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Childhoods Today, Volume 10, Issue 1, 2016 Motivation is Key: The Differing Predictors of Adolescents' Nonmedical Use of
Prescription Drugs
Whitney DeCamp, Western Michigan University; James Herzig, Western Michigan University; Brooke O'Neil, Western Michigan University; Daniel O'Connel , University of The nonmedical use of prescription drugs (NMUPD) persists as a problem among adolescents in the United States. Nonmedical prescription drugs rank behind only marijuana in terms of drug use by 12–17 year olds with 6.7 percent reporting use within the past twelve months (McCauley et al., 2010; Substance Abuse and Mental Health Services Administration [SAMHSA], 2011b). Data from Monitoring the Future, an annual survey of youth designed to monitor trends in il egal substance use, indicates that the rate for high school seniors within the past twelve months is 15 percent, with 22 percent reporting lifetime use (Johnston, O'Mal ey, Bachmann, & Schulenburg, 2011). According to data from the Drug Abuse Warning Network, prescription drugs account for half of al drug-related emergency room visits among 12–17 year olds (SAMHSA, 2011a). Furthermore, these same prescription drug-related emergency room visits have risen 24 percent from 2004 to 2009. Given the relatively high rates of NMUPD among youth and the increasing health consequences, understanding the risk factors that may lead to or correlate with NMUPD can potential y lead to more effective prevention and intervention strategies. Although research has begun to examine this important issue, differing types of NMUPD are often treated as one single concept or behavior. One clear distinction between types of NMUPD is between recreational users – individuals who engage in NMUPD to get high – and self-treating users – individuals who engage in NMUPD to treat a medical condition without a doctor's supervision (Gunter, Farley, & O'Connel , 2013). Treating self-treating users and recreational users as the same (i.e., studying NMUPD without distinguishing between the two in the research) could result in misunderstanding of the risk factors involved. With two very different motivations and goals for using prescription drugs, the assumption should be that these groups, who are only connected by the same broad classification of substances, are distinct until proven otherwise. Indeed, descriptive research has noted that recreational users are at a much higher likelihood of engaging in other risk behaviors (Gunter et al., 2013), suggesting that these two categories of users are different. Unfortunately, similar research distinguishing motivations has not examined the antecedents of NMUPD. In light of the lack of empirical research into the differing motivations for use, the current study examines risk factors with an emphasis on distinguishing between recreational users and self-treating users. Childhoods Today, Volume 10, Issue 1, 2016
Nonmedical Prescription Drug Use

One of the reasons for the rise in the NMUPD problem may be that there are an alarmingly high number of medications being prescribed to individuals in the United States and more than in previous years (Fortuna, Robbins, Caiola, Joynt, & Halterman, 2010). Fortuna and col eagues (2010) found that, when comparing how many doctor visits in which a control ed medication, such as opioids or sedatives, were prescribed to adolescents, the numbers increased substantial y from 2.3 mil ion in 1994 to 5.7 mil ion in 2007. The numbers also more than double – 7.8 million to 18.6 million – when comparing doctor visits in which a control ed medication was prescribed to young adults in the same time frame (Fortuna et al., 2010). In addition, the perception of many prescription drugs has shifted due to media, such as television and the Internet, in which prescription drug use appears more frequently and is more readily accepted than before (Compton & Volkow, 2006). Adolescents make the assumption that prescription drugs are safer than other drugs due to doctors prescribing them and friends and family members using them (Compton & Volkow, 2006). Because prescription drugs are being prescribed at increasing rates and the perceptions of them have become more positive, prescription drugs have become easier to obtain through friends and family. In fact, the National Survey on Drug Use and Health found that 55% of people (age 12 or older) obtained prescription pain relievers that they used nonmedical y from a relative or a friend at no cost (SAMHSA, 2011b). NMUPD is not solely an issue in the United States, however, as it is prevalent among adolescents in other countries as wel . According to the Ontario Student Drug Use and Health Survey (OSDUHS), a school-based survey of youth in Canada, 15% of students in grades 9-12 reported the nonmedical use of at least one prescription drug in the past year (Boak, Hamilton, Adalf, & Mann, 2013). Moreover, the non-prescribed opioid pain relievers are among the most commonly used drugs in grades 7-12, with 12% of the sample reporting use while 15% report using prescription opioid pain relievers nonmedical y in their lifetime (Boak, et al., 2013). In addition, the European School Survey Project on Alcohol and Other Drugs (ESPAD), a study of substance use of students in 36 countries in Europe, found that an average of 6% of students reported lifetime use of tranquilizers or sedatives without a prescription, with several countries reporting as high as 14% (Hibel , Guttormsson, Ahlström, Balakireva, Bjarnasonn, Kokkevi, & Kraus, 2012). Similarly, the Australian Institute of Health and Welfare household survey (2014) noted that the population of individuals 14 and older that used prescription drugs nonmedical y increased from 4.2% in 2010 to 4.7% in 2013. Clearly, NMUPD – among both adolescents and the population in general – is an international issue. Less clear, however, are the predictors and correlates of such behavior. Childhoods Today, Volume 10, Issue 1, 2016 Predictors of Nonmedical Prescription Drug Use

