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BACKGROUND: A prominent neuroscientific theory of drug addiction is the incentive sensitization model. Individual differences in the tendency to ascribe motivational salience to cues that predict reward, and involuntary "sign-tracking" (orientation towards) such cues have been identified as potentially important in understanding vulnerability to addiction and relapse. However, to date this behaviour has not been assessed in a treatment-seeking clinical population, who typically represent those most susceptible to alcohol-related harms and episodes of relapse. This highlights a significant gap in the literature pertaining to incentive sensitization and drug dependence. METHODS: Individuals accessing inpatient drug and alcohol services with alcohol as primary drug of concern were recruited to participate in a Cognitive Bias Modification (CBM) intervention. At the baseline assessment, participants completed various self-report measures (including the Alcohol Use Disorders Identification Test; AUDIT) in addition to a visual search task measuring sign-tracking to cues signalling monetary reward. At 3-month follow up, abstinence from alcohol was the primary outcome measure. All analyses and hypotheses were pre-registered. RESULTS: At baseline (57 participants), AUDIT scores correlated with sign-tracking to signals of monetary reward. In a subsequent regression analysis sign-tracking, gender and self-reported alcohol craving predicted abstinence at 3-month follow up (41 participants). CONCLUSIONS: Our work demonstrates that involuntary sign-tracking to cues signalling non-drug reward is associated with problematic alcohol use and return to use at 3-month follow up, in a treatment-seeking sample. Whether this automatic prioritisation of cues signalling reward is a consequence or vulnerability for problematic alcohol use remains to be investigated.

Contains fulltext : 303949.pdf (Publisher’s version ) (Open Access), Cognitive bias modification (CBM) has evolved from an experimental method testing cognitive mechanisms of psychopathology to a promising tool for accessible digital mental health care. While we are still discovering the conditions under which clinically relevant effects occur, the dire need for accessible, effective, and low-cost mental health tools underscores the need for implementation where such tools are available. Providing our expert opinion as Association for Cognitive Bias Modification members, we first discuss the readiness of different CBM approaches for clinical implementation, then discuss key considerations with regard to implementation. Evidence is robust for approach bias modification as an adjunctive intervention for alcohol use disorders and interpretation bias modification as a stand-alone intervention for anxiety disorders. Theoretical predictions regarding the mechanisms by which bias and symptom change occur await further testing. We propose that CBM interventions with demonstrated efficacy should be provided to the targeted populations. To facilitate this, we set a research agenda based on implementation frameworks, which includes feasibility and acceptability testing, co-creation with end-users, and collaboration with industry partners., 13 p.

AIMS: Treatment of methamphetamine dependence requires monitoring of recent use or abstinence. Self-report is commonly used for routine monitoring, but the accuracy of self-report is not established. For the treating clinician, the key accuracy statistic is the negative predictive value (NPV). The study aim was to estimate the NPV of self-reported non-use of methamphetamine compared with an oral fluid reference standard. DESIGN, SETTING AND PARTICIPANTS: This study was a secondary (subgroup) analysis from a randomized controlled pharmacotherapy trial. Three Australian outpatient addiction services took part. Particpants were 139 people dependent on methamphetamine. MEASUREMENTS: Weekly oral fluid samples over 12 weeks to determine methamphetamine (and amphetamine) concentrations were used as the reference standard. Self-report of any methamphetamine use in the previous 7 days by the time-line follow-back method was the index test. Standard diagnostic accuracy statistics were calculated for all available paired episodes (n = 1134). Three NPV values were calculated: unadjusted NPV and NPV adjusted for clustering of observations through logistic regression and generalized estimating equation (GEE). We also calculated the NPVs for a range of prevalence rates of methamphetamine use, for the calculated levels of sensitivity and specificity. FINDINGS: Sensitivity was 96.4% [95% confidence interval (CI) = 95-97.5], specificity was 63.7% (95% CI = 57.3-69.8) and positive predictive value (PPV) was 90.8% (95% CI = 88.8-92.6). The unadjusted NPV was 82.7% (95% CI = 76.5-87.9), adjusted NPV by logistic regression 82.7% (95% CI = 73.9-91.5) and GEE 76.8% (95% CI = 66.8-86.8). At a methamphetamine use prevalence of 5%, the estimated NPV would be 99.7% (95% CI = 99.6-99.9) and at 95% prevalence, 48.2% (95% CI = 39.6-57.0). CONCLUSIONS: Self-report of no recent methamphetamine use appears to be sufficiently accurate to be clinically useful at the expected prevalence rates of metham

