Substance Use & Misuse, 49:842–851, 2014 C 2014 Informa Healthcare USA, Inc. Copyright  ISSN: 1082-6084 print / 1532-2491 online DOI: 10.3109/10826084.2014.880723

ORIGINAL ARTICLE

Prescription Drug Misuse and Gender Jason A. Ford, Amy Reckdenwald and Briana Marquardt University of Central Florida, Orlando, Florida, USA and Mental Health Services Administration, 2010). Unintentional drug overdose deaths in the United States rose by 120% from 1999 to 2006, with prescription drugs being a major contributor (Toblin, Paulozzi, Logan, Hall, & Kaplan, 2010). Consequences of prescription drug misuse are not always limited to users, as there was a threefold increase in neonatal abstinence syndrome, a drug withdrawal syndrome in newborns following birth, due to the use of prescription opioids, from 2000 to 2009 (Patrick, Schumacher, Benneyworth, & Krans, 2012). Given the dramatic increase in prescription drug misuse and related negative consequences, considerable research has focused on this topic in recent years. This research has examined demographic characteristics of users (Arkes & Iguchi, 2008; Ford & Rivera, 2008; Harrell & Broman, 2009; Simoni-Wastila & Strickler, 2004; Wu, Pilowsky, & Patkar, 2008) and other risk factors for misuse (Ford & Arrastia, 2008; Herman-Stahl, Krebs, Kroutil, & Heller, 2006; Kroutil et al., 2006; SimoniWastila & Strickler, 2004; Wu et al., 2008). In addition, researchers have studied motives for misuse (McCabe, Cranford, Boyd, & Teter, 2007; Teter, McCabe, LaGrange, Cranford, & Boyd, 2006), sources of diversion (Cicero, Shores, Paradis, & Ellis, 2008; Ford & Lacerenza, 2011; Inciardi, Surrat, Kurtz, & Cicero, 2007; McCabe & Boyd, 2005; McCabe et al., 2007), and routes of administration (McCabe et al., 2007; Teter et al., 2006). Research has also examined use with other substances (McCabe, Boyd, & Teter, 2009; McCabe, Cranford, Morales, & Young, 2006) and negative outcomes associated with prescription drug misuse (Ford, 2008a; Ford & Lacerenza, 2011; Huang et al., 2006; McCabe et al., 2009; McCabe & Teter, 2007; McCabe, Cranford, & West, 2008). Finally, there is relatively little research testing theoretical explanations for prescription drug misuse (Ford, 2009; Ford & Schroeder, 2009; Ford, 2008b; Higgins et al., 2009). In the extant literature, an interesting finding has emerged that deserves additional research attention. A number of studies that focus on adolescent populations have found that females are at an increased risk for

In recent years, prescription drug misuse has become a serious public health issue. A number of studies in this area have identified females to be at an increased risk for prescription drug misuse during adolescence. Guided by Agnew’s general strain theory, the current research examined the relationship between prescription drug misuse and gender during adolescence. We used data from the 2010 National Survey on Drug Use and Health, a sample representative of the noninstitutionalized population of the United States. Logistic regression models were estimated to examine the relationship between gender, prescription drug misuse, strain, and depression. The findings indicated that females were at an increased for prescription drug misuse. We also found support for general strain theory, as strain and depression were significantly related to prescription drug misuse. In addition, we found evidence that strain was gendered in that elements of general strain theory accounted for the relationship between prescription drug misuse and gender. Keywords gender, prescription drug misuse, general strain theory, depression

INTRODUCTION

Prescription drug misuse is widely recognized as a serious public health issue. In 2010, seven million persons reported past month prescription drug misuse (Substance Abuse and Mental Health Services Administration, 2011). Initiation rates for misuse of prescription pain relievers alone were greater than any drug with the exception of marijuana (Substance Abuse and Mental Health Services Administration, 2011). When misused, the consequences of prescription drugs can be quite severe. Between 2002 and 2010, the number of people undergoing treatment for prescription pain reliever abuse or dependence doubled (Substance Abuse and Mental Health Services Administration, 2011). Nearly half of the 4.6 million drug-related Emergency Department visits in 2009 were attributed to negative reactions to prescription drugs (Substance Abuse

Address correspondence to Dr Jason A. Ford, PhD, University of Central Florida, Orlando, Florida, USA; E-mail: [email protected].