Previous research has identified numerous predictors of NMUPD at the individual level, a prominent one being the use of other il icit drugs or alcohol (Fleary, Heffer, & McKyer, 2011; Ford, 2009; McCabe et al., 2007; Schepis & Krishnan-Sarin, 2008; Wu et al., 2008). Unsurprisingly given this association, individual characteristics associated with il icit drug use, such as risk-taking and sensation-seeking traits, are also predictive of NMUPD (Arria, Caldeira, Vincent, O'Grady, & Wish, 2008; Boyd et al., 2009; Col ins et al., 2011; Schepis & Krishnan-Sarin, 2008). Sensation-seeking is a "trait defined by the seeking of varied, novel, complex and intense sensations and experiences and the wil ingness to take physical, social, legal and financial risks for the sake of such experiences" (Zuckerman, 1994, p. 27) and may be an especial y important risk factor for adolescents, as this trait has been shown to peak around the age of 16 for females and 18 for males (Romer & Hennessy, 2007). Evidence also points to traumatic life events and experiences of criminal and sexual victimization as being associated with NMUPD (Hal , Howard, & McCabe, 2010; Young, Grey, Boyd, & McCabe, 2011; Young et al., 2012). A history of victimization has been linked to an increased likelihood of adolescents self-treating with opioids to relieve physical pain (Young et al. 2012). However, while McCauley et al. (2010) found that past sexual and physical assault were individual y associated with increased NMUPD, witnessing violence was the only unique significant predictor. Adolescents who reported witnessing violence were twice as likely to also report past-year NMUPD (McCauley et al., 2010). Thus, it has been suggested that witnessing violence may be a symptom of a harmful environment in general rather than the root cause. Additional y, posttraumatic stress disorder (PTSD) is associated with adolescent NMUPD, as adolescents may be turning to prescription drugs to self-treat symptoms of PTSD (McCauley et al., 2010). Family and friends play an important role in adolescents' lives and can impact their decision to use prescription drugs. One potential protective factor associated with NMUPD is the amount of parental monitoring and involvement in the lives of their adolescent children (Twombly & Holtz, 2008; Schinke et al., 2008; Sung et al., 2005; Ford, 2009). For instance, Schinke et al. (2008) found that an increase in a mother's knowledge of her daughter's comings and goings was associated with a decrease in the daughter's prescription drug use. Col ins et al. (2011), however, did not find parental monitoring to be a significant predictor, giving question to the importance of this variable. Considering the importance of peers during adolescence, it is not unexpected that peer attitudes toward substance use have been found to be a significant risk factor for NMUPD. Indeed, research finds that NMUPD is more likely when close friends use any type of substance (Col ins et al., 2011; Schinke, Fang, & Cole, 2008) or approve of substance use (Ford, 2008). NMUPD are further affected by perceptions regarding drug availability and risk. Perceived availability of prescription drugs is significantly associated with increased Childhoods Today, Volume 10, Issue 1, 2016 NMUPD (Col ins et al., 2011), possibly because the most common source of nonmedical prescription drugs is through social contacts (SAMHSA, 2011). Research has found that as many as 70% of the students who report the nonmedical use of prescription opioid pain relievers in the past year acquired the drug from a person at home (Boak et al., 2013). Risk perception of NMUPD is also strongly associated with NMUPD (Twombly & Holtz, 2008; Arria et al., 2008; Col ins et al., 2011; Johnson et al., 2011; Quintero, Peterson, & Young, 2006; Friedman, 2006). The Partnership Attitude Tracking Survey (2013) found that a third of adolescents state that it is okay to self-treat using prescription drugs without a medication, while 27 percent believe using prescription drugs to get high is safer than using il egal drugs. Friedman (2006) comments that this lack of risk awareness could be due to the absence of stigmatization surrounding prescription