آیا اختلالات انگیزش در اختلالات طیف اسکیزوفرنی باعث ترویج مصرف کانابیس می شود؟ بررسی پاسخ رفتاری به پاداش طبیعی و نشانه های مصرف مواد مخدر

Deficits in incentive motivation are often present in both Schizophrenia Spectrum Disorders (SSD) and substance-use disorders. The current study aims to test whether the presence of such deficits confers vulnerability to cannabis use in individuals with SSD. SSD patients (n=35) and healthy controls (n=35) were each divided into a group with (n=20) and a group without (n=15) current cannabis use disorder. Subjects performed a behavioural task designed for schizophrenia patients in which they could seek exposure to pleasant and cannabis visual stimuli on the basis of internal representations of these stimuli. Intensity of cannabis use was assessed by self-report. SSD patients were significantly less likely than controls to exert effort to try to re-view pleasant stimuli but were not significantly less likely to work to avoid unpleasant stimuli. Lack of response to re-view pleasant stimuli significantly predicted higher subsequent cannabis self-administration in patients but not controls, after controlling for degree of prior exposure to cannabis. Deficits in incentive motivation may be an aspect of SSD which promotes cannabis use in this population.

1.1. Background There are negative consequences of cannabis use for individuals with Schizophrenia-Spectrum Disorders (SSD) (Zammit et al., 2008). In order to reduce this behaviour it is necessary to understand factors promoting cannabis use in this population. Some evidence suggests individuals with SSD report similar reasons for substance use as other young people (Kolliakou et al., 2011); however, more work is needed before elements of psychotic illness or its associated morbidity can be ruled out as important factors promoting cannabis use in SSD. One of the most striking deficits observed in many patients with schizophrenia is avolition, a negative symptom of schizophrenia consisting of lack of motivation to pursue goals or effortful activities (Foussias and Remington, 2010). There is a growing body of evidence of deficits in anticipating (Gard et al., 2007), delaying (Ahn et al., 2011), working for (Heerey and Gold, 2007), learning about (Yilmaz et al., 2012), or exploring (Strauss et al., 2011) rewards in this condition. “Wanting” and behavioural exertion to seek rewards are critically modulated by the dopamine system, which is believed to signal the motivational salience of incentive environmental stimuli and is highly implicated in both schizophrenia and addiction (Schultz et al., 1997, Howes and Kapur, 2009 and Heinz and Schlagenhauf, 2010). Some have argued that the primary reward-related deficit in SSD is an inability to mentally represent the value of a reward after it ceases to be experienced (Gold et al., 2008). On the other hand, liking, the degree of pleasure while in the midst of experiencing a reward, may be relatively intact (Gard et al., 2007 and Heerey and Gold, 2007). Habitual substance use may result in behavioural disengagement as the desired substance usurps attention and motivated behaviour towards itself (Anselme, 2009). On the other hand, behavioural disengagement may be a vulnerability factor to substance use in humans and animals (Terry-McElrath et al., 2011, Nader et al., 2012 and Puhl et al., 2012). Along these lines it is of note that a similar intervention, boosting dopamine receptors in the striatum, can both reduce addictive behaviours in animals (Nader and Czoty, 2005) and increase the tendency to work for rewards (Trifilieff et al., 2013). However, concerning cannabis users in the general population, there is little evidence of motivation deficits despite popular conceptions (Kaestner, 1994, Barnwell et al., 2006, Looby and Earleywine, 2007 and Grant et al., 2012). In the case of cannabis users with schizophrenia there has been inconsistent evidence regarding the association between substance use and symptoms of avolition (Potvin et al., 2006, Leventhal et al., 2008 and Koen et al., 2009). 