Predictors of prison-based treatment outcomes: a comparison of men and women participants

INTRODUCTION

From 1995 to 2002 the nation's state prison population increased by 27%, and the nation's federal prison population increased by 71% (1). Moreover, annual increases in the number of incarcerated women have be consistently larger than the increases in the number of incarcerated men for the past two decades (1-3). The growth within the nation's prison population largely has be due to the increased use of incarceration for drug-related offenses (1), which also has created an increased emergency for appropriate drug treatment programs for men and women within prison settings.

The beneficial community (TC) treatment model has be shown to be an effective method of substance maltreat treatment (4) and many TC programs hold been incorporated into American prisons over olden times two decades. Despite the increase in prison-based TC treatment, little is known more or less the individual characteristics and specific treatment needs of drug-dependent men and women participating in prison-based programs (5, 6). Moreover, abundant of the existing evaluations of prison-based treatment focus specifically on the programs for men (similar to community-based treatment evaluations). Only a handful of studies have assessed outcomes of women within prison-based treatment programs designed specifically for women, and even fewer studies enjoy compared and contrasted specific factors that are associated near outcomes relative to men or women (7). Understanding possible differences in the needs and reclamation processes of drug-dependent men and women offenders is crucial to help design appropriate prison-based substance harm programs.

This study begins to address the cavity in the literature about gender issues and treatment outcomes. We compare and contrast intake facts from a large token of drug-dependent men and women offenders who paroled from prison-based treatment programs inside California. We further assess posttreatment outcomes for men and women separately to identify the correlates of success specific to sexual category, and to examine the plausibility of "gender-specific" paths contained by the recovery process. The following literature review pieces together the available information on the conditions characteristics and treatment needs of men and women within prison-based treatment, their postrelease treatment outcomes, and gender-specific predictors of success.

Characteristics of Men and Women Entering Prison-Based Treatment

A review of the literature identified lone 3 published studies that directly compared the characteristics of incarcerated men and women in drug treatment programs. Peters, Strozier, Murrin, and Kearns (8) compared data from the intake assessments of 1,225 men and 430 women referred to a short-term cognitive behavioral incarcerate treatment program in Tampa, Florida. Langan and Pelissier (9) compared 1,332 men and 312 women who volunteered to contribute in cognitive behavioral drug treatment programs at 20 minimum, low, and surrounding substance security federal prisons around the country. Messina, Burdon, and Prendergast (10) replicated the design of the previous studies, comparing the characteristics of 4,509 women and 3,595 men from 16 prison-based TCs throughout California.

The findings from these 3 studies be strikingly consistent and paralleled findings on gender differences found contained by nonoffender populations (11, 12), indicating that women were more predictable than men to present greater challenges to treatment practitioners. For example, incarcerated women in treatment be significantly more likely than incarcerated men to hold severe substance abuse histories (e.g., using intricate drugs, using more frequently, using polysubstances, or taking drugs intravenously), to have grown up surrounded by homes where drug use be present, to have coexisting physical robustness and psychological problems, to be taking prescribed medications for psychological problems, and to enjoy been sexually and physically abused as children. However, men be found to have more serious criminal histories than women (8-10). Although the findings from the above guilty party populations are consistent, the extent to which the outlined differences among men and women at treatment entry may affect posttreatment outcomes largely is unknown.

Posttreatment Outcomes of Men and Women in Prison-Based Treatment

Fairly consistent findings from prison-based treatment evaluations for men have be reported: Treatment reduces posttreatment recidivism and drug use; men who verbs treatment in the community after release from prison do better than men who do not verbs treatment; and length of time in treatment is positively correlated next to greater success on parole (13-16). The effect of treatment tend to disappear at about 3 years (13, 14, 17).

However, findings from studies of men cannot be generalized to women for several reason. First, men and women have different pathway to crime and addiction (18-20) and continue to use drugs for different reason (21, 22). Women's patterns of drug name-calling have be described as more socially embedded than men's and primarily revolve around interpersonal relationships (23, 24). In certainty, women are frequently initiated to drug use by their male partner, and often verbs to use drugs to cope with offensive relationships (18, 22, 25). Histories of sexual and/or physical abuse are also highest preexisting conditions in subsequent addiction and criminality for women (6, 21, 26). Second, men and women tend to enter treatment for different reasons (27). Women cite kith and kin problems and health as motivation for entering treatment, while men are more possible to cite employment and legal issues (28). Third, the resources and services available surrounded by women's correctional facilities may be at variance than those available to men (21).

A small body of literature has evaluated posttreatment outcomes for women surrounded by prison-based TC treatment. The existing research, however, is limited, and findings are sometimes contradictory (for a full review, see Messina & Prendergast (7)). For example, two studies found that women in prison-based treatment have more success on parole compared next to a no-treatment group of inmates (16, 29); whereas another study found there be no difference between women in a prison treatment group versus women contained by a no-treatment group (30). Two other studies found that women in prison-based treatment have reductions within recidivism and drug use compared with a no-treatment group of women (31, 32). However, Wexler's study (16) found no difference within recidivism rates between treated and untreated women. Moreover, Rhodes and associates (33) conducted a 3-year follow-up of the women in Pelissier's study (32) and found that in attendance was no evidence of long-term treatment efficiency (33). (For a comprehensive review of community-based treatment outcomes for women, see Ashley, Marsden, and Brady (11)). Additional limitations of the existing research include reliance on bivariate comparisons within relatively small taste sizes, which does not allow for the control of pre-existing differences between groups or proper power to detect treatment effects.

Predictors of Treatment Outcomes for Men and Women

Only two studies were found that directly explored gender-specific predictors of treatment outcomes from men and women. Messina, Wish, and Nemes (34) compared and contrasted the correlates of nouns for 296 men and 116 women who were by chance assigned to community-based residential TC treatment differing primarily surrounded by the length of inpatient and outpatient phases. Pelissier and colleagues (35) compared and contrasted the correlates of nouns for 1,842 men and 473 women who participated surrounded by prison-based cognitive behavioral treatment in a multisite federal prison evaluation.

Both studies found that in that were similarities and differences near respect to predictors of outcomes for men and women. For example, Messina et al. (34) found that men and women who completed residential treatment followed by outpatient treatment had substantial reduction in drug use and arrests and increased employment. However, the longer residential treatment program have a particularly beneficial impact on women. Number of prior arrests and a history of physical knock about also were associated next to negative postdischarge outcomes for women, but not for men. Pelissier et al. (35) found that a history of prior commitments and disciplinary activities during incarceration increased the likelihood of post-treatment drug use and recidivism for both men and women. In enhancement, being Black similarly increased the possibility of drug use for both men and women, and age at release from prison (older) decreased the chance of drug use. A variety of other factor predicted outcomes for men only. Positive predictors of outcomes included living near a spouse at follow-up, participating in treatment (versus the no-treatment group), and employment. In contrast, only one extra factor was found to shrinking posttreatment drug use among women--participation in mental form treatment.

The different pathways and pattern of drug abuse for men and women, and the availability of gender-specific services, are adjectives considered to be directly related to the likelihood of treatment entry and rescue (11, 27). However, the limited research on femininity issues does not provide enough information to fully think through how treatment impacts men and women differently. Yet, the available evidence does suggest that outcomes for men and women should be assessed separately to identify specific factor that affect behavioral outcomes following treatment.

The purpose of this study is to determine if the characteristics of participants who paroled from the California prison-based TCs are differentially correlated beside treatment outcomes for men and women. This study includes separate models for men and women assessing treatment graduation, aftercare participation, and recidivism, and uses multivariate analyses next to appropriate independent variables selected specifically for men and women. Based on the prior research comparing treatment outcomes of men and women separately (34, 35), we formulated the following research ask: Do factors that predict aftercare contribution and reincarceration differ substantially for men and women who participated contained by prison-based treatment?

METHODS

The CDC Prison Treatment Expansion Initiative

Based on previous research in California testify to the effectiveness of prison-based TCs (16, 29, 30), the legislature and the California Department of Corrections (CDC) begin an initiative in the mid 1990s to expand treatment opportunities for inmates. As part of a set of this initiative, the CDC established TC treatment programs in designated housing units inside many of its prisons, including adjectives of the institutions that house women. The data for this study be collected as part of an evaluation of the CDC prison treatment expansion initiative.

This initiative includes two 5-year evaluation studies of the drug treatment programs inwardly the California state prison system. The University of California, Los Angeles (UCLA), Integrated Substance Abuse Programs (ISAP; formerly known as the UCLA Drug Abuse Research Center (DARC)) be contracted by CDC to evaluate these programs, with contract paperwork provided by CDC's Office of Substance Abuse Programs. The two evaluation studies cover 16 substance abuse programs within 10 prisons, totaling approximately 3,300 beds (8 mannish programs totaling 1,600 beds and 7 womanly programs totaling 1,700 beds). These programs became running between July 1998 and December 1999 and include participants at adjectives levels of protection (Level I-Minimum through Level IV-Maximum).

Prison-Based TCs in California

CDC contracts with community-based organization experienced in the TC model to provide services within the prisons (i.e., Amity Foundation, Center Point, Inc., Civigenics Inc., Mental Health Systems, Phoenix House, and Walden House). Although all of the programs provide treatment services using the TC model, respectively provider has adapted the model somewhat to conform to its own treatment philosophy and the specific wishes of its population, including providing appropriate programming for women. Characteristics of the prison-based TCs include: (1) activities that embody positive values that start a process of socialization; (2) treatment staff who provide positive role models (and heaps of whom are recovering addicts themselves); (3) an alternative concept of inmates specifically usually much more positive than prevailing beliefs and attitudes held by correctional staff; and (4) an aftercare component for graduates from the prison-based TC programs that provides funding for up to 6 months of continued treatment (residential or outpatient services) in the community following release to parole (36).