ObjectiveIn considering the cognitive harms of methamphetamine (MA) use, there is currently a limited appreciation of the profile of pre-existing, comorbid, or modifiable risk factors for cognitive impairment in individuals with MA-polydrug use who present to clinical services. This is in contrast to the well-recognized evidence in alcohol use groups. The aim of this study was to investigate the biopsychosocial and neuropsychological profiles of MA-polysubstance using individuals reporting cognitive impairment in comparison to an alcohol-using group.MethodsA retrospective file audit was undertaken of individuals who presented for assessment to a specialist addiction neuropsychology service and reported either more than 1 year of heavy MA use as part of a polydrug use history (n = 40) or having only used alcohol (n = 27). Clinical histories including demographic, medical, mental health, substance use, and neuropsychological assessment results were extracted from medical records. Between group comparisons were conducted to explore differences in the MA-polydrug vs. the alcohol group.ResultsIndividuals in the MA-polydrug group were significantly younger, commenced substance use at an earlier age, were more likely to have an offending history, and experienced an overdose than those in the alcohol group. No differences in comorbid neurodevelopmental, psychiatric or acquired brain injury diagnoses were observed between groups. For neuropsychological functioning, significant group differences were observed in overall IQ, semantic verbal fluency, and psychomotor tracking, where individuals in the alcohol group performed significantly worse.ConclusionsNeuropsychological profiles were largely eq

Abstract Introduction: Cognitive impairment is common in individuals presenting to alcohol and other drug (AOD) settings and the presence of biopsychosocial complexity and health inequities can complicate the experience of symptoms and access to treatment services. A challenge for neuropsychologists in these settings is to evaluate the likely individual contribution of these factors to cognition when providing an opinion regarding diagnoses such as acquired brain injury (ABI). This study therefore aimed to identify predictors of cognitive functioning in AOD clients attending for neuropsychological assessment. Methods: Clinical data from 200 clients with AOD histories who attended for assessment between 2014 and 2018 were analysed and a series of multiple regressions were conducted to explore predictors of cognitive impairment including demographic, diagnostic, substance use, medication, and mental health variables. Results: Regression modelling identified age, gender, years of education, age of first use, days of abstinence, sedative load, emotional distress and diagnoses of ABI and developmental disorders as contributing to aspects of neuropsychological functioning. Significant models were obtained for verbal intellectual functioning (Adj R2 = 0.19), nonverbal intellectual functioning (Adj R2 = 0.10), information processing speed (Adj R2 = 0.20), working memory (Adj R2 = 0.05), verbal recall (Adj R2 = 0.08), visual recall (Adj R2 = 0.22), divided attention (Adj R2 = 0.14), and cognitive inhibition (Adj R2 = 0.07).

Despite decades of research in the field of addiction, relapse rates for substance use disorders remain high. Consequently, there has been growing focus on providing evidence-based treatments for substance use disorders, resulting in the increased development and use of cognitive and psychological interventions. Such treatment approaches, including contingency management, community-reinforcement approach, and cognitive bias modification, have shown promising clinical efficacy in reducing substance use and promoting abstinence during treatment. However, these interventions are still somewhat limited in achieving sustained periods of abstinence post-treatment. The neurobiological mechanisms underpinning these treatment approaches remain largely unknown and under-studied, in part, due to a lack of translational animal models. The adoption of a reverse translational approach may assist in development of more representative models that can facilitate elucidation of the mechanisms behind these clinically relevant interventions. This review examines our current understanding of addiction neurobiology from clinical, preclinical research and existing animal models, and considers how the efficacy of such behavioral-oriented interventions alone, or in combination with pharmacotherapy, may be enhanced to improve treatment outcomes.

BACKGROUND AND AIMS: Approach bias modification (ApBM) targeting alcohol approach bias has been previously shown to reduce likelihood of relapse during the first 2 weeks following inpatient withdrawal treatment (IWT). We tested whether ApBM's effects endure for a longer period by analysing alcohol use outcomes 3, 6 and 12 months post-discharge. DESIGN: A double-blind, sham-controlled randomized controlled trial. SETTING: Four IWT units in Melbourne, Australia. PARTICIPANTS: Three hundred alcohol IWT patients (173 men, 126 women, 1 non-binary; mean age 43.5 years) were recruited between 4 June 2017 and 14 July 2019. Follow-up data collection was completed on 22 September 2020. INTERVENTION AND CONTROL TRAINING: Four ApBM sessions were delivered during IWT. ApBM trained participants (n = 147) to avoid alcohol and approach non-alcohol beverage cues. Controls (n = 153) responded to the same stimuli, but without approach/avoidance training. MEASUREMENTS: Date of first lapse was recorded for non-abstinent participants to determine time to first lapse. Time-line follow-back interviews assessed past-month alcohol consumption at each follow-up, with participants reporting no alcohol consumption classified as abstinent. In analyses of past-month abstinence, non-abstinence was assumed in participants lost to follow-up. Number of past-month drinking days, standard drinks and heavy drinking days (five or more standard drinks for women or non-binary; six or more standard drinks for men) were calculated for non-abstinent participants at each follow-up. FINDINGS: ApBM significantly delayed time to first lapse [ApBM median: 53 days, 95% confidence interval (CI) = 21-61; controls = 12 days, 95% CI = 9-21, P = 0.045]. Past-month abstinence rates at 3-, 6- and 12-month follow-ups were 33/153 (21.6%), 30/153 (19.6%), and 24/153 (15.7%) in controls; and 51/147 (34.7%), 30/147 (20.4%) and 29/147 (19.7%) in the ApBM group, respectively. Past-month abstinence was significantly more likely i

