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Correlates of dependence and treatment for substance use among people withcomorbid severe mental and substance use disorders
Giuseppe Carra, Cristina Crocamo, Paola Borrelli, Ioana Popa, Alessan-dra Ornaghi, Cristina Montomoli, Massimo Clerici
PII: S0010-440X(14)00345-9DOI: doi: 10.1016/j.comppsych.2014.11.021Reference: YCOMP 51442
To appear in: Comprehensive Psychiatry
Received date: 27 October 2014Accepted date: 26 November 2014
Please cite this article as: Carra Giuseppe, Crocamo Cristina, Borrelli Paola, Popa Ioana,Ornaghi Alessandra, Montomoli Cristina, Clerici Massimo, Correlates of dependence andtreatment for substance use among people with comorbid severe mental and substanceuse disorders, Comprehensive Psychiatry (2014), doi: 10.1016/j.comppsych.2014.11.021
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Correlates of dependence and treatment for substance use among people with comorbid severe
mental and substance use disorders. Findings from the “Psychiatric and Addictive Dual Disorder in Italy (PADDI)” Study
Giuseppe Carràa, Cristina Crocamo
b,c,*, Paola Borrelli
b, Ioana Popa
b, Alessandra Ornaghi
c,
Cristina Montomolib, Massimo Clerici
c
Research paper submitted for publication to Comprehensive Psychiatry
a Division of Psychiatry, Faculty of Brain Sciences, University College London. Charles Bell
House, 67–73 Riding House Street, London W1W 7EJ, UK. b
Department of Public Health, Experimental and Forensic medicine, Unit of Biostatistics and
Clinical Epidemiology, University of Pavia. Via Forlanini, 2 - 27100 Pavia, Italy.
c Department of Surgery and Interdisciplinary Medicine, University of Milano Bicocca. Via Cadore,
48 - 20900 Monza, Italy.
Word count: Abstract 218; Text 3422; Tables: 3
*Address for correspondence:
Cristina Crocamo, MSc. University of Milano-Bicocca, Department of Surgery and Interdisciplinary
Medicine, Via Cadore 48, 20900 Monza (MB), Italy.
Tel. /Fax +390392332277. E-mail: [email protected]; [email protected]
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Correlates of dependence and treatment for substance use among people with comorbid severe
mental and substance use disorders. Findings from the “Psychiatric and Addictive Dual Disorder in Italy (PADDI)” Study
Abstract
Objective People with severe mental illness (SMI) have often comorbid alcohol and other substance
disorders but substantial barriers to addiction care remain.
The study is aimed at describing correlates associated with dependence and with treatment for
substance use among people with SMI and comorbid substance disorders cared in community mental
health teams (CMHTs).
Methods This study capitalized on data from a national survey on comorbid severe mental and
substance use disorders, among 2,235 subjects in 42 CMHTs nationwide.
Results 26% of people with SMI and comorbid misuse suffered from dependence on alcohol and 21%
on any other substance. Use of opioids, liver diseases, involvement with criminal justice system, but
also area of residence, all were associated with dependence in people with SMI. As regards treatment
for substance use, only 50% of comorbid people with SMI were treated by specialist services in the
past 12 months. This was associated with opioids and cocaine use, as well as with liver diseases, and
involvement with criminal justice. People with schizophrenia and those living in Central and Southern
Italy, had the lowest chances to be treated for their comorbid substance use disorder.
Conclusions There are extensive unmet treatment needs among comorbid individuals with SMI.
Better integration of substance abuse and mental health care systems, and more effective reciprocal
referral procedures, are needed.
Keywords: correlation study; dual diagnosis; community mental health services; substance abuse
treatment centres.