drugs as wel as their increased availability compared to il icit drugs. However, Arria et al. (2008) found that among high-scoring sensation-seekers, risk perception is no longer associated with NMUPD. Increased risk information may be ineffective at curbing NMUPD for many of those most at risk. In terms of demographic characteristics, research has found some potential relationships between these characteristics and prescription drug use. Prior studies have been inconclusive as to which gender is at a higher risk of NMUPD (Ford, 2009; Young, Glover, & Havens, 2012). While a greater number of studies have found women more prone to NMUPD, perhaps due to their increased access in comparison to men (Simoni-Wastila, Ritter, & Strickler, 2004; Ford, 2009; Sung, Richter, Vaughan, Johnson, & Thom, 2005; Wu, Ringwalt, Mannel i, & Patkar, 2008; Boyd, Young, Grey, & McCabe, 2009; Schepis & Krishnan-Sarin, 2008), other studies have found the reverse, with women less likely to use NMUPD (SAMHSA, 2011b; Kroutil et al., 2006; McCabe, Teter, & Boyd, 2006). Stil others did not find significant gender differences in terms of use (Col ins et al., 2011). The ESPAD (Hibel et al., 2009; Hibel et al., 2012) found a slight difference between adolescent male and female NMUPD in which there were 8% of females reporting using tranquilizers or sedatives without a prescription compared to 5% for males. However, the importance of gender seems to vary from country to country, with no significant gender difference found in some countries and a substantial effect in others (Hibel et at., 2009). Despite the inconclusive research on gender differences in use, clear gender differences do exist for motivation behind drug use and type of drug used. Women are more likely to report self-treatment reasons for using prescription drugs, whereas men are more likely to report sensation-seeking reasons (Romer & Hennessy, 2007; Boyd et al., 2009; Young, Glover, & Havens, 2011; McCabe, Crawford, Boyd, & Teter, 2007). Women are also more likely to use sedatives, whereas men are more likely to use stimulants (McCabe, Teter, & Boyd, 2004). In terms of the source of prescription drugs, women tend to receive prescription drugs for free or steal them from a friend or family member, in contrast to men, who tend to purchase them or acquire them through a Childhoods Today, Volume 10, Issue 1, 2016 physician (Boyd, McCabe, & Teter, 2006; Col ins et al., 2011; Schepis & Krishnan-Sarin, 2009). Little is known as to whether the aforementioned risk factors are specific to one type of NMUPD motivation or the other. Drug use can also vary by race. Whites display higher rates of NMUPD than non- whites (Col ins et al., 2011; Ford, 2009; McCabe et al., 2007; Wu et al., 2008) and are also more likely to report sensation-seeking reasons (Boyd et al., 2009). Viana et al. (2012) found that whites were significantly more at risk than blacks for NMUPD but were not at a significantly elevated risk compared to Hispanic and Asian adolescents. It is also important to note the role of voice and agency in adolescent NMUPD. The sociology of childhood perspective considers the ways in which children have their
own agency and actively participate in their own lives, knowledge, and experiences
(Brady, Lowe, & Lauritzen, 2015; Corsaro, 2014; Mayal , 2002). Although childhood and
adolescence are temporary durations for a person, society sees childhood as inherently
different from adulthood and a permanent part of society, though individuals grow out of
it and new people enter it (Corsaro, 2014). Adults see childhood and adolescence as a
time when children are being prepared to enter society, but sometimes fail to
understand that children are already members of society. As Corsaro (2014) notes,
being active and participating members in a society impacts both children and their
childhoods and, likewise, both culture and society are impacted by children as wel .
Therefore, an adolescent demonstrating agency and contributing to their own lives
through NMUPD is not solely a psychological matter, but is also the result of greater
sociological forces as wel since both society and children reciprocal y influence one
another.

