Journal of Substance Abuse Treatment 51 (2015) 30–37

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Journal of Substance Abuse Treatment

Effects of a Brief Intervention for Substance Use on Tobacco Smoking and Family Relationship Functioning in Schizophrenia and Related Psychoses: A Randomised Controlled Trial Nopporn Tantirangsee, M.D. a,⁎, Sawitri Assanangkornchai, M.D., Ph.D. a, John Marsden, Ph.D. b a b

Epidemiology Unit, Faculty of Medicine, Prince of Songkla University, 15 Kanchanavanich Road, Hat Yai, Songkhla 90110, Thailand Addictions Department, Institute of Psychiatry, Psychology & Neuroscience, King's College London SE5 8AF, United Kingdom

a r t i c l e

i n f o

Article history: Received 24 May 2014 Received in revised form 18 October 2014 Accepted 27 October 2014 Keywords: Psychosis Schizophrenia Substance use Smoking Brief intervention Family support

a b s t r a c t Surveys indicate that substance use is prevalent in populations with schizophrenia. Family members may be able to support brief interventions (BI). We conducted a randomised controlled trial with 6-month follow-up among adult patients with schizophrenia and related psychoses who were referred to two hospitals in southern Thailand. Patients with psychosis were screened using the Alcohol Smoking and Substance Involvement Screening Test (ASSIST). 169 participants (all at moderate substance risk on the ASSIST) were randomised to receive simple advice (the clinics' treatment-as-usual, TAU condition), or single-session brief intervention (BI), or a single-session BI with family support (BI-FS). Given observed substance use, the primary outcome was the ASSIST tobacco smoking involvement score (SIS). Secondary outcomes were cigarettes smoked per day, change motivation (Taking Steps from the Stages of Change and Treatment Eagerness Scale), and DSM-IV Axis V Global Assessment of Relational Functioning (GARF). At follow-up, BI-FS participants reported a lower SIS (mean difference, −2.82, 95% confidence interval [CI] −4.84 to −0.81; Glass' effect size [Δ] = 0.57, 95% CI 0.19 to 0.95), smoked fewer cigarettes per day (mean difference −3.10, 95% CI −5.45 to −0.74; Δ = 0.56, 95% CI 0.18 to 0.94), had greater change motivation (mean difference 3.05, 95% CI 0.54 to 5.57; Δ = 0.41, 95% CI 0.03 to 0.79) and GARF (mean difference 6.75, 95% CI 1.57 to 11.93; Δ = 0.54, 95% CI 0.16 to 0.92). The BI-FS group also had better relational functioning in comparison to those receiving BI only (mean difference 5.44, 95% CI 0.20 to 10.67; Δ = 0.46, 95% CI 0.08 to 0.84). In schizophrenia and related psychoses, a brief intervention supported by a family member reduces smoking involvement, cigarette smoking intensity, and increases change motivation and relational functioning. © 2015 Elsevier Inc. All rights reserved.

1. Introduction Psychiatric epidemiology surveys report higher rates of psychoactive substance in schizophrenia compared to the general population (Volkow, 2009) and a marked global burden of disease for mental and substance use disorders (7.4% of all disability-adjusted life years worldwide; Whiteford et al., 2013). Use of alcohol, tobacco (smoking herein) and non-medical substances in people with schizophrenia is much higher than the general population. For example, in a community survey conducted in the USA, the rate of lifetime substance use among schizophrenics was as follows: alcohol (89%), smoking (70%), cannabis (45%), cocaine (20%), opioids (18%) and amphetamines (17%; Martins & Gorelick, 2011). A recent cohort study of schizophrenia and related psychoses (the latter including bipolar disorder with psychotic features and schizoaffective ⁎ Corresponding author at: Epidemiology Unit, Faculty of Medicine, Prince of Songkla University, 15 Kanchanavanich Road, Hat Yai, Songkhla 90110, Thailand. Tel.: + 66 849990662; fax: +66 74429754. E-mail address: [email protected] (N. Tantirangsee). http://dx.doi.org/10.1016/j.jsat.2014.10.011 0740-5472/© 2015 Elsevier Inc. All rights reserved.

disorder), calculated the following odds ratios for substance use relative to the general population: smoking (4.6), heavy alcohol use (4.0), heavy cannabis use (3.5) and recreational drug use (4.6; Hartz et al., 2014). A wide range of different explanations have been advanced to explain the high rate of substance use and related problems in schizophrenia. For example, people with schizophrenia and other psychoses may be motivated to use psychoactive substances as self-medication or because of social facilitation motivations (Blanchard, Brown, Horan, & Sherwood, 2000). Other explanations include biological factors such as increased sensitivity to the effects of substances (Mueser, Kavanagh, & Brunette, 2007), and “common factors” that increase vulnerability to both substance use and mental illness including personality disorders, poverty or early trauma (Hides, Lubman, & Dawe, 2004; Mueser, Drake, & Wallach, 1998). Substance use in this population adds complexity to clinical care and is associated with greater illness severity (Harrison et al., 2008), reduced medication compliance (Jonsdottir et al., 2013), more hospital episodes (Schmidt, Hesse, & Lykke, 2011), legal problems (Cantwell, 2003), family relationship difficulties (Salyers & Mueser, 2001; Wilson, Bennett, & Bellack, 2013), and an increased likelihood of relapse (Sorbara, Liraud, Assens, Abalan, & Verdoux, 2003).