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1. Introduction
People suffering from severe mental illnesses (SMI) have high rates of comorbid substance use, i.e.,
“dual diagnosis”1. The Epidemiologic Catchment Area (ECA) study found that 47% of people with
schizophrenia had a comorbid substance use disorder2. In Europe the lifetime rates for comorbid
schizophrenia and dependence on any substance are high for example in the UK (35 %), but
considerably lower in Germany (21%) and in France (19%) 3. Research in clinical populations with
this comorbidity is consistent in showing poor clinical and social outcomes4, 5
. Socio-demographic,
clinical, infectious diseases and legal adverse correlates are well documented 6-9
. However, a formal
diagnosis of dependence is often not reported, though its consequences may differ as compared with
simple abuse10
. DSM–IV diagnosis of dependence has been shown to be reliable and valid11
but
evidence in support of abuse was weaker12
. In fact, DSM 5 has combined DSM-IV substance abuse
and dependence into a single disorder, measured on a mild to severe continuum13
. Furthermore, for
people with dual diagnosis, not simply the use of substances but rather dependence predicts poor
outcomes14
. However, the bulk of evidence is about correlates of dual diagnosis in general15
, though
an early identification of factors specifically associated with dependence and only in people with SMI
can help clinicians in targeting clients who need to be in treatment for substance abuse.
As regards health care delivery, integrated treatment for people with dual diagnosis is still far from
standard practice worldwide and there are substantial barriers also to parallel treatment for substance
abuse for people with comorbid SMI16, 17
. Less than 10% of those in need receive separate treatment
for both their mental health and substance use problems18
. Community studies have examined patterns
of service use, generally combining mental health and substance abuse services, but less is known
about the use of each type of service separately19
. Although there are wide differences across
countries, individuals with dual diagnosis seem more likely to use mental health rather than substance
abuse services20
. However, risk of persistent drug and alcohol misuse is reduced if comorbid people
use also specialty substance abuse services21
. Unlike the USA, in many European countries including
Italy (see 5 for a review) mental health and substance abuse treatment delivered by different providers
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at the same time (parallel treatment) is standard practice for people with dual diagnosis because of the
separation of mental health and addiction services22
, even if a large evidence base supports integrated
treatment for dual diagnosis23
. Previous research has shown that among CMHT patients with
comorbid SMI and dependence, only a minority have contact with drug services24
. However, little is
known about factors associated to be referred to drug treatment programmes in countries with parallel
systems. In addition, findings from EU studies may be of general interest in relation to variations in
service use, since these are more likely to be reflections of the whole local mentally ill population than
those from the USA, where a variety of factors other than place of residence determines who uses
which service25
.
We capitalized on data from a national survey, the Psychiatric and Addictive Dual Disorders in Italy
(PADDI) project, providing the unmatched opportunity to study correlates of dependence and of
provision of interventions for substance abuse in a large, representative, sample of patients from
community mental health teams (CMHTs) with comorbid SMI and substance use disorders.
Particularly, this study will address two research questions: (1) which factors are associated to drug
and alcohol dependence in people with SMI undergoing treatment in CMHTs in Italy?; (2) which
factors are associated to be treated for substance abuse within programs of the National healthcare
system?
2. Material and methods
2.1 Setting and Sample
We conducted a cross-sectional survey exploring dual diagnosis within Italian Mental Health Care
Trusts (MHTs) in 2008. In Italy integrated programmes for dually diagnosed people are rare. MHTs,
serving the population living in a specific district, include psychiatric services that offer inpatient
(General Hospital Psychiatric Units), and outpatient (CMHTs) care, residential treatment and day-
centre activities. Substance misuse care is provided only by addicts’ outpatient clinics, with non-
statutory residential therapeutic communities playing an ancillary role5. CMHTs carry out most of
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outpatient mental health care, assigning each client with SMI a case manager26
. Thus they represent
the optimal setting to study the epidemiology of dual diagnosis in people with SMI. Tax-based
funding warrants universal access to all citizens across health care services, meaning that no selection
factors are in place determining whether individuals get care through the system.
The study population was defined as all people with SMI aged 18-65 years, allocated in the case-load
of a psychiatrist in participating CMHTs, and diagnosed also with an alcohol or a substance use
disorder. Participation of staff and data collection procedures were agreed by the ethic committee of
the University of Pavia and clients were approached for their informed, signed, consent.
