Where have they been? Service use of regular substance users with ...

Soc Psychiatry Psychiatr Epidemiol (2006) 41:470–479

DOI 10.1007/s00127-006-0044-4

ORIGINAL PAPER

Axel Perkonigg Æ Angela Settele Æ Hildegard Pfister Æ Michael Ho¨fler Æ Christine Fro¨hlich Petra Zimmermann Æ Roselind Lieb Æ Hans-Ulrich Wittchen

Where have they been? Service use of regular substance users with and without abuse and dependence

Accepted: 30 January 2006 / Published online: 25 March 2006

j Abstract Objective To present lifetime rates of service use for psychological and substance use related problems among regular substance users and to examine factors associated with service use. Method Data come from a prospective-longitudinal, epidemiological study of a community sample of adolescents and young adults (n = 2548, age 14– 24 years at baseline) in Munich, Germany. The Munich-Composite International Diagnostic Interview (M-CIDI) was used at baseline and at two follow-ups to assess substance use and service use. Results Cumulated lifetime incidence of any substance abuse or dependence was 43.7%. Of those with abuse and dependence 23% had ever used any services for psychological or substance use related problems. Illicit substance users especially those with dependence had the highest rates of lifetime service use (52.1%). Psychotherapists and counseling services were contacted most frequently among regular substance users over their lifetimes. Utlilisation rates of substance abuse services were low (2%). Comorbid anxiety disorders and distressing life events were associated with increased lifetime service use. Conclusions Only a minority of adolescents and young adults with substance use disorders have ever sought professional help. Specialized substance abuse ser-

A. Perkonigg, PhD Æ A. Settele, Dipl. Soz., MPH C. Fro¨hlich, Dipl. Psych P. Zimmermann, Dr. rer. nat. Æ H.-U. Wittchen, PhD Technische Universita¨t Dresden Dresden, Germany

SPPE 44

A. Perkonigg, PhD (&) Æ H. Pfister, Dipl. Inf. M. Ho¨fler, Dipl. Stat. Æ R. Lieb, PhD Æ H.-U. Wittchen, PhD Max-Planck-Institute of Psychiatry Clinical Psychology and Epidemiology Kraepelinstraße 2-10 80804 Munich, Germany Tel.: +49-89/30622-244 Fax: +49-89/30622-244 E-Mail: [email protected]

vices play only a minor role. The core role of psychotherapists and non-substance abuse specialized services needs critical research attention. Linkages between psychotherapists and the substance use service system should be strengthened to detect and intervene at early developmental stages of abuse and dependence. j Key words substance use disorders – help-seeking – service use – epidemiology – anxiety disorders

Introduction Despite the high prevalence of substance use disorders, relatively low rates of service use for psychological or substance use related problems have been reported in epidemiological studies of the general population [1–4]. The recently conducted National Comorbidity Survey Replication (NCS-R) revealed a 12-month mental health service use rate of 19.6% among those with alcohol dependence and 30.4% among those with drug dependence. Alcohol abuse (12.8%) and drug abuse (15.5%) had lower rates [3]. Specifically, for substance use related care, high levels of unmet need have been reported from the US-National Household Survey on Drug Abuse (NHSDA). Only 6% of those reporting any substance use problem in the past year had used substance abuse services. Among those with co-occurring mental syndromes, up to 18% received these services [5]. More recent data from the US-National Epidemiological Survey on Alcohol and Related Conditions found substance use treatment-seeking rates of 5.8 and 13.1% among those with 12-month alcohol use disorders or drug use disorder, respectively [6]. But lifetime rates are considerably higher. Using projections for anticipated future treatment seeking, Kessler

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et al. [7] found that between 50 and 85% will ever seek any professional help or help from self-help groups, yet this service use appears to occur a decade or more after the onset of symptoms. In other countries a wider range of pathways or barriers to access of care have to be taken into account. The European College of Neuropharmacology which assessed service use in 26 European countries, found that 8.3% of those with alcohol use disorders had talked to a medical doctor or other professional about problems with emotions or mental health in the past 12 months [8]. In Germany, with relatively free access and few financial barriers to care, 29% with any substance use disorder in the last 12-months had received at least minimal interventions for psychological or substance related problems [9]. Number of comorbid diagnoses was associated with significantly higher rates of service use. Generally, use of services among those with mental or substance use disorders has been linked to sociodemographic factors (gender, marital status, education, and race) [10–12], socioeconomic factors (insurance systems and health systems) [13, 14], psychosocial [15], social [16], and medical factors (additional somatic problems) [17] as well as factors related to mental or substance use problems itself (e.g., type of disorder, severity, comorbidity, and impairment) [2, 18, 19]. Among those with substance use disorders, specific clinical characteristics including a higher severity of dependence [7, 20], more family substance use behavior [21], earlier onsets of substance use [7], and comorbid mental disorders [19] were associated with service use. The relatively infrequent use of services by individuals with substance use problems is not well understood. Perceived need [22, 23] has been suggested as a key construct, which in particular might be low among substance users. Alternatively, a behavioral model of health service use [24] has been used to identify core predictors while the multistage model of Prochaska et al. [25] describes processes involved in the motivation for service use in different stages. Yet, many questions remain. Most findings from epidemiological studies focus on substance use disorders and do not differentiate between users with abuse or dependence and users with other use patterns. This lack of focus on other groups, such as those with regular or harmful use makes it difficult to examine the specific role of abuse and dependence symptoms on service use, compared with the potential impact of other substance use patterns as they relate to service use. In addition, few epidemiological studies account for differences between substances in the use of services. Clinical studies have included users of specific types of substances, yet these findings are limited in that results are not generalizable to the community. Finally, existing published epidemiological data on service use among individuals with substance use disorders often do not cover the full range