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Psychological interventions may be effective at helping to reduce substance use and related harms. Controlled trials of brief interventions (BI) based on motivational interviewing (Miller & Rollnick, 1991, 2002) have reported positive outcomes among those with psychosis, including: reduced alcohol consumption (Milner, Barry, Blow, & Welsh, 2010), increased rate of referral for smoking cessation treatment (Steinberg, Ziedonis, Krejci, & Brandon, 2004) and fewer and shorter hospital treatment episodes (Kavanagh et al., 2004). In trials of longer-term treatment (over 9–18 months) which have involved family members, Barrowclough et al. (2001) and Mueser et al. (2013) reported increased abstinence from substance use, reduced psychiatric symptoms, and improvements in general health and social functioning. To date, longer-term interventions have been evaluated only in Western health care systems with relatively high resources. The cost of intensive psychological therapies is likely to deter delivery in many treatment systems with modest resources, including Thailand. To our knowledge there has been no involvement of family members in BI for schizophrenia and related psychoses. Accordingly, our group set out to develop a low-cost BI for substance-related problems that includes a member of the patient's family to support the intervention. We targeted individuals at moderate (rather than high or low) risk for substance-related problems and following the recommendation from WHO that patients with severe scores on the ASSIST should be referred for intensive care. Our study was conducted at in two outpatient psychiatric treatment clinics: Songkhla Rajanagarinda Psychiatric Hospital (SKPH) and Satun General Hospital (SGH) in the Southern Region of Thailand. SKPH coordinates a network of local community psychiatry services across seven provinces, and SGH is one of the local members of the network. In each clinic, all patients admitted with schizophrenia or a related psychosis are screened for substance use using the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST; Humeniuk et al., 2008), and simply advised to cut down or quit. The ASSIST was designed to be responsive to the specific range of psychoactive substances uses by a specific population. There have been no substance use prevalence surveys of people with psychosis in Thailand, but surveys of the general population were used to guide the expected substance use profile for the past month, as follows: smoking (23.6%); harmful alcohol use (3.1%); kratom (0.6%; the chewed leaves of mitragyna speciosa, a μ-opioid receptor agonist; Assanangkornchai, Muekthong, Sam-Angsri, & Pattanasattayawong, 2007; Stolt et al., 2014); inhalants (0.07%); amphetamine (0.05%); and cannabis (0.03%; Aekplakorn et al., 2008; Assanangkornchai et al., 2008). We assumed that the target patient population would have a higher prevalence of substance use than these rates. Our study was a pragmatic, three-group, randomised controlled trial undertaken in parallel at SKPH and SGH. We hypothesised that in comparison to standard screening and simple advice (the treatment-asusual [TAU] control), participants receiving a BI-FS or a BI would have a better outcome, and that the BI-FS intervention would be more effective than BI alone. This report presents the findings from the study. 2. Methods 2.1. Participants Patients targeted for the study were diagnosed with psychosis and assigned to one of the following International Classification of Disease (ICD-10) psychosis disorders: schizophrenia (F20); acute and transient psychotic disorder (F23); and unspecified non-organic psychosis (F29) (World Health Organization [WHO], 1992). Eligible patients were: adult (18 years and over), able to read and write Thai, had regular contact with one or more family members, and screened positive with the ASSIST for recent psychoactive substance use in a moderate range of severity (see Section 2.5 below for information on scoring). A psychiatrist ruled out amphetamine-induced psychotic disorder (ICD-10; F15-15)

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differentially by clinical history and negative urine drug screen. Other exclusion criteria were communication or cognitive problems, aggression, presumed substance intoxication or onset of withdrawal. The study was implemented according to Good Clinical Practice guidelines. The protocol and research materials were reviewed by the Institutional Ethics Committees at the Faculty of Medicine, Prince of Songkla University (PSU: 55-222-18-5-2) and SKPH (15/2554) and the protocol was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12612001059853). A Trial Management Group at the PSU Faculty of Medicine (headed by author S.A.) was responsible for day-to-day running of the study. All enrolled participants gave their written informed consent. 2.2. Randomisation Patients were randomised in a 1:1:1 ratio to one of three study groups: a single-session BI, a single-session BI with family support (BI-FS), or an advice-only TAU. Prior to the study, an independent researcher from PSU generated a random list of participant-to-group assignments for the sequential, non-stratified randomisation procedure (using R software; R Core Team, 2014) and sealed these in sequentially numbered opaque envelopes. The procedure was implemented by the research team at each site after screening, and coordinated by lead investigator N.T. 2.3. Interventions All study interventions were delivered by a team of four psychiatric nurses (two at each site) who worked on the study throughout. The TAU group reflected the standard procedure at each clinic in which any patient diagnosed with psychosis who is screened at moderate risk with the ASSIST is advised to stop or reduce their use of each substance declared. For the study, a nurse met the participant in an interview room to report their ASSIST score and give this advice which took approximately 5 minutes. The BI group received a 30–45 minute face-to-face session by a study nurse giving personalised feedback from the ASSIST and motivating change using Motivational Interviewing techniques for BI interventions adapted by the WHO ASSIST group (Humeniuk et al., 2012). The BI materials were developed in treatment manual format and two expert reviewers in Thailand commented on a complete draft version before final editing of materials. The BI session included the following elements: • discussion of substance use patterns and motives; • education on intoxication, tolerance and withdrawal symptoms; • how physical and mental health problems can be caused or exacerbated by substance use; • behaviour change options designed to build motivation, intentions and goals; • cognitive and spiritual strategies to identify high-risk situations and cope with cravings; and • information on changing substance use, and accessing local services and supports. The BI-FS group received a 45–75 minute face-to-face session with a nurse with the participant's nominated key relative in attendance. The BI-FS session covered the six content areas from the BI above, supplemented with the following topics: • the importance and methods of good communication between family members; • general problem-solving techniques that the family can use to help members who face personal difficulties; and • specific methods the family can use to help the participant stop or reduce their use of the substances declared during the ASSIST screening.

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2.4. Study measures The following standardised, interviewer-administered instruments were used at baseline and follow-up (unless otherwise stated): Alcohol, Smoking and Substance Involvement Screening Test (ASSIST V3.0; WHO ASSIST Working Group, 2002). The ASSIST is a multi-substance screening test which has been developed in a wide range of mental health treatment settings and cultures, including Thailand (Humeniuk et al., 2008). Administration time has been a barrier to uptake in busy clinic practice (Mdege & Lang, 2011) and, after consultation with the WHO collaborating centre in Adelaide, South Australia, an adapted version of the ASSIST was used to expedite the screening process for the study. A mix of common and specific questions was included for each substance class. For example, there were four questions asked of participants who had smoked in the past 3 months: (1) How often have you had a strong desire or urge to smoke cigarettes? (2) Has a friend or relative or anyone else expressed concern about your smoking? (3) Have you tried and failed to control, cut down or stop using cigarettes? (4) How soon after you wake up do you have your first cigarette? Responses to Q1 were recorded using a five-point scale: never (0); once or twice (1); monthly (2); weekly (3); daily or almost daily (6). Responses to Q2 and Q3 were: no (0); yes (4). Responses to Q4 coded the participant's response as N60 minutes (0); 31–60 minutes (1); 6–30 minutes (2) and b 5 minutes (4). For alcohol, a measure of intoxication (six or more drinks [men] or four or more drinks [women] on a single occasion: no [0]; yes [4]) was also added to the question set. Scoring a multiple substance test is challenging because of variation in the number and severity of substances used. In the present study two summary scores were planned: (1) a [named] substance involvement score (SIS; categorized into low risk [score 0–3], the target moderate risk range [4–14 for smoking and alcohol, 4–12 for cannabis and 4–26 for all others substances] or high risk [15+ for smoking and alcohol, 13+ for cannabis and 27+ for all others substances]); and (2) Total Substance Involvement Score (TSIS), computed as the sum of the item weights for each substance (SIS) and overall to capture poly-substance use (TSIS). Time-line follow-back interview (TLFB; Sobell & Sobell, 1992). A past 28-day TLFB interview was used to record the number of days and amount of recent substance use. The TLFB has been shown to have good validity and reliability in psychotic patients (Carey, Carey, Maisto, & Henson, 2004; DeMarce, Burden, Lash, Stephens, & Grambow, 2007). Brief Psychiatric Rating Scale (BPRS; Overall & Gorham, 1962). The 18item BPRS assessed psychiatric symptoms at baseline. The BPRS includes symptoms of positive and negative psychosis, mania, depression and anxiety (each item rated as present-to-extremely severe; scored 1–7; total score range, 18–126). The BPRS is reliable with an intraclass correlation coefficient of 0.78 (Andersen et al., 1986). Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES V8; Miller & Tonigan, 1996). The 19-item SOCRATES was used to capture the participant's motivation to change substance use behaviours. There are three sub-scales: Recognition (score range 7–35), Ambivalence (range 4–20) and Taking Steps (range 8–40). These sub-scales are internally consistent (Cronbach's alpha 0.60–0.96; Miller & Tonigan, 1996) and higher scores indicate greater motivation. Global Assessment of Relational Functioning (GARF; American Psychiatric Association, 2000). The GARF is a single item rating scale to assess overall problem solving, organisation and the emotional climate of the family (scored 0–100 with higher scores reflecting better functioning). The GARF is reliable in psychiatric populations (alpha, 0.82; Denton, Nakonezny, & Burwell, 2010). 2.5. Outcome measures The primary outcome measure was a specific substance involvement score idiosyncratic to each participant. We determined this according to