2.2 Measures and procedures
CMHTs provide healthcare almost exclusively for people with SMI. However, in order to ensure
comparability between clients from different CMHTs, we adopted a clear, well established, definition
of SMI27
. Therefore, we included from administrative datasets only people who had diagnoses of
Schizophrenia and other psychotic disorders (Schizophrenia, Schizophreniform, Schizoaffective,
Delusional, Brief Psychotic, Shared Psychotic and NOS Psychotic disorders), Bipolar I–II disorders,
and 12-month depressive disorders (major depressive disorder and dysthymic disorder)28
. We also
considered people with clusters A and B personality disorders, since they are routinely in caseloads of
Italian CMHTs26
. At least one of the above mentioned DSM-IV diagnoses, along with a Global
Assessment of Functioning scale29
score of less than 60 during the worst month of the past year as
recorded in the clinical chart, was required to define SMI30
. All psychiatric diagnoses were then
checked, by fully trained consultant psychiatrists administering the 12-month patient version of the
SCID-I (Structured Clinical Interview for DSM-IV) and SCID-II (after screening self-report
questionnaire).
For substance use assessment, given self-report reduced reliability31
, and also the limited practical
gains of biological measures32
, we identified staff rating as an alternative, reasonably sensitive,
method (e.g.,24, 33
). Therefore, alcohol and substance disorders of people with SMI were screened by
their case managers using the Drake Clinician Rating Scales for Alcohol (AUS) and Drug (DUS)
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Use34
, which are based on DSM-IV. These instruments are not usually included in routine
documentation collection.
We defined a subject with SMI as suffering from dual diagnosis if at least one 12 month substance use
disorder could be detected using AUS and DUS.
2.3 Outcome definitions
Following our research questions, we defined two specific outcomes. The first was comorbid DSM-IV
12 month alcohol and other substances dependence (from now on dependence). Secondly, in order to
study the likelihood of comorbid SMI people from CMHTs of receiving treatment for substance use,
we adopted a broad definition. We explored any kind of treatment (including those of non-statutory
organizations, e.g., self-help groups) provided by specialty services in the past 12 months for
comorbid alcohol and/or other substances disorders. Long-term follow up for treatment received in
previous years was also considered.
2.4 Statistical analysis
Analyses were carried out using STATA 1035
. All statistical tests used the 5% level of significance,
and all p-values were two-tailed. Cohen's k coefficients were used to measure AUS/DUS inter-rater
reliability among case-managers. Mean (SD) and percentages were used for descriptive statistics,
provided also by gender. Univariate comparisons for categorical data were made between groups
using Pearson’s chi-square test and Student t test for continuous variables. In order to control for error
effects, Bonferroni multiple testing correction was used. We identified covariates significantly
associated with each outcome for inclusion in subsequent multivariate analyses, yielding odds ratios
(ORs) with 95% CIs. We then carried out logistic regressions of the effect of characteristics of
comorbid SMI patients independently on both outcomes, controlling for age, gender and other
variables significantly related in the univariate analyses. Likelihood Ratio Test was used to compare
nested models, exploring the contribution that different variables made to regression equations.
3. Results
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3.1 Socio-demographic, clinical and substance use characteristics
The caseloads of 257 case managers (88% response rate) from 42 MHTs across the country provided
individual data for 2,235 patients with dual diagnosis. SMI diagnoses comprised 681 (30.5%) subjects
with Schizophrenia and other psychotic disorders, 395 (17.7%) with Bipolar Disorders, 230 (10.3%)
with Depressive Disorders, and 929 (41.6%) suffering from Clusters A and B personality disorders.
AUS/DUS inter-rater reliability k coefficients ranged between 0.80 and 0.95 among different case-
managers rating the same patient. Women were 25% of the study sample, and they were significantly
older than men. Most subjects had just compulsory eight years education (74%), were unemployed
(58%), and often lived with their parents or relatives (80%). All socio-demographic characteristics
significantly differed by gender, apart from living conditions and employment status (Table 1). Men
more often had involvement with criminal justice and liver diseases and were more likely than women
to suffer from dependence on substances (in particular opioids) but not on alcohol. Women were more
likely to be dependent on prescription drugs.
Cumulative rates of simple use and abuse were 51% for Alcohol, and 48% for other substances
(Cannabis=28%; Opioids=10%; Cocaine=17%; Hallucinogens=5%; Prescription drugs=10%). In
terms of polysubstance use, just 9% in our sample misused no more than one substance (including
alcohol), and men (92%) were more likely than women (86%) to report polysubstance patterns
(p<0.001). Only 50% of comorbid people had received treatment in any substance use programme in
the past 12 months, and small proportions of them were on methadone/buprenorphine outpatient
maintenance programmes (9%) or else could benefit from inpatient detoxification (4%).