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prescription drug misuse (Boyd, McCabe, & Teter, 2006a; Ford, 2009; Schepis & Krishnan-Sarin, 2008; SimoniWastila & Strickler, 2004; Sung, Richter, Vaughan, Johnson, & Thom, 2005; Wu et al., 2008). This is interesting as adolescent females generally have lower rates of delinquency and substance use compared to males (see Kruttschnitt, 2013). We address this important gap in the research by drawing on Agnew’s general strain theory (1992) to examine factors that may account for the relationship between gender and prescription drug misuse. General Strain Theory

Agnew broadens the classic sociological notion of strain by conceptualizing strain to account for a variety of strains, and also how individuals cognitively, emotionally, and behaviorally cope with strain (Agnew, 1992). According to Agnew, the primary source of strain is negative relations with others, in which individuals are not treated as they would like to be treated. Agnew theorizes that strain can be produced from a variety of relationships with others, including relations that prevent or threaten to prevent one from achieving desired goals (e.g., economic success, status, academic success), relations that remove or threaten to remove something of value (e.g., death of a loved one, break up), and relations that introduce or threaten to introduce negatively valued stimuli (e.g., abuse). Agnew also argues that negative relationships with others produce negative affective states (e.g., anger, fear, disappointment, depression). To lessen the perceived strain caused from these negative emotions, individuals will engage in a variety of coping strategies, both criminal and noncriminal. He asserts that criminal behavior is the most likely outcome when anger is the resulting emotional state; an emotion that typically occurs when one externalizes the blame for the strain experienced. Though anger is an important emotion, Agnew (2006) states that other emotions are essential in explaining other avenues of coping, such as the relationship between depression and drug use. Since its conception, general strain theory has emerged into a leading social psychological theory (Agnew, 1992, 2001, 2006) with a large body of literature generally supporting its ability to explain crime, both violent and property, and drug use (Agnew, Brezina, Wright, & Cullen, 2002; Aseltine Jr., Gore, & Gordon, 2000; Baron, 2004; Broidy, 2001; Drapela, 2006; Ford & Schroeder, 2009; Mazerolle, Burton, Cullen, Evans, & Payne, 2000; Mazerolle & Piquero, 1998; Paternoster & Mazerolle 1994; Piquero & Sealock, 2000). Gender and Strain

Though originally formulated as a general theory of crime (gender-neutral), Broidy and Agnew (1997) advance general strain theory in an effort to understand gender differences in criminality. Under this approach, the overall general causal process of experiencing strain is theorized to be similar across gender; however, the context of the strain is posited to be different for males and females.