the highest value of this measure in instances of two or more substances declared at baseline. In instances of tied scores, the substance of most concern to the patient (recorded during screening) was used for the primary outcome. A change score was then computed (i.e. baseline minus follow-up) along with its 95% confidence interval (CI). In the event, due to the observed screening profile for the sample (see Table 1), the smoking involvement score (SIS) was taken forward as the sole primary outcome measure for the analysis. There were four planned secondary outcome measures: (1) the number of smoking days in the past month, (2) the number of cigarettes smoked per day, (3) change score for the Taking Steps sub-scale from the SOCRATES, and (4) the change score on the GARF. 2.6. Procedure For a pilot study in June 2012, a university graduate research assistant interviewed patients with psychosis who attended SKPH and SGH clinics to assess the likely acceptability of the study, the flow of the research questionnaires, and to also monitor the rate of admissions to inform sample size calculations. Table 1 Characteristics of the participants (N = 169). Characteristic (%)

Study site Songkhla Satun Gender Male Female Age (mean ± SD) Marital status Single Married Divorced Religion Buddhism Islam Educational level ≤Primary school Secondary school NSecondary school In employment No Yes Duration of illness b3 years ≥3 years Episode of illness b3 episodes ≥3 episodes ICD-10 diagnosis F20 (schizophrenia) F23 (transient psychotic disorder) F29 (unspecified nonorganic psychosis) Atypical antipsychotic use No Yes Substance use Smoking Alcohol Illicit substance Substance reported to be a concern Smoking Alcohol Illicit substance

Study condition

Total

TAU (n = 57)

BI (n = 54)

BI-FS (n = 58)

(N = 169)

48 (84.2) 9 (15.8)

44 (81.5) 10 (18.5)

52 (89.7) 6 (10.3)

144 (85.2) 25 (14.8)

57 (100) 52 (96.3) 57 (98.3) 166 (98.2) – 2 (3.7) 1 (1.7) 3 (1.8) 35.49 ± 7.0 35.52 ± 10.1 34.98 ± 11.0 35.33 ± 9.5 40 (70.2) 9 (15.8) 8 (14.0)

39 (72.2) 11 (20.4) 4 (7.4)

34 (58.6) 19 (32.8) 5 (8.6)

113 (66.9) 39 (23.1) 17 (10.0)

32 (56.1) 25 (43.9)

30 (55.6) 24 (44.4)

39 (67.2) 19 (32.8)

101 (59.8) 68 (40.2)

18 (31.6) 27 (47.4) 12 (21.1)

21 (38.9) 23 (42.6) 10 (18.5)

26 (44.8) 24 (41.4) 8 (13.8)

65 (38.5) 74 (43.8) 30 (17.7)

12 (21.1) 45 (78.9)

16 (29.6) 38 (70.4)

15 (25.9) 43 (74.1)

43 (25.4) 126 (74.6)

15 (26.3) 42 (73.7)

18 (33.3) 36 (66.7)

21 (36.2) 37 (63.8)

54 (32) 115 (68.0)

43 (75.4) 14 (24.6)

37 (68.5) 17 (31.5)

43 (74.1) 15 (25.9)

123 (72.7) 46 (27.3)

49 (86) 4 (7.0)

45 (83.3) 5 (9.3)

42 (72.4) 9 (15.5)

136 (80.5) 18 (10.7)

4 (7.0)

4 (7.4)

7 (12.1)

15 (8.9)

33 (57.9) 24 (42.1)

31 (57.4) 23 (42.6)

34 (58.6) 24 (41.4)

98 (58.0) 71 (42.0)

55 (96.5) 13 (22.8) 7 (12.3)

53 (98.1) 11 (20.4) 3 (5.5)

58 (100.0) 9 (15.5) 5 (8.6)

166 (98.2) 33 (19.5) 15 (8.9)

54 (94.7) 2 (3.5) 1 (1.8)

51 (94.4) 2 (3.7) 1 (1.9)

57 (98.3) 1 (1.7) –

162 (95.8) 5 (3.0) 2 (1.2)

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For the trial, lead investigator N.T. trained the four psychiatric nurses and the university graduate research assistant in administration of the study materials and the TAU, BI and BI-FS procedures. All nurses were trained and certificated in the use of BI and BI-FS procedures (under Thai BI implementation initiative coordinated by author S.A., and training for the present study coordinated by author N.T.). Each nurse received a total of 20 hours of training, over 5 days. As part of intervention fidelity monitoring, each nurse completed a checklist of techniques used in each delivered intervention session. Author N.T. checked all checklists weekly and additional training input was given as needed to maintain protocol adherence. Recruitment of participants took place between July 2012 and January 2013, and all follow-ups were completed by June 2013. A psychiatric nurse who was blind to the participant's allocated group conducted a personal follow-up interview in a private interview room at SKPH and SGH 6 months after the BI, BI-FS or TAU. Participants received 200 Thai Baht (about 6 US dollars) to offset their time to attend the follow-up. If efforts to secure a personal interview were unsuccessful, the follow-up was completed by telephone. 2.7. Sample size The number of participants for the trial was informed by study resources, the patient admission rate, and the standardised effect size (ES) reported from previous BI trials. The pilot study indicated that there would be approximately 30 eligible patients willing to take part each month and study resources would support recruitment of 60 participants in each group (n = 180). With an assumed 15% attrition, an analysis of variance (ANOVA; two-tailed 5% test) of mean scores for the primary outcome measure indicated that an ES as low as 0.38 could be detected with 80% power between conditions. This compared favourably to the 0.54 ES reported by Spirito and colleagues for an alcohol BI with a family session compared to BI alone (Spirito et al., 2011), and the 0.33 ES reported in the Humeniuk trial of an ASSIST-linked BI versus advice (Humeniuk et al., 2012).