Current Study

Given the problems of adolescent usage, it is important to determine what factors lead to NMUPD. Past research has yet to clearly ascertain whether certain risk factors
are more or less significant for adolescent users with varying motivations. The present
study uses a diverse sample of eleventh grade students to examine whether the effects
of risk factors vary by motivation for using NMUPD. That is, are there different risk
factors for recreational users than for self-treating users?

Data and Methodology

The data used in this study come from the Delaware School Survey, which is administered annual y by the University of Delaware Center for Drug and Health Studies to fifth, eighth, and eleventh grade students in al Delaware public and public-charter schools. This study uses data from eleventh grade (typical y 16-17 year old) students in 2006 and 2008. These years were selected because they were the only surveys to include questions about motivations for using prescription drugs. In both of these years, a census of eleventh grade students was attempted. Some classrooms (fewer than 15 Childhoods Today, Volume 10, Issue 1, 2016 percent) were randomly selected to participate in a different survey, and were excluded
from the sample. Otherwise, classrooms were surveyed in a method designed to survey
all eleventh grade students in Delaware who were present and wil ing to participate. In
2006, 5,728 eleventh grade students were present on the day when their school was
surveyed. Fewer than 2 percent of the students chose not to participate or were asked
not to participate by their parents, resulting in a total sample of 5,636 students. In 2008,
5,891 eleventh grade students were present and fewer than 3 percent chose not to
participate or were asked not to participate by their parents, resulting in a total sample
of 5,757 students. Combined, the two years provide a sample of 11,393 eleventh grade
students, representing approximately 98 percent of students present when the
classrooms were surveyed. Overal , the sample is 51 percent female and 49 percent
male. With regard to race, the sample is 57 percent non-Hispanic white, 26 percent non-
Hispanic black, 8 percent Hispanic, and 9 percent other/mixed.
Dependent Variables

The analyses in this study makes use of three dependent variables: nonmedical prescription drug use, nonmedical self-treatment prescription drug use, and nonmedical recreational prescription drug use. To measure nonmedical prescription drug use in general, several questions were used. First, participants were asked about several general categories of prescription drugs, including 1) "Downers, tranqs, barbs, Xanax to get high;" 2) "Pain kil ers, OxyContin, codine, Percocet, Tylenol III to get high;" 3) "Ritalin, Adderal , Strattera, Cylert or Concerta without a prescription;" and, in 2008 only, 4) "Prescription uppers, diet pil s, etc to get high." They were also asked about several specific drugs, including OxyContin, Codeine, Tylenol with codeine, Percocet, Percodan, Vicodin, Darvon, Darvacet, Endocet, Xanax, Somas, Ritalin, Adderal , Strattera, Albuterol, other asthma medication, or other prescription drug not prescribed. These variables were combined into a single dichotomous measure indicating whether the participant had used prescription drugs in the past year without a prescription (0 = no, 1 = yes). The descriptive statistics for this and other variables are displayed in Table 1. To further refine this into self-treatment and recreational uses, an additional question was asked: "For the times when you have used prescription drugs without a prescription, please indicate how often you used them for each reason listed below." The categories included: to relieve pain; to treat infection, al ergies, or il ness; to have fun or get high; to add muscle, strength, or endurance; to increase concentration; to relieve depression/anxiety; and to lose weight. Responses presented participants with various timeframes, but these are dichotomized for the present study to simply indicate whether they used prescription drugs for the listed reason within the past year. To measure nonmedical self-treatment prescription drug use, the categories for pain relief and treatment of infection, al ergies, and il ness are merged into a single self-treatment Childhoods Today, Volume 10, Issue 1, 2016 category (0 = did not self-treat in past year, 1 = did self-treat). Nonmedical recreational
prescription drug use is measured similarly with the fun/high category (0 = did not use
recreational y in past year, 1 = did use recreational y).
Independent Variables

Five scales are used in the analyses, including sensation-seeking, perceived risk of substance use, peer substance use, parental monitoring, and victimization. Each scale was created using factor extraction, which results in a standardized scale with a mean of zero and a standard deviation of one, with each variable's contribution to the scale being weighted on factor loadings. If a participant did not provide answers to at least half of the questions in any given scale, he/she is considered missing for the entire scale. The sensation-seeking measures are from the Zuckerman (1979) scale and include six indicators of sensation seeking: "I sometimes do crazy things just for fun;" "I like wild parties;" "I like to be around people who party a lot;" "I like to try new things even if they scare me or I know it's something I shouldn't do;" "I get a real kick out of doing things that are a little dangerous;" and "I like to have new or exciting experiences even if they are il egal." Participants were given four possible responses ranging from strongly agree to strongly disagree. The scale had acceptable internal reliability (α = .88) and retained 3.7 Eigenvalues. This scale is coded so that higher values indicate greater levels of self-control. Perceived risk was measured by combining five questions. Participants were asked, "How much do people risk harming themselves (physical y and other ways) when they…" Categories used here include: smoke one or more packs of cigarettes per day; have 5 drinks at a time, once or twice a week; smoke marijuana regularly; inhale glue or aerosols or other inhalants regularly; and use over-the-counter medication to get high. Although none of these directly measures risk relating to prescription drug use, combined these measures are expected to provide an idea of the perceived risk of substance use in general. Responses included: do not know, no risk, slight risk, moderate risk, and great risk. For purposes of scale construction, do not know and no risk are both coded as the lowest category, as both indicate the absence of a perceived risk. The scale had acceptable internal reliability (α = .88) and retained 3.3 Eigenvalues. Peer substance use was measured using the questions: how many of your friends smoke cigarettes, how many of your friends get drunk at least once a week, and how many of your friends smoke marijuana? Responses included none, a few, some, most, and al . As with perceived risk, these do not directly measure prescription drug use, but together indicate general substance use among peers. The scale had acceptable internal reliability (α = .81) and retained 2.2 Eigenvalues. Parental monitoring was measured using the indicators: my parents know where I am when I am not in school and my parents know what I am doing when I am not in school. Both Childhoods Today, Volume 10, Issue 1, 2016 indicators had responses of: never, not often, some of the time, often, and most of the time. Despite containing only two indicators, this scale also had acceptable reliability (α = .80) and retained most of the variance (1.68 Eigenvalues). The final scale, victimization, was measured using 36 dichotomous indicators of differing types of victimization. In a matrix grid, participants were presented with six forms of victimization (verbal abuse, bul ying, threats, shoving/pushing, fights, and fights/threats with weapons) and six categories of perpetrators (parents, siblings, boyfriend/girlfriend, kids in the neighborhood, kids in school, and adults in school). They were asked to mark al combinations that applied to them based on if they have happened to them in the past 30 days. Combined, the scale had acceptable internal reliability (α = .82) and retained 5.5 Eigenvalues. Demographic variables are also used as controls. These include dummy variables for gender (0 = male, 1 = female), and race/ethnicity variables of black,
Hispanic, and other race (white being the reference category).
Analytic Strategy