of available services or the full lifetime period of service use. Yet, data on lifetime use of all services are necessary for planning of early allocation strategies for interventions and the appropriate distribution of resources. To address this gap we will expand our recently reported epidemiological findings on prevalence and incidence of regular substance use and substance use disorders among adolescents and young adults from a randomly sampled German community cohort (Perkonigg et al. submitted) by reporting results on service use among regular substance users of a wide range of substance and use categories focusing on the following questions: (1) How many regular substance users with or without abuse or dependence have ever used services for psychological or substance related problems? (2) Which specific services are used? (3) Which factors are associated with service use? (4) What is the role of age-specific cumulative incidence rates of dependence and comorbidity in service use?

Methods j Sample and overall design Data were collected as part of the Early Developmental Stages of Psychopathology (EDSP) study. Objective, sample, and design have already been reported elsewhere [26, 27]. Briefly, the EDSP is a longitudinal epidemiological community study to explore prevalence and incidence, familial and other risk factors, and comorbidity and course of substance use and substance use disorders in a representative population sample of adolescents and young adults. The study is divided into three waves, the first conducted in 1995 (baseline, with all 14–24-year-olds; n = 3021), the second in 1996 or 1997 (only with the 14–17-year-olds at baseline: n = 1228), and the third in 1998 or 1999 (again with all 14–24-year-olds at baseline; n = 2548). The community sample was randomly drawn from government registries in Munich, Germany. As the study was designed as a longitudinal panel with special emphasis on EDSP and substance use disorders, 14–15-year-olds were sampled at twice the probability of people 16–21 years of age, and 22–24-year-olds were sampled at half this probability. All participants provided informed consent. At baseline, a total of 3021 interviews were completed, resulting in a response rate of 71%. The first follow-up study was conducted on average 19.7 months (range = 15– 25.6 months) after the baseline study with a response rate of 88%. Only the younger cohort (14–17-year olds at baseline) was included in this wave. The second follow-up was conducted in 1998 or 1999, an average of 42 months (range = 34–50 months) after baseline with a response rate of 84% (n = 2548) among all baseline participants. Sociodemographic characteristics of the baseline and follow-up samples have been published [27]. Briefly, at baseline, most of the respondents were attending school (89%) and living with their parents (98%); about 10% were in job training. The majority was classified as belonging to the middle class (61%). Noteworthy changes in sociodemographic characteristics from baseline to second follow-up were found for school (follow-up: 42% attended school) and employment status (follow-up: 24% were in job training program and 12% were employed).

472 j Instrument

j Assessment of service use

In all three waves, the computer-assisted version of the MunichComposite International Diagnostic Interview (M-CIDI) was used [28]. The M-CIDI allows for the standardized assessment of symptoms, syndromes, and diagnoses of a wide range of DSM-IV substance use and mental disorders along with information about onset, duration, as well as clinical and psychosocial severity during a personal interview. In all assessments the M-CIDI was supplemented by a separate respondents’ booklet that included several scales and questionnaires for assessing psychological constructs relevant to the study. For the purpose of this examination we additionally used a self-competence scale, which assesses the persons ability to cope with several problems (i.e., problems with friends) [29], the Munich Event list (MEL) covering 11 dimensions of life events (i.e., family dimension: parents separated) [30] and a Daily Hassles Scale [31], assessing the frequency of daily hassles in different areas (i.e., school or work), as well as a sub-scale from a proven questionnaire on health behaviors [32]. Detailed information on the validity and reliability of the M-CIDI has been described elsewhere [33, 34]. Test–retest validity of the M-CIDI was fair to good, with kappa values ranging from 0.64 (Yules Y = 0.80) to 0.78 (Yules Y = 0.82). For the two follow-up investigations, the M-CIDI was modified to cover the interval between the investigations with additional questions about the course since the preceding investigation.

The final section of the M-CIDI probes for the use of any kind of services because of psychological or psychiatric problems since the last assessment (or lifetime at baseline). Substance use related problems were not excluded, if the participants reported any substance use related service use (at the second follow-up all participants were additionally asked about service use because of substance use related problems). If the proband affirmed the use of any services a list of 30 in-patient services (e.g., psychiatric, psychosomatic, specific substance use related hospitals, and specific homes) and out-patient services (e.g., psychiatric ambulances, psychiatrists, and physicians) as well as out-patient counseling services (e.g., counseling services for substance use related problems, school problems, and problems with partner or family) was presented. All contacts with the specific types of services were coded, however we did not code the number of contacts. We report cumulated lifetime estimates of service use up to the age of 28 years until second follow-up assessment.