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Classical strain theorists tend to explain higher levels of male crime as directly related to the amount of strain experienced, suggesting that females experience less strain and as a result are involved in less crime. Nevertheless, there is a large body of literature indicating that females experience the same or even more strain than males (Kohn & Milrose, 1993; Mirowsky & Ross, 1995; Turner, Wheaton, & Lloyd, 1995). Taking this research into consideration, Broidy and Agnew (1997) offer a perspective explaining the gender gap in crime not by the amount of strain experienced but by the types of strain, the reaction to strain, and the factors that influence the use of coping strategies to alleviate strain. Drawing on prior literature (Campbell, 1993; Cernkovich & Giordano, 1979; Gilligan, 1982, Turner et al., 1995; Wethington, McLeod, & Kessler, 1987), Broidy and Agnew argue that males experience different types of strains than females and reason that certain types of strain may be more likely to result in crime than other types based on the emotional response elicited. This body of research indicates that males are more focused on material and extrinsic success and distributive justice, and as a result, are more likely to experience financial and work-related problems. Other problems include peer-related issues, such as conflict, jealousy, and competition, as well criminal victimization. According to Broidy and Agnew, these types of strains are more conducive to using aggression and violence. Females, on the other hand, are more focused on the establishment and maintenance of close relationships, finding the meaning/purpose of life, and procedural justice. As a result, they tend to experience strains associated with interpersonal relationships and work and family roles. Also, females are more likely to experience gender-based discrimination and certain criminal victimizations, such as sexual assault, rape, and violence within the home. Broidy and Agnew note that these types of strain are more conducive to self-destructive behaviors, such as drug use, or behaviors which allow one to avoid a situation or stressor. Furthermore, Broidy and Agnew suggest that the emotional responses to strain are gendered. Though females are more likely than males to respond to strain with depression (Mirowsky & Ross, 1995; Conger, Lorenz, Elder, Jr., Simons, Ge, 1993; Turner et al., 1995), it does not appear that males are angrier than females. Interestingly, both males and females are likely to respond to strain with anger, with some research even indicating that females are actually more likely to respond with this emotion (Mirowsky & Ross, 1995); however, Broidy and Agnew note that the accompanying emotions are different across gender. In addition to anger, females tend to also respond with internalized emotions such as fear, depression, anxiety, guilt, and shame, reasoned to be less conducive to crime; whereas males, typically respond with externalized emotions such as moral outrage (Campbell, 1993). Females have a tendency to blame themselves and worry their anger will hurt their close relationships; thus, females’ anger typically results in self-directed forms of

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deviance. Recent research on eating disorders supports this idea (Sharp, Terling-Watt, Atkins, Gilliam, & Sanders, 2001). On the other hand, males are quicker to externalize the blame to others and are less concerned about hurting the relationships they have with others. Their anger is typically expressed as anger towards others, which is more conducive to crime. Moreover, Broidy and Agnew suggest that factors that condition the use of coping strategies for strain vary across gender. Following previous research (Wethington et al., 1987) they argue that females lack a sense of mastery and self-esteem, which they reason makes them less likely to employ effective coping strategies and more likely to use self-destructive behaviors to deal with strain. Furthermore, females’ concern over relationships may cause them to avoid behaviors that may ruin these connections. Males, on the other hand, are more likely than females to use aggression and violence when they feel pressure or strain because they have lower self-control, less social support, and greater criminal opportunities (Gottfredson & Hirschi, 1990; Stark, Spirito, Williams, & Guevremont, 1989). Support for gendered experiences of strain is abundant (Agnew & Brezina, 1997; Baron, 2007; Broidy, 2001; Broidy & Agnew, 1997; Eitle, 2002; Hay, 2003; Jang, 2007; Jennings, Piquero, Gover, & Perez, 2009; Mazerolle, 1998; Sigfusdottir, Farkas, & Silver, 2004), with research indicating that females are more likely to experience a range of other emotions in addition to/besides anger in response to strain, such as depression and/or anxiety (Jang, 2007; Sigfusdottir et al., 2004), guilt (Hay, 2003), or other non-angry emotions (Broidy, 2001). As such, we reason that these reactions may explain why females are less likely to respond to strain with aggression and/or crime, but instead respond with other self-destructive behaviors like prescription drug misuse. The Current Study

The current research examines the relationship between gender and prescription drug misuse and is guided by general strain theory. To our knowledge, only a few studies show support for general strain theory in predicting prescription drug misuse (Ford & Schroeder, 2009; Schroeder & Ford, 2012). Consistent with the hypotheses outlined by Broidy and Agnew and the supporting research, we believe that females are more likely to respond to strain with depression. This is important as previous research with general strain theory links the negative emotion of depression to substance use rather than offending (Drapela, 2006; Ford & Schroeder, 2009; Stogner & Gibson, 2011). In addition, research on prescription drug misuse indicates that adolescents who are depressed are at an increased risk for prescription drug misuse (Ford & Hill, 2012; Ford & Schroeder, 2009, Wu et al., 2008). Thus, we believe females are at an increased risk for prescription drug misuse due to the fact that they are more likely to become depressed when they experience strain. We believe that the relationship between gender and prescription drug misuse is different from other forms of