Data Collection

Client-level background were collected by the treatment providers upon acknowledgment into the TC using the Intake Assessment (IA) instrument. The IA is designed to assess a client's pretreatment/preincarceration sociodemographic background, criminality, employment, and substance use, verbal abuse, or dependence. Adopted from the Initial Assessment developed at the Institute of Behavioral Research at Texas Christian University (37), the IA has be used extensively with criminal sprite populations and provides information that is adjectives for both clinical and evaluation purposes. The programs provided the intake data and treatment entry and discharge data to UCLA ISAP through disclosure agreements below CFR 42 Part 2, Section 2.52. The UCLA General Campus Institutional Review Board approved the study protocol. Postrelease return-to-custody rates came from the CDC's Offender Based Information System and include incarceration for both parole violation and new charges.

Eligibility

Participation contained by these programs is open to inmates who enjoy a documented history of substance use or abuse (based on a review of their criminal background as documented in their inmate crucial files), and who have between 6 and 24 months departed to serve on their current sentence. Those who meet these eligibility requirements are mandate into the treatment programs. There are, however, certain exclusionary criteria that preclude otherwise eligible inmates from entering the programs (e.g., gang-related opponent situations, documented membership surrounded by a prison gang, time spent in administrative segregation for hostility or weapons charges inwardly the last 12 months, and felony and Immigration and Naturalization Service holds).

Participants

The current study focuses on 4,164 women and 4,386 men who enter the participating programs between July 1998 and March 2001, paroled prior to February 1, 2002 (i.e., in order to be at risk for one year prior to our obtain return to custody data), and for whom intake data were available. Participants surrounded by the study were predominately White (39%) or Black (31%), be 35-years-old on average, and had completed approximately 11 years of rearing prior to their current incarceration. About half (45%) have never been married. Thirty-two percent be employed during the 30 days prior to their current incarceration, and 60% were parents. Participants reported an average of 15.5 arrests surrounded by their lifetime. Approximately 93% met DSM-IV criteria for alcohol or drug abuse or dependence, and 57% be serving time for a drug-related offense at the time of their treatment admission.

Data Analyses

The analyses for the current study are designed to examine the relevance of pretreatment differences between men and women on treatment outcomes (i.e., aftercare taking part and reincarceration). The distributions (shown in Table 1) of demographic characteristics, substance use, criminal, and psychological histories prior to incarceration by gender be evaluated using chi-square tests (for categorical variables) and t-tests (for continuous variables). Preliminary analyses (chi-square and t-tests results not shown) examining correlates of aftercare contribution and reincarceration were conducted separately for men and women to identify gender-specific predictors of outcomes for inclusion in the logistic regression models (see below).

Logistical regression analyses be conducted separately for men and women for each dependent unpredictable (aftercare participation and return-to-custody). Aftercare taking part was defined as any contribution in aftercare treatment (dummy coded; 0 = no and 1 = yes) and return-to-custody be defined as any return-to-custody during the 12 months since parole (dummy coded; 0 = no and 1 = yes). All logistic regression models included demographic variables and other correlates that were significantly related to the above outcomes (i.e., age, see, education, employment, matrimonial status, number of years incarcerated, primary drug disorder, and the presence of cooccurring disorders). Additional independent variables were included depending on the appropriateness to masculinity and the dependent variable. For example, histories of sexual and physical treat roughly were included in the regression models for the women offender only, as they be not significantly correlated with outcomes for the men. The logistic regression models examining predictors of association in aftercare included a motivation for treatment mark (yielding a distribution of motivation ranging from 0 to 6; see Burdon et al. (5)). Length of time contained by treatment also has be shown to be a strong predictor of treatment outcomes (15, 38). Therefore, we included a variable contained by the aftercare and return-to-custody regression models that defined total time in prison-based treatment. We also included a variable that defined total time in aftercare treatment in the return-to-custody regression models.

Adjusted likelihood ratios be used to interpret the statistically significant effect size at the p < .05 level: [Exp(Beta) - 1] x 100 = in tune odds ratio (e.g., the percentage increase or shrink in the likelihood of being returned to custody).

RESULTS

Bivariate Comparisons of Men and Women at Admission

Table 1 displays the preview characteristics for men (n = 4,164) and women (n = 4,386) entering the prison-based TCs during the selected study spell. Gender differences were found near regard to demographic characteristics, sexual and physical misuse histories, primary drug problem, substance abuse and criminal even-handedness histories, and the presence of cooccurring disorders. However, some of the differences that reached significance are rather small (i.e., years of education and motivation for treatment scores), as the full-size sample size substantially increased the chance of finding statistically significant differences between men and women.

Although the majority of men and women were White or Black, women be significantly more likely than men to be of Asian or American Indian fully clad (11 vs. 6%; p < .001) and to be divorced or separated (34 vs. 26%; p < .001). Women were elder than men (36.0 vs. 34.5 years; p < .001), had slightly smaller number education (11.0 vs. 11.4 years; p < .001), and be less potential to have be employed prior to incarceration (33 vs. 53%; p < .001). Women also were much more predictable than men to report having be sexually and physically abused as a child (27 vs. 13%; p < .001) and as an adult (27 vs. 3%; p < .001). Women be more likely to report cocaine/crack as their primary drug problem (34 vs. 19%; p < .001), while men be more likely to report methamphetamine/amphetamine as their primary drug problem (40 vs. 30%; p < .001). With the exception of methamphetamine/amphetamine, women be more likely to report each day drug use prior to incarceration and to report daily use of two or more drugs (24 vs. 19%; p < .001). Compared next to women, men were younger at the age of first arrest (17.1 vs. 21.3 years; p < .001), have been arrested more repeatedly in their lifetime (17.4 vs. 14.7 arrests; p < .001), and have been incarcerated longer in their lifetime (5.5 vs. 3.2 years; p < .001). However, women be more likely than men to enjoy a cooccurring psychiatric disorder (27 vs. 14%; p < .001) and to have a slightly sophisticated motivation for treatment score (1.3 vs. 1.1; p < .001).

Gender and Posttreatment Outcomes

Bivariate comparisons between men and women be conducted for the two posttreatment outcomes: aftercare participation and a return-to-custody inwardly 12 months from parole. Men were significantly more potential to participate within aftercare than women (46% of men vs. 41% of women; p < .001); yet, men who participate in aftercare did not stay as long as women (4.6 months for men vs. 5.1 months for women; p < .001). In adornment, men were significantly more plausible than women to be returned to custody within 12 months from parole (40% of men vs. 31% of women; p < .001), and be returned sooner than women (8.4 months for men vs. 9.2 months for women; p < .001).

Logistic regression analyses assessing the relationship of gender to aftercare contribution and 12-month return-to-custody rates were conducted previously beside this CDC sample (see Burdon et al. (5)). These results (not shown) indicated that when other factor (e.g., demographics, number of years in prison, substance maltreat disorder, time in prison treatment, and motivation) be controlled, gender be no longer a significant predictor of aftercare participation. The most momentous predictor of aftercare participation be motivation for treatment regardless of gender. However, sexual category remained associated with a return-to-custody inwardly 12 months from parole. After controlling for various other factor, men still were significantly more imagined to be returned to custody compared with women.

Gender-Specific Paths (Logistic Regression Models for Men and Women)

Aftercare Participation

Separate logistic regression models assessing predictors of aftercare contribution for men and for women are shown in Table 2.

Men: Seven out of 10 variables significantly predicted aftercare contribution among the men (length of prison-based TC treatment, age, race, motivation for treatment, length of lifetime incarceration, employment, and primary drug problem). For respectively additional afternoon in prison-based treatment, the probability of participating in aftercare increased by .4% (p < .001). For each secondary year of age, the odds of aftercare association increased by 5% (p < .001). Compared with Hispanic masculine participants, the probability of White males participating in aftercare were increased by 79% (p < .001), and the likelihood of Black males participating in aftercare were increased by 45% (p < .05). For respectively additional chalk up on the motivation for treatment scale, the likelihood of participating in aftercare were increased by 26% (p < .001). For respectively additional year of lifetime incarceration, the likelihood of aftercare participation decrease by 3% (p < .01). Compared with men who be unemployed prior to incarceration, the probability of aftercare participation for those who be employed were reduced by 26% (p < .01). Compared next to men who reported opiates as their primary drug problem, the odds of aftercare contribution for men who reported alcohol/other as their primary drug problem were reduced by 52% (p < .001). The presence of cooccurring disorders, prior childhood, and prior marital status be not significantly related to aftercare participation among the men.

Women: Three out of 11 variables significantly predicted aftercare association among the women (length of prison-based TC treatment, motivation for treatment, and primary drug problem). For each spare day of prison-based treatment, the probability of participating in aftercare increased by .2% (p < .001). For each secondary point on the motivation scale, the likelihood of participating in aftercare were increased by 13% (p < .01). Compared next to women who reported opiates as their primary drug problem, the odds of participating in aftercare for women who reported amphetamine/methamphetamine as their primary drug problem be reduced by 44% (p < .01). The presence of cooccurring disorders, sexual/physical abuse histories, prior teaching, prior employment, age, race, prior conjugal status and length of lifetime incarceration were not significantly related to aftercare taking part among the women.

Return-to-Custody

Separate logistic regression models assessing predictors of a 12-month return-to-custody for men and for women are shown in Table 3.

Men: Six out of 10 variables significantly predicted a 12-month return-to-custody among the men (the presence of cooccurring disorders, race, length of lifetime incarceration, age, employment, and total days in aftercare). Compared near men with one and only a substance abuse disorder, the likelihood of men with cooccurring psychiatric disorders mortal returned to custody within 12 months be increased by 40%, (p < .05). Compared with Hispanic men, the likelihood of white men being returned to custody be increased by 55% (p < .01), and the odds of black men individual returned to custody were increased by 63% (p < .001). For respectively additional year of lifetime incarceration, the probability of returning to custody within 12 months be increased by 8% (p < .001). For each supplementary year of age, the odds of men returning to custody inwardly 12 months were reduced by 4% (p < .001). Compared next to men who were seeking work prior to incarceration, the odds for those who be employed of returning to custody within 12 months be reduced by 29% (p < .001). For each more day of aftercare, the probability of returning to custody within 12 months be reduced by 1% (p < .001). Time in prison-based treatment, schooling, primary drug disorder, and prior marital status be not significantly related to a return-to-custody within 12 months.