1.2. Rationale and hypothesis As the nature of the reward deficits in schizophrenia has recently become better delineated (Gold et al., 2008, Ahn et al., 2011, Strauss et al., 2011 and Yilmaz et al., 2012), a key question should be how these deficits may promote maladaptive behaviours such as substance abuse, which has been conceptualised as pathological reward reinforcement (Di Chiara, 1995). Deficits in reward processing have been theorised to contribute to the co-morbidity of schizophrenia-spectrum and substance-use disorders (Roth et al., 2005 and Krystal et al., 2006); however, research in this area has not kept pace with the recent advances concerning reward deficits in schizophrenia. We theorised that deficits in incentive motivation may be an aspect of schizophrenia which could confer vulnerability to habitual cannabis use, an immediately rewarding behaviour requiring minimal exertion, and make it harder to replace cannabis with alternative recreational activities. Although this reasoning would apply to any substance of abuse, cannabis seemed the most pertinent substance to study given that it is often the most commonly abused substance in youth with psychotic illness (Koskinen et al., 2009). We employed a behavioural task (Heerey and Gold, 2007) which was designed for use in schizophrenia and has previously exposed incentive motivation deficits in this condition. This paradigm measures incentive motivation or “wanting”, operationalised as the effort exerted in a key-press procedure to seek re-exposure to pleasant images and images of cannabis. This paradigm quantifies willingness to exert effort in the present for an uncertain reward in the future and is particularly relevant to schizophrenia because response is made based on the mental representation of the value of the reward which is no longer visible when responding. We hypothesised that patients would be less inclined to seek natural rewards (pleasant images) than controls and that deficits in reward-seeking would predict the frequency of future cannabis self-administration.

3. Results 3.1. Demographic measures and substance use Patients and controls with and without cannabis use were compared on demographic measures and measures of substance use using t-tests and χ2 tests (see Table 1). Cannabis users (pooling patients and controls together) were younger than non-users (p=0.054), had lower education (p<0.001) and were more likely to smoke cigarettes (p<0.01). Patients (pooling cannabis users and non-users together) were more likely to be single than controls (p<0.05) and had lower education (p<0.001). Cannabis-using patients did not significantly differ from cannabis-using controls on any measure of current or lifetime substance use (all p's>0.19). Table 1. Demographic and substance-use characteristics. Control Patient p-Values from Fisher's/t-tests comparing patients to controls p-Values from Fisher's/t-tests comparing users to non-users Nonusers (n=15) Cannabis users (n=20) Nonusers (n=15) Cannabis users (n=20) Age (S.D.) 26.1 (3.9) 25.6 (5.5) 28.4 (5.1) 24.4 (4.3) 0.81 0.054 Years education (S.D.) 15.1 (2.1) 12.8 (1.6) 12.8 (2.0) 10.4 (2.0) <0.001 <0.001 Single marital status 6 (40%) 13 (65%) 12 (80%) 16 (80%) 0.041 0.31 Current cigarette smoker 5 (33%) 9 (45%) 3 (20%) 16 (80%) 0.34 0.004 Cannabis use frequency, past month (S.D.) 73 (57) 95 (85) 0.73 Grams of cannabis consumed past month (S.D.) 26.4 (46) 44.9 (56) 0.67 CAST score past year (S.D.) 15.5 (3.9) 17.5 (5.5) 0.19 CAST score lifetime (S.D.) 17.6 (3.6) 18.9 (4.8) 0.32 Years of regular cannabis use (S.D.) 5.7 (5.0) 6.7 (5.3) 0.56 Used other substances, past month 7 (35%) 5 (25%) 0.73 Chlorpromazine equivalents prescribed (S.D.) 315 (200) 235 (84) 0.18 Prescribed other types of psychiatric meds 4 (27%) 4 (20%) 1.0 SAPS global total score (S.D.) 5.2 (4.7) 3.4 (2.5) 0.18 SANS global total score (S.D.) 5.9 (3.7) 7.4 (3.6) 0.23 Months since treatment onset (S.D.) 34.6 (29) 31.4 (31) 0.76 Table options 3.2. Subjective ratings of stimuli ANOVAs on valence and arousal ratings of stimuli both showed significant