substance use in a number of important ways. First, prescription drugs are more available, use is more acceptable, they are perceived to be safer, and there is less likelihood of sanctions compared to other illicit drugs. All of which make prescription drug misuse a less risky or deviant form of substance use. This is relevant as prior research shows that females are less likely to be involved in serious forms of deviance (see Kruttschnitt, 2013). Second, research shows that females are more likely to be prescribed certain types of prescription drugs (Isaacson, Hooper, Alford, Parra, 2005; Roe, McNamara, & Motheral, 2002; SimoniWastila, 2000) and to list their own prescription to be a source of diversion (Green, Grimes Serrano, Licari, Budman, & Butler, 2009). This is important as history of prescriptions has been shown to be a risk factor for prescription drug misuse (Boyd et al. 2006a; McCabe, Teter, & Boyd, 2005; Simoni-Wastila, 2000). We believe these two reasons are consistent with the research on doing crime or “doing gender” as it applies to substance use (Measham, 2002; Messerschmidt, 2000). The notion of “doing gender” is important, in that, substance use can be a mechanism to act out the culturally idealized notion of gender. METHOD Data

The data for the current study are the 2010 National Survey on Drug Use and Health (NSDUH), an ongoing study sponsored by the U.S. Substance Abuse and Mental Health Services Administration that dates back to the 1970s. For the 2010 NSDUH a total sample of 68,487 persons aged 12 and older was generated using a statebased sampling plan, including all 50 states and Washington, D.C. The sample was designed to select roughly 3,600 respondents from each of the 8 largest states in the country and 900 respondents from the 42 remaining states and the District of Columbia. The states were then geographically divided into equally sized sampling regions. These state sampling regions were then broken down into smaller regions based on census tracts, which then served as the primary sampling unit with a minimum of 150 dwelling units in urban areas or 100 dwelling units in rural areas. Dwellings, or households, were then selected from the primary sampling units, and residents aged 12 and older were interviewed. The sampling design of the NSDUH produced a sample that was generalizable to the non-institutionalized population of the United States. Due to a subsampling step used to control the risk of disclosing the identity of any respondent, only 57,873 records appear in the public use data file (Substance Abuse and Mental Health Services Administration 2010). Because the focus of the current study is adolescent prescription drug misuse we restrict data analysis to respondents aged 12 to 17 (n = 18,614). The NSDUH implemented many strategies to improve the validity of the survey. Given that several survey items cover sensitive or illegal behaviors, respondent privacy was enhanced by the interview procedures. Respondents were surveyed in the privacy of their own homes, and a

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combination of computer-assisted personal interviewing (CAPI) and audio computer-assisted self-interviewing (ACASI) were used to collect the data (Substance Abuse and Mental Health Services Administration, 2011). This data collection strategy allowed survey respondents to enter responses directly into a computer, providing respondents with a highly private and confidential means of responding to questions, thereby increasing the level of honest reporting of illicit drug use and other sensitive behaviors (Aquilino, Wright, & Supple, 2000; Newman et al., 2002; Perlis, Des Jarlais, Friedman, Arasteh, & Turner, 2004). Measures

