 5 (very likely) (Cronbach’s α = .73).
880 Peralta and Steele
Table 4 Sample demographic characteristics (N = 465)
Percentage n
Gender Female 43 199 Male 55 257
Race White 88 409 African American 3 14 Hispanic 1 6 Other 3 13
Age Mean 20 18–20 55 252 21–22 39 177 23–24 5 18 25 and older 2 8
Greek Membership Greek 20 92 NonGreek 80 364
Year Freshmen 26 120 Sophomore 22 103 Juniors 21 96 Seniors 29 136
Participants
The sample size consisted of 465 students (see Table 4). Forty-three percent (n = 199) were male and 55% (n = 257) female, which is representative of the overall college population in the United States (Freeman, 2004). According to the registrar at this particular university, 662 students were registered for the 13 classes included in the sample, which indicates that the number of students missing from the sample was 197. Respondents may be missing for a number of reasons including absenteeism or not being qualified to take the survey (e.g., “age” and “undergraduates only” restrictions; enrollment in more than one class participating in the study).
Results
A minority of students (39%) reported NMPD use at least once in their lifetime (see Table 5). The mean age of NMPD use onset was 18. About 31% reported NMPD use in the last year, 23.4% in the last three months, and 14.4% in the last thirty days. Also, 24% of those who had used prescription drugs nonmedically, reported that they had used more than one prescription drug. Eighteen percent self-reported using three or more different types of prescription drugs. The three most common drugs respondents reported using were Vicodin (22.4%), Adderall (20.9%), and Ritalin (11.2%). When these drugs were organized into categories, opiates were the most common (27.3%) followed closely by stimulants (26%) and depressants (12.5%).
Nonmedical Prescription Drug Use Among College Students 881
Table 5 Rates of NMPD use
Variable Percentage n
Lifetime use 39 183 Past year 31 146 Last 3 months 23 109 Last 30 days 14 67 Used more than one prescription drugs in lifetime 24 116 Used three or more prescription drugs in lifetime 18 84 Vicodin 22 104 Adderall 21 97 Ritalin 11 52 Opiates 27 127 Stimulants 26 121 Depressants 13 58
Using OLS regression, we created models investigating the probability of lifetime NMPD use for those students who reported ever using NMPD a minority of the sample (see Table 6). Because of strong correlations among independent variables, these models were tested for multicollinearity. Multicollinearity can be potentially problematic for social learning theory by having damaging effects on regression outcomes. In particular, shared variance often happens with social learning models. If this issue is neglected, it can lead to misleading conclusions (Fox, 1981). However, in this study, multicollinearity was not a threat given inter-item correlations did not exceed .70. None of the variance inflation factors were near 5.0, providing more evidence that multicollinearity was not problematic for this study.
The first model was composed of “any lifetime NMPD use” and demographic control variables. A significant regression equation was found (F (8,260) = .3.333, p <.001), with an R2 of .09. However, none of the demographic independent variables were found to be significant at the .05 level. The results of this model explain a very small amount of the variance, approximately 9%, for the lifetime use of illicit prescription drugs. A second OLS regression model was calculated for lifetime use of NMPD and social learning variables. The regression equation was significant (F (5,424) = 43.874, p <.000) with an R2 of .34. We found support for three of our four hypotheses. The most robust significant predictor was differential association (β = .25), followed by imitation (i.e., friend’s reactions) (β = .26) and differential reinforcement (β = .20). Definitions and our second imitation variable, how friends view use, were not significant in this equation. The results of this model explain about 34% of the variance for lifetime NMPD use. Results for this model suggest that peer associations, or having friends that participate in this behavior, make it more probable that an individual will engage in NMPD use.