Women: Six of the 11 variables significantly predicted a 12-month return-to-custody among the women (length of prison-based TC treatment, age, nurture, total days in aftercare, the presence of a cooccurring psychiatric disorder, and length of lifetime incarceration). For respectively additional light of day in prison-based treatment, the likelihood of returning to custody within 12 months be reduced by .1% (p < .02). For each new year of age and education, the likelihood of returning to custody within 12 months be reduced by 4% (p < .001) and 6% (p < .05), respectively. For each other day spent contained by aftercare, the odds of returning to custody inside 12 months were reduced by 1% (p < .001). Compared next to women with with the sole purpose a substance abuse disorder, the probability of codisordered women returning to custody within 12 months be increased by 58%, (p < .001). For each supplementary year of lifetime incarceration, the odds of returning to custody inside 12 months were increased by 4% (p < .05). Sexual/physical assault histories, prior employment, race, primary drug problem, and prior married status were not significantly associated near a return-to-custody within 12 months.

DISCUSSION

The purpose of this study be to outline the differences between men and women offenders entering TC treatment and to explore the relationship of those differences to post-treatment outcomes. The differences found between men and women entering prison-based treatment in California mirrored the findings of previous studies of incarcerated treatment populations; whereby women be at a substantial disadvantage compared to their male counterparts contained by all areas of existence history except for their past criminal involvement (8, 9, 35). The point to which these differences affected posttreatment outcomes be less clear, as severely little research had previously examined gender-specific path of recovery.

Table 4 provides a summary of the significant predictors of the two outcome measures surrounded by the regression models, by gender. One of the most personage findings from this table is that there be fewer predictors of outcomes for women than for men (similar to findings reported in Pelissier et al. (35)). Even though women be significantly more likely than men to own more severe substance abuse histories, sexual and physical foul language histories, and cooccurring psychiatric disorders prior to incarceration, these variables were not associated near the outcome measures. For example, after controlling for other related factors, a history of sexual and/or physical name-calling as a child was no longer related to aftercare taking part or reincarceration among the women. However, a fairly small percentage of women and men contained by our sample reported histories of sexual and physical treat roughly. Previous studies have shown percentage ranging from 19% to 55% among criminal populations (8, 9). The low percentages reported here could be due to the reality that these particular question were asked by treatment personal prior to treatment entry and not experienced researchers. Since these question were singular asked from a partial sample of participant, the regression analyses might not have detected changeability due to histories of sexual/physical abuse.

Similarities Between Men and Women

Consistent next to previous findings from incarcerated populations, age, motivation for treatment, time in prison treatment, and time in aftercare were positively associated next to at least one (and surrounded by some cases both) of the outcomes for men and women (13-16, 29, 31). In addition, both men and women who reported opiates as their primary drug problem be most likely to jump to aftercare treatment compared to those who reported other drug dependencies. The direction of the correlation for age and motivation for treatment to outcomes are often replicated contained by offender populations, as elder parolees often "age-out" of criminal behavior and those next to substantial internal motivation are highly predictable to succeed upon release from prison. Moreover, selection bias be not likely to be an central factor in producing the "time in treatment" finding since length of time in prison treatment be not within the control of the inmate (which would create test bias), but rather be determined by when CDC placed the inmate in the treatment program and the length of their sentence. Since the propose time spent in prison treatment for men be 7.1 months (SD = 4.8) and 6.9 months (SD = 4.5 months) for women, it appears that a substantial number of inmates in this example were assigned to these TCs next to approximately 7 months remaining on their sentence.

Predictors that negatively affected outcomes for both men and women included the cooccurrence of psychiatric disorders during treatment and total years in prison over one's lifetime. Codisordered inmates and those beside more total years in prison contained by one's lifetime were more possible to be reincarcerated regardless of gender, a finding consistent near previous research indicating that those with the most severe psychological problems and those near serious criminal histories are more likely to recidivate (34, 39).

Differences Between Men and Women

Time contained by treatment warrants further clarification (discussed above), as it be also differentially associated with reincarceration among men and women. Total time in prison-based treatment and aftercare be related to a reduced likelihood of reincarceration for women singular, indicating the positive effect of continuous and long-term treatment episodes (similar to that reported in Messina et al. (34)). In contrast, only time surrounded by aftercare was related to a reduced possibility of reincarceration for men. This finding creates an interesting dilemma, as it also appears that men were more promising to go to aftercare treatment than women, but did not stay as long as the women. The lower aftercare contribution rate reported for women may have be due to gaps contained by reporting procedures. The Female Offender Treatment and Employment Program (FOTEP) aftercare treatment program was an other option for women paroling from prison in California. Women entering the FOTEP program did not access aftercare treatment using one and the same procedure as men or women parolees opting for other forms of aftercare (e.g., outpatient, sober living, residential). As a result, background on the number of women entering the FOTEP aftercare program may not have be complete.

Another difference between men and women was that see was a significant predictor of both outcomes for men, but not at adjectives for women. Among the men, Whites and Blacks were more expected than Hispanics to participate surrounded by aftercare treatment and to be returned to custody. Previous findings from this sample (see Burdon et al. (5)) hold shown that a greater proportion of Hispanics reported living with family/relatives prior to their current incarceration. In increase, a recent review of studies that examined drug use behaviors among Hispanics found that social support systems (including familial factors) are important factor in preventing drug invective among this population (40). These findings suggest that the familial support systems for Hispanics are stronger, and that they may tend to rely on these support systems to a greater degree and next to greater success following release to parole than Whites or Blacks.

Finally, anyone employed prior to incarceration decreased the odds of aftercare participation and a return to custody for men (similar to that reported contained by Pelissier et al. (35)), but was not related to outcomes for women. In contrast, prior instruction decreased the possibility of reincarceration for women, but was not related to outcomes for men.

Limitations

It should be noted that the current study relied on broad intake data collected by treatment personnel for a roomy sample of men and women entering prison-based treatment. Due to the overall range of the CDC initiative, the questions available on the IA instrument be limited within both range and depth. The IA instrument be not originally designed to capture detailed differences between men and women entering prison-based treatment, and, consequently, many factor that may be predictive of posttreatment outcomes for women were fictional. For example, the questions on the IA on the subject of histories of sexual and physical abuse be dichotomous (yes/no) questions, which did not inquire around the specific type of abuse, the perpetrator of the invective, the age at which it occurred, or the duration of the mishandle, which have previously be shown to be related to women's recovery (6, 21). In rider, the findings generated by this study are set to inmates who were preferred for treatment participation and thus, cannot be generalized to general inmate populations in state prison.

Implications and Conclusion

The results of this study hold highlighted relevant individual-level factors that serve as predictors of taking part in aftercare treatment and 12-month return to custody rates among men and women parolees of prison-based TC treatment programs. One of the most consistent findings, relative to previous research, is the nouns for both men and women associated with aftercare taking part. The consistency of this finding indicates the need to place greater prominence on promoting appropriate aftercare treatment for inmates in the prison-based treatment programs, regardless of gender.

In contrast, consistent findings in connection with the increased likelihood of reincarceration among inmates near cooccurring psychiatric disorders highlights the difficulty involved in delivering decisive treatment services to codisordered men and women in correctional settings. Because treatment staff may not be suitably trained to treat certain psychiatric disorders that offender present upon entry into prison-based programs, perhaps here should be separate treatment tracks for codisordered offenders to provide important treatment to this high-risk population. At the very smallest, referrals to appropriate aftercare treatment should be contained by place upon release from prison programs, which would require increased communication, coordination, and collaboration between substance abuse and psychiatric treatment systems (41). The dignified prevalence rates of psychiatric disorders among incarcerated drug offenders across the nation suggest that these issues are probably not inimitable to California (39).

In conclusion, the limited number of identified predictors of outcomes for women is celebrity. It would appear that we know more about what lead to successful outcomes for men than for women. Indeed, the limitations of the available data of our study may enjoy drawn further attention to the gap contained by our knowledge of gender-specific path to recovery. Future studies will want to explore and incorporate additional predictors of posttreatment outcomes that more appropriately emulate paths of repossession for women. Future studies also may need to explore superfluous posttreatment outcomes for women such as improved relationships near children, living situations, and psychological status.

Risk for marijuana-related problems among college students: an application of zero-inflated distrustful binomial regression

Marijuana is the most commonly used illicit drug in the U.S. Approximately 46% of college students report having tried marijuana, 27% report use contained by the past year, and 16% report previous 30-day use (1); thus, a significant proportion of college students use marijuana. Furthermore, problems associated with use are, unluckily, not uncommon. For example, short-term cognitive impairments and impairment contained by educational behaviour have be associated with bulky marijuana use (2-4). Given this, identification of individuals who use marijuana and report associated problems is an far-reaching issue. However, despite the relative prevalence of use, many college students hold never tried marijuana or do not currently use it. As a result, an assessment of marijuana-related problems will yield a mixed distribution near a high number of zero-values. Some respondents will report not experiencing problems because they in reality did not use marijuana at all during the assessment pane and those who do use the drug will report a range of problems including, for some users, nought. Identifying variables that predict nonusers as well as identify predictors of the number of problems experienced among users are both of interest. Zero-inflated Poisson (ZIP; e.g., Lambert (5)) and a subsequent generalization of ZIP, Zero-inflated cynical binomial regression (ZINB; e.g., Heilbron (6)) are two statistical techniques that allow one to accomplish both of these objectives within a single analysis. They, thus, represent parsimonious procedures that allow one to examine effects over the full distribution. These mixed distributions are a common element in research investigating risk behaviors near low base rates (6).