The dependent variable for the current research was prescription drug misuse in the past year, coded 0 = No, 1 = Yes. In the NSDUH, prescription drug misuse was defined as the use of “drugs that people are supposed to take only if they have a prescription from a doctor.” Respondents were instructed that the research was only interested in their use of prescription drugs if “the drug was not prescribed for you, or you took the drug only for the feeling or experience it caused.” Prescription drug misuse included use of any of the following: pain relievers, tranquilizers, stimulants, or sedatives. To measure strain, we created an index of negative life experiences. This index included the following seven survey items which were all coded 0 = No Strain, 1 = Strain. First, respondents were asked how they felt about going to school during the past 12 months (1 = hated going to school). Second, respondents were asked how often, in the past twelve months, their teachers let them know they did a good job (1 = never). Third, students were asked about their grades for the last semester (1 = D average or less). Fourth, respondents were also asked how often, in the past twelve months, their parents let them know they did a good job (1 = never). Fifth, respondents were asked how often, during past 12 months, their parents told them they were proud of something they had done (1 = never). Sixth, respondents were asked how many times, in the past 12 months, they argued or had fights with at least one parent (1 = ten or more times). Finally, respondents were asked about their overall health (1 = poor). These seven items were summed to create an index with a possible score ranging from 0 to 7. We used a measure of depression to account for negative affect. A respondent was classified as having a major depressive episode in the past year (coded 0 = No and 1 = Yes) if they reported experiencing at least five of the following: felt sad, empty, or depressed most of the day or discouraged; lost interest or pleasure in most things; experience changes in appetite or weight; sleep problems; other noticed you were restless or lethargic; felt tired or low energy nearly every day; felt worthless nearly every day; inability to concentrate or make decisions; any thoughts or plans of suicide. In our analysis, we included controls for demographic characteristics and the use of other illicit drugs. Our main variable of interest gender was coded 0 = Male, 1 =

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Female. The age range for respondents in the sample was 12 to 17. We also included a dichotomous control for race/ethnicity, coded 0 = Non-white, 1 = White. A measure of total family income was coded 0 = less than $50,000, 1 = $50,000 or more. Income was coded in this manner to closely approximate a split between families living above and below the median household income in the United States of $49,445 in 2010 (DeNavas-Walt, Proctor, & Smith, 2011). Finally, a measure of other illicit drug use in the past year was coded 0 = No, 1 = Yes and includes the use of cocaine, crack, heroin, hallucinogens, LSD, PCP, ecstasy, inhalants, and methamphetamines. Other illicit drug use was included as a control due to its strong correlation to prescription drug misuse (Ford, 2009; Harrell & Broman, 2009; Herman-Stahl et al., 2006; Kroutil et al., 2006; Simoni-Wastila & Strickler, 2004). Analytic Strategy

Analyses were conducted in several stages. We estimated several logistic regression models with prescription drug misuse as the dependent variable. In the first, or baseline model we included gender and several controls for prescription drug misuse. The goal was to determine if female respondents were at an increased risk for prescription drug misuse. In the second model we added our measure of strain to the baseline model. For the third model we added our measure of depression to the baseline model. In the fourth, or complete, model we added both strain and depression to the baseline model. We expect both strain and depression to be significantly associated with prescription drug misuse, and we also expect that strain and depression will account for the relationship between gender and prescription drug misuse. We were also interested in the indirect connection between strain and prescription drug misuse. We estimated a logistic regression model to determine if strain was significantly related to our measure of negative affect, depression. We estimated this model again for only respondents who had reported at least one source of strain. We did this to determine if “strained” females were at an increased risk for depression compared to “strained” males. In order to take into account the complex multistage sampling design of the NSDUH, analyses were conducted using the SVYSET and SVY commands in STATA. These commands allowed STATA to consider survey design effects, including stratification and weight variables and the primary sampling unit, when estimating test statistics. RESULTS

Sample characteristics for the 17,619 respondents that were included in the analysis are shown in Table 1. The prevalence of prescription drug misuse in the past year was 7.2%. The sample was 49% female with an average age of 14.59 years. With regard to the controls 59% of the sample was white, 48% reported a total family income of $50,000 or greater and 6.5% reported other illicit drug use in the past year. The prevalence of reporting a major

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TABLE 1. Sample characteristics (N = 17,619)

Female Age White Income > $50,000 Prescription drug misuse Other drug use Depression Strain

Range

Mean/ proportion

Standard deviation

0.1 12–17 0.1 0.1 0.1 0.1 0.1 0–7

0.486 14.587 0.591 0.480 0.072 0.065 0.082 0.441

0.500 1.704 0.491 0.500 0.261 0.245 0.274 0.786

depressive episode in the past year was 8.2%. Finally, the mean score on our index of strain was .441. In greater detail, roughly 68% of the sample reported no strain, 24% reported only one strain, 5% reported two strains, and 3% reported three or more strains. Prescription Drug Misuse