Summary of recommendations and levels of evidence: Chapter 2: Screening and assessment for unhealthy alcohol use Screening Screening for unhealthy alcohol use and appropriate interventions should be implemented in general practice (Level A), hospitals (Level B), emergency departments and community health and welfare settings (Level C). Quantity–frequency measures can detect consumption that exceeds levels in the current Australian guidelines (Level B). The Alcohol Use Disorders Identification Test (AUDIT) is the most effective screening tool and is recommended for use in primary care and hospital settings. For screening in the general community, the AUDIT-C is a suitable alternative (Level A). Indirect biological markers should be used as an adjunct to screening (Level A), and direct measures of alcohol in breath and/or blood can be useful markers of recent use (Level B). Assessment Assessment should include evaluation of alcohol use and its effects, physical examination, clinical investigations and collateral history taking (Level C). Assessment for alcohol-related physical problems, mental health problems and social support should be undertaken routinely (GPP). Where there are concerns regarding the safety of the patient or others, specialist consultation is recommended (Level C). Assessment should lead to a clear, mutually acceptable treatment plan which specifies interventions to meet the patient’s needs (Level D). Sustained abstinence is the optimal outcome for most patients with alcohol dependence (Level C). Chapter 3: Caring for and managing patients with alcohol problems: interventions, treatments, relapse prevention, aftercare, and long term follow-up Brief interventions Brief motivational interviewing interventions are more effective than no treatment for people who consume alcohol at risky levels (Level A). Their effectiveness compared with standard care or alternative psychosocial interventions varies by treatment setting. They are most effective in prim

Importance: More than half of patients with alcohol use disorder who receive inpatient withdrawal treatment relapse within weeks of discharge, hampering subsequent uptake and effectiveness of psychological and pharmacologic interventions. Cognitive bias modification (CBM) improves outcomes after alcohol rehabilitation, but the efficacy of delivering CBM during withdrawal treatment has not yet been established. Objective(s): To test the hypothesis that CBM would increase the likelihood of abstaining from alcohol during the 2 weeks following discharge from inpatient withdrawal treatment. Design, Setting, and Participant(s): In a randomized clinical trial, 950 patients in 4 inpatient withdrawal units in Melbourne, Australia, were screened for eligibility between June 4, 2017, and July 14, 2019, to receive CBM or sham treatment. Patients with moderate or severe alcohol use disorder aged 18 to 65 years who had no neurologic illness or traumatic brain injury were eligible. Two-week follow-up, conducted by researchers blinded to the participant's condition, was the primary end point. Both per-protocol and intention-to-treat analysis were conducted. Intervention(s): Randomized to 4 consecutive daily sessions of CBM designed to reduce alcohol approach bias or sham training not designed to modify approach bias. Main Outcomes and Measures: Primary outcome was abstinence assessed using a timeline followback interview. Participants were classified as abstinent (no alcohol use in the first 14 days following discharge) or relapsed (any alcohol use during the first 14 days following discharge or lost to follow-up). Result(s): Of the 950 patients screened for eligibility, 338 did not meet inclusion criteria, 108 were discharged before being approached, and 192 refused. Of the 312 patients who consented (referred sample), 12 withdrew before being randomized. In the final population of 300 randomized patients (CBM, n = 147; sham, n = 153), 248 completed the intervention and 272 comple

Introduction: Alcohol approach bias, the tendency to automatically move toward alcohol cues, has been observed in people who drink heavily. However, surprisingly, some alcohol-dependent patients demonstrate an alcohol avoidance bias. This inconsistency could be explained by the clinical or demographic profile of the population studied, yet this has not been examined in approach bias modification (ABM) trials to date. We aimed to determine the proportion of patients with an approach or avoidance bias, assess whether they differ on demographic and drinking measures, and to examine the clinical correlates of approach bias.Method: These research questions were addressed using baseline data from 268 alcohol-dependent patients undergoing inpatient withdrawal treatment who then went on to participate in a trial of ABM.Results: At trial entry (day 3 or 4 of inpatient withdrawal), 155 (57.8%) had an alcohol approach bias and 113 (42.2%) had an avoidance bias. These two groups did not differ on any demographic or relevant drinking measures. Approach bias was significantly and moderately associated with total standard drinks consumed in the past 30 days (r = 0.277, p = 0.001) but no other indices of alcohol consumption or problem severity.Conclusion: Whilst the majority of alcohol-dependent patients showed an alcohol approach bias, those with an avoidance bias did not differ in demographic or clinical characteristics, and the strength of approach bias related only to recent consumption. Further research is needed to develop more accurate and personally tailored measures of approach bias, as these findings likely reflect the poor reliability of standard approach bias measures.