patient status×stimulus type interactions (F(3,63)=3.09, p=0.033; F(3,63)=5.38, p=0.002 respectively) and significant cannabis status×stimulus type interactions (F(3,63)=31.1, p<0.001; F(3,63)=10.4, p<0.001 respectively). Patients had significantly lower valence ratings of pleasant stimuli (p=0.008) and lower arousal ratings of unpleasant stimuli (p=0.019) but did not differ from controls on the other stimulus types. Compared to non-users, cannabis users (patients and controls) had significantly higher valence and arousal ratings of cannabis stimuli (p's<0.002) but did not differ on the other stimulus types. 3.3. Incentive behavioural response Fig. 1 shows behavioural responses made by the four subject groups according to stimulus type. Compared to controls (users and non-users pooled), patients responded less often to re-view pleasant stimuli (χ2=6.1, p=0.046; for proportions see Table 2) but did not respond significantly less often to avoid unpleasant stimuli (χ2=4.6, p=0.10). Cannabis-using patients did not respond less often to re-view cannabis stimuli than cannabis-using controls (χ2=0.50, p=0.80). Compared to non-users (patients and controls pooled), cannabis users did not respond less often to re-view pleasant stimuli (χ2=3.5, p=0.17) and responded much more often to re-view cannabis stimuli (χ2=15.1, p=0.001). Subjects who responded to re-view pleasant images did not provide significantly higher ratings on valence and arousal of these images (t's<1, p's>0.3). Table 2. Proportion of subjects responding to the different stimulus types. Response type Number of stimuli eliciting behavioural response Control Patient χ2 Cramer's V Cannabis χ2 Cramer's V Non-user User Re-view pleasant None 10 (29%) 20 (57%) 6.1⁎ 0.30 9 (30%) 21 (53%) 3.5 0.23 1–6 14 (40%) 7 (20%) 11 (37%) 10 (25%) >7 11 (31%) 8 (23%) 10 (33%) 9 (23%) Avoid unpleasant None 8 (23%) 14 (40%) 4.6 0.26 8 (27%) 14 (35%) 0.79 0.11 1–6 12 (34%) 5 (14%) 7 (23%) 10 (25%) >7 15 (43%) 16 (46%) 15 (50%) 16 (40%) Re-view cannabis None 10 (50%) 12 (60%) 0.46 0.11 29 (97%) 22 (55%) 15⁎⁎ 0.47 1–6 7 (35%) 6 (30%) 1 (3%) 13 (33%) >7 3 (15%) 2 (10%) 0 (0%) 5 (13%) ⁎ p<0.05. ⁎⁎ p<0.01. Table options 3.4. Prediction of future cannabis self-administration based on motivated responding There was a significant interaction between patient status and incentive responding to pleasant images in linear regression analysis predicting cannabis self-administration over the month post-testing (β=−1.2, p<0.01), thus subsequent regression analyses were performed separately in patients and controls. In cannabis-using patients, lower rates of responding in all conditions, to re-view either pleasant or cannabis stimuli or to avoid unpleasant stimuli, predicted higher rates of cannabis self-administration over the month post-testing (all β values between −0.27 and −0.35; see Table 3; all regressions included level of exposure to cannabis in the month prior to testing as an independent variable). In control subjects, measures of motivated responding did not significantly predict subsequent cannabis self-administration. Table 3. Prediction of intensity of future cannabis use using linear regressions with behavioural response measures and exposure to cannabis in the month prior to testing as independent variables. Prediction of frequency of cannabis self-administration at 1 month post-testing Controls (n=20) Patients (n=20) Adjusted R2 for model β p Adjusted R2 for model β p Responses to re-view pleasant stimuli 0.10 0.14 0.55 0.80 −0.34 0.006 Level of exposure to cannabis in the month prior to testing 0.43 0.065 0.75 <0.001 Responses to re-view cannabis stimuli 0.18 0.30 0.17 0.80 −0.35 0.006 Level of exposure to cannabis in the month prior to testing 0.48 0.038 0.72 <0.001 Responses to avoid negative stimuli 0.10 0.14 0.55 0.75 −0.27 0.051 Level of exposure to cannabis in the month prior to testing 0.45 0.061 0.73 <0.001 Table options Measures of valence and arousal of pleasant stimuli did not significantly correlate with cannabis self-administration in patients or controls (R's<0.25).