TABLE 1 about here
Table 2 shows rates of dependence and of substance use treatment by SMI diagnoses. We found
negligible differences as regards dependence in different diagnostic groups. People with schizophrenia
were less likely to suffer from alcohol dependence, as compared to people with bipolar disorders, and
from substance dependence, as compared to people with personality disorders. Furthermore, those
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with schizophrenia were also less likely to have received any kind of treatment for substance use in
the past year, apart from inpatient detoxification, compared to all the other groups.
TABLE 2 about here
3.2 Characteristics associated with 12 month dependence and treatment for substance use
disorders
3.2.1 Univariate analyses
Table 3 shows the influence of several variables at univariate level on dependence and on the
provision of any treatment for alcohol and other substances disorders with unadjusted, but significant,
ORs (95% CIs). Living in Central and Southern, as compared with Northern, Italy was associated with
a higher likelihood of dependence, but geographical area had no influence on being referred to
specialty treatment. Criminal justice sanctions were associated with high odds for both dependence
and referral to treatment. People who lived alone were less likely to access treatment. As regards
physical health conditions, HIV-positive serostatus and liver diseases were associated with both
dependence and substance abuse treatment. In relation to variables describing specific substances
misuse, comorbid people who used opioids were more likely to be dependent and to receive specialty
treatment, similarly to those who used cocaine. Assuming schizophrenia as reference category, people
with bipolar and cluster A and B personality disorders were more likely to be dependent.
3.2.2. Multivariate analyses
In order to explore factors associated with each outcome, we fitted several models (controlling for age
and gender) that included significant attributes from the univariate analyses, but retaining only
variables which made a statistically significant contribution to final regression models in terms of
goodness of fit. Adjusted ORs (95% CIs) are shown in table 3 for dependence and provision of
specialty treatment in the past 12 months.
TABLE 3 about here
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We focussed on variables which, along with statistical significance, carried substantial odds ratios and
differences that were large enough to be of clinical significance. Living in Central and Southern, as
compared to Northern, Italy influenced both outcomes at multivariate level, with higher odds of
suffering from dependence, and relatively lower odds of accessing specialty services. However, most
of results from univariate analyses were confirmed. Sanctions inflicted by criminal justice system and
liver diseases showed a moderate effect on both outcomes. As regards specific substances misuse,
odds of suffering from dependence were fourfold greater for opioids users, who were also to a similar
degree more likely to receive appropriate treatment. This was true, though to a lesser extent, also for
cocaine users. More importantly, people with schizophrenia were less likely to receive any kind of
treatment for substance use as compared to all the other diagnostic groups.
4. Discussion
We analysed with a structured diagnostic assessment a large sample of people with co-occurring
severe mental and substance use disorders in CMHTs nationwide. We were thus able to study a
number of correlates in relation to dependence syndromes and provision of treatment for substance
disorders by specialty services in the past 12 months. Data were collected in 2008 but no major
changes of the treatment system have been implemented meanwhile, allowing sufficient
generalization to the contemporary situation and also comparison to similar data from other nations
and health systems. The study documents areas where policy is falling short and improvements in
patient care are needed.
4.1 Dependence and specialist treatment rates
Among people with comorbid SMI and substance use disorders, 26% and 21% suffered from 12
month dependence on alcohol and on any other substance, respectively. However, the most salient
finding of this study is that only 50% of comorbid people in CMHTs had been cared also by drug and
alcohol specialty services in the past 12 months. A specific concern is about
methadone/buprenorphine maintenance programmes that were offered only to 207 out of 326 opiate
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dependent clients. These findings from a nationally representative sample reveal a largely
unrecognized and underserved population at risk. This is consistent with evidence for example from
the comparable UK COSMIC study showing that CMHTs’ dependent patients receive any alcohol or
drug abuse treatment even more rarely than those from our sample24
. Comparisons might be less
appropriate with countries like USA where a variety of factors other than place of residence
determines who uses which service36
. Indeed, the 2005 National Survey on Drug Use and Health
identified that among people with co-occurring mental and substance use disorders, just
approximately half (47%) received treatment at a specialty facility. Of these, 34% received treatment
only for their mental health problems and 4% received specialty substance abuse treatment only,
showing unmet treatment needs perhaps even more serious than those from our findings19
.