Three logistic regression models are estimated overal . First, a model predicting past-year NMUPD is used as a baseline model, showing the results that are obtained without distinguishing users by their motivation for using. Second, two models are estimated predicting self-treatment and recreational NMUPD. The findings from these models are then compared to each other and to the baseline model to establish any distinctions that emerge when different uses are considered as separate behaviors. As is common with survey research involving self-administered questionnaires, some data are missing for some cases. This ranges between one percent and eight percent of cases, depending on the variable in question. In order to overcome this limitation, multiple imputation is used. This strategy involves using other variables in the dataset, including those not used in the present analyses, to estimate maximum likelihood derived values for missing data among the independent variables, and doing so over multiple iterations to al ow for some variation. Results for the multiple iterations are then merged together after the regressions are estimated. This strategy is preferable to listwise deletion, which may bias data by excluding people less likely to provide ful response sets, and mean replacement, which may result in zero-biased slopes. Results
General NMUPD

The results for the regression predicting general NMUPD are presented in Table 2. In general, the risk factor variables are al significant predictors of NMUPD. The sensation-seeking scale indicates that as self-control increases, the likelihood of using Childhoods Today, Volume 10, Issue 1, 2016 prescription drugs decreases. Perceived risk of substance use is also significant, with an increase in perceived risk corresponding to a decrease in the odds of NMUPD. Peer use, on the other hand, is a significant predictor of increased prescription drug use. Parental monitoring also behaves as expected in this model, with an increase in monitoring corresponding to a decrease in the odds of NMUPD. The victimization scale,
conversely, indicates that an increase in victimization results in an increase in the
likelihood of using prescription drug use. With respect to the control variables, females
are more likely to use prescription drugs without a prescription, whereas racial/ethnic
minorities were less likely to engage in NMUPD.