Assessment of substance use and substance use disorders Section B (nicotine), I (alcohol), and L (drugs) of the M-CIDI refer to substance use (frequency and quantity) and abuse and dependence according to DSM-IV. Details have been presented in Lachner et al. [35]. The substance use sections start with a screen on use of the substances followed by questions on frequency and quantity as well as symptoms of abuse and dependence. All sections close with questions on onset, duration and recency of use and symptoms. In the alcohol section specific figures for different kinds of drinks from the respondents’ booklet are used to help the respondent to report about frequency and quantity of alcohol use. In the drug section the intake of psychotropic prescription substances is assessed first. Among those misusing prescription drugs further data are assessed. In case of use of illicit substances a list containing specific substances together with their ‘street-names’ is presented probing for eight classes: cannabis, amphetamines, opioids, cocaine, PCP, hallucinogens, inhalants, and the class of sedatives, hypnotics, or anxiolytics. An open category of any other substances and a category of polysubstance use are added. Questions on symptoms of DSM-IV abuse and dependence of illicit substances were only applied to those who had used these substances more than four times. Among participants negating to respond to illicit drug use openly (‘commitment probe’) the section is not administered. Test–retest reliability of these sections ranges between a kappa of 0.55 for drug abuse and a kappa of 0.64 for nicotine dependence. Good agreement was found for the quantity and frequency questions. In case of validity there was a good agreement between DSM-IV diagnoses for substance use disorders assigned by clinicians and those assessed with the M-CIDI and assigned according to the M-CIDI DSM-IV algorithms (j = 0.86). Cumulated lifetime estimates at second follow-up are based on the following substance use categories (with and without abuse and dependence):

– regular alcohol use: at least three times per week over a period of at least 6 months;

– harmful alcohol use: use of more than 40 gram alcohol per day (women: more than 20 gram per day) over a period of at least 6 months; – regular nicotine use: at least 4 weeks of daily use; – regular use of illicit substances: use of illicit substances for five times or more (includes prescription drugs in case of misuse).

j Statistical analysis Data were weighted to consider different sampling probabilities as well as systematic non-response at baseline. The Stata Software package was used to calculate proportions and standard errors as well as robust confidence intervals for weighted data [36]. We used cumulated rates of the EDSP-data cumulating respondents, data from each assessment up to the second follow-up to account for time lags on service use among substance users. As n = 102 participants refused to respond to the questions on illicit substance use openly at least one assessment, analyses referring to illicit substances are based on n = 2.446 participants. Logistic regressions with odds ratios (OR) controlling for age and gender were used to analyze differences on service use between substance use categories and crude associations between service use and predictors. Additionally we performed logistic regressions including all variables under consideration to analyze associations between service use and predictor variables. To compare individuals with and without service use and comorbid anxiety or mood disorders with regard to the age-specific cumulative incidence of substance dependence methods from survival analyses were used. The curves were computed with the Kaplan Meier method and differences were assessed with hazard ratios (HRs) from Cox regression models stratified for gender and age cohort (i.e., different curves according to sex and age cohort are calculated non-parametrically before testing for differences according to service use and comorbidity [37]). The assumption of the hazard ratio being independent of age (‘proportional hazard assumption’) was tested with Schoenfeld residuals [37]. In the presence of a significant interaction we added the terms ‘age*comorbidity’ or ‘age*service use’, respectively to the model. The age-specific hazard ratio HR(t) is given in such a model by HR(main effect)*HR(interaction)age [37].

Results j Lifetime use of services among regular substance user groups Table 1 reports on cumulated lifetime incidence rates of specific substance use, abuse and dependence categories and the lifetime use of services due to psychological or substance use related problems by these categories. Nearly 62% of the sample had ever used any substance regularly during life. The 44% of the sample (n = 1046) met lifetime criteria for abuse or dependence, 26% for any mental and substance use disorder. The majority had used nicotine regularly (47.1%),

473

whereas alcohol abuse or dependence (28.5%) were the most frequent substance use disorders among the three classes of substances. Table 1 shows in the upper part that among all users with abuse or dependence of alcohol, nicotine or illicit drugs, 23% had ever used any services for psychological or substance related problems up to the second follow-up. Compared to respondents with mental disorders but without substance use disorders, those with abuse and dependence and no mental disorders had significantly lower rates of lifetime service use (7.6% vs. 24.6%; OR = 0.23; 95% CI 0.14–0.38). But they did not differ significantly from those with no regular use of substances and no mental disorders (7.6% vs. 8.1%; OR = 0.90; 95% CI 0.53–1.54) in the last row of Table 1. However, the difference in lifetime service use between those with mental disorders and no abuse or dependence and those with both was significant (24.6% vs. 33.7%; OR = 1.6; 95% CI 1.2– 2.2). Dependent illicit drug users had the highest rates of lifetime service use in all three substance classes (52.1%). Regular users, irrespective of abuse and dependence (see the lower part of Table 3), had lower rates of lifetime service use than those with abuse or dependence but significantly higher rates than nonregular lifetime users (including non-users), which is shown as a reference group in the next to last line of Table 3 (21.2% vs. 15.5%, OR = 1.6; 95% CI 1.3–2.0). Excluding only those with dependence, there was no difference in any lifetime use of services between the groups (15.9% vs. 15.5%, OR = 1.1; 95% CI 0.8–1.5). Though the difference was not significant, even lower rates of lifetime service use compared to non-users or non-regular users could be found for regular users of alcohol with no lifetime use of other substances (10.1% vs. 15.5%, OR = 0.7; 95% CI 0.4–1.3).