4.2 Correlates of 12 month dependence in people with SMI
Previous studies have suggested that the early identification of several correlates may assist clinicians
in managing dependence in DD people37, 38
. Our study adds important information on relatively new
correlates. Involvement in the criminal justice system often results from illegal drug-seeking
behaviour and participation in activities that reflect, in part, disrupted behaviour ensuing from
dependence39
. However there is the need for further research exploring if SMI condition may modify
the association between criminal justice sanctions and dependence as compared with non SMI people.
Furthermore, adverse health consequences such as liver diseases are associated with both drug
dependence40
and SMI41
. Thus it is not surprising that our findings show an important risk for liver
diseases in SMI people with dependence. As regards dependence potential of individual drugs, our
findings show that opioids and cocaine induce powerful dependence, confirming the general tendency
of these classes of substances42
. However the most striking feature is the role played by geographic
area of residence on the chances of suffering from dependence, since people with SMI living in
Central and Southern Italy were more likely to suffer from this condition as compared with those
living in Northern Italy. Higher availability of substances, along with relatively scarce preventive
programmes, are the most likely explanations, that are confirmed by figures showing that quantity of
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seizures of drugs by law enforcement agencies are mainly concentrated in Central and Southern Italy,
and that prevention is unevenly implemented across the country43
. Furthermore, studies of inequalities
in health between geographic areas have shown no significant association with urbanization for
substance use disorders, but this was the case for SMI (e.g.,44
). Additional research specifically
exploring the association with dual diagnosis is needed.
4.3 Correlates of provision of treatment for substance abuse by specialty services
The correlates of provision of treatment by specialty services matched up just in part those of
dependence, providing useful clues for the design of policy initiatives that can improve access to care
for comorbid people with SMI. Our findings show that “external” drivers such as legal issues and
comorbid physical conditions, but also area of residence and psychiatric diagnosis, may play a major
role in terms of provision of treatment for substance abuse. First, if treatment for drug dependence is
offered as an alternative to criminal justice sanctions, people with SMI are more likely to be treated by
specialty services. Indeed, substance abuse services have been traditionally more closely affiliated
with criminal justice system rather than with mental health care one21
. Our findings also confirm
previous evidence that if people with SMI suffer from liver diseases (Hepatitis B and C), this
increases their odds to be treated by drug and alcohol services45
.
Secondly, as regards geographic area of residence, our findings show that despite people with
comorbid SMI and living in Central and Southern Italy are more likely to suffer from dependence,
they have lower odds to get relevant treatment than those living in Northern regions. Possible
explanations for this puzzling result are the regional barriers to substance abuse treatment for people
with comorbid mental disorders living in Central and Southern regions, with possibly less efficient
regional health systems26
. A second possible explanation is that many individuals perceive substance
abuse services as more stigmatizing than those for mental health care. This may be more true for
social and cultural reasons in central and southern areas of the country46
, reflecting differences in
public attitudes.
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As regards individual classes of substances, subjects using drugs with the highest harm potential
(heroin and cocaine) were more likely to access specialty services, which is largely consistent with the
relevant literature, (e.g.,47
). However, our findings also show that different comorbid psychiatric
disorders are associated with different chances to be treated by addiction services48
. Overall, cluster A
and B personality disorders are the comorbid disorders that increase the chance to be treated. On the
other hand, comorbid people with schizophrenia have the lowest chances to use addiction services.
Ineffective referral from CMHTs, differential difficulties in engaging different clinical populations in
traditional addiction services, lack of competencies and skills among drug and alcohol services staff,
poor treatment-seeking behaviours in individuals with comorbid psychotic disorders, all are possible
explanations supporting the need for an integrated approach5.
