Development of the motivational thought frequency scale for alcohol abstinence (MTF-A).

BACKGROUND AND AIMS: For most treatment-seeking patients with severe Alcohol Use Disorder (AUD), abstinence is the clinically indicated goal. Existing AUD motivation scales are non-specific about treatment consumption goals, which limit their effectiveness. Desires and mental imagery are relevant in the motivation for AUD treatment engagement. The Motivational Thought Frequency Scale for an abstinence goal (MTF-A) was adapted from the MTF for controlled drinking (MTF-CD). This study psychometrically evaluated the MTF-A in an alcohol-dependent sample engaged in treatment with a goal of abstinence. To enhance the clinical utility of the scale, a secondary aim was to evaluate a psychometrically equivalent short version of the MTF-A. METHOD: A sample N of 329 treatment-seeking patients with AUD (mean age of 44.44 years, SD = 11.89 years, 72% male) who were undertaking a cognitive behavioral treatment (CBT) program for abstinence completed the Motivational Thought Frequency Scale for Abstinence (MTF-A) and the Severity of Alcohol Dependence Questionnaire (SADQ). The MTF-A measured motivation for abstinence through four factors: intensity, self-efficacy imagery, incentives imagery, and availability. Confirmatory factor analyses (CFAs) were conducted to examine factor structure and model fit. Cronbach's alpha assessed internal consistency. Predictive validity was determined by logistic regression predicting first-session treatment non-attendance and alcohol consumption between baseline assessment and commencement of treatment, controlling for potential confounds. RESULTS: A four-factor structure provided the best fit for the MTF-A, compared with one- and three-factor models. A shortened 9-item MTF-A scale (S-MTF-A) provided better fit than the 13-item MTF-A scale. Both MTF-A and S-MTF-A displayed good internal consistency. Although both MTF-A and S-MTF-A successfully predicted first-session treatment non-attendance, neither predicted alcohol consumption between the baseline assessment and commencement of treatment. CONCLUSIONS: The model fit of the four-factor, 9-item S-MTF-A was superior to the original 13-item MTF-A. Both scales were predictive of participation of AUD treatment. Desires and mental imagery play an important role in AUD treatment motivation.

Relationship between alcohol craving dimensions and features of comorbid mental health in an alcohol dependent sample.

BACKGROUND AND AIMS: Negative affect and alcohol craving are common features of Alcohol Use Disorder (AUD). Both independently contribute to AUD severity and poorer treatment outcomes, but their relationship is poorly understood. Multidimensional alcohol craving measures now allow for examination of key dimensions of craving. This study explored the relationship between depression, anxiety, stress, and the alcohol craving dimensions of intensity, imagery and intrusiveness. METHOD: Five-hundred and twenty-five treatment seeking AUD patients (mean age of 39.79 years, SD = 11.57 years, 67% male) completed the Depression Anxiety Stress Scales (DASS), Alcohol Use Disorder Identification Test-Consumption items (AUDIT-C), and Alcohol Craving Experience (ACE-F) questionnaire, which measured the frequency of craving intensity, imagery and intrusiveness. Regression models predicted main effects of predictors and moderation by alcohol consumption. RESULTS: Higher levels of stress were independently associated with increased craving intensity, imagery and intrusiveness. Significant positive associations were also found between anxiety and craving imagery. The association between depression and craving was not significant after controlling for other predictors. CONCLUSIONS: AUD patients experienced higher cravings when stressed and greater imagery when anxious. These results support the need to consider the relationships between stress and craving when managing alcohol dependence.

Precision Mental Health Care for Cannabis Use Disorder: Utility of a bioSocial Cognitive Theory to Inform Treatment.