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3. Results 3.1. Participant characteristics and baseline measures Of 663 potentially eligible patients screened, 341 patients reported no substance use in the past 3 months. Among the users, 11 were categorised as low-risk and 59 as high-risk (see Fig. 1). These patients were excluded. Targeting the 252 moderate-risk patients, 27 were not eligible and 56 declined to participate, with the remainder (N = 169) randomised to one of the three conditions. At 6-month follow-up, 158 (93.5%) cases completed the interview (111 were able to attend the outpatient department for this [70.4%] and 47 cases were followed-up by telephone [29.7%]). Table 1 shows the characteristics of the study participants. Almost all were male (98.2%), with a mean age of 35.3 years (SD = 9.5, range = 18–66 years). Paid employment was the norm (75%). Of these, the majority [73%] reported seasonal work for 9 months each year in the local agricultural sector. Schizophrenia was the most common disorder (80.5%) with the remaining participants diagnosed with brief psychotic disorder or an unspecified non-organic psychosis. The mean duration of illness was 7.6 years (SD = 6.6) with an average of 2.4 treatment episodes (SD = 2.4) before enrolment to the study. There was no statistical significant difference of baseline characteristics between groups [maximum chi-square(4) = 6.15, P = 0.19]. Tobacco was the most prevalent substance used in the past 3 months (98.2%; with 94.6% daily smokers). On average, 13.9 cigarettes (SD = 7.7) were smoked each day. Almost all smokers reported concern about smoking and health. Alcohol use was reported by 19.5%, with an average of 2.9 (SD = 2.6) standard drinks per day consumed, and just five participants reported that drinking was a concern for them. Fifteen participants (8.9%) had used a non-medical substance in the past 3 months, mainly krathom. Six participants also reported drinking a kratom-based infusion (reputedly a mixture of krathom juice, opioid cough syrup, cola soft drink and benzodiazepines). A minority reported using methylamphetamine (n = 5) and cannabis (n = 4).

2.8. Statistical analysis

3.2. Primary outcome measure

An advance-specified statistical analysis plan followed the intent-totreat principle. Baseline differences between groups were compared using chi-square tests for categorical variables and one-way ANOVA for scaled or continuous variables. Given the two-centre study design, the analysis was implemented using a mixed-effects (two-level) linear regression model (R software, version 3.03; NLME package; Pinheiro, Bates, DebRoy, Sarkar, & R Core Team, 2013) with age, and mean-centred values for the baseline TSIS, BPRS and Recognition scales as covariates. The hypothesis test value for model contrasts was set at 5% and, given the pre-planned analysis, we did not adjust for type I error. Fixed-effects for covariates and treatment condition were computed for each model and random-effects were computed as intercepts for study site. Residual plots informed homoscedasticity and normality (but did not show any deviation from normal). ANOVA showed no differences between the two sites on all outcomes. Glass's effect size (Δ) was computed for between group contrasts for all statistically significant differences (Hedges, 1981). With no evidence that the minimal level of missing outcome data observed was not missing-at-random (Little & Rubin, 1987), a multiply imputed dataset was created for the analysis by chained equations (R's MICE package; Buuren & Groothuis-Oudshoorn, 2011). In addition to the outcome measure, study group, site, age [18–30 and 31–45 years], baseline substance use score, marital status, religion, education level, occupation, and duration of illness variables were included in the imputation model. Five sets of probabilistic values were imputed and combined using Rubin's rules (Rubin, 1987).

Given the observed profile of substance use at screening, we focused the analysis on the smoking involvement score (SIS). Table 2 shows the primary and secondary outcome measures among participants (n = 166) who were current smokers in each group at baseline and 6 month follow-up. There were no differences on all baseline measures [maximum F(2,163) =1.14, P = 0.32]. The results of the two-level, mixed-effects models for the outcome measures are shown in Table 3. After adjustment for covariates and site-level patient correlation effects, there was a significant reduction in the SIS in the BI-FS group compared to TAU (mean difference, − 2.82, 95% CI −4.84 to − 0.81; Δ = 0.57, 95% CI 0.19 to 0.95). There was no change in SIS among the BI group at follow-up (P N 0.05), nor was there a difference in SIS between the BI-FS and BI groups (P N 0.05). 3.3. Secondary outcome measures For the secondary outcome measures, there were no statistically significant reductions in the number of smoking days among the BI-FS and BI groups compared to TAU (P N 0.05). For the BI-FS group in comparison to TAU, there were reductions in the number of cigarettes smoked per day (mean difference − 3.10, 95% CI − 5.45 to − 0.74; Δ = 0.56, 95% CI 0.18 to 0.94), increases in change motivation (Taking Steps mean difference 3.05, 95% CI 0.54 to 5.57; Δ = 0.41, 95% CI 0.03 to 0.79), and increases in relational functioning (GARF mean difference 6.75, 95% CI 1.57 to 11.93; Δ = 0.54, 95% CI 0.16 to 0.92). On this latter measure, participants who received the BI-FS intervention reported

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N. Tantirangsee et al. / Journal of Substance Abuse Treatment 51 (2015) 30–37

Fig. 1. Flow of participants through the trial.