Statistics for the regression analysis with prescription drug misuse as the dependent variable are shown in Table 2. In the baseline model, gender was significantly related to prescription drug misuse. Female respondents were at an increased risk (OR = 1.294) for prescription drug misuse compared to males. We initially thought the relationship between gender and prescription drug misuse may be due to a specific class of prescription drugs TABLE 2. Impact of gender, strain, and depression on prescription drug misuse

Female

Age

White

Income

Other drug use Strain

Depression

Baseline

Strain

Depression

Complete

.258∗∗ (.071) [1.294] .275∗∗∗ (.026) [1.317] .163 (.096) [1.177] .333∗∗∗ (.085) [1.396] 2.462∗∗∗ (.102) [11.734]

.175∗ (.070) [1.191] .284∗∗∗ (.029) [1.329] .166 (.094) [1.181] .336∗∗∗ (.083) [1.400] 2.353∗∗∗ (.106) [10.517] .343∗∗∗ (.048) [1.409] —

.188∗ (.074) [1.207] .280∗∗∗ (.028) [1.323] .150 (.098) [1.161] .323∗∗∗ (.085) [1.381] 2.368∗∗∗ (.102) [10.680] —

.114 (.075) [1.121] .291∗∗∗ (.030) [1.338] .161 (.095) [1.174] .330∗∗∗ (.085) [1.391] 2.287∗∗∗ (.106) [9.848] 0.295∗∗∗ (.049) [1.343] 0.527∗∗∗ (.095) [1.694]

.604∗∗∗ (.093) [1.831]

Note. Logistic regression models estimated with unstandardized regression coefficient, (linearized standard error), and [OR] shown in the table. ∗ p < .05, ∗∗ p < .01, ∗∗∗ p < .001.

so we estimated this model separately for each class (results not shown in table). These findings indicated that females were at an increased risk for misuse of pain relievers (OR = 1.194), stimulants (OR = 1.633), and tranquilizers (OR = 1.365). Consistent with other research focusing on prescription drug misuse age, income, and other drug use were all significantly related to prescription drug misuse in the expected direction. In the second regression model shown in Table 2, we added our measure of strain to the baseline model. The findings indicated that strain was significantly correlated to prescription drug misuse. Respondents, who reported greater strain, or more negative life events, were at an increased risk for prescription drug misuse (OR = 1.409). While the unstandardized regression coefficient for female was reduced by 32% once strain was included in the model, it was still significantly related to prescription drug misuse (OR = 1.191). Based on the steps necessary to test statistical mediation outlined by Baron and Kenny (1986), this result suggests that strain partially mediated the relationship between gender and prescription drug misuse. In the third regression model, also shown in Table 2, we added our measure of depression to the baseline model. Depression was significantly related to prescription drug misuse, as the risk for prescription drug misuse was increased (OR = 1.831) for respondents who had reported a major depressive episode. The inclusion of depression in the model reduced the unstandardized regression coefficient for gender by 27%, but the coefficient remained significant (OR = 1.207). As with strain, depression partially mediated the relationship between gender and prescription drug misuse. In the complete model, also shown in Table 2, we added both strain and depression to the baseline model. It appears that the inclusion of both of these measures accounted for the relationship between gender and prescription drug misuse. Specifically, the unstandardized regression coefficient for gender was reduced by 56% and became non-significant. Furthermore, consistent with general strain theory, respondents who report increased levels of strain (OR = 1.343) or depression (OR = 1.694) were at an increased risk for prescription drug misuse. Similar to the baseline model, age, income and other drug use were all significantly correlated to prescription drug misuse in the expected direction. Depression