Distributions of risk behaviors surrounded by general populations frequently will hold a large number of zero-values. That is, a big proportion will not engage within the targeted risk behavior, while a smaller proportion of at risk individuals will report varying levels of the risk behavior and associated consequences. Such distributions pose difficulties for adjectives statistical methods based upon average distributions. ZINB regression models are one method for analyzing such data. ZINB models assume two distinct populations; one where the target behavior is always elsewhere, the other in which the target behavior can be any integer, including zilch (6). More specifically, in the current study, one population would other score not anything on a marijuana problems measure because they did not use marijuana during the assessed time spell (current nonusers) and the other population could score any plus, including zero, because they are adjectives in the risk behavior (users--who may or may not experience problems). Thus, the prediction of counts is conditional upon the probability of the values one from a hypothetical subsample of participants that are predicted to "always" gain zero on the weigh. The model allows one to either use different sets of predictors to predict the two criterions (i.e., other zero-values and counts) or to utilize the same predictor set and evaluate whether variables are differentially associated next to the respective criterions (7).

For the current study, we employed the same predictor set to predict zero-values (i.e., current nonusers) and counts (i.e., number of problems among expected users) within order to examine the differential predictive power of the variables of interest. Such differentiation is of supposed interest in substance use research. That is, identifying both the types of variables that are associated beside use initiation or low-level experimentation as well as the types of variables that are primarily associated beside the prediction of use problems represents a common aspiration in substance use research. One model of substance use proposes that social-environmental variables are associated primarily near use initiation or low-level use while psychobiological variables are more strongly associated with use-related problems (8, 9). The role of psychosocial variables, such as use motives, expectancies, or perceived use utility do not clearly fit into this dichotomy. Indeed, these psychosocial variables hold relations with both use and use-related problems (10-12). This study examined one social-environmental unsettled (social norms), one psychosocial variable (perceived marijuana use utility), and one biopsychological unstable (impulsivity). Social norms are a social-environmental undependable consistently associated with marijuana use (13, 14). Perceived use-utility is a psychosocial changeable more associated with marijuana use than problems (12). In contrast, impulsivity is a biopsychological irregular more associated with problematic use (15).

Social norm may be defined as either the actual or perceived behavior of individuals in social networks as in good health as the group member's attitudes toward target behaviors (i.e., whether group member think one should absorb in the behavior). In the present study, social norm are represented by both the perceived marijuana use behavior and attitudes of peers. Social normative variables frequently are associated with marijuana use (13, 14, 16). Although the basis for this relationship traditionally has be attributed to the influence of social networks on use behavior, recent research on social norms and alcohol suggests that screening effects (i.e., choosing social networks with similar use practices) may also be of exigency (17). Indeed, selection of marijuana using peer groups may be influenced by variables such as sensation seeking (13) and house relations (14). Such selection effects suggest that affective, cognitive, and social normative variables are not independent of respectively other. Individuals may be choosing social networks that not only hold similar marijuana use practices but likely share adjectives beliefs about the costs and benefits of marijuana. The potential interdependence of affective, cognitive, and social normative predictors of marijuana use make their concurrent assessment of interest. In a study on drug refusal, peer influence is cited as a stronger influence on drug use decisions by low-level users while heavier drug users are more imagined to cite emotional determinants and seldom cited peer influence as a factor (18). Thus, social norm may be more strongly associated with use initiation and low-level use a bit than use-related problems.

Marijuana use, like heaps behaviors, may be influenced by the perceived costs and benefits of use. Evaluation of marijuana and other drug use has be operationalized in diverse ways, range from the global evaluation of attitudinal constructs (19) to specific expectancies of drug effects (20) to subjective expected utility models explicitly examining cost and benefits (21). An extramural way of evaluating the perceived utility of drug use is to examine it in relation to personal goal (22). For instance, personal strivings are ongoing goals that individuals are characteristically trying to get done through their behavior (23). Drug use is expected to increase to the extent that it is congruent with the attainment of such valued goal. Previous cross-sectional research has indicated that perceived conflict/utility of marijuana use in achieve personal strivings is associated with marijuana use initiation as okay as frequency and problems (12). This study seeks to somewhat replicate this finding in a multivariate context.

Impulsivity is related to difficulty with the restraint of one's own behavioral and excited responses (24). Impulsivity, although commonly referred to as "behavioral" undercontrol, also may be described as an over-reliance on affective rather than cognitive cues (25). Impulsivity have well-documented relations with substance use problems (8, 26, 27). Impulsivity have evidenced direct relations with marijuana-related problems above and beyond use frequency (15). Thus, impulsivity may probable be associated with use-related problems among expected users.

PURPOSE

The purpose of this study is to examine associations between social norm, impulsivity, perceived use utility and marijuana-related problems in a indication of undergraduates. Zero-inflated negative binomial regression is used to predict the current nonusers from the users in the indication, as well as the number of problems for the predicted users. Based on previous research, social norm are hypothesized to predict current nonusers, while impulsivity is expected to be associated with the number of problems experienced by the predicted users. Perceived use utility is hypothesized to be a significant predictor of both current nonusers as capably as number of problems.

METHOD

Participants

Participants included 292 students at a small state university; all participated within research for partial fulfillment of course requirements. Women made up 70% of the token. The sample range in age from 18 to 26 (M = 19.69, SD = 1.56); 94% be White, 1% Black, 2% Asian, 1% Native American, and 1% multiracial.

Measures

Marijuana Use and Problems

Lifetime marijuana use was assessed by a 7-point anchored rating scramble (0 = no use, 6 = more than 300 days). Marijuana use in the closing 30 days was assessed by a 9-point anchored rating scramble (0 = no use, 8 = more than once a day).

Marijuana-related problems in the ending 30 days were assessed by 23 items. Items be rated on a 5-point scramble ranging from 0 (never) to 4 (more than 10 times). This go up was designed for adolescents and, thus, is appropriate for this population. This amount is internally consistent (alpha = .86) and has evidenced expected relations next to marijuana use in previous research (11, 27). Sample items included "not competent to do your homework or study for a test," and "feel physically or psychologically dependent on marijuana."

Impulsivity

Eysenck's Impulsivity Scale (29) includes 24 items assessing lack of control over behavior; respectively item is dichotomous. The alpha coefficients for men and women exceed .82 (29). Two items dealing specifically with drug use be excluded, yielding a 22-item size. The alpha coefficient in this taste was .78. Sample items included "Do you habitually do and say things lacking stopping to think?" and "Are you an hot-headed person?"

Social Norms

Social norm were assessed by the following three items:

1. Number of friends who use marijuana: 7-point anchored rating ascend none (1) to all (7).

2. Friends' attitude toward participant using marijuana once a month or smaller amount: strongly disapprove (1) to strongly approve (5).

3. Friends' attitude toward participant using marijuana twice a month or more: strongly disapprove (1) to strongly approve (5).

The mean of the standardized items be used (alpha = .90).

Strivings Assessment

Personal strivings are "goals that sprawl directly behind individuals' behavioral choices (i.e., what an individual is characteristically trying to do)" (30). In the personal strivings assessment, participant first listed 10 personal strivings, near the instructions describing a personal striving as "an objective you are typically trying to accomplish." Participants be given examples such as "trying to be physically attractive," "trying to seek out contemporary and exciting experiences," and "trying to avoid being notice by others." Participants were instructed to focus of actual instances of their behavior and to base their results on the actual intention of the behavior. Personal strivings be found to be stable in college students; 45% of the strivings tabled at initial assessment were scheduled again 18 months later (31). The remainder of the assessment focused on the five strivings that the participant identified as most descriptive of themselves.

To assess perceived conflict/utility between strivings and marijuana use, the five strivings were enter into a matrix that included five columns to represent levels of marijuana use: (1) prudence, (2) at least once a year but smaller amount than once a month, (3) at least once a month but smaller number than once a week, (4) 1-3 days a week, and (5) most every day. The participant rated the extent to which respectively level of marijuana use would help out or hinder the attainment of respectively personal striving using a 5-point scale (-2 = especially harmful effect, +2 = terribly helpful effect) and a gain was enter in respectively cell. A marijuana use-striving conflict/utility score be created for each personal striving (reverse scoring the thriftiness column). Finally these sums were combined into a single marijuana use-strivings conflict/ utility (i.e., use utility) chalk up (alpha = .92). Higher scores correspond to greater perceived utility of marijuana within achieving goal. Lower (more negative) scores correspond to greater perceived conflict between marijuana use and aspiration attainment.

Procedure

Participants completed questionnaires online in small groups beside adequate space to ensure privacy within a computer lab under the supervision of a research assistant. Previous research supports the reliability and truthfulness of Internet-based assessment of drug use (32). All participants provided written informed consent. Participants generate a unique code for themselves and did not place their describe on the questionnaires, thus, ensure their anonymity. The assessment session lasted approximately one hour. Two previous manuscript focusing on alcohol use have be derived from this dataset (33, 34).

RESULTS

Descriptive Statistics

Approximately 49% of the sample reported have used marijuana at least once contained by their lifetime and 21% reported use in times gone by 30 days. Average use in the second 30 days among those who had tried marijuana be 1-2 days (rating scale M = 1.48, SD = 2.25). The be set to on the problems measure for those who have tried marijuana was 3.41 (SD = 6.49). Thus, a colossal percentage of participants reported no marijuana use and the penny-pinching number of problems was outstandingly low. ZINB models are designed for examining this type of distribution. Table 1 presents the summary statistics and correlation matrix for the predictors.

