Recreational Drug Use and Suicidality Among Italian Young Adults Marco Innamorati, PsyD Maurizio Pompili, MD David Lester, PhD Roberto Tatarelli, MD Paolo Girardi, MD

ABSTRACT. The aim of the study was to explore recreational drug use patterns among a sample of Italian young adults and to examine the role of substance misuse on suicidality. Three hundred and forty Italian young adults between 19 and 30 years of age completed measures of suicidality (Reasons for Living Inventory, Beck Hopelessness Scale, and Suicide Score Scale), depression (Zung Depression Scale), problem drinking (Michigan Alcohol Screening Test), and drug use (Drug Abuse Screening Test). Respondents were classified as problem drug users and drinkers (14.7% and 24.1%, respectively), and men were overrepresented in both groups. Alcohol and drugs misuse was significantly associated with reasons for living, hopelessness, suicidal attitudes, and depression. A multiple regression analysis resulted in four models predictive of suicide risk and four predictors were extracted—the Drug Abuse Screening Test, the Zung Depression Scale, and Loss of Motivation as positive predictors of suicide risk with Survival and Coping Beliefs as negative predictors. KEYWORDS. Problem drinking, drug abuse, suicide risk, hopelessness, reasons for living, depression

INTRODUCTION Suicide and drug abuse are two major public health problems. It is estimated that between 10% and 18% of adults across diverse regions of the world report lifetime suicidal ideation and 3% to 5% have made at least one suicide attempt at some point in their life.1−3 Recreational drugs use has obtained a “firm footing” in the society,4 a phenomenon that is the result of the normalization of drugs in Europe and in other western countries. Five major dimensions explain such

normalization: access and availability of drugs, drug trying rates, prevalent usage, the attitudes of adolescents and young adults toward recreational drug use, and the degree of cultural accommodation of illegal drug use.5 European adolescents are exposed to drugs. In a longitudinal study in Northern England, Aldridge et al.6 reported an 80% prevalence of adolescents being offered drugs by the age of 16. The Report on attitudes and opinions about drugs of young people in the European Union7 estimated that approximately 64% of European

Marco Innamorati is affiliated with the Universit`a Europea di Roma, Rome, Italy. Maurizio Pompili is affiliated with the Department of Psychiatry, Sant’Andrea Hospital, Rome, University of Rome “La Sapienza,” Italy, and the McLean Hospital, Belmont, Massachusetts. David Lester is affiliated with The Richard Stockton College of New Jersey, Pomona, New Jersey. Roberto Tatarelli and Paolo Girardi are affiliated with the Department of Psychiatry, Sant’Andrea Hospital, Rome, University of Rome “La Sapienza,” Italy. Address correspondence to: Marco Innamorati, PsyD, Via Calcinaia 13, 00139 Roma, Italy (E-mail: [email protected]). Journal of Addictive Diseases, Vol. 27(4) 2008 Available online at http://www.haworthpress.com
C 2008 by The Haworth Press. All rights reserved. doi: 10.1080/10550880802324796 51

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youths between the ages of 15 and 24 years have been exposed to drug use (e.g., “I know people who use cannabis”) and 26% and 46%, respectively, have been offered cannabis and other drugs. The exposure to drugs is associated with a high use of legal and illicit recreational drugs. In the previous study,7 28.9% of the youths 15 to 24 years old reported having tried cannabis at least once in their lifetime (17.2% in Italy) and 8.8% reported having tried other illicit drugs (2.7% in Italy). Cannabis can act as a gateway drug, encouraging other forms of illicit drug use.8 Europe is also the continent with the highest consumption of alcohol among adolescents. The “Health Behaviour in School-aged Children” project,9 a cooperative research project organized by the World Health Organization, analysing health-related attitudes and behavior in adolescents 11 to 15 years old, estimated that alcohol consumption was customary for most adolescents. The rates of reported drunkenness increased steeply across age groups and those who report having been drunk two times or more comprised up to 67% for 15 year olds. In young adults, recreational drug use is an increasingly popular activity, even more alarmingly than in younger ages. Gledhill-Hoyt et al.10 analyzed drug use in more than 40,000 students at approximately 100 U.S. colleges between 1993 and 1999 and reported an increasing trend in lifetime prevalence and yearly prevalence of cannabis and other illicit drug use from the first year of their study. The 2000 British Crime Survey reported that 27% of adolescents 16 to 19 years old and 30% of young adults 20 to 24 years old admitted having used illicit drugs in the past year.11 O’Malley and Johnston12 summarized data from national survey studies about the prevalence and trends in alcohol and other drug use among American college students. The authors estimated that between 38% and 44% of university students had engaged in “heavy drinking” at least once in the past 2 weeks (i.e., they drank five or more drinks on a single occasion). Research indicates some differences in the patterns of recreational drug use among young adults by profession (students/nonstudents), sex, and ethnicity.12−13 O’Malley and Johnston12