The final step in our analysis was to examine the connection between strain and the negative affective state of depression, with results shown in Table 3. Consistent with general strain theory, there was a significant relationship between strain and depression. Respondents who reported higher levels of strain were at an increased risk for depression (OR = 1.830). It is also important to note that gender, age, and race were all significant correlates of depression. We were also interested in the gendered response to strain and whether “strained” females were more likely to be depressed than “strained” males. In the second regression model shown in Table 3, estimated only for respondents

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TABLE 3. Impact of gender and strain on depression All respondents Female

Age

White

Income

Strain

1.156∗∗∗ (.074) [3.177] 0.194∗∗∗ (.025) [1.214] 0.230∗ (.092) [1.220] 0.131 (.078) [1.140] 0.605∗∗∗ (.034) [1.830]

Strained respondents only 1.030∗∗∗ (.102) [2.800] 0.207∗∗∗ (.032) [1.231] 0.301∗ (.134) [1.352] 0.038 (.104) [1.039] —

Note. Logistic regression models estimated with unstandardized regression coefficient, (linearized standard error), and [odds ratio] shown in the Table. ∗ p < .05, ∗∗ p < .01, ∗∗∗ p < .001.

who reported one or more strain, gender was significantly related to depression. In fact, the risk of reporting a major depressive episode was increased nearly three times (OR = 2.800) for females. DISCUSSION

In recent years, prescription drug misuse has increased dramatically among adolescents and young adults. This increase in prevalence has been followed by an increase in negative outcomes associated with prescription drug misuse, namely trips to emergency departments and deaths. Prescription drug misuse is now a serious public health issue that has generated much research attention. Many epidemiological based studies have identified demographic characteristics of users and other risk factors for use. An interesting finding in this literature, that has largely been ignored, is that female adolescents are at an increased risk for prescription drug misuse compared to males. While some research has examined gender as a risk factor for prescription drug misuse (Benotsch et al., 2013; Havens, Young, & Havens, 2011; Kelly & Parsons, 2007; McCabe, Boyd, & Teter, 2001) or examined gender-specific risk factors for misuse (Back, Payne, Simspon, & Brady, 2010; Tetrault et al., 2008), very little research has provided a theoretically grounded explanation for gender differences in misuse. The goal of the current research was to fill this important gap in the literature by examining the relationship between prescription drug misuse and gender. Our analysis was guided by Agnew’s (1992) general strain theory, which views depression as a likely negative affective state produced by strain for females. This is important as there is a strong connection between depression and pre-

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scription drug misuse. The findings of the current research echoed those of previous research, identifying females as being at an increased risk for prescription drug misuse. Our baseline logistic regression model indicated that the risk of prescription drug misuse increased roughly 29% for females. While strain and depression separately did not account for the relationship between prescription drug misuse and gender, when both variables were added to the baseline regression model there was no longer a significant relationship between prescription drug misuse and gender. This indicated that adolescent females were at an increased risk for prescription drug misuse due to strain and depression. The links between gender, strain, depression, and prescription drug misuse found in the current research were supportive of the previous literature. The work of Broidy and Agnew (1997) identified that females were more likely to experience strain related to interpersonal relationships and our measure of strain included several items related to interpersonal relationships. This is important as female adolescents place a higher value on these types of relationships than males (Giordano & Cernkovich, 1997), making difficulties in these types of relationships a greater source of strain for females. In addition, previous research has also indicated that females were at an increased risk for depression (Bhatia & Bhatia, 2007; Ustun, 2000). This may be the case because females are exposed to more risk factors for depression prior to adolescence and also appear to face a greater amount of new challenges during early adolescence than boys (Hyde, Mezulis, & Abramson, 2008; Nolen-Hoesksema & Girgus, 1994). In addition, adolescent females are more likely to feel badly for a longer period of time after experiencing troubling situations/events and are also more likely to doubt their problem solving skills and view their problems as unsolvable (National Institute of Mental Health, 2009). In addition to providing an explanation for the increased risk of prescription drug misuse among females, the current research also found support for general strain theory. There was a direct association between strain and prescription drug misuse, as respondents who reported strain were at an increased risk for prescription drug misuse. Furthermore, we also found evidence for an indirect connection between strain and prescription drug misuse via our measure of negative affect, depression. Our analysis found that strain increased the risk for depression. In turn, depression increased the risk for prescription drug misuse by roughly 69%. These findings contribute to the large number of studies documenting the empirical validity of general strain theory. In particular, a number of studies identify depression or psychological distress as an important measure of negative affect that links strain to alcohol or drug use (Drapela, 2006; Ford & Schroeder, 2009; Stogner & Gibson, 2011). The current research also found evidence to support the argument that the relationship between strain and crime is gendered, particularly that males and females have different responses to strain. In our analysis, we found that