4.4 Limitations
We acknowledge several limitations. First, alcohol and substance disorders of people with SMI were
screened by staff-report. This may inflate the association between dependence and receipt of
treatment, since providers may be more likely to recommend substance-related services for those who
are perceived as having more severe problems. Nonetheless, at least with respect to dependence, staff
screening provides valid and reliable estimates49
. In addition, we could not collect data about referrals
and low rates of use of drug and alcohol services might be explained by poor compliance of people
with SMI. Having to go to two different settings to treat two problems is likely to reduce willingness
to attend treatment. We also restricted the sample to people with SMI with GAF < 60 i.e., the
individuals with more severe and probably more treatment resistant illness. We have thus restricted
also the ability to examine associations between substance use disorders and severity, eliminating
patients who may have had severe illness, but done well under treatment. Furthermore, we did not
cover special populations (e.g., SMI prisoners, homeless, and those in residential long term
programmes) who have perhaps more severe forms of substance disorders21
, as well as tobacco
use/dependence, which is common in severely mentally ill populations. In addition, because of
peculiar characteristics in designing and financing of European health, our results may not generalize
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to other settings, especially with regard to correlates of service use. Finally, limitations regarding
temporal relationship and causality, inherent to cross-sectional design, should be obviously
considered.
5. Conclusions
There are extensive unmet needs for comorbid substance use disorders among individuals receiving
mental health treatment for SMI in CMHTs. A large proportion of them do not receive treatment by
addiction services, especially if schizophrenia is the comorbid SMI. Better integration of programmes
for alcohol and other substances disorders in the mental health care system either more effective
referral procedures across the two separate systems of care are needed.
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Disclosures and acknowledgments
The authors declare that there are no conflicts of interest.
Role of funding source
The “Psychiatric and Addictive Dual Disorder in Italy (PADDI)” Study was funded by the Italian
Government Department for Anti-drug Policies (DPA).
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Table 1. Socio-demographic, clinical and 12 months substance use† characteristics
Total
N=2235
Women
N=552
Men
N=1683
P*
N % N % N %
Age, years (Mean, SD) 39 11 42 11 39 10 <0.001a
Education (compulsory only) 1647 74 363 66 1284 76 <0.001
Unemployed 1258 58 331 62 927 57 ns
Living alone 427 20 99 19 328 20 ns
Family situation (single) 1755 81 387 72 1368 84 <0.001
Children 649 31 247 48 402 26 <0.001
Criminal justice sanctions 373 17 36 7 337 20 <0.001
Geographic area (Italy)
Northern
Central
Southern
1415
331
489
63
15
22
393
105
54
71
19
10
1022
226
435
61
13
26
<0.001b
Liver diseases
Hepatitis B
Hepatitis C
667
108
299
30
5
13
129
19
59
23
3
11
538
89
240
32
5
14
<0.001
ns
ns
HIV-positive 81 4 25 5 56 3 ns
Family history
Psychiatric disorders
Substance use
697
379
31
17
186
112
34
20
511
267
30
16
ns
0.04
Alcohol Dependence 588 26 143 26 445 26 ns
Other than alcohol Dependence
Cannabis
Opioids
Cocaine
Hallucinogens
Prescription drugs
460
103
326
103
11
53
21
5
15
5
0.5
2
83
14
52
21
1
24
15
3
9
4
0.2
4
377
89
274
82
10
29
22
5
16
5
0.6
2
<0.001
ns
<0.01
ns
ns
<0.01
SMI diagnoses
Schizophrenia and other psychotic
Bipolar
Depressive
Cluster A/B personality
681
395
230
929
30
18
10
42
99
115
87
251
18
21
16
45
582
280
143
678
35
17
8
40
<0.001c
12 months substance use specialist
treatment
Specialist counselling
Outpatient maintenance§
Residential treatment
Detoxification hospital admission
1118
671
207
197
79
50
30
9
9
4
262
170
41
38
25
47
31
7
7
5
856
501
166
159
54
51
30
10
9
3
ns
ns
ns
ns
ns †AUS/DUS assessment. *Bonferroni multiple testing correction. aStudent’s t test. All Pearson’s χ2 tests d.f.=1, but b =2 and c=3. §Methadone/buprenorphine. Each participant may have been using more than one substance and having received more than one specialist
programme in the past 12 months.