NMUPD by Motivation

The results for models predicting prescription drug use by motivation for using are presented in Table 3. Beginning with the self-treatment model, there are several key similarities with the general model. Aside from the lack of significance for perceived risk, the significance of the effects in the self-treatment models are identical or similar to those in the previous model. This diminished effect from perceived risk is understandable given that the perceived risk of substance use may not be considered relevant when weighed against the possible risks of not treating an ailment. The results predicting recreational use provide further dissimilarities to previous models. For many theoretical variables – including sensation-seeking, perceived risk, peer use, parental monitoring, and race – the effects continue to be significant and are also stronger in comparison to either of the previous models. An especial y noteworthy change in this model is the change in direction for victimization's effect, which now corresponds to decreased risk of NMUPD. Thus, victims are less likely to be using non-prescribed prescriptions drugs for recreational purposes, yet more likely to be using them for self-treatment. Another noteworthy difference between the models is their overal ability to explain the likelihood of using prescription drugs. The coefficient of determination is .16
for self-treatment and .37 for recreational use. This suggests that explaining which
students are self-treating is more difficult using these predictors.
Discussion
Nonmedical prescription drug use among adolescents has increased significantly in the past twenty years, and it remains a troubling problem. With increased accessibility and a more accepting society, prescription drugs are being prescribed and used at increasing rates making them more readily available for possible nonmedical use (Compton & Volkow, 2006; Fortuna et al., 2010). Roughly one sixth of students (15%) in grades 9-12 report the nonmedical use of at least one prescription drug within the previous year (Boak et al., 2013). Among adolescents, nonmedical prescription drugs rank behind only marijuana in terms of use prevalence and account for about half of al Childhoods Today, Volume 10, Issue 1, 2016 drug-related emergency-room visits (SAMHSA, 2011; Substance Abuse and Mental Health Services Administration, 2010). More effective prevention strategies for NMUPD requires a more thorough understanding of the factors behind this trend. Although previous research has established a number of risk and protective factors associated with NMUPD, few studies have examined these factors in relation to the differing motivations for NMUPD. This study examined which predictors of NMUPD were associated with either recreational or self-treatment users. Consistent with previous research, perceived risk of substance use, peer substance use, parental monitoring, sensation-seeking, and history of victimization are al found to be significantly associated with NMUPD. Specifical y, perceived risk of substance use and parental monitoring are negatively associated with NMUPD, whereas victimization, sensation-seeking, and peer use are positively associated with NMUPD. When predicting NMUPD by motivational use, one important difference emerged for both recreational and self-treatment users. Perceived risk of substance use is not significantly associated with NMUPD for self-treatment, which represents an important departure from previous research finding it to be strongly associated with NMUPD in general (Twombly & Holtz, 2008; Arria et al., 2008; Col ins et al., 2011; Johnson et al., 2011; Quintero, Peterson, &Young, 2006; Friedman, 2006). This finding has new implications for the effectiveness of drug risk awareness programs, particularly for adolescents who are self-treating. Also noteworthy is the finding that the relationship between victimization and NMUPD differs by motivation. Although victimization is positively associated with NMUPD general y and for those individuals reporting self-treatment as their motivation, it was negatively associated with those individuals using recreational y. This stands in stark contrast to previous studies, which found victimization to be associated with increased NMUPD (Hal , Howard, & McCabe, 2010; Young, Grey, Boyd, & McCabe, 2011; Young et al., 2012). Essential y, these results suggest that previous research could find the opposite relationship among recreational users, and a stronger relationship among self-treatment users. The net result is that examining both types of users together results in a weaker effect due to these opposite effect directions. Thus, for both groups, the importance of victimization is understated when failing to include the interaction between victimization and the motivation for use. It should be noted that the present study is, of course, limited by the data used. Namely, the data used are cross-sectional. Though the models include control variables, the time-order ultimately remains unproven. For example, it is possible that NMUPD might lead to seeking out peers who also use other substances. Longitudinal research would be a valuable next step for future studies in this area. Despite this limitation, several key findings of this study remain noteworthy. For example, perceived risk is not even significant in the model predicting self-treatment, which is not limited by cross-sectional data because the lack of an empirical link is noteworthy regardless of Childhoods Today, Volume 10, Issue 1, 2016 time-order. This particular finding makes sense, too, given that conditions leading to self-treatment are dangerous themselves, and thus the dangers of the drug may seem less important. Another example of a finding that particularly withstands cross-sectional limitations is the opposing directions from victimization, which corresponds to an increased risk for self-treatment and a decreased risk for recreational use. This may be particularly useful for practitioners, as it clearly delineates the type of substance use for which victims are at risk. It is also important to consider the agency of the child with regards to NMUPD. As they are social actors contributing to their own lives as wel as having an impact on society, their voices are surprisingly left out of research. Society looks at children and creates policies and programs to impact issues, such as NMUPD, from an adult-oriented view, thus stifling the voices of children (Corsaro, 2014). According to Mayal (2002), in order to develop effective policies and programs for adolescents, experiences and knowledge needs to be understood from the point of view of the child. Although the present findings may not directly indicate the thought process of adolescents engaging in NMUPD, the correlated and predictors help us to better understand the context of these decisions, particularly in light of the important distinction between a child choosing to use prescriptions drugs recreational y rather than choosing to use them medical y. This, too, may be useful to practitioners. The approach one takes to discourage a child from choosing to use drugs for recreation (e.g., highlighting the dangers of using drugs outside of their intended purpose) should be quite different from the approach to discourage a child from choosing to self-treat (e.g., encouraging them to seek assistance from medical professionals). Ultimately, these findings also send a clear message that the motivation for use should not be ignored when col ecting data or performing analyses in future research. Groups and individuals who council or otherwise treat/help adolescents with NMUPD issues (or at risk for such use) would also do wel to note the importance of distinguishing between the types of motivations. These findings indicate that, though self-treating and recreational users share some common characteristics in comparison to non-users, they also have significant differences between each other as wel .
Childhoods Today, Volume 10, Issue 1, 2016 Notes
The data used in this research were col ected by the University of Delaware Center for
Drug and Health Studies as part of a study supported by the Delaware Health Fund and
by the Division of Substance Abuse and Mental Health, Delaware Health and Social
Services. The views and conclusions expressed in this manuscript are those of the
authors and do not necessarily represent those of the University of Delaware or the
sponsoring agencies.