A final model (Table 6, model 3), composed of all variables, was significant (F(13,238) = 11.639, p <.000), with an R2 of .39. The most robust significant predictor was differential association (β = .24) followed by differential reinforcement (β = .22) and imitation (i.e., friend’s reactions (β = .22). The other two social learning variables, friends view use (i.e., imitation) and definitions, were similarly not significant in this equation. In our final model, partial support for social learning theory was again found for three of the four aspects of social learning theory. In terms of our imitation variable, it appears a friend’s reaction to
882 Peralta and Steele
Table 6 Lifetime NMPD use, Standardized Beta Coefficients
Model 1 Model 2 Model 3 Variables Demographics Social learning Full model
Control Variables Gender (Female = 1) −0.04 0.03 Race (White = 1) −0.02 −0.05 Greek membership −0.01 −0.20 Current residence 0.11 0.10 Overall GPA −0.01 −0.07 Age 0.18 0.13 Income (50 k—170 + k) 0.11 −0.02 Year in school −0.01 −0.03
Social Learning Variables Differential association 0.25∗∗∗ 0.24∗∗∗
Definitions 0.03 0.01 Imitation (friend’s reactions) 0.26∗∗∗ 0.22∗∗
Imitation (friend’s view of use) −0.01 −0.02 Differential reinforcement 0.20∗∗∗ 0.22∗∗∗
R2 0.09 0.34 0.39
Significance ∗.05, ∗∗ .01, ∗∗∗ .001.
personal use is a more significant factor compared to a friend’s general attitude toward NMPD use. The results of this model explain about 39% of the variance in lifetime NMPD use. As in previous models, peer associations, or having friends that participate in this behavior, made it more likely that an individual would also engage in NMPD use. We should note here that similar findings were found for past year NMPD use with differential association, differential reinforcement, and imitation increasing the reported use of NMPD (results not presented here but are available upon request). We should add that gender was significant for NMPD use in our past year model (also not presented here).
Discussion
The rates of lifetime, last-year, and last-month NMPD use were higher than anticipated, yet NMPD users were a minority in our sample of college students. This study reveals that 39.4% of the sample reported lifetime use of nonmedical prescription drugs, while 31% had reported use in the last year and 14.4% in the last month. The three most popular prescription drugs chosen by respondents were Vicodin (22.4%), Adderall (20.9%), and Ritalin (11.2%). The elevated rates of use reported here could be due to the general ease of overall accessibility given sales and production of these drugs have increased over the last ten years (Manchikanti, 2007). Perhaps students are more likely to be exposed to prescription drugs legitimately (through physician prescription) due to relative socio- economic privilege associated with college-student status. Furthermore, college students are more likely to be treated for ADHD compared to the general population, which may exacerbate risk for NMPD use (see Johnston, O’Malley, and Bachman, 2003).
The percentages for lifetime use of stimulants presented here are larger than what national studies of undergraduate students have estimated. Typically, these studies have
Nonmedical Prescription Drug Use Among College Students 883
prevalence rates between 6.9% and 8.1% for lifetime use of stimulants (McCabe, Knight, Teter, and Weschler, 2005; Teter et al., 2005), while 26% of our sample reported lifetime recreational use of stimulants. The university chosen for this study could be a factor in the higher prevalence rate for stimulant use. A study by McCabe, Knight, Teter, and Wechsler (2005) revealed that prevalence rates differed by region (i.e., some universities’ prevalence rates of stimulant use were as low as zero, while other schools had rates as high as 25%). The location of the university in which this study took place was in the North Central region of the USA, an area found to have higher rates of prescription drug use.
Another factor that could account for differences in prevalence rates could be due to our questionnaire design. The questionnaire listed approximately 30 well-known prescription drugs for students to choose from and an opportunity for students to write in the names of drugs not listed (eight students chose to use the open-ended category and of those most wrote a street name variation of the drug listed). Requiring respondents to choose drugs limited to “opiates,” “stimulants,” or “depressants” may yield conservative estimates. Using categorical options can limit the accuracy of substance abuse data collection instruments because respondents may not know what category the drug he or she took belonged to thus increasing the likelihood of skipping questions. Listing common names of prescription drugs may trigger the respondents’ memory that he or she did in fact use a particular drug within the time frame under investigation.
In our research, the lifetime rate of nonmedical opiate use was slightly smaller com- pared to one national study by McCabe, Knight, Teter, and Wechsler (2005), which discov- ered that 33% of college students in that sample admitted to lifetime opiate use, while only 27.3% of this study’s sample reported lifetime nonmedical use of opiates. In our study, the rate of lifetime depressant use was 12.5%. Other studies have reported rates of sedative and tranquilizer use at 6% and 8% respectively (McCabe, West, and Wechsler, 2007).