Globally, cannabis is the most frequently used controlled substance after alcohol and tobacco. Rates of cannabis use are steadily increasing in many countries and there is emerging evidence that there is likely to be greater risk due to increased concentrations of delta-9-tetrahydrocannabinol (THC). Cannabis use and Cannabis Use Disorder (CUD) has been linked to a wide range of adverse health outcomes. Several biological, psychological, and social risk factors are potential targets for effective evidence-based treatments for CUD. There are no effective medications for CUD and psychological interventions are the main form of treatment. Psychological treatments based on Social Cognitive Theory (SCT) emphasize the importance of targeting 2 keys psychological mechanisms: drug outcome expectancies and low drug refusal self-efficacy. This mini-review summarizes the evidence on the role of these mechanisms in the initiation, maintenance, and cessation of cannabis use. It also reviews recent evidence showing how these psychological mechanisms are affected by social and biologically-based risk factors. A new bioSocial Cognitive Theory (bSCT) is outlined that integrates these findings and implications for psychological cannabis interventions are discussed. Preliminary evidence supports the application of bSCT to improve intervention outcomes through better targeted treatment.

Testing the biosocial cognitive model of substance use in cannabis users referred to treatment.

BACKGROUND: The bioSocial Cognitive Theory (bSCT) hypothesizes two pathways linking dimensions of impulsivity to substance use. The first predicts that the association between reward sensitivity and substance use is mediated by positive outcome expectancies. The second predicts that the relationship between rash impulsiveness and substance use is mediated by refusal self-efficacy. This model has received empirical support in studies of alcohol use. The present research provides the first application of bSCT to a cannabis treatment population and aims to extend its utility to understanding cannabis use and severity of dependence. DESIGN: 273 patients referred for cannabis treatment completed a clinical assessment that contained measures of interest. SETTING: A public hospital alcohol and drug clinic. MEASUREMENTS: The Sensitivity to Reward Scale, Dysfunctional Impulsivity Scale, Cannabis Expectancy Questionnaire, Cannabis Refusal Self-Efficacy Questionnaire and Severity of Dependence Scale-Cannabis were completed, along with measures of cannabis consumption. FINDINGS: The bSCT model provided a good fit to the data for cannabis use and severity of dependence outcomes. The association between reward sensitivity and each cannabis outcome was fully mediated by positive cannabis expectancies and cannabis refusal self-efficacy. The relationship between rash impulsiveness and each cannabis outcome was fully mediated by cannabis refusal self-efficacy. CONCLUSIONS: Findings support the application of the bSCT model to cannabis use and dependence severity and highlight the important role of social cognitive mechanisms in understanding the association between impulsivity traits and these outcomes. The differential association of impulsivity traits to social cognition may assist targeted treatment efforts.

Treatment seeking in cannabis dependence: The role of social cognition.

BACKGROUND AND AIMS: Relatively few cannabis dependent individuals seek treatment and little is known about the determinants of treatment seeking. Social Cognitive Theory (SCT) provides a useful framework for examining human behaviour and motivation which may be helpful in explaining treatment seeking. This study examined the differences in cannabis outcome expectancies and cannabis refusal self-efficacy between treatment seekers and non-treatment seekers with cannabis dependence. DESIGN: Non-treatment seekers were referred to an illicit drug diversion program. Treatment seekers commenced an outpatient cannabis treatment program and completed a comprehensive assessment that included measures of cannabis outcome expectancies and refusal self-efficacy. SETTING: A public hospital alcohol and drug outpatient clinic. PARTICIPANTS: 269 non-treatment seekers and 195 individuals commencing cannabis dependence treatment. MEASUREMENTS: The Cannabis Expectancy Questionnaire (CEQ), Cannabis Refusal Self-Efficacy Questionnaire (CRSEQ), Severity of Dependence Scale - Cannabis (SDS-C), General Health Questionnaire (GHQ-28) and Readiness to Change Questionnaire (RTC) were completed. FINDINGS: Treatment seekers had significantly higher levels of negative cannabis outcome expectancies and significantly lower levels of emotional relief refusal self-efficacy (belief in ability to resist using cannabis when experiencing negative affect) (ps<0.001). Treatment seekers had significantly higher levels of psychological distress and self-perceived cannabis dependence compared to non-treatment seekers (ps<0.001). CONCLUSIONS: High negative cannabis outcome expectancies and low emotional relief refusal self-efficacy may play a key role in motivation to seek treatment.

Social cognitive predictors of treatment outcome in cannabis dependence.

