Alcohol and Alcoholism Vol. 35, No. 1, pp. 60-65, 2000
© 2000 Medical Council on Alcoholism
A COMPARISON OF SUBSTANCE USE BETWEEN FEMALE INMATES AND FEMALE SUBSTANCE MISUSERS IN TREATMENT
University of Oklahoma Health Sciences Center, 800 NE 15th Street, Suite 410, Oklahoma City, OK 73104 and
1 State of Oklahoma Department of Corrections, Oklahoma City, OK, USA
Received 6 November 1998; first review notified 17 May 1999; accepted 20 May 1999
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ABSTRACT |
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Recent literature documents extensive substance misuse histories among US female prison inmates. The primary purpose of the present study was to determine whether histories of personal and familial substance misuse distinguished female inmates from substance misusers in treatment. After accounting for drug-related offences, we hypothesized that the inmates would have more extensive histories of personal and familial substance misuse and that they would have initiated substance use at an earlier age. Contrary to our expectations, the two samples were similar on many measures of alcohol and drug use. Similarly, differences in family histories of substance misuse were not in the predicted direction. As hypothesized, however, the inmates did report earlier age at onset of drinking. Of particular clinical relevance was the finding that, despite similar alcohol consumption levels, inmates reported fewer alcohol-related adverse medical, legal, and psychosocial consequences than did the treatment sample.
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INTRODUCTION |
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TOPFOOTNOTESABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSREFERENCES |
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Cultural expectations as well as empirical data suggest an association between substance use and criminality, even if crimes such as trafficking illegal substances are disregarded (Maguire and Pastore, 1996
; Zhang et al., 1997). Numerous studies report high prevalence rates of lifetime alcohol and drug misuse among inmate populations in the USA (e.g. Abram, 1989; Smith and Newman, 1990; Abram and Teplin, 1991; Teplin, 1994). Males represent the majority of inmates and thus constitute the subject population for most studies. However, across the USA, female inmates are increasing at a faster rate than male inmates (Gilliard and Beck, 1998). This changing distribution increases the importance of focusing on or including female subjects in the study of substance misuse and criminality. Although few studies have examined substance misuse in female prison inmate populations, the exceptions have consistently reported extensive substance misuse histories (e.g. Blount, et al., 1991; Eronen, 1995; Jordan et al., 1996; Marcus-Mendoza and Briody, 1996; McClellan et al., 1997). Given the prevalence of substance misuse in inmate samples, it is tempting to conclude that there is a direct relation between substance misuse and criminality. However, not all substance misusers serve time in jail. Identifying distinguishing characteristics of incarcerated and non-incarcerated substance misusing women may aid in the development of more effective intervention and treatment efforts. One question particularly relevant to early prevention and intervention efforts is whether aspects of personal or familial substance misuse histories serve to differentiate incarcerated from non-incarcerated women. Thus, the primary purpose of this study was to compare personal and familial substance misuse histories between female prison inmates and female substance misusers recruited from treatment units.
Based on the literature, we constructed three hypotheses. The first hypothesis was that the inmates would have more extensive substance misuse histories than the treatment sample. This hypothesis was based on data linking the severity of substance misuse to several measures of criminality, such as rate of prior arrests and incarcerations among female inmates (Blount et al., 1991) and on the assumption that more extensive substance misuse would lead to more severe consequences, such as incarceration. Our second hypothesis was that the inmates would have an earlier age of onset for alcohol and drug use. This hypothesis was based on prior research documenting an inverse relationship between severity of substance misuse and age at first arrest (Blount et al., 1991) and an association between antisocial personality disorder and criminal behaviour often characterized by early onset of alcohol and drug abuse (Randolph and Yates, 1993). Our third hypothesis was that inmates would be more likely to report extensive family histories of substance misuse, although we expected both samples to report high rates. This hypothesis was based on the increased risk for temperament traits, such as behavioural disinhibition among children of alcoholics (COAs) compared to non-COAs (Sher, 1991). In summary, we expected that the inmates would have more extensive personal and family histories of substance misuse and would have initiated substance misuse at an earlier age than did the treatment sample.