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Social Learning Theory and Nonmedical Prescription Drug Use among Adolescents. Sociological Spectrum, 28(3), 299-316. Ford, J. A. (2009). Nonmedical Prescription Drug Use Among Adolescents. Youth & Society, 40(3), 336-352. Fortuna, R., Robbins, B., Caiola, E., Joynt, M., & Halterman, J. (2010). Prescribing of control ed medications to adolescents and young adults in the United States. Pediatrics, 126(6), 1108-1116. Friedman, R. A. (2006). The changing face of teenage drug abuse – the trend toward prescription drugs. New England Journal of Medicine, 354(14), 1448–1450. Gunter, W. D., Farley, E. J., & O'Connel , D. J. (2013). Self-treatment vs. recreational motives: Differentiating nonmedical use of prescription drugs among youth. International Journal of Child, Youth and Family Studies, 4, 245–258. Hal , M. T., Howard, M. O., & McCabe, S. E. (2010). Prescription drug misuse among antisocial youths. Journal of Studies on Alcohol and Drugs, 71(6), 917-924. Hibel , B., Guttormsson, U., Ahlström, S., Balakireva, O., Bjarnasonn, T., Kokkevi, A., & Kraus, L. (2009). The 2007 ESPAD report: Substance use among students in 35 European countries. European School Survey Project on Alcohol and Other Drugs (ESPAD), The Swedish Council for Information on Alcohol and other Drugs (CAN), The European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), Council of Europe Co-operation Group to Combat Drug Abuse and Il icit Trafficking in Drugs (Pompidou Group) Hibel , B., Guttormsson, U., Ahlström, S., Balakireva, O., Bjarnasonn, T., Kokkevi, A., & Kraus, L. (2012). The 2011 ESPAD report: Substance use among students in 36 European countries. European School Survey Project on Alcohol and Other Drugs (ESPAD), The Swedish Council for Information on Alcohol and other Drugs (CAN), The European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), Council of Europe Co-operation Group to Combat Drug Abuse and Il icit Trafficking in Drugs (Pompidou Group) Childhoods Today, Volume 10, Issue 1, 2016 Johnston, L. D., O'Mal ey, P. M., Bachman, J. G., & Schulenberg, J. E. (December 14, 2011). Marijuana use continues to rise among U.S. teens, while alcohol use hits historic lows. University of Michigan News Service: Ann Arbor, MI. Retrieved from: http://www.monitoringthefuture.org/pressreleases/11drugpr.pdf Kroutil, L. A., Van Brunt, D. L., Herman-Stahl, M., Hel er, D. C., Bray, R. M., & Penne, M. A. (2006). Nonmedical use of prescription stimulants in the United States. Drug and Alcohol Dependence, 84(2), 135-143. Mayal , B. (2002). Towards a sociology for childhood: Thinking from children's lives. Buckingham: Open University Press. McCabe, S. E., Cranford, J. A., Boyd, C. J., & Teter, C. J. (2007). Motives, diversion and routes of administration associated with nonmedical use of prescription opioids. Addictive behaviors, 32(3), 562-575. McCabe, S. E., Teter, C. J., & Boyd, C. J. (2006). Medical use, il icit use, and diversion of abusable prescription drugs. Journal of American Col ege Health, 54(5), 269-278. McCabe, S. E., Teter, C. J., & Boyd, C. J. (2004). The use, misuse and diversion of prescription stimulants among middle and high school students. Substance use & misuse, 39(7), 1095-1116. McCauley, J. L., Danielson, C. K., Amstadter, A. B., Ruggiero, K. J., Resnick, H. S., Hanson, R. F., & Kilpatrick, D. G. (2010). The role of traumatic event history in non-medical use of prescription drugs among a national y representative sample of US adolescents. Journal of Child Psychology and Psychiatry, 51(1), 84-93. Partnership Attitude Tracking Study. (2013). Teens and Parents, 2012. Retrieved September 9, 2013 from http://www.drugfree.org/wp-content/uploads/2013/04/PATS-2012-FULL-REPORT2.pdf. Quintero, G., Peterson, J., & Young, B. (2006). An exploratory study of socio-cultural factors contributing to prescription drug misuse among col ege students. Journal of Drug Issues, 36(4), 903-932. Romer, D., & Hennessy, M. (2007). A biosocial-affect model of adolescent sensation seeking: The role of affect