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“strained” females were at an increased risk for depression compared to “strained” males. This finding is consistent with other research that identifies females as being more likely to respond to strain with depression (Broidy & Agnew, 1997; Jang, 2007; Sigfusdottir et al., 2004). The response to strain is important as Agnew (2006) argued that the negative affective state of anger was more closely linked to criminal offending, while the negative affective state of depression was more closely related to substance use. A few limitations in the current research are worth noting. First, our data is cross-sectional. Given the theoretical assertions of general strain theory, we would ideally use longitudinal data which would allow for the measurement of strain, depression, and prescription drug misuse at different times. It is important to note however, that it is not uncommon to test general strain theory using cross-sectional data (Hay, Meldrum, & Mann, 2010; Ford & Schroeder, 2009; Patchin & Hinduja, 2011; Sigfusdottir, Kristjansson, & Agnew, 2012). Second, much of the research on the gendered nature of strain highlights the fact that females are more likely to experience strains related to discrimination and criminal and sexual victimizations. We were unable to include these in our measure of strain due to the fact that they were not included in the NSDUH. A more complete test of the gendered nature of the relationship between strain and prescription drug misuse would include these types of measures. Third, our finding may be due to females being more likely to selfmedicate when negative life experiences lead to psychological distress or depression (Gradus, Street, Kelly, & Stafford, 2008; Zullig & Divin, 2012). Unfortunately, we were not able to test this with our data. Self-medication occurs when individuals attempt to relieve the symptoms associated with psychological distress through the numbing effects of alcohol or other drugs (Khantzian, 1997; Stewart & Conrod, 2003). The idea that females may be misusing prescription drugs to self-medicate is bolstered by that fact that research on motivations associated with prescription drug misuse highlight self-medication as a primary motivation (Boyd, McCabe, Cranford, & Young, 2006b; McCabe et al., 2009; Teter et al., 2006). As with much of the literature on prescription drug misuse among adolescents, we found that females were at an increased risk. Our investigation indicates that Agnew’s general strain theory, specifically a gendered approach, may help us understand why females are at an increased risk for prescription drug misuse. Future research in this area should examine longitudinal data, with genderspecific types of strain, and measures of self-medication to gain a more complete understanding of the relationship between prescription drug misuse and gender.

Declaration of Interest

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the article.

THE AUTHORS Jason A. Ford, Ph.D., is an Associate Professor of Sociology at the University of Central Florida. His current research interests include substance use among adolescents and young adults and also the factors related to stability and change in crime and deviance over the life course.

Amy Reckdenwald, Ph.D., is an Assistant Professor at the University of Central Florida’s Department of Sociology. Her current research interests are in the areas of violence, particularly as it relates to domestic violence, sexual violence, homicide-suicides, and intimate partner homicides, as well as race and gender issues in victimization and offending. Her work has appeared in journals, such as Criminology, Journal of Criminal Justice, Feminist Criminology, Violence and Victims, and Homicide Studies. Briana Marquardt, M.A., is a graduate of the University of Central Florida. While there, she earned a B.S. in psychology and an M.A. in sociology. Her current research interests include substance use and abuse, recidivism, juvenile delinquency, and other topics within criminology. She seeks to look at role the media may play in certain crimes, as well as the way crime is portrayed in the media. Briana is also interested in the role of gender in crime, and explanations for the trends and differences which occur.

GLOSSARY

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