j Use of specific services Table 2 tabulates the cumulated data of most of the diagnostic and substance use categories on lifetime use of specific in-patient and out-patient services because of psychological or substance related problems. In terms of in-patient service use, illicit substance users fulfilling diagnostic criteria for dependence had used psychiatric hospitals (10%) most frequently. These rates differed from those of non-users or non-regular users of substances (10.3% vs. 0.5%, OR = 22.5, 95% CI, 5.5–91.6). The majority of out-patient service use was in the form of psychotherapy contacts. In particular, harmful alcohol users and dependent users across all substances, as well as all regular users of illicit substances, were more likely to have contacted psychotherapists and were also, on a lower level, more frequent users of other services in contrast to other regular users. Use of physicians was the least frequent type of service use in terms of out-patient services. A closer look at lifetime utilization patterns among illicit drug users (not shown in Table 2) revealed that

about one-fourth of regular cannabis users reported having used services due to psychological or substance related problems. Yet, only 9.8% had ever contacted out-patient substance use counseling services and 4.7% in-patient services for substance abusers. When multiple illicit drug users were removed from this analysis, only 5.8 and 1.5% among pure cannabis users, respectively, had used services. Regular users of sedatives, hypnotics, and anxiolytics had a relatively high rate (56.9%) of any lifetime service use but only about one-fourth had ever used substance use services. It is also important to note that more than 50% of opioid users had not used services and among those who had used services, the proportion of using specific substance use services was only 20.5% for both types. But many had contacted psychotherapists or counseling services during their lifetime. Lifetime use of multiple types of services (more than one) was more frequent among all groups of regular substance users than among non-users or non-regular users with the exception of pure alcohol users. The 18.5% of regular users compared to 9.8% of non-users used three or more different types of services (OR = 3.1, 95% CI 1.6–5.7).

j Correlates of service use Table 3 shows the ORs and 95% CIs drawn from logistic regressions on associations between regular users of the three substance classes and specific correlates of service use. It is noteworthy that we did not exclude lifetime use of multiple substances, however, we controlled for lifetime use of other substances in the multiple analyses. Female gender among alcohol and nicotine users, marital status among nicotine users and ‘being out of job’ among all substance users groups were positively associated with service use in the crude analyses, whereas other sociodemographic variables did not seem to play a role in this relatively young sample. A higher rate of comorbid use of other substances, especially illicit drugs, low self-competence and motivation to change something in life were also significantly associated with the outcome. Yet, the strongest positive associations were found with daily hassles across all classes of substances. In the multiple analyses, where we had to exclude some variables from the analyses because they covered only a short term, only anxiety disorders with ORs between 2.6 and 3.1 and life events with lower ORs between 1.7 and 1.9 remained significant across all substances. Additionally, mood disorders among nicotine users (OR = 1.6; 95% CI 1.1–2.4) and specific somatic problems among illicit drug users (OR = 1.8; 95% CI 1.1–2.8) were associated with any lifetime service use in the multiple analyses. It is important to note that fulfilling criteria for a dependence diagnosis was not significantly related to lifetime service use in the multiple analyses across all substance user groups.

474 Table 1 Lifetime use of services for psychological or substance related problems in the EDSP among different lifetime diagnostic and substance user groups Proportion of those with lifetime use of servicesb

Cumulated lifetime incidencea Diagnostic and substance user groupsc

n

%

n

%

95% CI

Any Any Any Any Any Any Any Any Any

1046 702 574 1271 638 467 235 614 432

43.7 29.7 23.1 50.8 25.4 19.7 10.0 25.7 18.0

234 186 117 364 156 166 20 200 34

23.0 26.9 21.4 29.2 24.6 36.4 7.9 33.7 7.6

(20.3–26.0) (23.3–30.7) (17.8–25.4) (26.5–32.1) (21.0–28.5) (31.7–41.5) (4.5–12.6) (29.6–38.0) (5.3–10.9)

Alcohol abuse or dependence Alcohol dependence Alcohol abuse

714 215 499

28.5 9.2 19.3

136 50 86

19.8 23.1 18.3

(16.7–23.4) (17.4–30.0) (14.7–22.5)

Nicotine dependence Illicit drug abuse or dependence Illicit drug dependence Illicit drug abuse

615 219 71 166

24.8 8.5 3.1 6.3

172 73 34 51

28.3 35.1 52.1 31.1

(24.5–32.5) (28.2–42.6) (38.9–65.0) (23.8–39.5)

Alcohol abuse or depend. with any mental disorder Alcohol abuse or depend. w/o any mental disorder Nicotine dependence with any other mental disorder Nicotine dependence w/o any mental disorder Illicit substance abuse or depend. with any mental disorder Illicit substance abuse or depend. w/o any mental disorder

385 329 417 198 130 89

15.2 13.4 16.9 7.9 5.1 3.5

111 25 153 19 61 12

30.5 7.7 37.2 9.3 48.6 15.1

(25.5–36.0) (0.5–11.6) (32.1–42.6) (5.7–14.9) (39.1–58.3) (8.2–26.1)

Any abuse or dependence of two substance classes Any abuse or dependence of three substance classes

278 93

11.2 3.8

71 34

24.4 40.0

(19.3–30.3) (28.9–52.2)

1481 784

61.7 32.2

310 125

21.2 15.9

(18.9–23.6) (13.3–18.9)

611 261 316

28.1 12.2 14.4

121 37 78

20.0 13.6 25.8

(16.7–23.7) (9.6–18.8) (20.8–31.5)