evaluation and peer-group influence in adolescent drug use. Prevention Science, 8(2), 89-101. Childhoods Today, Volume 10, Issue 1, 2016 Schepis, T. S.,& Krishnan-Sarin, S. (2008). Characterizing adolescent prescription misusers: a population-based study. J Am Acad Child Adolesc Psychiatry, 47(7), 745-754. Schepis, T.S. and Krishnan-Sarin, S. (2009). Sources of Prescriptions for Misuse by Adolescents: Differences in Sex, Ethnicity, and Severity of Misuse in a Population-Based Study. Journal of the American Academy of Child and Adolescent Psychiatry, 48(8): 828-836. Schinke, S. P., Fang, L., & Cole, K. C. (2008). Substance use among early adolescent girls: risk and protective factors. J Adolesc Health, 43(2), 191-194. Simoni-Wastila, L., Ritter, G., & Strickler, G. (2004). Gender and other factors associated with the nonmedical use of abusable prescription drugs. Substance use & Misuse, 39(1), 1-23. Substance Abuse and Mental Health Services Administration. (2011a). Drug Abuse Warning Network, 2008: National Estimates of Drug-Related Emergency Department Visits. Retrieved from: http://www.samhsa.gov/data/2k11/DAWN/ED/DAWN2k8ED.pdf Substance Abuse and Mental Health Services Administration. (2011b). Results from the 2010 National Survey on Drug Use and Health: Summary of National Findings NSDUH Series H-41, HHS Publication No. (SMA) 11-4658. Rockvil e, MD: Substance Abuse and Mental Health Services Administration. Sung, H. E., Richter, L., Vaughan, R., Johnson, P. B., & Thom, B. (2005). Nonmedical use of prescription opioids among teenagers in the United States: trends and correlates. J Adolesc Health, 37(1), 44-51. Twombly, E. C., & Holtz, K. D. (2008). Teens and the misuse of prescription drugs: evidence-based recommendations to curb a growing societal problem. J Prim Prev, 29(6), 503-516. Viana, A. G., Trent, L., Tul , M. T., Heiden, L., Damon, J. D., Hight, T. L., & Young, J. (2012). Non-medical use of prescription drugs among mississippi youth: Constitutional, psychological, and family factors. Addictive Behaviors, 37(12), 1382. Wu, L. T., Ringwalt, C. L., Mannel i, P., & Patkar, A. A. (2008). Prescription pain reliever abuse and dependence among adolescents: a national y representative study. J Am Acad Child Adolesc Psychiatry, 47(9), 1020-1029. Childhoods Today, Volume 10, Issue 1, 2016 Young, A. M., Glover, N., & Havens, J. R. (2012). Nonmedical use of prescription medications among adolescents in the united states: A systematic review. Journal of Adolescent Health, 51(1), 6-17. Young, A., Grey, M., Boyd, C. J., & McCabe, S. E. (2011). Adolescent sexual assault and the medical and nonmedical use of prescription medication. Journal of Addictions Nursing, 22(1-2), 25-31. Young, A., McCabe, S. E., PhD., Cranford, J. A., PhD., Ross-Durow, P., & Boyd, C. J., PhD. (2012). Nonmedical use of prescription opioids among adolescents: Subtypes based on motivation for use. Journal of Addictive Diseases, 31(4), 332. Zuckerman, M. (1979). Sensation Seeking: Beyond Optimal Level of Arousal. Halsted Zuckerman, M. (1994). Behavioral Expressions and Biosocial Bases of Sensation Seeking. New York: Cambridge University Press. Childhoods Today, Volume 10, Issue 1, 2016 Table 1: Descriptive Statistics NMUPD Self-Treatment NMUPD Recreational Use Sensation-Seeking Dangerous Things Exciting Things Parental Monitoring Other Race/Ethnicity * To conserve space, the descriptive statistics and factor loadings for the 36 indicators that make up victimization are not displayed. They are available from the authors by request.   Childhoods Today, Volume 10, Issue 1, 2016 Table 2: Logit Regressions Predicting NMUPD Use   Sensation-Seeking Control Parental Monitoring Other Race/Ethnicity * p < .05 ** p < .01   Childhoods Today, Volume 10, Issue 1, 2016 Table 3: Logit Regressions Predicting NMUPD Use by Motivation   Non-prescribed for Non-prescribed for recreational use   Sensation-Seeking Parental Monitoring Other Race/Ethnicity

Source: http://childhoodstoday.group.shef.ac.uk/download.php?id=86

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