IMPORTANCE: More than half of patients with alcohol use disorder who receive inpatient withdrawal treatment relapse within weeks of discharge, hampering subsequent uptake and effectiveness of psychological and pharmacologic interventions. Cognitive bias modification (CBM) improves outcomes after alcohol rehabilitation, but the efficacy of delivering CBM during withdrawal treatment has not yet been established. OBJECTIVE: To test the hypothesis that CBM would increase the likelihood of abstaining from alcohol during the 2 weeks following discharge from inpatient withdrawal treatment. DESIGN, SETTING, AND PARTICIPANTS: In a randomized clinical trial, 950 patients in 4 inpatient withdrawal units in Melbourne, Australia, were screened for eligibility between June 4, 2017, and July 14, 2019, to receive CBM or sham treatment. Patients with moderate or severe alcohol use disorder aged 18 to 65 years who had no neurologic illness or traumatic brain injury were eligible. Two-week follow-up, conducted by researchers blinded to the participant's condition, was the primary end point. Both per-protocol and intention-to-treat analysis were conducted. INTERVENTIONS: Randomized to 4 consecutive daily sessions of CBM designed to reduce alcohol approach bias or sham training not designed to modify approach bias. MAIN OUTCOMES AND MEASURES: Primary outcome was abstinence assessed using a timeline followback interview. Participants were classified as abstinent (no alcohol use in the first 14 days following discharge) or relapsed (any alcohol use during the first 14 days following discharge or lost to follow-up). RESULTS: Of the 950 patients screened for eligibility, 338 did not meet inclusion criteria, 108 were discharged before being approached, and 192 refused. Of the 312 patients who consented (referred sample), 12 withdrew before being randomized. In the final population of 300 randomized patients (CBM, n = 147; sham, n = 153), 248 completed the intervention and 272 completed the f

INTRODUCTION: The QuitNic pilot trial aimed to test the feasibility of providing a nicotine vaping product (NVP) compared with combination nicotine replacement therapy (NRT) to smokers upon discharge from a smoke-free residential substance use disorder (SUD) treatment service. METHODS: QuitNic was a pragmatic two-arm randomized controlled trial. At discharge from residential withdrawal, 100 clients received telephone Quitline behavioral support and either 12-week supply of NRT or an NVP. Treatment adherence and acceptability, self-reported abstinence, cigarettes smoked per day (CPD), frequency of cravings, and severity of withdrawal symptoms were assessed at 6 and 12 weeks. Results are reported for complete cases and for abstinence outcomes, penalized imputation results are reported where missing is assumed smoking. RESULTS: Retention on was 63% at 6 weeks and 50% at 12 weeks. At 12 weeks, 68% of the NRT group reported using combination NRT while 96% of the NVP group used the device. Acceptability ratings for the products were high in both groups. At 12 weeks, 14% of the NVP group and 18% of the NRT group reported not smoking at all in the last 7 days. Mean CPD among continued smokers decreased significantly between baseline to 12 weeks in both groups; from 19.91 to 4.72 for the NVP group (p < .001) and from 20.88 to 5.52 in the NRT group (p < .001). Cravings and withdrawal symptoms significantly decreased for both groups. CONCLUSIONS: Clients completing residential withdrawal readily engaged with smoking cessation post-treatment when given the opportunity. Further research is required to identify the most effective treatments postwithdrawal for this population at elevated risk of tobacco-related harm. TRIAL REGISTRATION NUMBER: ACTRN12617000849392. IMPLICATIONS: This pilot study showed that smoking cessation support involving options for nicotine replacement and Quitline-delivered cognitive behavioral counseling is attractive to people after they have been discharg

INTRODUCTION AND AIMS: There has been a rapid increase in smoking crystalline methamphetamine in Australia. We compare the clinical and demographic characteristics of those who smoke versus inject the drug in a cohort of people who use methamphetamine. DESIGN AND METHODS: Participants (N = 151) were dependent on methamphetamine, aged 18-60 years, enrolled in a pharmacotherapy trial for methamphetamine dependence, and reported either injecting (n = 54) or smoking (n = 97) methamphetamine. Measures included the Timeline Followback, Severity of Dependence Scale, Amphetamine Withdrawal Questionnaire, Craving Experience Questionnaire and the Brief Psychiatric Rating Scale (symptoms of depression, hostility, psychosis and suicidality). Simultaneous regression was used to identify independent demographic correlates of smoking methamphetamine and to compare the clinical characteristics of participants who smoked versus injected. RESULTS: Compared to participants who injected methamphetamine, those who smoked methamphetamine were younger and less likely to be unemployed, have a prison history or live alone. Participants who smoked methamphetamine used methamphetamine on more days in the past 4 weeks than participants who injected methamphetamine (26 vs. 19 days, P = 0.001); they did not differ significantly in their severity of methamphetamine dependence, withdrawal, craving or psychiatric symptoms (P > 0.05). After adjustment for demographic differences, participants who smoked had lower craving [b (SE) = -1.1 (0.5), P = 0.021] and were less likely to report psychotic symptoms [b (SE) = -1.8 (0.7), P = 0.013] or antidepressant use [b (SE) = -1.1 (0.5), P = 0.022]. DISCUSSION AND CONCLUSIONS: Smoking crystalline methamphetamine is associated with a younger less marginalised demographic profile than injecting methamphetamine, but a similarly severe clinical profile.