Several of the hypotheses for social learning theory and NMPD use were supported in this study. Our regression models provide some support for social learning theory as at least a partial explanation for NMPD use among college students (39% of the variance in lifetime NMPD use was explained in the social learning need). Results suggest that NMPD use is influenced by peer associations. This finding corresponds to other studies conducted on deviant behavior in general and substance abuse specifically (Akers, 1994; Akers, Krohn, Lanza-Kaduce, and Radosevich, 1979; Durkin et al., 2005; Lanza-Kaduce, Akers, Krohn, and Radosevich, 1984; Michaels and Miethe, 1989; Triplett and Payne, 2004; Winfree, Sellers, and Clason, 1993).
We recommend that future research designs include the analysis of family influence data in the interest of expanding upon social learning theory. Also, because we may have a conceptualization bias in that the respondent is related to as being the potential or actual fo- cus of pressure — a unidirectional movement – future research should take bi-directionality into consideration because the individual can be a source of pressure on others. Of relevance, comprehensive information on social networks was not collected. However, information on Greek membership and off or on campus residence was collected. Future research should expand upon the implications for other types of social networks (e.g., clubs and other so- cial organizations). The study of multidimensional, complex processes-involving percep- tions, expectations, judgments, decision-making, and learning or not learning necessitates a range of adaptation and functioning skills, abilities, and energies. Data collection related to these issues allows for a more comprehensive sense of the person–unfortunately, these are data that were not collected and thus limit our study. Others who pursue social learning theory in treatment approaches should contend with competing paradigms such as “natural recovery” processes (Burman, 1997) and “rational addiction” (Becker and Murphy, 1988)
884 Peralta and Steele
of the behavioral economists and the work of Kahneman (2003) who has documented the irrationality of human judgment. Finally, it is problematic that the sample was largely com- posed of white students. More research is needed to understand the dynamics of substance use in the context of racialized and gendered social structures given the significant varia- tions found in substance use by gender (Wechsler, Dowdall, Maenner, Gledhill, and Lee, 1998; Wilsnack, Vogeltanz, Wilsnack, and Harris, 2000; Peralta, 2007) and race (Wallace and Bachman, 1991; Peralta, 2005; Hallman and Broman, 2009; Peralta and Steele, 2009). Bridging the literatures discussed here is promising for the development of substance use and misuse theory building and science-based treatment approaches.
Declaration of interest: The authors report no conflict of interest. The authors alone are responsible for the content and writing of this paper.
THE AUTHORS
Dr. Robert L. Peralta is an assistant professor of Soci- ology at the University of Akron, Ohio, USA. He earned his Ph.D. from the University of Delaware in 2002. His areas of interest and expertise include substance use and abuse, deviance, gender, social inequality, and interper- sonal violence. Alcohol use in intimate partner violence and the association between alcohol use and the construc- tion of gender are the focus of his current research. Some of his publications appear in the Journal of Drug Issues; The Journal of Ethnicity in Substance Abuse; Sex Roles; Journal of Men’s Studies; Gender Issues; Journal of the American Board of Family Practice; Deviant Behavior, and Violence and Victims.
Jennifer Steele is a Ph.D. candidate in the Department of Sociology, University of Akron, Ohio, USA. She received the M.A. degree from Ohio University. Jennifer’s research interests include substance use and abuse, deviance, social inequality, and interpersonal violence.
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Appendix A
List of drug options available to respondents
Oxycodone Dexedrine Oxycontin (hillbilly heroin) Ativan Percodone Valium Oxycet Librium Percocet Xanax Darvon Halcion Propoxyphene Amytal Hydrocodone Seconal Vicodin Phenobarbital Lortab Nembutal Lorcet Prescription diet pills Codeine (Captain Cody) Fentanyl Meperidine
(phentermine, adpex, merida, tenuate, didret xenical, Ionamin, Bontril, phendinnetrazine, diethylpropion)
Demerol Ritalin (smart drug)
Other (please list, even if you know only the street name)
Concerta Adderall Methyphenidate
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