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METHODS |
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TOPFOOTNOTESABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSREFERENCES |
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Participants
Inmate participants were 164 women recruited from the Mabel Bassett Correctional Center in Oklahoma City, OK, USA between July 1994 and December 1995. This 333-bed state prison for women houses minimum-, medium-, and maximum-security inmates. Inmates were recruited in small group sessions at which trained research assistants explained the nature of the research. Participation was voluntary and uncompensated as required by state regulations. A history of substance misuse was not an inclusion criterion for participation in the incarcerated sample.
Of the 164 inmates, 161 reported a primary offence for their current incarceration. Primary offences were categorized as violent (e.g. murder, manslaughter, child abuse, assault, robbery), property (e.g. burglary, larceny, motor theft, arson, fraud, stolen property), drug-related (e.g. possession, trafficking), public order (e.g. weapons, prostitution), and other. One-half (50.9%) of the inmates were incarcerated for a violent offence, 24.8% for a property offence, 21.7% for a drug-related offence, 0.6% for a public order offence, and 1.9% for other types of offence. Because a minority of inmates were incarcerated on drug-related charges, the entire inmate sample was combined for analyses, unless otherwise indicated.
The comparison group was a sample of 164 female substance misusers. The 164 participants were selected randomly from a database of 480 female participants recruited from chemical-dependency treatment facilities between January 1994 and December 1996. These data were collected as part of the screening procedures for an on-going study of cognitive deficits associated with polysubstance misuse. Participation was voluntary and participants were not paid for participation in the screening phase of the project from which the database was constructed.
All participants provided written informed consent prior to participation. Procedures to protect confidentiality were explained carefully to all prospective participants. This project was approved by the University of Oklahoma Health Sciences Center Institutional Review Board.
Materials and procedure
All participants were administered a battery of penciland-paper questionnaires in groups. Inmates were tested in the prison and treatment participants were tested in the treatment facilities. The battery consisted of demographic information, the Beck Depression Inventory (BDI; Beck et al., 1988), the Spielberger State–Anxiety Inventory (AI; Spielberger, 1983), the Shipley Institute of Living Vocabulary and Abstraction Scales (SILS-V, SILS-A; Zachary, 1986), substance misuse histories, and a detailed four-generation family history tree of substance misuse adapted from Mann et al. (1985).
Substance misuse history
Alcohol histories included the Quantity Frequency Index (QFI; Cahalan et al., 1969) for the 6 months prior to treatment or incarceration, problem-drinker status, ages at first alcohol consumption and first intoxication, and lifetime alcohol-related consequences. The QFI is a measure of quantity and frequency of alcohol consumption that estimates the average number of ounces of absolute ethanol consumed per day. Problem-drinker status involved a self-report of whether the participant considered herself to be, now or ever have been, an alcoholic or problem drinker, and, if so, for how long (chronicity). All participants, regardless of problem-drinker status, were asked to report whether they had ever experienced any of a list of 10 alcohol-related consequences. These self-reported lifetime consequences of alcohol abuse were dichotomously coded for presence vs absence and then divided into three categories. Specific consequences by category were as follows. (1) Psychosocial consequences, these were marital or relationship problems, job problems, disapproval of family or friends, abusive behaviour, and attendance at Alcoholics Anonymous meetings. (2) Medical consequences, these were severe withdrawal, cirrhosis, black-outs, and passing out. (3) Legal consequences, these were arrests. The terms passing out and black-outs are commonly used phrases in the USA. Passing out refers to the behavioural phenomenon of an alcohol-related sleep-like state. This state contrasts with black-outs, which are conscious states during which the individual engages in typical or normal behaviours, but for which he or she later has no memory. In either case, no reference to underlying physiology or aetiology is intended. Illicit drug-use histories included queries as to whether illicit drugs had been used, the respondent's drug of first choice, and years of use.
Family history
Participants completed a four-generation family tree by indicating whether family members never used alcohol, were social drinkers, had an alcohol problem, a drug problem, both an alcohol and drug problem, or that the substance-use history was unknown regarding the family member. Participants were instructed that the only criterion for endorsing a relative's alcohol or drug problem was the participant's subjective opinion.