BACKGROUND: Globally, methamphetamine use has increased in prevalence in recent years. In Australia, there has been a dramatic increase in numbers of people seeking treatment, including residential rehabilitation, for methamphetamine use disorder (MUD). While residential rehabilitation is more effective for MUD than withdrawal treatment (i.e. "detoxification") alone, relapse rates remain high, with approximately half of rehabilitation clients using methamphetamine within 3 months of rehabilitation. "Approach bias modification" (ABM) is a computerised cognitive training approach that aims to dampen automatically triggered impulses to approach drugs and drug-related stimuli. ABM has been demonstrated to reduce alcohol relapse rates, but no randomised controlled trials of ABM for MUD have yet been conducted. We aim to test whether a novel "personalised" form of ABM, delivered during rehabilitation, reduces post-treatment methamphetamine use, relative to a sham-training control condition. Secondary outcomes will include dependence symptoms, cravings, and approach bias. METHODS: We aim to recruit 100 participants attending residential rehabilitation for MUD at 3 sites in the Melbourne metropolitan area. Participants will complete baseline measures of methamphetamine use, craving, dependence severity, and approach bias before being randomised to receiving 6 sessions of ABM or "sham" training. In the active condition, ABM will be personalised for each participant, using those methamphetamine images that they rate as most relevant to their recent methods of methamphetamine use as "avoidance" images and using positive images representing their goals or healthy sources of pleasure as "approach" images. Approach bias and craving will be re-assessed following completion of training, and methamphetamine use, dependence, and craving will be assessed 4 weeks and 3 months following discharge from residential treatment. DISCUSSION: This study is the first randomised controlled trial

Introduction and Aims: There has been a rapid increase in smoking crystalline methamphetamine in Australia. We compare the clinical and demographic characteristics of those who smoke versus inject the drug in a cohort of people who use methamphetamine. Design and Methods: Participants (N = 151) were dependent on methamphetamine, aged 18–60 years, enrolled in a pharmacotherapy trial for methamphetamine dependence, and reported either injecting (n = 54) or smoking (n = 97) methamphetamine. Measures included the Timeline Followback, Severity of Dependence Scale, Amphetamine Withdrawal Questionnaire, Craving Experience Questionnaire and the Brief Psychiatric Rating Scale (symptoms of depression, hostility, psychosis and suicidality). Simultaneous regression was used to identify independent demographic correlates of smoking methamphetamine and to compare the clinical characteristics of participants who smoked versus injected. Results: Compared to participants who injected methamphetamine, those who smoked methamphetamine were younger and less likely to be unemployed, have a prison history or live alone. Participants who smoked methamphetamine used methamphetamine on more days in the past 4 weeks than participants who injected methamphetamine (26 vs. 19 days, P = 0.001); they did not differ significantly in their severity of methamphetamine dependence, withdrawal, craving or psychiatric symptoms (P > 0.05). After adjustment for demographic differences, participants who smoked had lower craving [b (SE) = −1.1 (0.5), P = 0.021] and were less likely to report psychotic symptoms [b (SE) = −1.8 (0.7), P = 0.013] or antidepressant use [b (SE) = −1.1 (0.5), P = 0.022]. Discussion and Conclusions: Smoking crystalline methamphetamine is associated with a younger less marginalised demographic profile than injecting methamphetamine, but a similarly severe clinical profile.

Gambling problems commonly co-occur with other mental health problems. However, screening for problem gambling (PG) rarely takes place within mental health treatment settings. The aim of the current study was to examine the way in which mental health clinicians respond to PG issues. Participants (n = 281) were recruited from a range of mental health services in Victoria, Australia. The majority of clinicians reported that at least some of their caseload was affected by gambling problems. Clinicians displayed moderate levels of knowledge about the reciprocal impact of gambling problems and mental health but had limited knowledge of screening tools to detect PG. Whilst 77% reported that they screened for PG, only 16% did so “often” or “always” and few expressed confidence in their ability to treat PG. However, only 12.5% reported receiving previous training in PG, and those that had, reported higher levels of knowledge about gambling in the context of mental illness, more positive attitudes about responding to gambling issues, and more confidence in detecting/screening for PG. In conclusion, the findings highlight the need to upskill mental health clinicians so they can better identify and manage PG and point towards opportunities for enhanced integrated working with gambling services.

Although there is general consensus that altered brain structure and function underpins addictive disorders, clinicians working in addiction treatment rarely incorporate neuroscience-informed approaches into their practice. We recently launched the Neuroscience Interest Group within the International Society of Addiction Medicine (ISAM-NIG) to promote initiatives to bridge this gap. This article summarizes the ISAM-NIG key priorities and strategies to achieve implementation of addiction neuroscience knowledge and tools for the assessment and treatment of substance use disorders. We cover two assessment areas: cognitive assessment and neuroimaging, and two interventional areas: cognitive training/remediation and neuromodulation, where we identify key challenges and proposed solutions. We reason that incorporating cognitive assessment into clinical settings requires the identification of constructs that predict meaningful clinical outcomes. Other requirements are the development of measures that are easily-administered, reliable, and ecologically-valid. Translation of neuroimaging techniques requires the development of diagnostic and prognostic biomarkers and testing the cost-effectiveness of these biomarkers in individualized prediction algorithms for relapse prevention and treatment selection. Integration of cognitive assessments with neuroimaging can provide multilevel targets including neural, cognitive, and behavioral outcomes for neuroscience-informed interventions. Application of neuroscience-informed interventions including cognitive training/remediation and neuromodulation requires clear pathways to design treatments based on multilevel targets, additional evidence from randomized trials and subsequent clinical implementation, including evaluation of cost-effectiveness. We propose to address these challenges by promoting international collaboration between researchers and clinicians, developing harmonized protocols and data management systems, and prioritizin