ZINB Model

The ZINB regression model was estimated beside the ZINB command in Stata 8.0 (35) which solves for parameter estimates using maximum chance estimation. ZINB models have two sets of predictors, one set is used to predict zero-values (current nonusers surrounded by this case) and one is used to predict counts among the predicted users. All cases are used in both analyses but are weighted base on the results of the logistic component of the model (see below). In this manner, the model is predicting a zero-score to be generate from one of two populations. More specifically, one set of predictors is used in a logistic model, within which the likelihood of the inspection being a current nonuser is computed, and a second set of predictors is used within a negative binomial model that predicts the count of expected problems, which may be zilch or some positive integer. Thus, the probability that an observation is other zero is modeled by probability, [omega], and the probability that the supervision follows a negative binomial distribution near mean [lambda] is (1-[omega]). More specifically,

P(Y = O) = [omega] (1)

P(Y ~ Negative Binomial ([lambda], [alpha])) = (1 - [omega]) (2)

conceding the following distribution of counts:

P(0) = [omega] + (1 - [omega]) x F(0|[lambda]) (3)

P(k) = (1 - [omega])) x F(k|[lambda]) (4)

where F represents the quotation distribution (negative binomial with fixed parameter [alpha]), [omega] represents the predicted probability of self always-zero, modeled by the logistic component of the model, and [lambda] represents the predicted mean of the refusal binomial component of the model. While the data modeled contained by this study are not true count data, this analytic technique is appropriate for two reason: first, the data are distributed exclusively on the nonnegative integers and tend to show heteroskedasticity (exactly resembling true count data); second, the data appear to be a true mixture model (thus, the need for zero-inflation). As such, even though the notes technically are not generated by a count process, the resultant distribution have the important characteristics expected of a count process and, thus, a count model is appropriate.

Gender, social norm, use utility, and impulsivity were included as predictors in both components of the model (i.e., prediction of zero-values as capably as the number of problems among the predicted users). Thus, the two-part model was parameterized as

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (5)

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (6)

The odds ratio for the full ZINB model was [chi square] (9) = 109.47, p < .001; maximum possibility [R.sup.2] = .31, indicating that the overall model was significant. The maximum-likelihood [R.sup.2] is a standard of fit that is analogous to the coefficient of determination ([R.sup.2]) in familiar least squares (OLS) regression (e.g., Hardin and Hilbe, (36)). Both the logistic component of the model (LR [chi square](4) = 41.21, p < .0001) and the glum binomial component of the model (LR [chi square](4) = 22.25, p = .0002) were significant, indicating that the prediction of current nonusers and the prediction of marijuana-related problems be both significant.

Furthermore, support for the ZINB model over other possible count-data models was strong. The Vuong question paper for nonnested models supported the use of a zero-inflated model over a standard negative binomial model, z = 3.51, independent p = .0002, and the LR test for overdispersion also be significant (LR [chi square](1) = 152.96, p < .0001) demonstrating that a ZIP model would be inappropriate.

With regard to the hypothesized predictors in the ZINB regression model, just social norms predicted zero-scores (i.e., expected current nonusers). Perceived use utility, impulsivity, and femininity were not significant predictors of zero-scores. In contrast, perceived use utility be significantly positively associated with number of problems among expected users. Social norm, impulsivity, and gender be not significant predictors of number of problems among expected users. Full results of the regression analysis are presented in Table 2.

DISCUSSION

The results demonstrate that social norm and perceived use utility are related to nonuse and marijuana-related problems, respectively, among college students. The primary strength of this study is the use of ZINB regression to simultaneously predict current nonusers as well as the predicted count of marijuana-related problems among expected users. Differential results emerge in language of statistical predictors of nonuse versus predicted marijuana-related problems; in focused, social norms differentiated expected nonusers from users, while perceived marijuana use utility predicted the number of problems contained by users. These results generally are consistent next to models that propose social-environmental variables as being more associated next to use initiation and low-level use and biopsychological variables as being more associated next to use-related problems. However, it is important to document that such a result would not have be observable within the framework of the more traditional OLS regression analysis. Thus, the statistical modeling employed here study allowed for the emergence of theoretically consistent results.

Examining respectively set of predictors more closely, both social norms and perceived use utility be hypothesized to predict current nonusers. However, only social norm and not perceived use utility was a significant predictor of current nonusers. In previous research, use utility have been significantly associated beside use initiation (12). In the current study, use utility and social norms be fairly outstandingly correlated, which may have contributed to the observed difference surrounded by the results. Much like traditional OLS regression, ZINB regression is susceptible to problems beside multicollinearity, and these findings may be due to such a result.

As hypothesized, perceived use utility was associated beside number of marijuana-related problems among expected users. Previous cross-sectional research has observed significant association between perceived use utility and marijuana-related problems (12). The current study provides a partial replication of this relationship contained by a multivariate context.

Impulsivity was hypothesized to be significantly associated beside problems among expected users and to not be a significant predictor of current nonusers. However, impulsivity was associated marginally beside both the number of problems among expected users and the prediction of current nonusers (p's < .07). Thus, the pattern of relationships did not conform to the hypothesis.

Several limitations should be noted. Marijuana use be quite low within the sample. Although the rates be equal to that reported in national sample, the extent to which these relationships hold among samples near higher rates of use and problems will stipulation to be determined in future studies. Also, the token was predominantly women and White, and sweeping statement of the results to populations with different demographic characteristics desires to be determined. Finally, the cross-sectional analysis precludes causal interpretations. For example, longitudinal studies are needed to take to mean the relation between social norms and marijuana use behavior over time and, thus, examine the relative strength of social influence versus social test effects.

The current study employed ZINB regression to predict marijuana-related problems in a mixed distribution of current users and nonusers within a sample of college students. The analysis approach provides a parsimonious agency to analyze risk behaviors with low bottom rates. Furthermore, the analyses allowed for a theoretical separation of prediction of users versus nonusers, and predicted marijuana-related problems among predicted users. Results indicated that social norm predicted nonusers, while perceived use utility predicted the number of problems reported by expected users. Results generally be consistent with theories of the differential association of social-environmental variables and biopsychological variables near use and problems, respectively.

Assessing the service linkage of substance abuse agencies near mental health and primary caution organizations

INTRODUCTION

One of the major challenge facing the field of substance rough up treatment is the coordination of community-based services for clients with cooccurring mental or physical strength disorders (1). Given their multiple health desires, these clients often are required to involve yourself in in two or more specialized programs that involve providers in areas such as mental strength and primary care. As a result of this specialization, heaps policymakers and researchers have raise the concern that the substance abuse treatment system may be too fragmented to deliver forceful care (2, 3).

The fragmentation of community-based substance mishandle treatment became an issue within the 1980s when the plight of persons disabled next to serious cooccurring disorders was familiar as a burgeoning social problem (4). The issue has intensified in recent years as manage care have assumed a stronger presence in behavioral strength care and as an increasing numbers of individuals with substance name-calling, mental illness, and chronic condition problems such as HIV/AIDS have begin to be treated in outpatient settings (1). Treatment of these multineed individuals constitutes a major frustration among outpatient substance knock about treatment providers because many of these folks are revolving door clients who enter treatment, often discontinue impulsive, relapse, and recycle anew (1). Some researchers have suggested that within order to exhaust recidivism among these substance abuse clients, multiple types of treatment must be provided concurrently through better linkage of exactness between outpatient substance abuse treatment agencies (OSATs) and other service providers (1, 5-9).

Indeed, empirical evidence supports the worth of concurrent treatment. Joe and colleagues (10) showed that methadone clients had less relapse to opiate use when they received ancillary services, extremely mental health trouble. McLellan and associates (11) found similar results in a study of 649 opiate, alcohol, and cocaine patients. An evaluation of a combined substance verbal abuse and mental health skin management program also found a 31% downgrading in the number of days homeless for dually diagnosed people as compared to 6% in a typical service control group (12). More lately, Jerrell, Wilson, and Hiller (13) showed in a demonstration project that clients reception services through a well-implemented dual disorder treatment program functioned better in the community than clients not acceptance services from such a program.

These research findings notwithstanding, linking services from different health prudence sectors is considered problematic and is much understudied surrounded by substance abuse treatment (1). In individual, little is known more or less the pattern of service linkage that OSATs maintain beside mental health and primary nurture agencies. This study is intended to begin bridging this aperture by conducting an in-depth analysis of information collected from a national sample of OSATs that participate in the 1999 National Drug Abuse Treatment System Study. In addendum, it analyzes how the service linkages of OSATs are related to their organizational structure, client mix, and manage care taking part. Finally, it examines barriers to service linkage as perceived by OSAT managers.

Results of the study contribute to the literature and practice surrounded by the following ways. First, they provide, to the best of our knowledge, the first empirical assessment in relation to the extent of linkages that OSATs establish beside mental health and primary assistance providers. The information is essential for a clear understanding of how individuals beside substance abuse problems are treated surrounded by community-based outpatient settings, thereby verifying the point of fragmentation in substance mishandle treatment. Second, the study takes a nuanced belief and examines whether organizational and client factors are associated next to service linkages. It identify conditions under which the establishment of service linkage may be promoted or inhibited. Third, for health plans and policymakers concerned nearly fragmentation of the substance abuse treatment system, kind the barriers to service linkage from the OSATs' perspective may suggest useful intervention strategies.

METHODS

Study Design and Sample

The study be part of a research hard work to understand the network activities of outpatient substance swearing treatment units (OSATs) surrounded by treating multineed substance abuse clients. OSATs be defined as health effort facilities next to resources dedicated primarily (>50%) to treating individuals beside substance abuse problems, including alcohol and other drugs, on a nonresidential idea (14-18).

The OSATs included in this study be a stratified random taster selected from the National Drug Abuse Treatment System Study (NDATSS) conducted surrounded by 1999. The NDATSS contributed a sampling frame of 518 outpatient nonmethadone treatment units that have complete information on managed attention arrangements and clients. To ensure adequate variability in manage care association, which we anticipated might influence significantly the networking actions of OSATs, we stratified and sampled OSATs base on their size and extent of participation surrounded by managed strictness programs in 1999, categorized as "abundantly," "some," and "none." Creation of these categories took into picture the impact of managed vigilance on an OSAT's sources of funding and clients served. If an OSAT reported no involvement with manage care or if it have fewer than 10 clients, it be placed in the "none" category. The remaining unit were categorized base on the percentage of clients covered under manage care arrangements (both private and public). OSATs near 25% of clients or fewer covered below managed attention to detail arrangements were labeled as have "some" managed support involvement. Those with more than 25% of clients covered by manage care arrangements be labeled as having "a lot" of manage care involvement.