Four types of family-history analyses were conducted (Alterman et al., 1987; Tivis et al., 2000). First, family history positive (FH+) for substance abuse was defined as one or more primary relatives or three or more secondary relatives reported by the participant to have an alcohol, drug, or alcohol and drug problem. Participants reporting a positive family history were further classified according to family members' type of substance problems: alcohol, drug, or both alcohol and drug. Across all methods of considering family history, family members labelled unknown were grouped as if they had no substance misuse problem. This approach results in a conservative estimate of FH+.
Second, to assess lineality of substance misuse, percentages of participants reporting the presence of substance misuse in mother only, father only, or both parents were calculated. Third, a multigenerational classification of family history of substance misuse (alcohol and/or drug) included: (a) single generation (FH+SG; self only, no substance misusing parent); (b) double generation (FH+DG; self, at least one substance misusing parent, and no substance misusing grandparents); (c) triple generation (FH+TG; self and at least one substance-misusing parent and one or more substance-misusing grandparents). Fourth, a quantitative classification was made by assigning 1 point for each primary relative and 0.5 point for each secondary relative with a substance misuse problem. To account for differences in family size, point totals were divided by the total number of family members.
Race
Because the two samples differed in racial composition, 
2 (4, n = 328) = 41.19, P = 0.001, comparisons were made to determine if selected variables differed as a function of race. Because of the small number of participants representing some minorities, racial groups were collapsed into ‘white’ and ‘non-white’. The non-white group included all subjects self-identified as African American, Hispanic, Native American, and other. Table 1 depicts the racial composition of both samples. Although the analyses were based on a dichotomous classification, percentages of each racial group comprising the non-white category are provided in Table 1.
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Statistics
Between groups comparisons were analysed with independent t-tests and
2-tests, as appropriate. Due to the exploratory nature of this study, 
was set at a traditional level of 0.05, although multiple tests were conducted. |
RESULTS |
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TOPFOOTNOTESABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSREFERENCES |
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Demographic and psychosocial variables
These are presented in Table 2
. The inmates were younger than the treatment sample [t(325) = 3.96, P = 0.0001]. The two samples reported equal years of education, but the inmates scored lower than the treatment sample on the SILS-V [t(313) = 4.49, P < 0.0001] and SILS-A [t(184) = 2.05, P = 0.04]. The inmates scored lower than the treatment sample on the AI [t(300) = 4.53, P < 0.0001], and slightly, though not significantly, lower on the BDI [t(325) = 1.81, P = 0.07]. Group means were not clinically significant on any of the affective measures.
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Alcohol variables
Alcohol variables are presented in Table 3
. The inmate and treatment samples were similar for many alcohol variables. The QFI and years of regular alcohol use did not differ between the samples [t < 1; t(183) = 1.59, P = 0.1136]. Both samples reported their first alcohol consumption at age 12 years. However, the inmates were younger than the treatment sample at the age of their first intoxication, [t(289) = 2.07, P = 0.04]. Surprisingly, the treatment sample reported more psychosocial [t(304) = 9.14, P < 0.0001], medical [t(303) = 7.84, P < 0.0001], and legal [t(304) = 2.64, P = 0.009] consequences than did the inmates. The treatment sample also reported more inpatient treatment for substance misuse than the inmates [t(287) = 6.01, P < 0.0001].
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Problem drinkers
Despite reporting similar quantities of alcohol consumed, the two samples differed in the number of participants self-reporting as ‘problem drinkers'. Only 34% of the inmates reported being ‘problem drinkers' whereas 66% of the treatment sample endorsed this status [
2 (1, n = 321) = 35.69, P = 0.001] (Table 3
). Therefore, data on alcohol variables were reanalysed using only the participants from each group who reported being a ‘problem drinker’. These data are depicted in Table 4. Using these restricted samples, the differences between the two groups on drinking histories were found to be greater. Inmates had higher QFIs than the treatment sample, [t(146) = –2.42, P = 0.02], although chronicity did not differ. The inmates were younger than the treatment sample at both age of first drink [t(157) = 2.29, P = 0.02] and age of first intoxication, [t(156) = 3.00, P = 0.003]. Although drinking less and starting at a later age, the treatment sample ‘problem drinkers' reported more psychosocial [t(157) = 4.96, P < 0.0001] and medical [t(156) = 4.12, P = 0.0001] consequences than did the inmate ‘problem drinkers' (Table 4).