BACKGROUND: Drug-related outcomes expectancies and refusal self-efficacy are core components of Social Cognitive Theory. Both predict treatment outcome in alcohol use disorders. Few studies have reported expectancies and refusal self-efficacy in cannabis dependence. None have examined both, although both constructs are key targets in Cognitive-Behavioural Therapy (CBT). This study tests the predictive role of expectancies and refusal self-efficacy in treatment outcome for cannabis dependence. DESIGN: Outpatients completed a comprehensive assessment when commencing cannabis treatment and predictors of treatment outcome were tested. SETTING: A university hospital alcohol and drug outpatient clinic. PARTICIPANTS: 221 cannabis-dependent patients participated in a 6-week CBT program where the goal was abstinence. MEASUREMENTS: Cannabis Expectancy Questionnaire and Cannabis Refusal Self-Efficacy Questionnaire, cannabis dependence severity [Severity of Dependence Scale], psychological distress [General Health Questionnaire] at baseline; the timeline follow-back procedure at baseline and each session. FINDINGS: Patients reporting lower confidence in their ability to resist cannabis during high negative affect (emotional relief refusal self-efficacy) had a lower likelihood of abstinence (p=0.004), more days of use (p<0.001), and larger amount used (p<0.001). Negative cannabis expectancies predicted greater likelihood of abstinence (p=0.024). Higher positive expectancies were associated with lower emotional relief self-efficacy, mediating its association with outcome (p<0.001). CONCLUSIONS: Emotional relief refusal self-efficacy and negative expectancies are predictive of better treatment outcomes for cannabis dependence. Positive expectancies may indirectly predict poorer outcome because of a negative association with self-efficacy, but this conclusion remains tentative as directionality could not be established.

The craving experience questionnaire: a brief, theory-based measure of consummatory desire and craving.

BACKGROUND AND AIMS: Research into craving is hampered by lack of theoretical specification and a plethora of substance-specific measures. This study aimed to develop a generic measure of craving based on elaborated intrusion (EI) theory. Confirmatory factor analysis (CFA) examined whether a generic measure replicated the three-factor structure of the Alcohol Craving Experience (ACE) scale over different consummatory targets and time-frames. DESIGN: Twelve studies were pooled for CFA. Targets included alcohol, cigarettes, chocolate and food. Focal periods varied from the present moment to the previous week. Separate analyses were conducted for strength and frequency forms. SETTING: Nine studies included university students, with single studies drawn from an internet survey, a community sample of smokers and alcohol-dependent out-patients. PARTICIPANTS: A heterogeneous sample of 1230 participants. MEASUREMENTS: Adaptations of the ACE questionnaire. FINDINGS: Both craving strength [comparative fit indices (CFI = 0.974; root mean square error of approximation (RMSEA) = 0.039, 95% confidence interval (CI) = 0.035-0.044] and frequency (CFI = 0.971, RMSEA = 0.049, 95% CI = 0.044-0.055) gave an acceptable three-factor solution across desired targets that mapped onto the structure of the original ACE (intensity, imagery, intrusiveness), after removing an item, re-allocating another and taking intercorrelated error terms into account. Similar structures were obtained across time-frames and targets. Preliminary validity data on the resulting 10-item Craving Experience Questionnaire (CEQ) for cigarettes and alcohol were strong. CONCLUSIONS: The Craving Experience Questionnaire (CEQ) is a brief, conceptually grounded and psychometrically sound measure of desires. It demonstrates a consistent factor structure across a range of consummatory targets in both laboratory and clinical contexts.

The relationship between cannabis outcome expectancies and cannabis refusal self-efficacy in a treatment population.