A total of 62 OSATs be selected and interviewed. The declaration to limit the taste to a small fraction of the total programs in NDATSS be based on practical concerns of research budget and survey effecting. The research project involved interviews with OSATs as in good health as mental health and primary trouble providers with which the OSATs be linked. It be anticipated that each OSAT might hold service linkages next to up to 6 care providers (3 surrounded by mental health and 3 within primary care). Thus a small increase in the number of OSATs sampled would significantly increase the number of organization that had to be interviewed.

Data Collection

The information collection occurred contained by 2001 using a telephone interview near a designated respondent at each OSAT. The respondent be either the component's director or an administrator/clinical supervisor who was in good health informed about the organizational structure and client services of the section. Based on a comparison of data from the 1990 NDATSS and the 1990 Drug Services Research Study, Friedmann and colleagues (19) showed that reports of unit-level administrator were a reliable source of information on OSATs' organizational features such as treatment volume and staffing.

Experienced interviewers, specifically trained in the rule of the survey, conducted the phone interviews. In addition, several steps be taken to ensure high part and validity of phone-survey information. First, the survey questionnaire was pretested next to a comparable sample of 10 OSATs and their nominated mental condition and primary care agencies that be not included in our study sample. Results and feedback from the pretest help to identify problems in the planned survey procedures, approaches, and interview content, and to refine question about how clients be obtained and referred between OSATs and other agencies. Second, prior to the phone interview, component directors were sent a missive explaining the study along with work sheets for their preparation of answers. Third, respondents be guaranteed confidentiality and feedback reports.

The interview gathered information give or take a few the unit's organizational setting, staffing, client mix, accreditation, revenue, manage care involvement, and services. Each respondent also be asked to name up to 3 primary thought organizations and up to 3 mental condition agencies that provided service to the OSAT's substance abuse clients, to describe the character of each of these service linkage (e.g., client referrals, information and resource sharing), and to indicate the barrier to working with mental strength and primary care agencies within general. The resulting background, therefore, described up to 6 interagency linkage in an OSAT's instant service network.

We chose to examine the service linkage with primary effort and mental health agencies for 3 reason. First, they served the most problematic clients of OSATs--that is, persons beside cooccurring mental or physical health problems--whose condition needs could be best met if their comorbidities be addressed concurrently. Second, these agencies be health related and be likely to be beneath the purview of managed supervision organizations. Third, developing and maintain the service linkages between OSATs and these agencies might be difficult (19). Thus, insight these important on the other hand potentially challenging relationships be critical. Setting 6 as the number of primary care and mental robustness agencies that an OSAT could nominate was base on our knowledge of OSAT's network activities and our experience within the pretest. Limiting the nominations also prevented unnecessarily overburdening the respondent and consequently helped ensure giant quality of the information reported.

Table 1 compares the organizational attributes and client mix of OSATs in the study token with those from the 1999 NDATSS. Thirty-nine percent of the OSATs in the study indication were freestanding; the remaining OSATs be part of a mental vigour center (26%), a multiunit substance abuse program (21%), or a hospital (14%). Most of the OSATs be private nonprofit (61.3%), 24.2% were for-profit and 14.5% public. The average number of full-time staff surrounded by OSATs was 24.9 and the average number of clients served within the past year be 915 (not reported in the table). In jargon of client mix, on average over 50% of clients served in the study's OSATs have dual diagnosis; of those clients, the majority either have mild mental health problems or have experience trauma such as physical or sexual abuse.

The study taste was similar to the NDATSS indication in vocabulary of organizational setting, ownership type, and client mix. Due to the stratified sampling used in the study and the positive correlation between managed attention involvement and organizational size, the study sample contained more larger OSATs and a smaller amount smaller OSATs (as indicated by the number of clients and full time staff) than the NDATSS sample overall. Thus, findings reported here article are generalizable to OSATs with a greater amount of managed consideration involvement, not to the NDATSS sample.

Measures

As mentioned above, the ID of service linkages be based on the designated OSAT respondent's report. Each respondent be asked to nominate up to 3 mental health and 3 primary exactness agencies that provided services to its substance abuse clients. To invasion the full impact of managed attention to detail, the survey included 4 questions to consider the OSAT's managed safekeeping involvement: "How many manage care arrangements does your element participate surrounded by (both private and public)?" "How many manage care contracts does your program enjoy?" "What percentage of your revenues come from managed diligence arrangements?" and "What percentage of your clients have services salaried for by managed diligence arrangements?" In addition, the survey included two question in relation to the perceived impact of manage care on service linkage: "As a result of managed meticulousness, has your program's relationship next to [the nominated organization] improved or deteriorated?" and "All things considered, [would you agree] that manage care have improved your program's skill to work with [the nominated organization]?"

The organizational attributes displayed in Table 1 be included as covariates in the analysis for service linkages between respectively OSAT and its nominated mental health and primary keeping agencies (20). The interview questions used to determine those covariates are available in the Appendix. To exhaust the small cell problem in the analysis and to conserve the statistical power for multivariate analysis, we collapsed some of the groupings presented in Table 1. Therefore, organizational setting referred to whether the OSAT be freestanding or was a subsidiary of a parent strength care union. Ownership type identified the for-profit versus nonprofit tax status of the OSAT. We also grouped the OSATs into 3 category based on the percentage of clients next to comorbidities--low (<25%), medium (25-60%), and high-ranking ([greater than or equal to] 60%). The groupings for the 2 indicators of OSATs' unit size--the number of FTE salaried staff (<10, 10-29, and [greater than or equal to] 30) and the number of clients served in the second year (<250, 250-599, >600)--remained the same.

Finally, respectively OSAT respondent was asked to assess the extent to which 17 specific financial and functioning conditions--including clients' financial ability, insurance reimbursement, and different program clientele--represented barrier to working with other agencies within meeting the strength needs of substance verbal abuse clients. Their assessment was reported base on a 5-point Likert scale range from "no extent" to "very great extent."

Analysis

Pearson correlation and chi-square analyses be first performed to assess the bivariate relationships of organizational attributes next to service linkages of OSATs. Based on these analyses, covariates near statistical significance at p < 0.30 were special for proportional odds logistic regression analysis to explain the service linkage of OSATs. Proportional odds logistic regression is a preferred analytic method for ordinal dependent variables (21).

The assessment of barrier to service linkages be based on the percentage of OSATs reporting that a specific condition be at least to some extent (including "some extent," "great extent," and "exceptionally great extent") a barrier to working beside other agencies in serving substance foul language clients.

RESULTS

OSAT Service Linkages

In general, a predetermined extent of service linkages be found in the study taste (Table 2). The average number of ties between OSATs and primary care and mental form agencies was 3.3. The majority of OSATs (59.7%) have 3 or fewer ties; OSATs beside 6 ties represented a distinct minority (6.5%).

The extent of service linkages diverse by type of external agencies. Results showed that OSATs had more links to mental form agencies than to primary care providers; this is possibly due to the certainty that among substance abuse clients treated within OSATs, cooccurring mental health problems (42%) and trauma experience (34%) be more common than physical form problems (14%), including pregnancy (Table 2).

Organizational Covariates of OSAT Service Linkages

OSATs varied surrounded by their organizational arrangements and client mix. We examined whether organization type, ownership, size and clients' health inevitability were associated beside the OSAT's linkages beside mental health and primary effort agencies. Results based on the chi-square analysis are presented contained by Table 3. (The chi-square results should be interpreted with forewarning because some of the cells own a small number of observations--i.e., an expected count of smaller quantity than 5). With the exception of percentage of clients with comorbidities, none of the organizational variables be correlated with total linkage or linkages near mental health or primary assistance providers.

The percentage of clients with comorbidities displayed a statistically significant correlation next to mental health linkage (Z2 = 10.92,p = 0.03). The result suggests a linear and positive relationship between the 2 variables; the number of ties that an OSAT had beside mental health agencies increased along next to the percentage of OSAT clients with comorbidities.

The impact of manage care on OSAT service linkage was assessed using both aim and subjective measures. First, OSATs' managed nurture involvement (based on the number of managed safekeeping arrangements, percentage of revenues from managed guardianship, and percentage of clients covered by managed watchfulness programs) was correlated next to the number of service linkages beside mental health and primary carefulness agencies. As Table 4 shows, none of the correlations was statistically significant, suggesting that manage care involvement be unrelated to the extent of OSATs' linkages next to external agencies.

Further, the designated respondent was asked whether he or she perceived any progress in the OSAT's service linkage in former times year as a result of managed assistance involvement. Results showed that the majority of OSATs (57.4%) perceived no change and that the percentage of OSATs detecting a refusal influence of managed strictness on their service linkages (26.2%) be higher than that of OSATs perceiving a positive impact of manage care (16.4%) (Table 5). Interestingly, a significant proportion of OSAT respondents (52.4%) disagreed or strongly disagreed that manage care have improved their service linkage with mental strength or primary care agencies, 32.8% perceived no difference, and one and only 14.7% experienced an improvement as a result of manage care involvement.

Finally, 3 proportional likelihood logistic regression models--one each for the total number of service linkage, the number of mental health linkage, and the number of primary care linkages--were run beside covariates that were correlated near any of the 3 service linkage variables at p<0.30 in the bivariate analysis. The covariates included number of managed supervision arrangements, percentage of clients covered by managed fastidiousness, freestanding (vs. subsidiary) organizational type, and percentage of clients with comorbidities.