1207 592

47.1 22.3

266 94

22.3 15.7

(19.8–25.1) (12.7–19.2)

Regular illicit drug use Regular illicit drug use w/o dependence Only regular use of alcohol Only regular use of nicotine Only regular use of illicit drugs Only regular use of alcohol and nicotine Regular use of all three substance classes

782 711 140 422 128 137 270

32.3 29.3 6.6 15.5 5.2 6.1 12.8

213 179 13 66 29 18 76

27.8 25.3 10.1 15.8 23.9 13.1 28.3

(24.5–31.5) (21.9–29.0) (5.7–17.1) (12.2–20.7) (16.6–33.2) (8.0–20.6) (22.7–34.6)

Any regular use with any other mental disorder Any regular use w/o any other mental disorder

817 664

34.3 27.4

250 60

31.5 8.2

(28.1–35.2) (6.3–10.7)

No regular use of any substance No regular use of any substance/No mental disorder

965 561

38.3 20.7

143 41

15.5 8.1

(13.1–18.2) (5.9–11.1)

abuse or dependence dependence abuse mental disorder mental disorder w/o any substance use disorder dependence with any other mental disorder dependence w/o any other mental disorder abuse or dependence with any mental disorder abuse or dependence w/o any mental disorder

Any regular substance use Any regular use w/o dependence Regular alcohol use Regular alcohol use w/o harmful use, dependence Harmful alcohol use Regular nicotine use Regular nicotine use w/o dependence

a

Unweighted n, weighted %, 95% confidence interval Unweighted n, conditional weighted percent on diagnostic or substance user groups under consideration c Regular alcohol use: at least three times per week over a period of at least 6 months; harmful alcohol use: use of more than 40 gram alcohol per day

(women: more than 20 gram per day) over a period of 6 months; regular nicotine use: daily use of nicotine for at least 4 weeks; categories excluding diagnostic subgroups (e.g., any regular use without dependence) are defined as use without ever fulfilling criteria for the diagnosis under consideration

j Age-specific cumulative incidence of comorbid and non-comorbid substance dependence by service use

had never used services we performed survival analyses and Cox-regressions. Additionally, we distinguished those with comorbid lifetime mental disorders (anxiety and mood disorders) from those with no lifetime mental disorders. Figures 1a–d shows the corresponding curves for the aggregated group and for the three specific substance classes. Persons

b

In order to examine age-specific differences of cumulative incidence of dependence and age of onset among those that had used any services vs. those that

6 4 19 5 8 1 7 16 5 15 9

Illicit drug dependence (n = 71) Illicit drug abuse (n = 166)

Any regular use (n = 1481) Regular w/o dependence (n = 784)

Regular alcohol use (n = 611) Regular alcohol use w/o harmful use/depend. (n = 261)

Harmful alcohol use (n = 316) Regular nicotine use (n = 1207) Regular nicotine use w/o dependence (n = 592)

Regular illicit drug use (n = 782) Regular illicit drug use w/o dependence (n = 711)

2.6 1.8

2.8 1.8 1.2

1.6 0.4

1.7 0.8

10.0 4.2

2.3

2.5 0.9

1.8 2.7 1.6

4 3

1 5 2

1 0

5 2

1 1

3

0 2

0

9 4

4 3 2

4 0

n

b

0.5 0.5

0.5 0.4 0.1

0.2 –

0.3 0.1

1.2 1.1

0.6

– 0.7

–

0.7 0.9

0.5 0.5 0.6

0.5 –

%

Psychosomatic hospital

Unweighted N, weighted % See definitions in Table 1 c In-patient therapy in hospitals for substance abuse patients d Day hospitals, homes, and other e School-psychologists, educational services, and other counseling services f Psychiatric out-patient services, self-help groups, and others

a

11

Nicotine dependence (n = 615)

1 4 3

0.4

22 13

Any mental disorder (n = 1271) Any abuse or depend. with any mental disorder (n = 614) Any abuse or depend. w/o any mental disorder (n = 432)

Alcohol dependence (n = 215) Alcohol abuse (n = 499)

2.2 2.9

14 14 6

Any abuse or dependence (n = 1046) Any dependence (n = 702) Any abuse (n = 574)

0.5 0.3

5 2

No regular use of any substance (n = 965) No regular use/no mental disorder (n = 561)

%

n

Diagnostic and substance user groups

Psychiatric hospital

In-patient services

9 3

4 9 3

5 1

10 1

6 7

6

4 2

1

9 9

10 9 8

0 0

n

1.2 0.3

1.5 0.8 0.3

0.9 0.3

0.7 0.1

9.2 5.2

1.2

2.3 0.4

0.4

0.7 1.4

1.0 1.4 1.6

– –

%

Specific subst. use servicec

15 13

7 18 6

8 1

19 6

2 4

12

6 3

1

24 15

16 13 6

8 1

n

1.9 1.9

2.5 1.5 1.0

1.3 0.1

1.3 0.9

1.8 2.4

1.9

2.9 0.6

0.3

1.8 2.4

1.5 1.7 1.1

0.8 0.1

%

Any other in-patient serviced

33 30

14 38 11

22 5

45 18

3 9

27

10 14

4

59 31

35 27 19

24 7

n

4.8 4.8

5.7 3.4 2.1

4.3 2.2

3.3 2.6

4.3 7.4

4.5

5.6 3.3

1.2

5.1 5.4

3.7 4.2 4.1

2.6 1.1

%

Psychiatrist

21 16

11 30 10

16 5

33 12

5 6

20

4 8

1

45 24

25 21 13

13 2

n

2.8 2.6

3.6 2.5 1.7

2.6 1.7

2.2 1.4

5.4 3.3

3.2

1.9 1.7

0.2

3.5 3.9

2.4 3.1 2.2

1.5 0.4

%

Physician

Out-patient services

Table 2 Lifetime use of specific services for psychological or substance related problems among selected diagnostic and substance user groupsa