People seeking treatment for substance use disorders (SUD) ultimately aspire to improve their quality of life (QOL) through reducing or ceasing their substance use, however the association between these treatment outcomes has received scant research attention. In a prospective, multi-site treatment outcome study ('Patient Pathways'), we recruited 796 clients within one month of intake from 21 publicly funded addiction treatment services in two Australian states, 555 (70%) of whom were followed-up 12 months later. We measured QOL at baseline and follow-up using the WHOQOL-BREF (physical, psychological, social and environmental domains) and determined rates of "SUD treatment success" (past-month abstinence or a statistically reliable reduction in substance use) at follow-up. Mixed effects linear regression analyses indicated that people who achieved SUD treatment success also achieved significantly greater improvements in QOL, relative to treatment non-responders (all four domains p < 0.001). Paired t-tests indicated that non-responders significantly improved their social (p = 0.007) and environmental (p = 0.033) QOL; however, their psychological (p = 0.088) and physical (p = 0.841) QOL did not significantly improve. The findings indicate that following treatment, QOL improved in at least some domains, but that reduced substance use was associated with both stronger and broader improvements in QOL. Addressing physical and psychological co-morbidities during treatment may facilitate reductions in substance use.

BACKGROUND: There are currently no approved pharmacotherapies for managing methamphetamine dependence. N-acetylcysteine (NAC) has been found to reduce the craving for methamphetamine and other drugs, but its effect on methamphetamine use and other clinically related endpoints are uncertain. The N-ICE trial is evaluating the safety and efficacy of NAC as a take-home pharmacotherapy for methamphetamine dependence. METHODS/DESIGN: This is a two-arm parallel double-blind placebo-controlled three-site randomised trial (ratio 1:1) using permuted block randomisation, with variable block sizes. It is stratified by site, sex and whether the methamphetamine is injected or not. Participants (N = 180; 60 per site) need to be dependent on methamphetamine, interested in reducing their methamphetamine use and not currently receiving treatment for substance use disorders. The trial is being conducted in outpatient settings in Melbourne, Geelong and Wollongong, Australia. Participants will receive either 2400 mg oral NAC or a matched placebo, delivered as a take-home medication for 12 weeks. Two 600 mg capsules are self-administered in the morning and two more in the evening. Adherence is being monitored using eCAP™ medication bottle lids, which record the date and time of each occasion the bottle is opened. The primary outcome is methamphetamine use during the 12-week trial medication period, measured as (a) days of use, assessed using the timeline followback, and (b) methamphetamine-positive saliva tests, taken weekly. Secondary measures include weekly assessment of methamphetamine craving, severity of methamphetamine dependence, methamphetamine withdrawal symptoms and psychiatric symptoms (depression, suicidality, psychotic symptoms and hostility). Adverse events are monitored at each weekly assessment. Tolerability is assessed using the Treatment Satisfaction Questionnaire for Medication. DISCUSSION: The N-ICE trial is the first clinical trial to assess whether NAC can reduce me

Background: There are currently no approved pharmacotherapies for managing methamphetamine dependence. N-acetylcysteine (NAC) has been found to reduce the craving for methamphetamine and other drugs, but its effect on methamphetamine use and other clinically related endpoints are uncertain. The N-ICE trial is evaluating the safety and efficacy of NAC as a take-home pharmacotherapy for methamphetamine dependence. Methods/design: This is a two-arm parallel double-blind placebo-controlled three-site randomised trial (ratio 1:1) using permuted block randomisation, with variable block sizes. It is stratified by site, sex and whether the methamphetamine is injected or not. Participants (N = 180; 60 per site) need to be dependent on methamphetamine, interested in reducing their methamphetamine use and not currently receiving treatment for substance use disorders. The trial is being conducted in outpatient settings in Melbourne, Geelong and Wollongong, Australia. Participants will receive either 2400 mg oral NAC or a matched placebo, delivered as a take-home medication for 12 weeks. Two 600 mg capsules are self-administered in the morning and two more in the evening. Adherence is being monitored using eCAP™ medication bottle lids, which record the date and time of each occasion the bottle is opened. The primary outcome is methamphetamine use during the 12-week trial medication period, measured as (a) days of use, assessed using the timeline followback, and (b) methamphetamine-positive saliva tests, taken weekly. Secondary measures include weekly assessment of methamphetamine craving, severity of methamphetamine dependence, methamphetamine withdrawal symptoms and psychiatric symptoms (depression, suicidality, psychotic symptoms and hostility). Adverse events are monitored at each weekly assessment. Tolerability is assessed using the Treatment Satisfaction Questionnaire for Medication. Discussion: The N-ICE trial is the first clinical trial to assess whether NAC can reduce me