As Table 6 shows, 3 covariates be significantly associated with the total number of service linkage in OSATs at p < 0.10. The coefficients for the number of manage care arrangements and percentage of clients next to comorbidities were positive, whereas the coefficient for percentage of clients covered by manage care be negative. One covariate-percentage of clients next to comorbidities--was significantly and positively related to the number of mental health linkage (p < 0.01), confirming the chi-square result in Table 3. For the number of primary care linkage, only one covariate--percentage of clients covered by manage care--was statistically significant (p < 0.05) and the coefficient was negative.

Perceived Barriers to Service Linkages

To assess problems associated near the creation and maintenance of service linkage between OSATs and external service providers, the designated respondents were asked to rate a detail of potential barriers to working beside other agencies in jamboree the health desires of substance abuse clients.

As Table 7 indicates, the cited reason were similar for mental condition and primary care agencies. However, several issues seem to be more problematic for mental health linkage: "client's ability to wages out of pocket," "client stigma," "caseload problems," "long waiting list," "insufficient staff," "insufficient discretionary funding," "mistrust," and "resource competition." It is interesting to entry that the 2 most frequently cited barriers to service linkages--"client's fitness to pay out of pocket" and "deficient insurance reimbursement"--were related to clients' financial ability to gain needed services. Managed care restrictions be considered to be a barrier to service linkage for about 60% of OSATs included in the study taster.

DISCUSSION

Fragmentation of the substance abuse treatment system is perceived to be a key problem in treatment for folks with cooccurring substance knock about, mental and physical disorders. A suggested solution is improvement of service linkage of OSATs with primary precision and mental health agencies (20). To know the extent of service linkages surrounded by OSATs and to identify correlates of and barriers to such linkage, we conducted an analysis of information collected from a sample of 62 OSATs. Results suggested a mosaic outlook of the substance abuse treatment system near either impossible or good word about the extent of service linkage depending on one's perspective.

The bad word was that we might still hold a long way to budge if linking OSATs with other vigour care providers be considered a solution to the reorganization of substance abuse treatment. The analysis indicated that a majority of OSATs have 3 or fewer linkage with any mental health or primary perfectionism agencies, suggesting that treatment of substance abuse might be fragmented as various researchers and policymakers had assumed. Also, the expertise of OSATs to work with other programs appeared to be fixed by managed consideration, which has have an increasingly strong presence in the behavioral health transfer system. While the multivariate analysis suggested mixed results associated with manage care involvement (depending on the estimate of managed watchfulness involvement and the type of service linkages examined), the majority of the designated respondents of OSATs disagreed (some strongly) that manage care have improved their service linkage. Moreover, a significant proportion of respondents cited managed attention to detail restrictions as a barrier to their collaboration near mental health and primary aid agencies in treating substance invective clients.

There was obedient news, however, essentially in that OSATs appeared to own adjusted their pattern of service linkages to the wants of substance abuse clients. Mental strength problems were more prevalent than physical illnesses among the clients treated at the OSATs surrounded by the study sample. Correspondingly, OSATs also have more service linkages next to mental health agencies than near primary care providers. Furthermore, the multivariate analysis showed that within OSATs with a difficult percentage of comorbid clients, a greater number of service linkages near mental health providers be established. Together, these findings suggested that OSATs might be responsive to client health requirements in service design, irrespective of the idiosyncrasy of their organizational structure and the degree of their manage care involvement.

Two other findings are outstanding. First, interviews with OSAT respondents indicated that of adjectives the reasons cited, clients' financial problems, including lacking insurance coverage, represented the most significant barrier to linkage with, and client referral to, mental health and primary thinking agencies. As proposals have be considered to move toward the parity of behavioral strength services with medical trouble in the design of robustness insurance benefits, it would be interesting to see if the proposed change would own any positive impact on interagency linkages and service integration in substance maltreat treatment. Second, a significant proportion of OSATs also cited organizational capacity and financial issues (e.g., caseload problems, long waiting list, insufficient staff, and insufficient discretionary funding) as limitations to linkages beside mental health and primary vigilance providers. With diminishing government funding during the current monetary downturn, the situation may be exacerbated, further fragmentizing health service confinement for individuals with substance assault problems.

This study represents an initial step toward a systematic examination of service linkage in OSATs surrounded by relation to their organizational attributes and managed attention involvement. There are several ways to extent this research effort. First, within addition to the extent of service linkage, there are other ways to takeover OSATs' interagency networking actions, for example, the degree of coordination, horizontal of trust, and amount of resources invested in the collaborative relationship. Questions also could be raised as to whether the most critical outcome is not the number of OSAT ties to other providers but the proportion of individuals reception needed primary care and mental vigour services. A few well-organized service linkage may serve clients as effectively as, or more effectively than, several linkages, outstandingly if the clients' health wants are relatively homogeneous. Alternatively, one could argue that multiple service linkages are mandatory because they allow on OSAT to identify appropriate referrals for finicky subgroups of substance abuse clients. Which of these arguments applies to substance ill-treat treatment is an empirical question that could be address in adjectives research.

It is important to transcribe that the extent of service linkages reported surrounded by this article was assessed from the vantage point of the OSAT. The existence and efficiency of the service linkages would necessitate to be corroborated by the OSAT's service partners. Arguably, it is with the sole purpose the mutually positive and intense relationships that contribute to effective service provision to multineed clients.

Location in a hospital, a mental health center, or a multi-substance harm program might introduce additional ebb and flow in how OSATs connect with external service providers. It might eat up the necessity for service linkages because of the resources and systematic support from the parent organization that allows onsite service integration in the OSAT. Alternatively, it might facilitate service linkage by mitigating the managed strictness burden or financial constraints on the OSAT. The small sample size contained by the study limited the statistical power to detect significant differences between these groupings, but this is clearly an big avenue for further research.

Managed care is not a monolith, however (15-17, 22); it might affect OSATs' service linkage in ways that are more complex than observed within this study. A research question worth investigating is whether and how the complexity and diversity of manage care's oversight mechanism may influence OSATs' decision to provide mental and physical form services either on-site or through collaboration near external service providers. Many of the OSAT respondents interviewed perceived a negative impact of manage care on service linkage. If the presence of managed fastidiousness in behavioral robustness services continues to grow and if the oversight mechanisms of manage care organization become more stringent, collaboration between OSATs and other health consideration providers is likely to be hampered. If equal changes simultaneously diminish OSATs' resources to provide services onsite, the access to care and treatment outcomes of substance misuse clients may be adversely affected. Further pains to clarify these relationships would enhance our understanding of the organizational constraints that service providers struggle next to in treating multineed substance harm clients.

Finally, OSATs' decision to collaborate next to other service providers may be contingent upon conditions in their organizational environments, such as the availability of mental health and primary nurture providers in the local flea market. Such environmental constraints need to be taken into explanation in directive to design feasible policy interventions to modernize substance abuse treatment, especially contained by nonmetropolitan and rural areas.

APPENDIX

Interview Questions Regarding Organizational and Client Attributes Organizational Setting

(1) What statement best describes your program?

a. This program is free standing. It is not part of a parent management that provides other types of services.

b. This program is part of a parent concern that primarily provides services other than substance treat roughly treatment.

c. This program is part of a parent running that primarily provides substance abuse treatment.

(2) If your program is module of a parent organization, is that parent managing a

a. hospital?

b. mental health center?

c. multi-program substance maltreat organization?

Ownership Type

What is the rates status of your program?

a. Public

b. Private, non-profit

c. For-profit

Unit Size

(1) How many full-time or full-time equivalent salaried staff, including consultants, are employed by your program?

(2) How many clients did your program serve within the past year?

Client Mix

What percentage of the clients that you enjoy admitted to your program enjoy been identified beside the following characteristics ...

a. both substance abuse and severe mental condition problems such as psychoses, schizophrenia, or severe depression?

b. both substance abuse and mild or moderate mental condition problems?

c. severe mental health problems such as psychoses, schizophrenia, or severe depression?

d. mild or moderate mental robustness problems?

e. substance abuse problems with the sole purpose?

f. HIV positive or have AIDS?

g. other severe medical problems?

h. pregnant woman?

i. hold experienced trauma such as physical or sexual abuse?

j. out of work and claiming benefit?

k. homeless?

l. involved in the criminal justice system?

Screening for substance use patterns among patients referred for a mixture of sleep complaints

There is a growing body of evidence suggesting that there is a significant relationship between substance invective and insomnia. For example, Brower et al. (1) found that the majority of alcoholic patients entering treatment reported insomnia-related symptoms, such as difficulty initiating and maintaining sleep. Similarly, Williams et al. (2) and Vitiello (3) report that beside increased use of alcohol, rapid eye movement sleep and sleep-onset latency halt and slow wave sleep and delayed night disturbances of sleep increase. Interestingly plenty, while many factor interact with insomnia, difficulty falling asleep is reported to be the most significant factor associated next to substance use (4). In addition, the use of any single substance (stimulants, depressants, narcotics, or other illicit drugs) or a combination of substances is associated next to sleep problems (5). While this relationship is well documented, the underlying piece of equipment between sleep patterns and drug and alcohol assault is not well embedded (5, 6). Therefore, the presence of insomnia should be viewed as a red flag to physicians and form care professionals, indicating that an assessment for drug and alcohol foul language is warranted

Sleep disturbances are apparent within person taking illicit drugs and alcohol (7) and hold been found to keep trying long after withdrawal from these substances have occurred. For example, Currie et al. (8), and Brower et al. (1) report that recovering alcoholics can experience significant sleep problems months after quitting drinking. Of significance is the certainty that Currie et al. (8) found that 50% of participants reported sleep problems prior to alcohol dependence beginning. In addition, Drummond et al. (6) report that contained by a follow-up study on alcohol-abstinent participants, some aspects of the recovering patients sleep still showed anomalous patterns after 27 months of complete stinginess. The same pattern of results is adjectives across different cultures.