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Illicit drug use
Inmate and treatment samples reported similar illicit drug-use histories. The proportion of treatment sample (78%) and inmate (71%) participants reporting a history of illicit drug use did not differ [
2(1, n = 328) = 1.95, P = 0.16]. Excluding the 35 inmates reporting a drug-related primary offence (i.e. possession or trafficking) from this comparison did not change the proportion of treatment sample (78%) and inmate (70%) participants reporting a history of illicit drug use [2(1, n = 293) = 2.6, P = 0.11]. Both samples reported similar drugs of choice. The majority of inmates and treatment sample participants reported stimulants as their drug of first choice (60 and 59%, respectively), followed by marijuana (26 and 20% respectively), depressants (12 and 17%, respectively), and other (3% for both samples). Inmates reported illicit drug use for a mean of 8.74 years (SD = 5.91) compared to 12.29 years (SD = 11.98) reported by the treatment sample [t(134) = 1.72, P = 0.09].
Family history
Family-history data are presented in Table 5. Both samples reported extensive family histories of substance misuse, but significantly more of the treatment sample reported positive family histories of substance misuse than did the inmate sample. Further, the majority of both samples reported a family history of both alcohol and drug problems.
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When family size was accounted for by dividing the number of substance-misusing family members by the total number of family members, the inmates reported more substance-misusers among their family members. That is, although fewer inmates met criteria for FH+, the inmates reported a greater density of familial substance misuse, than did the treatment sample. The two groups did not differ on the number reporting a substance misusing mother only or a substance misusing father only, but significantly more treatment sample participants than inmates reported that both parents were substance misusers. The groups differed significantly according to a multigenerational classification of family history of substance misuse.
Because our conservative family-history approach classified unknowns as not having an alcohol or drug problem, the question arose as to whether more treatment sample participants were FH+ because they had greater knowledge of their family members. For this reason, we compared the percentage of relatives reported unknown for the two samples. The treatment sample responded unknown to a significantly smaller percentage of primary (M = 2.3% vs M = 9.9%) and secondary relatives (M = 21.6% vs M = 32.6%) than did the inmates [t(326) = –4.19, P < 0.0001 t(326) = –3.4583, P = 0.0006 and respectively].
Race
As previously mentioned, the racial composition of the two samples differed. For this reason, comparisons between whites and non-whites were made to determine if race accounted for observed differences between the inmate and treatment samples. White and non-white participants did not differ in years of education [M = 11.9 years for whites and M = 11.7 for non-whites, t(323) < 1] or QFI [M = 6.3 for whites and M = 6.0 for non-whites, t(296) < 1]. White and non-white participants differed on percentages self-reporting as ‘problem drinkers' [58% of whites and 42% of non-whites, 2(1, n = 321) = 8.08, P = 0.004] and white participants (M = 7.3) reported more alcohol-related negative consequences than non-white participants [M = 6.3, t(316) = 2.13, P = 0.03]. White participants reported a younger age at first alcohol consumption (M = 11.9) than non-white participants [t(296) = –2.6, P = 0.01], but not at first intoxication, [t(289) = –1.7, P = 0.09]. White and non-white participants differed in reported drug of first choice [2(4, n = 274) = 39.8, P = 0.001]. White participants' drug of first choice was distributed across marijuana (24%), cocaine (19%), amphetamines (24%), and other (20%). A majority of non-white participants (55%) reported cocaine as the drug of first choice, followed by marijuana (16%), amphetamines (10%), and other (10%). White and non-white participants did not differ in the percentage reaching criteria for FH+. Eighty-four per cent of white subjects and 88% of non-white participants were classified as FH+ [2(1, n = 328) = 1.03, P = 0.31].