BACKGROUND: Up to 95% of people entering treatment for use of alcohol or other drugs (AOD) smoke tobacco. Smokers receiving treatment for AOD use are interested in quitting and make quit attempts, but relapse is more common and rapid compared with the general population of smokers. New ways to address smoking in this population are needed. Electronic nicotine devices (ENDs) or electronic cigarettes hold significant potential as both cessation aids and harm reduction support. This study focuses on the potential of ENDs to facilitate smoking cessation and to sustain it in the medium term among people in treatment for AOD use. The aim of this trial is to explore the effectiveness, feasibility and acceptability of ENDs for smoking cessation compared with combination nicotine replacement therapy (NRT) for clients after discharge from a smoke-free AOD residential withdrawal service. METHODS/DESIGN: The study is a pragmatic randomised controlled trial. In total, 100 participants will be recruited following admission to a smoke-free residential withdrawal service in Melbourne, Australia. Participants will complete a baseline survey and be randomised to either the END group (n = 50) or the NRT group (n = 50) prior to discharge. Both groups will receive telephone counselling support from quitline. Follow-up measures will be assessed at 6 and 12 weeks following discharge. The primary outcome is continuous abstinence from smoking at 12 weeks post discharge. Secondary outcomes include: 7-day point prevalence from smoking, point prevalence abstinence from all nicotine (including NRT and ENDs), cravings and withdrawal, time to relapse, and treatment adherence (use of NRT, ENDs and quitline). DISCUSSION: This is the first randomised controlled trial to assess the effectiveness and acceptability of ENDs within a population dependent on AOD, a priority group with very high levels of smoking. The research will test a model of how to incorporate novel smoking cessation support into a p

BACKGROUND AND AIMS: Despite the over-representation of people with gambling problems in mental health populations, there is limited information available to guide the selection of brief screening instruments within mental health services. The primary aim was to compare the classification accuracy of nine brief problem gambling screening instruments (two to five items) with a reference standard among patients accessing mental health services. DESIGN: The classification accuracy of nine brief screening instruments was compared with multiple cut-off scores on a reference standard. SETTING: Eight mental health services in Victoria, Australia. PARTICIPANTS: A total of 837 patients were recruited consecutively between June 2015 and January 2016. MEASUREMENTS: The brief screening instruments were the Lie/Bet Questionnaire, Brief Problem Gambling Screen (BPGS) (two- to five-item versions), NODS-CLiP, NODS-CLiP2, Brief Biosocial Gambling Screen (BBGS) and NODS-PERC. The Problem Gambling Severity Index (PGSI) was the reference standard. FINDINGS: The five-item BPGS was the only instrument displaying satisfactory classification accuracy in detecting any level of gambling problem (low-risk, moderate-risk or problem gambling) (sensitivity = 0.803, specificity = 0.982, diagnostic efficiency = 0.943). Several shorter instruments adequately detected both problem and moderate-risk, but not low-risk, gambling: two three-item instruments (NODS-CLiP, three-item BPGS) and two four-item instruments (NODS-PERC, four-item BPGS) (sensitivity = 0.854-0.966, specificity = 0.901-0.954, diagnostic efficiency = 0.908-0.941). The four-item instruments, however, did not provide any considerable advantage over the three-item instruments. Similarly, the very brief (two-item) instruments (Lie/Bet and two-item BPGS) adequately detected problem gambling (sensitivity = 0.811-0.868, specificity = 0.938-0.943, diagnostic efficiency = 0.933-0.934), but not moderate-risk or low-risk gambling. CONCLUSIONS

© 2018 Australasian Professional Society on Alcohol and other Drugs Introduction and Aims: Prescribed psychotropic medications contribute to overdose mortality among people with alcohol and other drug (AOD) disorders. We report on prescribed psychotropic medication use among AOD treatment service attendees, focusing on sedative drugs. Design and Methods: Prospective multi-site naturalistic outcome study in residential and outpatient AOD treatment facilities in Victoria and Western Australia. A convenience sample of 480 people (57% male; mean age 36.1) entering treatment were surveyed, of whom 313 (65%) were followed up by telephone interview after a median of 377 days. Participants’ prescribed psychotropic medication use was ascertained by self-report at baseline and follow-up. Results: At baseline, 41% of participants reported prescribed sedative medication (benzodiazepine, zopiclone or zolpidem) use within the past month, including prescriptions to treat withdrawal symptoms. At follow-up, the cohort reported a reduced rate of past month prescribed sedative use (23%; P < 0.001) and this rate did not significantly differ between those who continued to use their primary drug of concern and those who were abstinent at follow-up (P = 0.08). Among those with opioids as their primary drug of concern, one-third were still being prescribed a sedative at follow-up (P > 0.99 for change from baseline). At baseline, 40% of participants were prescribed an antidepressant and 13% an antipsychotic medication, which remained similar at follow-up (45% and 13%, respectively). Discussion and Conclusions: The high level of prescribed sedative drug use reported by people receiving AOD treatment is a serious public health concern given the increasing incidence of drug overdose deaths in Australia.