greater relational functioning than the BI group (GARF mean difference 5.44, 95% CI 0.20 to 10.67; Δ = 0.46, 95% CI 0.08 to 0.84). Finally, there was some evidence of a reduction in the alcohol consumption (standard drink per day) between BI-FS and TAU (mean difference −3.13, 95% CI −6.03 to −0.23; Δ = 1.07, 95% CI 0.10 to 2.04), but the low number of participants (13 in the TAU group and 9 in the BI-FS group; Table 1) precluded reliable analysis and interpretation (the data not reported here). 4. Discussion 4.1. Main findings In comparison to screening and simple advice, we found that a screening procedure linked to a BI with family support (BI-FS) was effective at reducing a composite measure of hazardous smoking (SIS; the primary outcome measure), and also smoking intensity (cigarettes per day), and increasing change motivation and relationship functioning. Contrary to expectation, a BI with no family support was not associated with positive outcomes on these measures with the exception of increased change motivation. Increasing change motivation is an

important objective for motivational interviewing influenced BI, and one previously observed in the target population (Lahti, Maria, & KoskiJannes, 2013). However, our results do not encourage further development of a single-session BI among the moderate-severity substance use population with schizophrenia and related psychoses in Thailand. These negative results stand in contrast to the findings of reduced substance use following a BI-only intervention among patients with early psychosis (≤3 episodes; Kavanagh et al., 2004), and increased smoking cessation following a group MI among individuals with psychiatric disorder (Kisely, Wise, Preston, Malmgren, & Shannon, 2003). However, one study of brief motivational interventions for substance use in psychiatric in-patient services failed to show an effect (Baker et al., 2002). Therefore, the data on brief motivational interventions for co-occurring disorders are in fact somewhat inconsistent. Compared to the BI alone group, our BI-FS intervention helped participants improve their family relationship functioning. This underscores the value of including a family member in the BI process. As a group, the BI-FS participants did not reduce the number of days they smoked cigarettes. This accords with reports from the nurses who delivered the intervention who noted that most participants chose to

Table 2 Outcomes score in current smokers at baseline and 6-month follow up. Measure

Study condition TAU (n = 55) Baseline

Primary outcome SIS Secondary outcomes Cigarettes per day Smoking days, month Taking Steps GARF

BI (n = 53) 6-month

Baseline

BI-FS (n = 58) 6-month

Baseline

6-month

7.60 (2.02)

9.24 (5.24)

7.74 (2.41)

8.25 (5.44)

8.17 (2.10)

7.16 (5.39)

14.00 (7.96) 28.64 (5.16) 25.89 (5.74) 71.09 (9.49)

11.65 (8.35) 26.15 (8.40) 27.40 (5.27) 69.89 (10.67)

14.57 (8.00) 29.47 (2.69) 24.23 (5.63) 69.62 (9.00)

10.68 (7.82) 26.62 (8.54) 29.55 (3.82) 69.75 (10.86)

13.41 (7.29) 29.52 (2.58) 25.50 (6.50) 71.43 (10.69)

7.93 (6.06) 24.74 (10.86) 30.16 (4.46) 77.09 (12.76)

Note. Numbers in the table are mean (SD); TAU, treatment-as-usual; BI, brief intervention; BI-FS, brief intervention with family support; SIS, Smoking Involvement Score; Taking Steps, subscore from SOCRATES; GARF, Global Assessment of Relational Functioning.

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Table 3 Mixed-effects linear models of outcome measures at 6-month follow-up. Parameter

Intercept Age TSIS BPRS Recognition BI (with TAU as referent) BI-FS (with TAU as referent) BI-FS (with BI as referent) Random effects (level-two) Study site (SD) Random effects (level-one) Residual (SD) ICC Deviance

SIS (primary)

Smoking days

Cigarettes per day

Taking Steps

Coef. (SE)

Coef. (SE)

Coef. (SE)

Coef. (SE)

GARF Coef (SE)

−0.68 (2.35) 0.04 (0.04) 0.01 (0.10) 0.04 (0.04) −0.03 (0.10) −0.98 (1.03) −2.82 (1.02)⁎⁎ −1.85 (1.03)

−2.45 (2.94) 0.00 (0.07) 0.14 (0.17) 0.03 (0.06) −0.17 (0.17) −0.31 (1.73) −2.24 (1.71) −1.93 (1.72)

−5.14 (2.05)⁎ 0.08 (0.05) −0.09 (0.12) 0.02 (0.05) −0.19 (0.12) −1.44 (1.21) −3.10 (1.19)⁎ −1.66 (1.21)

2.14 (2.19) −0.02 (0.06) −0.09 (0.13) 0.11 (0.05)⁎ −0.65 (0.13)⁎⁎⁎ 4.09 (1.29)⁎⁎ 3.05 (1.27)⁎ −1.03 (1.29)

5.66 (4.51) −0.19 (0.11) 0.05 (0.26) 0.01 (0.10) −0.05 (0.27) 1.31 (2.66) 6.75 (2.62)⁎ 5.44 (2.65)⁎

4.59 (2.14)

–

–

–

–

28.70 (5.36) 0.14 1034.28

80.82 (8.99) – 1196.99

39.56 (6.29) – 1083.39

45.00 (6.71) – 1103.89

190.87 (13.82) – 1333.64

Note. SIS, Smoking Involvement Score (primary outcome measure); Taking Steps sub-scales from SOCRATES; GARF, Global Assessment of Relational Functioning; TSIS, Total Substance Involvement Score, mean centered; BPRS, Brief Psychiatric Rating Scale, mean centered; Recognition sub-scales from SOCRATES, mean centered; Coef, coefficient; SE, standard error; SD, standard deviation; ICC, intra-class correlation; BI, brief intervention; BI-FS, brief intervention with family support. Level-two variance and ICC values marked as “–” are zero. ⁎ P b 0.05. ⁎⁎ P b 0.01. ⁎⁎⁎ P b 0.001.

gradually reduce their cigarette use rather than attempting to quit altogether. This is consistent with the Barrowclough et al. (2001) study, where an integrated psychosocial treatment with family intervention did not result in a significant change to the percentage of days of abstinence compared to a routine care control group. Smoking in schizophrenic patients is a major concern because it can increase the mortality risk significantly, and the risk increases as more cigarettes are smoked (Kelly et al., 2011). Nevertheless, a reduction in smoking could result in several clinical benefits: lower doses of antipsychotic medication (Krishnadas, Jauhar, Telfer, Shivashankar, & McCreadie, 2012; Salokangas, Honkonen, Stengard, Koivisto, & Hietala, 2006) due to drug metabolism (Sagud et al., 2009); reduced psychosis severity (Vanable, Carey, Carey, & Maisto, 2003), and direct improvements in cardiovascular function (Dervaux & Laqueille, 2008). The significant increase in GARF score in the BI-FS group compared to TAU and BI groups highlighted the effectiveness of the family support. This could provide patients with psychosis with tangible benefits. A discussion with a nurse and family member about substance use and its relationship to mental health status could increase awareness of risks and harms. Including the family member in a discussion about communication could also improve the family climate and facilitate problem solving (Potvin, Stip, & Roy, 2003).