BACKGROUND AND AIMS: Self-efficacy beliefs and outcome expectancies are central to Social Cognitive Theory (SCT). Alcohol studies demonstrate the theoretical and clinical utility of applying both SCT constructs. This study examined the relationship between refusal self-efficacy and outcome expectancies in a sample of cannabis users, and tested formal mediational models. DESIGN: Patients referred for cannabis treatment completed a comprehensive clinical assessment, including recently validated cannabis expectancy and refusal self-efficacy scales. SETTING: A hospital alcohol and drug out-patient clinic. PARTICIPANTS: Patients referred for a cannabis treatment [n = 1115, mean age 26.29, standard deviation (SD) 9.39]. MEASUREMENTS: The Cannabis Expectancy Questionnaire (CEQ) and Cannabis Refusal Self-Efficacy Questionnaire (CRSEQ) were completed, along with measures of cannabis severity [Severity of Dependence Scale (SDS)] and cannabis consumption. FINDINGS: Positive (ß = -0.29, P < 0.001) and negative (ß = -0.19, P < 0.001) cannabis outcome expectancies were associated significantly with refusal self-efficacy. Refusal self-efficacy, in turn, fully mediated the association between negative expectancy and weekly consumption [95% confidence interval (CI) = 0.03, 0.17] and partially mediated the effect of positive expectancy on weekly consumption (95% CI = 0.06, 0.17). CONCLUSIONS: Consistent with Social Cognitive Theory, refusal self-efficacy (a person's belief that he or she can abstain from cannabis use) mediates part of the association between cannabis outcome expectancies (perceived consequences of cannabis use) and cannabis use.

Alcohol consumption in young adults: the role of multisensory imagery.

Little is known about the subjective experience of alcohol desire and craving in young people. Descriptions of alcohol urges continue to be extensively used in the everyday lexicon of young, non-dependent drinkers. Elaborated Intrusion (EI) Theory contends that imagery is central to craving and desires, and predicts that alcohol-related imagery will be associated with greater frequency and amount of drinking. This study involved 1535 age stratified 18-25 year olds who completed an alcohol-related survey that included the Imagery scale of the Alcohol Craving Experience (ACE) questionnaire. Imagery items predicted 12-16% of the variance in concurrent alcohol consumption. Higher total Imagery subscale scores were linearly associated with greater drinking frequency and lower self-efficacy for moderate drinking. Interference with alcohol imagery may have promise as a preventive or early intervention target in young people.

Polysubstance use in cannabis users referred for treatment: drug use profiles, psychiatric comorbidity and cannabis-related beliefs.

BACKGROUND: Population-based surveys demonstrate cannabis users are more likely to use both illicit and licit substances, compared with non-cannabis users. Few studies have examined the substance use profiles of cannabis users referred for treatment. Co-existing mental health symptoms and underlying cannabis-related beliefs associated with these profiles remains unexplored. METHODS: Comprehensive drug use and dependence severity (Severity of Dependence Scale-Cannabis) data were collected on a sample of 826 cannabis users referred for treatment. Patients completed the General Health Questionnaire, Cannabis Expectancy Questionnaire, Cannabis Refusal Self-Efficacy Questionnaire, and Positive Symptoms and Manic-Excitement subscales of the Brief Psychiatric Rating Scale. Latent class analysis was performed on last month use of drugs to identify patterns of multiple drug use. Mental health comorbidity and cannabis beliefs were examined by identified drug use pattern. RESULTS: A three-class solution provided the best fit to the data: (1) cannabis and tobacco users (n = 176), (2) cannabis, tobacco, and alcohol users (n = 498), and (3) wide-ranging substance users (n = 132). Wide-ranging substance users (3) reported higher levels of cannabis dependence severity, negative cannabis expectancies, lower opportunistic, and emotional relief self-efficacy, higher levels of depression and anxiety and higher manic-excitement and positive psychotic symptoms. CONCLUSION: In a sample of cannabis users referred for treatment, wide-ranging substance use was associated with elevated risk on measures of cannabis dependence, co-morbid psychopathology, and dysfunctional cannabis cognitions. These findings have implications for cognitive-behavioral assessment and treatment.

Development and validation of the cannabis refusal self-efficacy questionnaire (CRSEQ) in adult cannabis users in treatment.