Background and aims Relatively little is known about co-occurring gambling problems and their overlap with other addictive behaviors among individuals attending mental health services. We aimed to determine rates of gambling and substance use problems in patients accessing mental health services in Victoria, Australia. Methods A total of 837 adult patients were surveyed about their gambling and administered standardized screening tools for problem gambling and harmful tobacco, alcohol, and drug use. Prevalence of gambling problems was estimated and regression models used to determine predictors of problem gambling. Results The gambling participation rate was 41.6% [95% CI = 38.2-44.9]. The Problem Gambling Severity Index identified 19.7% [CI = 17.0-22.4] as "non-problem gamblers," 7.2% [CI = 5.4-8.9] as "low-risk" gamblers, 8.4% [CI = 6.5-10.2] as "moderate-risk" gamblers, and 6.3% [CI = 4.7-8.0] as "problem gamblers." One-fifth (21.9%) of the sample and 52.6% of all gamblers were identified as either low-risk, moderate-risk, or problem gamblers (PGs). Patients classified as problem and moderate-risk gamblers had significantly elevated rates of nicotine and illicit drug dependence (p < .001) according to short screening tools. Current diagnosis of drug use (OR = 4.31 [CI = 1.98-9.37]), borderline personality (OR = 2.59 [CI = 1.13-5.94]), bipolar affective (OR = 2.01 [CI = 1.07-3.80]), and psychotic (OR = 1.83 [CI = 1.03-3.25]) disorders were significant predictors of problem gambling. Discussion and conclusions Patients were less likely to gamble, but eight times as likely to be classified as PG, relative to Victoria's adult general population. Elevated rates of harmful substance use among moderate-risk and PG suggest overlapping vulnerability to addictive behaviors. These findings suggest mental health services should embed routine screening into clinical practice, and train clinicians in the management of problem gambling.

© 2017 Informa UK Limited, trading as Taylor & Francis Group. Background: Globally, many nurses and midwives are working at an advanced practice level. The role of a Nurse and/or Midwife Consultant encompasses a diverse and complex interaction between five specified domains namely Clinical Service and Consultancy, Clinical Leadership, Research, Education, and Clinical Services Planning and Management. Objective: The objective of this replication study was to identify the key drivers and mitigating factors that impact the role of Australian Nurse and/or Midwife Consultants. Design: Cross-sectional survey. Methods: The study was conducted in a large metropolitan health district in Sydney, Australia. Participants for this study consisted of all Nurse and/or Midwife Consultants working within a health district in New South Wales (NSW). Data were collected by an anonymous online survey. Key drivers and mitigating factors perceived to influence their role were identified using previously implemented instruments. Data were analysed using SPSS version 21. Results: Responses were obtained from 122 Nurse and/or Midwife Consultants. The number of years of experience as a Nurse and/or Midwife Consultant ranged from 6 months to 25.5 years. Personal attributes which included personal motivation and own communication skills were identified as key drivers to role performance with a mean score of 7.7±0.6. Other key drivers included peer support, organisational culture, personal attributes, professional learning, Nurse and/or Midwife Consultant experience, and collaborative relationships. Of the 14 mitigating factors to the role, the most common factors were lack of resources to set up and develop the role (2.6 ± 0.9), lack of secretarial support (2.6 ± 1.1), lack of managerial support (2.45 ± 1.1), and lack of understanding of the role by other health professionals (2.40 ± 0.8). Conclusions: Understanding the key drivers and mitigating factors that influence the role of the Nurse an

Background and Aims: Our understanding of patient pathways through specialist Alcohol and Other Drug treatment and broader health/welfare systems in Australia remains limited. This study examines how treatment outcomes are influenced by continuity in specialist Alcohol and Other Drug treatment, engagement with community services and mutual aid, and explores differences between clients who present with a primary alcohol problem relative to those presenting with a primary drug issue. Method: In a prospective, multi-site treatment outcome study, 796 clients from 21 Alcohol and Other Drug services in Victoria and Western Australia completed a baseline interview between January 2012 and January 2013. A total of 555 (70%) completed a follow-up assessment of subsequent service use and Alcohol and Other Drug use outcomes 12-months later. Results: Just over half of the participants (52.0%) showed reliable reductions in use of, or abstinence from, their primary drug of concern. This was highest among clients with meth/amphetamine (66%) as their primary drug of concern and lowest among clients with alcohol as their primary drug of concern (47%), with 31% achieving abstinence from all drugs of concern. Continuity of specialist Alcohol and Other Drug care was associated with higher rates of abstinence than fragmented Alcohol and Other Drug care. Different predictors of treatment success emerged for clients with a primary drug problem as compared to those with a primary alcohol problem; mutual aid attendance (odds ratio = 2.5) and community service engagement (odds ratio = 2.0) for clients with alcohol as the primary drug of concern, and completion of the index treatment (odds ratio = 2.8) and continuity in Alcohol and Other Drug care (odds ratio = 1.8) when drugs were the primary drugs of concern. Conclusion: This is the first multi-site Australian study to include treatment outcomes for alcohol and cannabis users, who represent 70% of treatment seekers in Alcohol and Other Drug