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DISCUSSION |
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TOPFOOTNOTESABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSREFERENCES |
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These data suggest a remarkable similarity between female inmates and women in chemical-dependency treatment facilities on personal substance-use histories, including their alcohol consumption and reported drugs of choice. Thus, it is noteworthy that no category of substance was differentially associated with incarceration. Despite these similarities, several differences were noted that may be relevant to treatment or intervention.
Family history
Although both groups reported extensive family histories of substance misuse, a greater percentage of the treatment sample met criteria for FH+. However, a comparison of the percentages of family members with an unknown substance-use history suggested that the higher rate of FH+ among the treatment sample may have been an artifact of differences in knowledge about family members. Even given this bias in the family-history description, the inmates reported a greater density of substance misuse within their families. Thus, a high density of substance-misusing family members was associated with incarceration.
Perceptions
Although the two groups reported similar alcohol consumption, fewer inmates (34%) than participants in the treatment sample (66%) identified themselves as ‘alcoholics or problem drinkers’. When data for only the participants endorsing ‘problem drinker’ status were compared, these inmates reported consuming on average 6 oz. of pure ethanol more per day than the equivalent treatment subgroup. Interestingly, the inmates reported fewer alcohol-related consequences than did the treatment sample.
Several explanations may account for these differences. Subjects in the treatment sample may have been influenced by their treatment experiences in acknowledging the problematic nature of their drinking. The inmates may have been unable or unwilling to acknowledge the problematic nature of their alcohol use, in spite of experiencing serious problems associated with drinking. Alternatively, alcohol-related consequences among the inmates may have appeared trivial relative to their non-alcohol-related problems, and thus resulted in their failure to note the association. Whatever the reason, the dissociation between use levels and the perception of negative consequences suggests that substance misuse treatment relying on participants' acknowledgement of this association may be relatively ineffective in this group.
These results are consistent with the report by El-Bassel et al. (1998) on female inmates who completed the University of Rhode Island Change Assessment Scale (URICA). The majority of inmates in their sample were classified in the ‘denial cluster’. Similar to our inmate sample, the ‘denial cluster’ failed to acknowledge the association between negative consequences and their behaviour. Taken together, these studies identify a common area of challenge in addressing substance misuse treatment with female inmates. Further research addressing readiness to change (DiClemente and Prochaska, 1985; DiClemente and Scott, 1997) and motivation enhancement techniques (Miller and Rollnick, 1991) within this population may be fruitful.
Limitations
Differences in many of the self-report variables may be a function of temporal or environmental differences between the samples. For example, temporal differences between the period of interest (the 6-month period prior to treatment or incarceration) and the time of report probably differed between the two samples. That is, treatment samples generally were reporting recent events, whereas inmates reported more distant events. Environmental differences may have differentially affected participants' truthfulness in answering sensitive questions, such as those pertaining to illegal drug activity. Similarly, affective measures may be a function of temporal and environmental differences. However, the similarities between the two samples diminishes our concerns about the impact of temporal and environmental factors.
In summary, these data did not support our hypotheses that the inmates would have more extensive substance misuse histories, either personal or familial, than the treatment sample. Of clinical relevance, however, was that inmates were less likely to perceive a relation between substance misuse and adverse consequences. This observation suggests in particular a need for prison-based treatment programmes to emphasize the link between substance misuse and negative consequences, to encourage inmates to examine the role of substance use in their offending, and to foster the development of support networks during and after incarceration.
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ACKNOWLEDGEMENTS |
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This project was supported by NIAAA Grant No. R01 AA09163 to Dr S. J. Nixon and a College of Medicine Alumni Research Foundation Award to Dr B. Pfefferbaum. J.A.P. was supported by a NIDA Institutional Training Grant (Frank Holloway, PI). The authors gratefully acknowledge Warden Neville Massie, the staff and inmates of the Mabel Bassett Correctional Center, the staff and clients of the participating treatment units, and the research assistants who administered the protocol.
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FOOTNOTES |
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* Author to whom correspondence should be addressed.
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