For some, sleep disturbance can be so severe as to reverse treatment success and precipitate a relapse to addiction or dependence (9, 10). In certainty, Brower et al. (1) found that the presence of insomnia was the most significant factor predicting relapse. Similar findings are reported by Vitiello (3). Furthermore, bill from drug use can in itself induce assorted disruptions involving mood, sleep, and food intake, which further impede recovery (11). Consequently, Maher (9) suggests that vigilance is required when treating insomnia in patients next to drug and alcohol problems.

The relationship between drug abuse, alcohol mishandle, and insomnia further may be complicated by the presence of other psychiatric issues such as mood, anxiety, and depression. Other factors including lifestyle and behavioral customs also play a part (12). According to MacKenzie et al. (13), anxiety and depression could be considered as signs for alcohol relapse, which, in return, can verbs to negatively impact individuals' quality of sleep. Similarly, Foster et al. (14), Breslau et al. (15) and Foster and Peters (16) report a significant interaction between depression and insomnia among mildly, moderately, and severely dependent drinkers. A study by Roehrs et al. (17) found that sleep and mood effects appear to be associated near the reinforcing effects of alcohol as a hypnotic for insomniacs. This means that alcohol might be used as a self-medicating substance by individuals next to sleep problems. A cross-sectional study by Loyaza et al. (18) on medical students found a significant relationship between insomnia and the presence of psychiatric disorders. Interestingly, Loyaza et al. (18) also found gender differences within the type of insomnia reported. Females had more difficulties maintain sleep and males more difficulties with falling asleep next and waking up impulsive.

Furthermore, Johnson and Breslau (5) carried out a longtitudinal study to obtain background gathered from 13,831 adolescents next to psychiatric problems. The researchers found that the use of cigarettes, alcohol, and illicit drugs each be associated with reported sleep problems, internalization (e.g., depression and anxiety), and externalization tendency such as deviance and aggression. A similar study by Wong et al. (19) found that early sleep problems and precipitate onset of alcohol use, which are mediate by early presence of attention problems, anxiety, depression, and aggression surrounded by early childhood, are marker for later alcohol and drug use disorders. Therefore, sleep disturbance can provide the treating professional near information to better plan treatment for alcohol and drug abusers in the context of psychiatric issues. According to Pary et al. (20), the treating health professional wants to get to the root of sleeping problems by screening for medical, psychiatric, and sleep disorders, as all right as chemical dependency. The interaction of insomnia with substance use and psychiatric illnesses may further pose a treatment resist when dealing with medication. A survey of 311 physicians in the United States revealed that plentiful are reluctant to prescribe medication to insomniacs in the early taking back phase for fear of a denial interaction between medication and drugs or alcohol, which might be present in their system (21).

Screening for alcohol and drug related problems in primary care settings sleep disorders clinics is extremely crucial. For some, this setting might be the only place where on earth early detection can materialize. According to National Institute on Alcohol Abuse and Alcoholism (22), structured interviews and self-report measures are useful, inexpensive, noninvasive, and relatively accurate tools. These screening tools should be select based on staff experience and training, time constraints, and population characteristics; they also involve to be used on a consistent basis. While tons studies suggest that primary health settings potentially can play a significant role in the impulsive detection and intervention process (by using measures such as Michigan Alcohol Screening Test [MAST] and Drug Abuse Screening Test [DAST] screening tools), few doctors screen for substance and alcohol use (23, 24).

According to Statistics Canada (25-27), the overall percentage of individuals 15 years or older reporting illicit dependence be 0.7%, of which men reported 1% use and women 0.4% use. The reports from Statistics Canada identify that alcohol dependence among Canadian population was even highly developed (9%), of which 6.2% were categorized as slightly probable cases of alcohol dependence and 2.6% importantly probable cases of alcohol dependence. Statistics Canada also reported that males overall had a sophisticated alcohol dependency than women (9.5% of males vs. 3% females categorized as "slightly probable cases of alcohol dependence" and 3.8% males vs. 1.3% females categorized as "highly probable defence of alcohol dependence").

This particular study sought to examine substance use pattern among patients referred for a variety of sleep complaints. Based on the findings that sleep disorders next to or without a concurrent psychiatric disorder are closely associated next to substance disorders, higher rates of substance use pattern among patients with a variety of sleep complaints were to be expected.

METHOD

Participants (N = 46) be outpatients in a sleep disorders center within Ontario, Canada; 44% were manly and 30% were feminine, gender be unknown for 26%, mean age be 46 years. All participants be referred to the center for a variety of sleep-related complaints. Typically, here sleep center patients sought consultation for around various sleep complaints including sleep apnea, continuous positive airway pressure (CPAP) consultation for sleep apnea, restless legs syndrome, insomnia, daytime sleepiness/fatigue, narcolepsy, sleep-wake diary, parasomnias, or seizures. It should be noted however, that surrounded by this study participants did not specify the character of their sleep complaints. These complaints, however, are most likely representative of our own clinical taste. Thirteen cases were excluded from this study due to incomplete answers on the DAST and MAST.

Materials used here particular study included two brief screening tools for alcohol and drug use, namely the MAST and the DAST. All participant gave written informed consent to play a part in this study. A sleep medication physician met with adjectives the participants for a sleep consultation.

The MAST is a widely used weigh for assessing alcohol abuse. This question paper consists of 25-item questionnaire designed to provide rapid and potent screening for long-term alcohol-related problems. The MAST can be used in either a paper-and-pencil or interview format Seizer (51). The MAST score are divided into 3 categories, a win of 0-3 for "nonalcoholic," a score of 4 for "suggestive of alcoholism," and a ranking of 5 and above for "indicates alcoholism." According to Conley (28), the MAST measure is reliable and correlates outstandingly with DSM-IV (29) diagnostic criteria. Other studies arrived at similar conclusions in connection with the acceptable reliability and authenticity of the MAST (30-32). Various versions of the MAST hold been adapted to assorted populations and also have be found to be reliable and valid measures (33, 34).

The DAST test measures drug use and related problems. This 20-item instrument may be given as any self-report or in a structured interview. The DAST rack up is divided into 5 categories including (nonreported drug use), 1-5 (low even drug use), 6-10 (moderate level drug use), 11-15 (substantial rank drug use) and 16-20 (severe level drug use). It is constructed similarly to the early MAST and has be shown to have well-mannered validity, test-retest reliability, and elevated internal consistency (35-41). In addition, the DAST have been used within a variety of settings including the workplace (40), psychiatric settings (39), community form settings (36), as well as by common practice physicians (42). Furthermore, the DAST has shown to be potent in screening for drug rough up across diagnostic groups such as individuals with dually diagnosed mental condition problems (43) and adults with attention-deficit/hyperactivity disorders (38). According to Tassiopoulos et al. (44), though, confirmation of self-report disclosure on subjective test (such as the MAST and DAST measures) that rely on individuals' honest account of drug/alcohol use should be corroborated beside biochemical analysis (such as using urine samples).

RESULTS

Results of the MAST found that, overall, 76% of participants fell into "nonalcoholic" category, 11% fell into the "suggestive of alcoholism" category, and 13% of participant fell into the "indicates alcoholism" category. Out of a total of 20 male participant, 80% fell into the "nonalcoholic" category, 5% fell into the "suggestive of alcoholism" category, and 15% fell into the "indicates alcoholism" category. Out of 14 female participant, 86% fell into the "nonalcoholic" category, 7% fell into "suggestive of alcoholism" category, and 7% fell into the "indicates alcoholism" category.

Results of the DAST found that, overall, 65% fell into the "none reported" category, 33% of participants fell into the "low level" category, and 2% fell into the "substantial level" category. Out of a total of 20 mannish participants, 60% fell into the "none reported" category, 35% fell into the "low level" category, and 5% fell into the "substantial level" category. Out of a total of 14 womanly participants, 71% fell into the "nonreported" category and 29% fell into the "low level" category. Our study also found that 2% of participant fell into both the "indicates alcoholism" category on the MAST and "substantial level" category on the DAST.

Chi-square analyses were perform to compare the distribution of males and females across substance use categories on the MAST and the DAST. No significant differences be observed.

DISCUSSION

Consistent with the literature, our study found considerably sophisticated drug and alcohol use patterns among patients beside a variety of sleep complaints than in the broad population. Related to this, our study found that overall, 24% had alcohol problems, of which 13% of participant had alcohol dependence, compared next to 2.6% from Statistics Canada; our study found that 2.2% of participants have drug dependence, compared with 0.7% from Statistics Canada (25-27). These findings support our hypothesis that folks with diverse sleep-related problems are more likely to enjoy substance use issues because alcohol and drug use is likely to negatively impact sleep power. Given these significant findings, sleep medicine physicians and primary comfort physicians should consider routinely using brief screening tools such as the MAST and the DAST for assessing alcohol and drug patterns among their patients.

With respect to masculinity differences, and consistent with Statistics Canada (25-27) reports, our study found high drug and alcohol use patterns among males than females. A cutting of our study was that the preview size was small, limiting the knack to apply the findings to the general sleep disorders population. Related to the small preview size, the number of males and females limited our wherewithal to make shrewd comparisons. One might consider for future hint how findings differ along gender lines.

Another reduction is the use of self-report questionnaires. The issue of social desirability other needs to be considered within self-report questionnaires that do not contain acceptability scales (impression management) as some individuals downplay their symptom picture. This might be especially relevant when asking sensitive questions in the order of alcohol and illicit drug use because of its attached social stigma and the fact that illicit drug use is illegitimate in Canada.

Thus, individuals may hold vested interests in concealing their drug use. In addition, individuals who are in denial of their substance use problems may also not provide an accurate picture of their substance use patterns. These same factor also may account for the fairly high percentage of individuals who did not fully complete the questionnaire.

Another limitation of this study is that this study did not examine the possible role that psychiatric factor might play in mediate between substance use and sleep related problems. The role of psychiatric issues warrants further investigation.