Fourth, while our findings indicate that the intervention is effective in reducing tobacco smoking, the quit rate was unimpressive and this suggests a need for integrated therapies combining psychological and pharmacological interventions (Tsoi, Porwal, & Webster, 2013). Fifth, we targeted individuals with a moderate risk for substance use problems (in the event, many in the sample were seasonally employed) so opportunities remain for study of treatment among the population with a severe substance profile where social deprivation is likely to be more prevalent. However, it was found that people with severe co-occurring disorders continue to have contact with family members, and thus there is potential for family-based treatment even with such individuals (Clark, 2001; Mueser et al., 2009). 4.3. Conclusions We found it feasible to implement routine screening in busy mental health clinics using a brief version of the ASSIST (see Ali, Meena, Eastwood, Richards, & Marsden, 2013 for a new brief version of the ASSIST which meets or exceeds the psychometric performance of the long version). The results highlight the value of a BI with a family member to help patients with psychosis address psychoactive substance use, but do not lend support for a single-session BI alone. There is now support for further development and study of the BI-FS approach.

4.2. Strengths and limitations Role of funding source The study has some strengths, including an adaptation of BI methods based on WHO materials and the blinding of the follow-up interviewer to study group to reduce potential bias. We also note several limitations. Firstly, there were relatively few reports of substance use other than tobacco. This was a pragmatic trial in routinely delivered mental health services, but it is possible that substance use is not as prevalent in those with psychosis in Thailand as has been observed in other cultures. Second, we able to recruit only three women to the trial, so further work is needed to evaluate gender-specific acceptance and impact of BI in the study population. Third, outcome measures relied on participant selfreport and are subject to recall bias. Including biochemical verification of smoking outcomes is standard in the smoking cessation field (e.g. measurement of carbon monoxide in expired air or salivary cotinine; Society for Research on Nicotine & Tobacco, 2002). We recommend that future BI research in this population should include a standard outcome classification for smoking trials to facilitate comparison of effects (e.g. the Russell Standard; West, Hajek, Stead, & Stapleton, 2005).

The study was funded by the Integrated Management for Alcohol Intervention Program (I-MAP) 55-01-029 54-015, and the I-MAP had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. Contributors S.A., N.T and J.M. designed the study and wrote the protocol and S.A. and N.P. managed the project. N.P. and J.M. undertook the statistical analysis during N.T.'s research placement at the Addictions Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London. N.T. wrote the first draft of the manuscript with J.M. and the other authors contributed to and approved the submitted and revised version of the manuscript. N.T. took the decision to submit the manuscript and its revision for publication.

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Conflict of Interest N.T. and S.A. declare no potential conflicts of interest relevant to this article. The Epidemiology Unit, PSU is supported by a Discipline of Excellence Grant at the Prince of Songkla University and the National Science and Technology Development Agency, Ministry of Science and Technology, Thailand. J.M. works in an integrated United Kingdom university (King's College London) and National Health Service Academic Health Sciences Centre (King's Health Partners) and declares the following financial relationships: part-time employment as Senior Academic Advisor for the Alcohol and Drugs Team, Health and Wellbeing Directorate, Public Health England; clinical consultations to Reckitt-Benckiser Pharmaceuticals (RBP) in 2011 and Merck Serono in 2013, and untied educational grant funding at King's College London from RBP for a pharmacogenetic study of opioid medication-assisted treatment (MAT; 2010-2013) and a randomised controlled trial of personalised psychological interventions in opioid MAT (from RBP via Action on Addiction). Acknowledgments This study was conducted as part of N.T.'s PhD studies at PSU and supported by the Royal Golden Jubilee PhD Program scholarship. The authors thank the outpatient department staff in SKPH and SGH hospitals and study participants for their collaboration. References Aekplakorn, W., Hogan, M. C., Tiptaradol, S., Wibulpolprasert, S., Punyaratabandhu, P., & Lim, S. S. (2008). Tobacco and hazardous or harmful alcohol use in Thailand: Joint prevalence and associations with socioeconomic factors. Addictive Behaviors, 33, 503–514, http://dx.doi.org/10.1016/j.addbeh.2007.10.010. Ali, R., Meena, S., Eastwood, B., Richards, I., & Marsden, J. (2013). Ultra-rapid screening for substance-use disorders: The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST-Lite). Drug and Alcohol Dependence, 132, 352–361, http://dx.doi. org/10.1016/j.drugalcdep.2013.03.001. American Psychiatric Association (2000). Diagnostic and statistical manual of mental disorders DSM-IV-TR fourth edition (text revision) (4th ed.). Washington, DC: American Psychiatric Publishing. Andersen, J., Larsen, J. K., Korner, A., Nielsen, B. M., Schultz, V., Behnke, K., et al. (1986). The Brief Psychiatric Rating Scale: Schizophrenia, reliability and validity studies. Nordic Journal of Psychiatry, 40, 135–138. Assanangkornchai, S., Kanato, M., Perngparn, U., Aramrattana, A., Kanika, N., & Sirivongse Na Ayudhya, A. (2008). Current situation of substance-related problems in Thailand. Journal of the Psychiatric Association of Thailand, 53(Suppl. 1), 24S–36S. Assanangkornchai, S., Muekthong, A., Sam-Angsri, N., & Pattanasattayawong, U. (2007). The use of Mitragynine speciosa (“krathom”), an addictive plant, in Thailand. Substance Use & Misuse, 42, 2145–2157, http://dx.doi.org/10.1080/10826080701205869. Baker, A., Lewin, T., Reichler, H., Clancy, R., Carr, V., Garrett, R., et al. (2002). Evaluation of a motivational interview for substance use within psychiatric in-patient services. Addiction, 97, 1329–1337, http://dx.doi.org/10.1046/j.1360-0443.2002.00178.x. Barrowclough, C., Haddock, G., Tarrier, N., Lewis, S. W., Moring, J., O'Brien, R., et al. (2001). Randomized controlled trial of motivational interviewing, cognitive behavior therapy, and family intervention for patients with comorbid schizophrenia and substance use disorders. American Journal of Psychiatry, 158, 1706–1713, http://dx.doi.org/10. 1176/appi.ajp.158.10.1706. Blanchard, J. J., Brown, S. A., Horan, W. P., & Sherwood, A. R. (2000). Substance use disorders in schizophrenia: Review, integration, and a proposed model. Clinical Psychology Review, 20, 207–234, http://dx.doi.org/10.1016/S0272-7358(99)00033-1. Buuren, S. V., & Groothuis-Oudshoorn, K. (2011). Mice: Multivariate imputation by chained equations in R. Journal of Statistical Software, 45(3), 1–67. Cantwell, R. (2003). Substance use and schizophrenia: Effects on symptoms, social functioning and service use. British Journal of Psychiatry, 182, 324–329, http://dx.doi.org/ 10.1192/bjp.02.259. Carey, K. B., Carey, M. P., Maisto, S. A., & Henson, J. M. (2004). Temporal stability of the timeline followback interview for alcohol and drug use with psychiatric outpatients. Journal of Studies on Alcohol and Drugs, 65, 774–781. Clark, R. E. (2001). Family support and substance use outcomes for persons with mental illness and substance use disorders. Schizophrenia Bulletin, 27, 93–101. DeMarce, J. M., Burden, J. L., Lash, S. J., Stephens, R. S., & Grambow, S. C. (2007). Convergent validity of the timeline followback for persons with comorbid psychiatric disorders engaged in residential substance use treatment. Addictive Behaviors, 32, 1582–1592, http://dx.doi.org/10.1016/j.addbeh.2006.11.015. Denton, W. H., Nakonezny, P. A., & Burwell, S. R. (2010). Reliability and validity of the Global Assessment of Relational Functioning (GARF) in a psychiatric family therapy clinic. Journal of Marital & Family Therapy, 36, 376–387, http://dx.doi.org/10.1111/j. 1752-0606.2009.00144.x.