109 91

45 134 39

62 14

158 60

18 28

95

27 39

16

192 106

122 98 57

64 14

n

Psychotherapist

14.7 13.6

14.2 11.9 7.6

10.5 6.4

11.4 8.5

25.3 16.9

15.8

12.2 8.9

3.3

16.3 18.6

12.3 14.5 10.6

7.2 3.2

%

21 11

8 20 4

9 1

21 3

10 9

16

7 4

5

16 15

20 18 12

0 0

n

2.5 1.2

2.5 1.6 0.5

1.4 0.3

1.3 0.3

14.7 6.5

2.6

3.4 0.7

1.0

1.2 2.3

1.8 2.4 2.1

– –

%

Subst. use counseling/ therapy

83 70

30 94 30

50 16

113 44

13 19

64

26 33

14

127 72

86 70 42

57 19

n

10.7 9.8

10.0 7.5 4.3

7.8 4.9

7.5 5.5

19.5 12.3

10.4

11.4 6.8

3.1

9.9 12.0

8.3 9.7 7.7

6.2 4.0

%

Other counseling servicese

30 21

14 40 15

18 4

46 18

9 7

25

9 5

1

57 31

32 28 11

18 4

n

4.1 3.2

4.4 3.6 2.9

3.0 1.6

3.4 2.3

12.9 4.7

4.3

3.7 1.3

0.2

4.6 5.7

3.5 4.4 2.2

1.8 0.8

%

Any other out-patient servicef

475

comorbidity/service use

50

comorbidity/no service use no comorbidity/service use

40 no comorbidity/no service use

30 20 10 0

Respondents with nicotine dependence, %

8

10

12

14

16

18 Age

20

22

24

26

28

Cumulative lifetime incidence of nicotine dependence 50

comorbidity/service use

45 comorbidity/no service use

40 35

no comorbidity/service use

30

no comorbidity/no service use

25 20 15 10 5 0 8

10

12

14

16

18 Age

20

22

24

26

28

Respondents with alcohol dependence, %

Cumulative lifetime incidence of any dependence 60

Cumulative lifetime incidence of alcohol dependence 16

comorbidity/service use

14

comorbidity/no service use

12

no comorbidity/service use

10

no comorbidity/no service use

8 6 4 2 0 8

Respondents w. illicit substance use dependence, %

Respondents with any dependence, %

476

10

12

14

16

18 Age

20

22

24

26

28

Cumulative lifetime incidence of illicit substance use dependence 14

comorbidity/service use

12

comorbidity/no service use no comorbidity/service use

10

no comorbidity/no service use

8 6 4 2 0 8

10

12

14

16

18 20 Age

22

24

26

28

Fig. 1 Cumulative lifetime incidence and onset of dependence of different classes of substances by comorbidity and service use

with comorbid mental disorders had significantly higher incidence rates of substance dependence than those without comorbid disorders (HR = 2.2; 95% CI 1.9–2.6) (see Fig. 1a). Lifetime service use among those with any dependence was also associated with higher age-specific incidences (HR = 1.5, 95% CI 1.2– 1.8). Dependent users with both characteristics were most frequent. However, no significant interaction between the two variables was found (HR = 1.5; 95% CI 0.9–2.6). Furthermore, neither comorbid dependent users nor those that had used services had earlier ages of onset. The specific substance classes differ from this general pattern: – We found an association between comorbid disorders and the overall incidence of alcohol dependence (HR = 2.1; 95% CI 1.5–2.9) but none between lifetime service use and alcohol dependence (Fig. 1b). No interactions between age of onset and comorbidity and between age of onset and service use were found. – Among those with nicotine dependence both comorbidity (HR = 2.2; 95% CI 1.8–2.6) and lifetime service use (HR = 1.6; 95% CI 1.3–1.9) were associated with the age-specific incidence rates of nicotine dependence (Fig. 1c). Those using services also tended to have significantly earlier ages of onset (HRInteraction = 0.89; 95% CI 0.82–0.98; HRMain effect = 9.59; 95% CI 2.29–40.19). But earlier ages of onset were not found among those with comorbid disorders (HRInteraction = 1.00; 95% CI 0.93–1.09).

– Most comorbid dependent illicit substance users who use services do so before the age of 28 years (Fig. 1d). There was a strong association between dependence and service use (HR = 4.8; 95% CI 2.8–8.1) and also one between dependence and comorbidity (HR = 1.9; 95% CI 1.1–3.3). Yet, other associations e.g., between age of onset and service use among dependent users of illicit substances were not significant.