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Table 2. Dependence† and treatment for substance use by SMI diagnoses 1.Schizophrenia
and other
psychotic
disorders
(N=681)
2.Bipolar
disorders
(N=395)
3.Depressive
disorders
(N=230)
4.Cluster A/B
personality
disorders
(N=929)
P Post hoc#
N % N % N % N %
Alcohol
Dependence
150
22
121
31
65
28
252
27
0.036
1-2*
Other substances
Dependence
122
18
79
20
38
17
221
24
0.033
1-4*
12 months substance use
specialist treatment
Specialist counselling
Outpatient maintenance§
Residential treatment
Inpatient detoxification
265
162
41
40
23
38
24
6
6
3
203
121
43
32
13
51
31
11
8
3
112
75
20
15
4
49
33
9
7
2
547
313
103
110
39
59
34
11
12
4
<0.001
<0.001
0.016
<0.001
ns
1-2***
, 1-3*,
1-4***
, 3-4*
†AUS/DUS assessment. All tests are Pearson’s χ2 test with 3 d.f. #Bonferroni multiple testing correction: *p<0.05 **p<0.01 ***p<0.001. §Methadone/buprenorphine. Each participant may have been using more than one substance and having received more than one specialist
programme
in the past 12 months.
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Table 3. Characteristics significantly associated with 12 month Dependence and with provision of
specialty treatment for substance disorders
Dependence Specialty services treatment
Unadjusted
OR (95%
CI)
P Adjusted
OR*
(95% CI)
P Unadjusted
OR (95%
CI)
P Adjusted
OR§
(95% CI)
P
Gender1 1.39 (1.14
to 1.69) 0.001 1.24
(1.00 to
1.54)
ns 1.15 (0.94
to 1.39)
ns 1.07
(0.85 to
1.34)
ns
Age 1.02 (1.01
to 1.02) <0.001 1.02 (1.01
to 1.03) <0.001 0.98 (0.97
to 0.99) <0.001 0.99 (0.99
to 1.00) ns
Geographic
area2
2.54 (2.12
to 3.05) <0.001 2.17 (1.79
to 2.64) <0.001 1.15 (0.97
to 1.36) ns 0.78 (0.64
to 0.96) 0.020
Criminal
justice
sanctions
1.96 (1.56
to 2.45) <0.001 1.36 (1.04
to 1.76) 0.023 2.43 (1.91
to 3.08) <0.001 1.59 (1.20
to 2.11) 0.001
Education3 0.79 (0.65
to 0.95) 0.012 0.90 (0.73
to 1.12) ns
Employment4 0.86 (0.72
to 1.00) 0.047 1.02 (0.84
to 1.25) ns
Living
condition5
1.36 (1.10
to 1.69) 0.004 1.38 (1.08
to 1.75) 0.010
HIV+ 1.95 (1.24
to 3.07) <0.001 0.98 (0.59
to 1.62) ns 2.96 (1.78
to 4.91) <0.001 1.45 (0.80
to 2.61) ns
Liver disease 2.90 (2.39
to 3.51) <0.001 1.93 (1.56
to 2.37) <0.001 1.79 (1.49
to 2.15) <0.001 1.53 (1.23
to 1.91) <0.001
Substances Opioids 4.18 (3.37
to 5.19) <0.001 4.24 (3.34
to 5.38) <0.001 6.11 (4.77
to 7.82) <0.001 4.71 (3.60
to 6.15) <0.001
Cocaine 2.41 (1.94
to 2.98) <0.001 1.53 (1.19
to 1.98) 0.001
Cannabinoids 0.76 (0.64
to 0.91) 0.003 0.60 (0.47
to 0.75) <0.001
12-month
DSM-IV
diagnoses6
Bipolar
Disorders 1.62 (1.26
to 2.09) <0.001 1.76 (1.36
to 2.26) <0.001 1.96 (1.47
to 2.61) <0.001
Depressive
Disorders 1.20 (0.88
to 1.63) ns 1.58 (1.16
to 2.13) 0.003 2.04 (1.45
to 2.88) <0.001
Cluster A and
B personality
Disorders
1.51 (1.24
to 1.86) <0.001 2.38 (1.93
to 2.93) <0.001 2.46 (1.96
to 3.10) <0.001
Analyzed: *N=2235; §N=2106.
Reference categories: 1females, 2Central and Southern vs. Northern Italy, 3compulsory only, 4unemployed, 5living alone, 6Schizophrenia and other psychotic disorders
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