Dervaux, A., & Laqueille, X. (2008). Smoking and schizophrenia: Epidemiological and clinical features. Encephale, 34, 299–305, http://dx.doi.org/10.1016/j.encep.2007.04.003. Harrison, I., Joyce, E. M., Mutsatsa, S. H., Hutton, S. B., Huddy, V., Kapasi, M., et al. (2008). Naturalistic follow-up of co-morbid substance use in schizophrenia: The West London first-episode study. Psychological Medicine, 38, 79–88, http://dx.doi.org/10. 1017/S0033291707000797. Hartz, S. M., Pato, C. N., Medeiros, H., Cavazos-Rehg, P., Sobell, J. L., Knowles, J. A., et al. (2014). Comorbidity of severe psychotic disorders with measures of substance use. Journal of the American Medical Association (JAMA) Psychiatry, http://dx.doi.org/10. 1001/jamapsychiatry.2013.3726. Hedges, L. V. (1981). Distribution theory for glass's estimator of effect size and related estimators. Journal of Educational and Behavioral Statistics, 6, 107–128. Hides, L., Lubman, D. I., & Dawe, S. (2004). Models of co-occurring substance misuse and psychosis: Are personality traits the missing link? Drug and Alcohol Review, 23, 425–432, http://dx.doi.org/10.1080/09595230412331324545. Humeniuk, R., Ali, R., Babor, T. F., Farrell, M., Formigoni, M. L., Jittiwutikarn, J., et al. (2008). Validation of the Alcohol, Smoking And Substance Involvement Screening Test (ASSIST). Addiction, 103, 1039–1047, http://dx.doi.org/10.1111/j.1360-0443.2007. 02114.x. Humeniuk, R., Ali, R., Babor, T., Souza-Formigoni, M. L., de Lacerda, R. B., Ling, W., et al. (2012). A randomized controlled trial of a brief intervention for illicit drugs linked to the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) in clients recruited from primary health-care settings in four countries. Addiction, 107, 957–966, http://dx.doi.org/10.1111/j.1360-0443.2011.03740.x. Jonsdottir, H., Opjordsmoen, S., Birkenaes, A. B., Simonsen, C., Engh, J. A., Ringen, P. A., et al. (2013). Predictors of medication adherence in patients with schizophrenia and bipolar disorder. Acta Psychiatrica Scandinavica, 127, 23–33, http://dx.doi.org/10.1111/j. 1600-0447.2012.01911.x. Kavanagh, D. J., Young, R., White, A., Saunders, J. B., Wallis, J., Shockley, N., et al. (2004). A brief motivational intervention for substance misuse in recent-onset psychosis. Drug and Alcohol Review, 23, 151–155, http://dx.doi.org/10.1080/09595230410001704127. Kelly, D. L., McMahon, R. P., Wehring, H. J., Liu, F., Mackowick, K. M., Boggs, D. L., et al. (2011). Cigarette smoking and mortality risk in people with schizophrenia. Schizophrenia Bulletin, 37, 832–838, http://dx.doi.org/10.1093/schbul/sbp152. Kisely, S. R., Wise, M., Preston, N., Malmgren, S., & Shannon, P. (2003). A group intervention to reduce smoking in individuals with psychiatric disorder: Brief report of a pilot study. Australian and New Zealand Journal of Public Health, 27, 61–63, http://dx.doi. org/10.1111/j.1467-842X.2003.tb00381.x. Krishnadas, R., Jauhar, S., Telfer, S., Shivashankar, S., & McCreadie, R. G. (2012). Nicotine dependence and illness severity in schizophrenia. British Journal of Psychiatry, 201, 306–312, http://dx.doi.org/10.1192/bjp.bp.111.107953. Lahti, J., Maria, R., & Koski-Jannes, A. (2013). Motivating interview and its effectiveness in the treatment of dual diagnosis patients. Duodecim, 129, 2063–2069. Little, R. J. A., & Rubin, D. B. (1987). Statistical analysis with missing data. New York: Wiley & Sons. Martins, S. S., & Gorelick, D. A. (2011). Conditional substance abuse and dependence by diagnosis of mood or anxiety disorder or schizophrenia in the U.S. population. Drug and Alcohol Dependence, 119, 28–36, http://dx.doi.org/10.1016/j.drugalcdep.2011.05.010. Mdege, N. D., & Lang, J. (2011). Screening instruments for detecting illicit drug use/abuse that could be useful in general hospital wards: A systematic review. Addictive Behaviors, 36, 1111–1119, http://dx.doi.org/10.1016/j.addbeh.2011.07.007. Miller, W. R., & Rollnick, S. (1991). Motivational interviewing: Prepare people for change. New York: Guilford Press. Miller, W. R., & Rollnick, S. (2002). Motivational interviewing: Preparing people to change addictive behaviour (2nd ed.). New York: Guilford Press. Miller, W. R., & Tonigan, J. S. (1996). Assessing drinkers' motivation for change: The Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES). Psychology of Addictive Behaviors, 10, 81–89. Milner, K. K., Barry, K. L., Blow, F. C., & Welsh, D. (2010). Brief interventions for patients presenting to the Psychiatric Emergency Service (PES) with major mental illnesses and at-risk drinking. Community Mental Health Journal, 46, 149–155, http://dx.doi. org/10.1007/s10597-009-9182-y. Mueser, K. T., Drake, R. E., & Wallach, M. A. (1998). Dual diagnosis: A review of etiological theories. Addictive Behaviors, 23, 717–734, http://dx.doi.org/10.1016/S0306-4603(98) 00073-2. Mueser, K. T., Glynn, S. M., Cather, C., Xie, H., Zarate, R., Smith, L. F., et al. (2013). A randomized controlled trial of family intervention for co-occurring substance use and severe psychiatric disorders. Schizophrenia Bulletin, 39, 658–672, http://dx.doi.org/10. 1093/schbul/sbr203. Mueser, K. T., Glynn, S. M., Cather, C., Zarate, R., Fox, L., Feldman, J., et al. (2009). Family intervention for co-occurring substance use and severe psychiatric disorders: Participant characteristics and correlates of initial engagement and more extended exposure in a randomized controlled trial. Addictive Behaviors, 34, 867–877, http://dx. doi.org/10.1016/j.addbeh.2009.03.025. Mueser, K. T., Kavanagh, D. J., & Brunette, M. F. (2007). Implications of research on comorbidity for the nature and management of substance misuse. In P. M. Miller, & D. J. Kavanagh (Eds.), Translation of Addictions Science into Practice (pp. 277–320). Amsterdam: Elsevier. Overall, J. E., & Gorham, D. R. (1962). The Brief Psychiatric Rating Scale. Psychological Reports, 10, 799–812. Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D., & R Core Team (2013). nlme: Linear and nonlinear mixed effects models. R package version 3.1-111. Potvin, S., Stip, E., & Roy, J. Y. (2003). Schizophrenia and addiction: An evaluation of the self-medication hypothesis. Encephale, 29, 193–203. R Core Team (2014). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.