BACKGROUND: There are few valid clinical assessment instruments for cannabis. Self-efficacy, or the ability of users to resist temptation, is a central feature of social cognitive theory. This study outlines the development and validation of the cannabis refusal self-efficacy questionnaire (CRSEQ), which measures the situational confidence to refuse cannabis. METHOD: One thousand two hundred and forty-six patients referred for cannabis assessment completed the CRSEQ including measures of cannabis consumption and dependence severity (severity of dependence scale-cannabis, SDS-C). The CRSEQ was subject to independent exploratory (n=621, mean age 26.88, 78.6% male) and confirmatory (n=625, mean age 27.51, 76.8% male) factor analysis. RESULTS: Three factors: Emotional Relief, Opportunistic and Social Facilitation were identified. They provided a good statistical and conceptual fit for the data. Emotional relief cannabis refusal self-efficacy was identified as most predictive of cannabis dependence, after controlling for cannabis consumption. CONCLUSIONS: The CRSEQ is recommended as a psychometrically sound and clinically useful measure for cannabis misuse treatment planning and assessment.

Measuring alcohol craving: development of the Alcohol Craving Experience questionnaire.

AIMS: To develop a measure of craving based on the Elaborated Intrusion (EI) theory of desire and to examine the construct, concurrent and discriminant validity of the instrument. DESIGN: Cross-sectional. SETTING AND PARTICIPANTS: Patients from a hospital alcohol and drug out-patient service (n = 230), participants in a randomized controlled trial (n = 219) and students in a university-based study of alcohol craving (n = 202) were recruited. MEASUREMENTS: The Alcohol Craving Experience questionnaire (ACE) was developed to measure sensory aspects of craving (imagining taste, smell or sensations of drinking and intrusive cognitions associated with craving) when craving was maximal during the previous week (ACE-S: strength), and to assess frequency of desire-related thoughts in the past week (ACE-F: frequency). All participants completed the ACE and the Alcohol Use Disorders Identification Test (AUDIT). The Obsessive Compulsive Drinking Scale (OCDS) and the Depression Anxiety and Stress Scale (DASS) were completed by hospital patients and randomized control trial participants. FINDINGS: Exploratory factor analysis on the ACE-S and ACE-F resulted in a three-factor structure representing imagery, intensity and intrusion. An attempt to confirm this factor structure required a reduction in items (two from ACE-S, five from ACE-F) before a good fit to the three-factor model was obtained. Concurrent validity with the OCDS, with severity of alcohol dependence and with depression, anxiety and stress, was demonstrated. The ACE discriminated between clinical and non-clinical populations and between those at higher risk of alcohol dependence and those at lower risk. CONCLUSIONS: A new scale, the Alcohol Craving Experience questionnaire, based on the Elaborated Intrusion theory of desire appears to capture key constructs of the theory and correlate with indices of alcohol dependence.

Validation of the Cannabis Expectancy Questionnaire (CEQ) in adult cannabis users in treatment.

BACKGROUND: Outcome expectancies are a key cognitive construct in the etiology, assessment and treatment of Substance Use Disorders. There is a research and clinical need for a cannabis expectancy measure validated in a clinical sample of cannabis users. METHOD: The Cannabis Expectancy Questionnaire (CEQ) was subjected to exploratory (n=501, mean age 27.45, 78% male) and confirmatory (n=505, mean age 27.69, 78% male) factor analysis in two separate samples of cannabis users attending an outpatient cannabis treatment program. Weekly cannabis consumption was clinically assessed and patients completed the Severity of Dependence Scale-Cannabis (SDS-C) and the General Health Questionnaire (GHQ-28). RESULTS: Two factors representing Negative Cannabis Expectancies and Positive Cannabis Expectancies were identified. These provided a robust statistical and conceptual fit for the data. Internal reliabilities were high. Negative expectancies were associated with greater dependence severity (as measured by the SDS) and positive expectancies with higher consumption. The interaction of positive and negative expectancies was consistently significantly associated with self-reported functioning across all four GHQ-28 scales (Somatic Concerns, Anxiety, Social Dysfunction and Depression). Specifically, within the context of high positive cannabis expectancy, higher negative expectancy was predictive of more impaired functioning. By contrast, within the context of low positive cannabis expectancy, higher negative expectancy was predictive of better functioning. CONCLUSIONS: The CEQ is the first cannabis expectancy measure to be validated in a sample of cannabis users in treatment. Negative and positive cannabis expectancy domains were uniquely associated with consumption, dependence severity and self-reported mental health functioning.