Discussion Key findings of this study include: (1) Only about onefourth of those with substance use disorders have ever used any services for help with psychological or substance related problems by the age of 28. Most of this use appeared to be through contacting psychotherapists. (2) The majority of regular lifetime substance users with or without substance use disorders also had at least one comorbid mental disorder during their lifetime. Comorbidity, especially with anxiety disorders, was the strongest predictor of lifetime service use across all substances. There are only a small proportion of service users among regular substance users who do not have a comorbid mental disorder. (3) Those with dependence had higher lifetime service use rates, but this might be due to higher rates of comorbid disorders among those with dependence. (4) Life events and daily hassles were also strongly associated with use of services across all users of substances.

477 Table 3 Factors associated with service use among regular substance users seeking help for psychological or substance related problems Any use of services among regular users of Alcohola (n = 611)

Nicotine (n = 1207)

Illicit drugs (n = 782)

Controlled for age and gender

Multiple analysis

Controlled for age and gender

Multiple analysis

Controlled for age and gender

Multiple analysis

Analyzed factors

AORb

95% CIb

ORc

95% CIc

AORb

95% CIb

ORc

95% CIc

AORb

95% CIb

ORc

95% CIc

Gender Age Financial situation (bad) Living alone Marital status (separated, divorced) Out of job (some time during last 5 years) Regular use of other substance: Alcohola Nicotine Illicit drugs Substance use disorders: Alcohol dependence Nicotine dependence Dependence of any illicit drug Other mental disorders: Any mood disorder Any anxiety disorder Somatic problemsd Psychosocial stress and cognitive factors: Life eventse Daily hassles (only baseline) Self-competence (only baseline)f Motivation to change something In life (only baseline)

1.8 1.0 1.5 1.1 11.3

(1.1–2.8) (0.9–1.1) (0.9–1.1) (0.7–1.8) (0.9–138.6)

1.1 1.0 1.4 0.8 9.4

(0.6–2.0) (0.9–1.1) (0.8–2.3) (0.4–1.4) (0.3–323.4)

1.7 1.0 1.3 1.1 3.4

(1.3–2.4) (0.9–1.1) (0.9–1.7) (0.8–1.6) (1.1–10.5)

1.3 1.0 1.2 1.0 1.7

(0.8–1.9) (0.9–1.1) (0.8–1.7) (0.6–1.5) (0.5–6.7)

1.9 1.1 1.3 1.1 2.1

(1.3–2.6) (0.9–1.1) (0.9–1.8) (0.7–1.7) (0.4–10.5)

1.2 1.0 1.3 0.9 0.9

(0.8–2.0) (0.9–1.1) (0.9–2.1) (0.6–1.5) (0.6–1.5)

2.5

(1.4–4.5)

1.3

(0.6–2.9)

1.9

(1.2–3.0)

1.2

(0.7–2.2)

1.9

(1.1–3.2)

1.3

(0.7–2.5)

– 1.9 3.2

–

– –

1.2 – 2.7

(0.9–1.7)

(1.1–3.2) (1.9–5.2)

(0.8–2.0) (0.7–1.5)

... ...

(2.0–3.8)

–

1.3 1.1 –

1.9 1.8 1.9

(1.1–3.1) (1.2–2.8) (1.2–3.0)

1.2 1.7 0.6

(0.6–2.5) (0.7–4.2) (0.2–1.8)

1.4 2.1 2.3

(0.9–2.2) (1.5–2.9) (1.6–3.2)

0.8 0.8 2.2

(0.4–1.4) (0.4–2.0) (0.9–5.8)

1.4 2.0 2.2

(0.9–2.2) (1.4–2.8) (1.5–3.2)

0.6 0.8 2.3

(0.3–1.2) (0.4–1.9) (0.9–5.9)

3.0 3.9 2.0

(1.9–4.8) (2.4–6.3) (1.3–3.2)

1.7 2.6 1.4

(0.9–3.0) (1.5–4.4) (0.8–2.5)

2.7 4.1 1.8

(2.0–3.7) (3.0–5.7) (1.3–2.4)

1.6 3.0 1.4

(1.1–2.4) (1.9–4.4) (0.9–2.1)

2.4 3.6 1.9

(1.7–3.4) (2.5–5.2) (1.4–2.7)

1.4 3.1 1.8

(0.9–2.2) (1.9–4.9) (1.1–2.8)

2.6 6.0 1.9

(1.8–3.7) (2.7–13.0) (1.3–2.7)

1.9 – –

(1.3–2.8)

2.3 4.8 1.7

(1.8–2.9) (2.8–8.2) (1.4–2.2)

1.8 – –

(1.4–2.4)

2.0 5.6 1.9

(1.6–2.7) (3.0–10.1) (1.4–2.5)

1.7 ... ...

(1.2–2.3)

2.1

(1.3–3.2)

–

2.5

(1.8–3.6)

–

2.34

(1.6–3.5)

...

a

Harmful alcohol users included Adjusted odds ratios and 95% confidence intervals from logistic regressions controlling for age and gender; boldface type indicates significant associations (p < 0.05) c Odds ratios and 95% confidence intervals from multiple logistic regressions with sociodemographic variables, all dependence variables, all other mental

disorder variables and life events; boldface type indicates significant associations (p < 0.05) d Somatic problems: cardiovascular complaints or diseases, high blood pressure or gastrointestinal diseases in the last 12-months before the second follow-up e Cumulated over the last 10 years up to second follow-up f Higher scores are associated with lower self-competence