N. Tantirangsee et al. / Journal of Substance Abuse Treatment 51 (2015) 30–37 Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys. New York: Wiley & Sons. Sagud, M., Mihaljevic-Peles, A., Muck-Seler, D., Pivac, N., Vuksan-Cusa, B., Brataljenovic, T., et al. (2009). Smoking and schizophrenia. Psychiatria Danubina, 21, 371–375. Salokangas, R. K., Honkonen, T., Stengard, E., Koivisto, A. M., & Hietala, J. (2006). Cigarette smoking in long-term schizophrenia. European Psychiatry, 21, 219–223, http://dx.doi. org/10.1016/j.eurpsy.2005.07.008. Salyers, M. P., & Mueser, K. T. (2001). Social functioning, psychopathology, and medication side effects in relation to substance use and abuse in schizophrenia. Schizophrenia Research, 48, 109–123, http://dx.doi.org/10.1016/S0920-9964(00)00063-3. Schmidt, L. M., Hesse, M., & Lykke, J. (2011). The impact of substance use disorders on the course of schizophrenia—A 15-year follow-up study: Dual diagnosis over 15 years. Schizophrenia Research, 130, 228–233, http://dx.doi.org/10.1016/j.schres.2011.04.011. Sobell, L. C., & Sobell, M. B. (1992). Timeline followback: A technique for assessing selfreported alcohol consumption. In R. Z. Litten, & J. Allen (Eds.), Measuring alcohol consumption: Psychosocial and biological methods (pp. 41–72). New Jersey: Humana Press. Society for Research on Nicotine and Tobacco (2002). Biochemical verification of tobacco use and cessation. Nicotine & Tobacco Research, 4, 149–159, http://dx.doi.org/10. 1080/14622200210123581. Sorbara, F., Liraud, F., Assens, F., Abalan, F., & Verdoux, H. (2003). Substance use and the course of early psychosis: A 2-year follow-up of first-admitted subjects. European Psychiatry, 18, 133–136, http://dx.doi.org/10.1016/S0924-9338(03)00027-0. Spirito, A., Sindelar-Manning, H., Colby, S. M., Barnett, N. P., Lewander, W., Rohsenow, D. J., et al. (2011). Individual and family motivational interventions for alcohol-positive adolescents treated in an emergency department: Results of a randomized clinical trial. Archives of Pediatrics & Adolescent Medicine, 165, 269–274, http://dx.doi.org/10. 1001/archpediatrics.2010.296. Steinberg, M. L., Ziedonis, D. M., Krejci, J. A., & Brandon, T. H. (2004). Motivational interviewing with personalized feedback: A brief intervention for motivating smokers with schizophrenia to seek treatment for tobacco dependence. Journal of

37

Consulting and Clinical Psychology, 72, 723–728, http://dx.doi.org/10.1037/0022006X.72.4.723. Stolt, A. C., Schroder, H., Neurath, H., Grecksch, G., Hollt, V., Meyer, M. R., et al. (2014). Behavioral and neurochemical characterization of kratom (Mitragyna speciosa) extract. Psychopharmacology, 231, 13–25, http://dx.doi.org/10.1007/s00213-013-3201-y. Tsoi, D. T., Porwal, M., & Webster, A. C. (2013). Interventions for smoking cessation and reduction in individuals with schizophrenia. Cochrane Database of Systematic Reviews, 2, CD007253, http://dx.doi.org/10.1002/14651858.CD007253.pub3. Vanable, P. A., Carey, M. P., Carey, K. B., & Maisto, S. A. (2003). Smoking among psychiatric outpatients: Relationship to substance use, diagnosis, and illness severity. Psychology of Addictive Behaviors, 17, 259–265, http://dx.doi.org/10.1037/0893-164X.17.4.259. Volkow, N. D. (2009). Substance use disorders in schizophrenia—Clinical implications of comorbidity. Schizophrenia Bulletin, 35, 469–472, http://dx.doi.org/10.1093/schbul/ sbp016. West, R., Hajek, P., Stead, L., & Stapleton, J. (2005). Outcome criteria in smoking cessation trials: Proposal for a common standard. Addiction, 100, 299–303, http://dx.doi.org/10. 1111/j.1360-0443.2004.00995.x. Whiteford, H. A., Degenhardt, L., Rehm, J., Baxter, A. J., Ferrari, A. J., Erskine, H. E., et al. (2013). Global burden of disease attributable to mental and substance use disorders: Findings from the Global Burden of Disease Study 2010. Lancet, 382, 1575–1586, http://dx.doi.org/10.1016/S0140-6736(13)61611-6. WHO ASSIST Working Group (2002). The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): Development, reliability and feasibility. Addiction, 97, 1183–1194, http://dx.doi.org/10.1046/j.1360-0443.2002.00185.x. Wilson, C. S., Bennett, M. E., & Bellack, A. S. (2013). Impact of family history in persons with dual diagnosis. Journal of Dual Diagnosis, 9, 30–38, http://dx.doi.org/10.1080/ 15504263.2012.744937. World Health Organization (1992). The ICD-10 classification of mental and behavioural disorders: Clinical descriptions and diagnostic guidelines. Geneva: World Health Organization.