Our findings of low cumulated lifetime rates of service use are generally consistent with findings from most other epidemiological studies [1–3]. Exact comparisons are not possible, however, because of differing age ranges. It can be expected that due to the longer time lag of a decade or more between onset and treatment seeking, which has been described in other studies [7], service use rates might increase in this young sample in the future. Alternatively, because of the declining risk of new onsets of substance use disorders in older age groups incidence rates of substance use disorders may decrease. This is noteworthy because lifetime estimates of mental or substance use disorders often carry the risk of interpretation errors when estimated in young samples. Among the different substance classes, service use among those with alcohol abuse or dependence as well as of regular alcohol users is less frequent. One reason for these (relatively) lower rates may be the smaller proportion of comorbid disorders, which

could be associated with lower perceived need in this subgroup [22]. The high lifetime comorbidity rates of substance use disorders with mental disorders are also consistent with other studies [6]. It is therefore not surprising that most of those that had ever used services had contacted psychotherapists and other counseling services. We have not coded the reasons for the use of psychotherapists and other counseling services in all waves, though we can hypothesize that it might be due to comorbid mental disorders, which is supported by our analyses of the correlates of service use. This is an important finding given that the allocation of resources, especially resources for early prevention, which are currently mostly bound to specific bodies of the specialized sector. Yet, it is surprising that the findings for use of physician services are relatively low, especially in case of alcohol dependence. This might be related to the caginess of younger patients to report on problems resulting from alcohol use as well

b

478

as the low rate of recognition by physicians, especially among younger persons. One surprising finding was the extremely low rate of lifetime service use in the specialized substance use care sector. Only a fraction of those who might be in need of a specialized treatment (e.g., those fulfilling criteria for substance use dependence) have ever used these services specifically tailored to substance use problems. One reason might again be the lack of perceived need concerning substance use problems in this relatively young sample with few impairments and disabilities. This interpretation may also support the low rate of contacts with physicians. Previous research has suggested there might be a specific need in the service delivery system for services available to this group of younger (harmful or dependent) users [38]. Our study supports this conclusion. In this region of Germany, most of the specialized services except some few specific services for younger users of illicit substances are available to meet the need of those with a chronic substance use dependence and might be overextended with younger users in earlier stages of dependence. Social and psychosocial reasons not to contact these services should be investigated. Fear of adverse consequences, for example problems with parents, teachers, or employers, as well as fear of labeling processes might contribute to motivation and decisions on help-seeking within the current system. Partially consistent with other studies, we found few associations with so-called predisposing factors for service use. Female gender among alcohol and nicotine users and marital status among nicotine users was associated with lifetime service use, whereas none of these variables seemed to play a role among illicit drug users. However, psychosocial stress and somatic problems, which might be related to perceived need as well as motivational factors, are associated with service use in addition to mental disorders. Surprisingly, meeting criteria for dependence was also not found to be a significant correlate of lifetime service use. Lifetime service use might therefore be more due to symptoms of other mental disorders than to dependence symptoms. We could not replicate findings from other studies that have shown associations between the age of onset of symptoms of dependence and service use [7]. Results of our age-specific incidence rates of dependence and corresponding Cox-regressions showed that only the association between onset and service use among those with nicotine dependence was significant. But another finding of these analyses was also interesting. Whereas, both comorbidity and service use were associated with higher age-specific cumulative incidence rates of dependence, we found no interactions between these variables in these analyses, despite the finding that comorbidity had been proven to be an important correlate of service use. This suggests that other factors, for

example life events or impairment from comorbid disorders, might mediate the associations of other disorders, service use, and onset of dependence. This has a number of strengths, including the longitudinal design and the representative sample, though some limitations should be noted. First, we neither assess specific reasons for service use nor we did assess data on onset, contents or duration of service contacts. This will be part of the next follow-up, in addition to detailed information on treatment and course of substance use. Second, multiple responses about the use of specific types of services from one individual were possible. This means that rates of use of specific services reflect the number of contacts and not the number of persons that have used these services. This aspect of the study does not influence other findings. Third, we used retrospective information from respondents about service use and other variables. Thus recall errors cannot be excluded but are minimized because of the relatively young age of the sample. Fourth, our kappas for the reliability of abuse and dependence diagnosis are only modest. This might be associated with the type and age of this fairly young community sample and could also be judged as an advantage in comparison with many previous studies that have examined reliability primarily in patient samples. Thus, our findings should be generalized to community cases and not to patient samples with a majority of severely ill and chronic cases. Fifth, data were gathered using a personal interview and were not based on records of the service delivery system. Although, this might be a source of error it is important to state that the findings should not reflect the intensity or quality of care from the services used. Finally, results are based on an age-stratified community sample and are not representative of Germany as a whole or other European countries, although many of our findings correspond with findings from other studies as discussed above. Therefore it should be obvious that these findings generally raise doubts about existing allocation strategies allow this system to meet the needs of regular users of psychotropic substances with or without substance use disorders in younger age groups. j Acknowledgments This paper has been prepared in the context of the project ‘‘Community based need evaluation II & allocation and transfer’’ (PI: Hans-Ulrich Wittchen) of the Addiction Research Network ASAT (Allocating Substance Abuse Treatments to Patient Heterogeneity). Contact information: e-mail: asatkoordination@ mpipsykl.mpg.de (www.asat-verbund.de). ASAT is sponsored by a federal grant of the Federal Ministry of Education and Research (01EB9405/06, 01EB9901/6, 01EB0140–0142, 01EB0440).The authors thank Dr. Renee Goodwin for her valuable language editing.

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