found differences in the prevalence and patterns of drug use between college students and young adults who do not attend college by reviewing national survey studies. The former group had a higher prevalence rate of alcohol use and party and weekend drinking, but lower rates for the use of illicit drugs. Sex differences have also been reported. For example, Innamorati et al. (unpublished material) reported sex differences in most rates by evaluating legal and illicit drug use in more than 200 university students, which is consistent with the results of O’Malley and Johnston,12 who found that alcohol use rates are higher for male college students than for female college students. Drug and alcohol use in adolescents and young adults may be associated with increased rates of psychological and behavioral problems,14−17 health problems,18 and self-harm and suicide risk.19−21 Harris and Barraclough22 concluded that alcohol dependence is a risk factor for suicide, and Inskip et al.23 estimated a lifetime risk of suicide of 7% for alcohol dependence, which is higher than the lifetime risk for affective disorders (estimated at 6%). Suicide is one of the leading causes of death among young adults, and recreational drug use may be associated with a higher suicide risk. Despite intensive efforts, effective prediction of suicidal behavior has remained elusive, suggesting that our understanding of the interplay of predisposing and precipitating factors remains incomplete. Most studies on suicide evaluate short-term risk factors of suicidal behavior, such as suicidal ideation and recent suicide attempts, the major precursors and the most powerful predictors of attempted and completed suicide.24−26 However, single, short-term risk factors are not sufficient for predicting suicide. Studies should address the prediction of suicidal behavior in the long-term and the need to identify a sufficient number of predictors sensitive enough to identify suicidality but few enough to avoid interaction effects that could result in utility problems.27,28 The aims of the current study were to evaluate recreational drug use patterns among a sample of Italian young adults and to explore the role of substance misuse on suicidality. Suicidality was measured by means of three different variables:

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hopelessness, current and past suicidal ideation and behavior, and reasons for living. Reasons for living are positive, life-oriented, cognitive attributes that may keep a person from considering or attempting suicide. Several studies with adults and college students have suggested that non-suicidal people endorse significantly more reasons for living than suicidal persons.29,30 The final objective was to evaluate the role of some anamnestic and clinical variables in predicting suicide risk.

METHODS Participants Participants were 340 young adults (142 men and 198 women) between 19 and 30 years old (Table 1). Participants, who were contacted during their daily activities, agreed to take part voluntarily in the study. Most of the participants were university students (67.1%). At the time of the study, all of the participants lived in Rome. Subjects were asked to complete the questionnaires anonymously. The study was approved by the institutional review board.

Instruments All respondents completed six measures: the Reasons for Living Inventory (RFL),31 the Michigan Alcohol Screening Test (MAST),32 the Drug Abuse Screening Test (DAST),33 the Beck Hopelessness Scale (BHS),34 the Zung TABLE 1. Anamnestic Variables Variable Sex Male Female Age, y (SD) Young adults 19 to 24 years old Young adults 25 to 30 years old Profession Employed University students Living Alone Relatives unemployed Father Mother

N (%)

41.8% 58.2% 22.58 (3.44) 76.2% 23.8% 32.9% 67.1% 3.8% 14.7% 39.7%

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Self-Rating Depression Scale (SDS),35 and the Suicide Score Scale (SSS), a questionnaire developed by the authors. The SSS is a 12-item (yes/no) questionnaire developed to obtain information about previous suicidal ideation, planning, or attempts, both in the previous year and lifetime. Patients were asked the following questions about the previous year: Have you felt tired of living and thought that life was not worth living? Have you thought that, for yourself, your family and your friends, it would be better if you were dead? Have you thought of harming yourself but not to the point of dying? Have you thought of ending your life? Have you thought of a method for committing suicide? Have you attempted suicide? Referring to lifetime (excluding the past 12 months), patients were asked: Have you ever felt tired of living and thought that life was not worth living? Have you ever thought that for yourself, your family and your friends, it would be better if you were dead? Have you ever thought of harming yourself but not to the point of dying? Have you ever thought of ending your life? Have you ever thought of a method for committing suicide? Have you ever attempted suicide? The SSS had a good Cronbach alpha reliability for 851 undergraduate students (Part 1 = .75; Part 2 = .80) and an inter-item mean correlation of .35 (Part 1 = .31; Part 2 = .41). The SSS score correlated moderately with scores on the Reasons for Living Inventory (r = −0.32; P < .001) the Zung Depression Scale (r = −0.41; P < .001) and the Aggression Questionnaire (r = −0.53; P < .001), indicating reasonable construct validity. The RFL is a set of 48 statements developed from a survey of college students, workers, and senior citizens, who were asked about their reasons for living and their reasons for not committing suicide when the thought occurred to them. The RFL is based on a cognitive behavioral view of suicidal behavior, which hypothesizes that cognitive patterns, whether beliefs, expectations, or capabilities, are significant mediators of suicidal behaviors.31 A compelling advantage of the RFL is its positive wording. According to Range and Knott,36 simply completing it may have a suicide prevention impact.

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Respondents answer using a 6-point Likert scale, ranging from (1) extremely unimportant to (6) extremely important. Factor analysis has yielded six distinct subscales: Survival and Coping Beliefs, Responsibility to Family, Child Concerns, Fear of Suicide, Fear of Social Disapproval, and Moral Objections.31,37 The number of items for each scale range from 3 to 24. Subscale and total scores were divided by the number of items, and so scores ranged from 1 to 6. Enough evidence exists supporting the validity of the RFL.31,37 Innamorati et al.38 evaluated the psychometric properties of an Italian adaptation of the Reasons for Living Inventory and documented the adequacy of the factorial structure previously reported and internal consistencies ranging from .93 to .73. The BHS is a 20-item scale for measuring the cognitive component of the syndrome of depression. This scale assesses three major aspects of hopelessness: feelings about the future, loss of motivation, and expectations. Research consistently supports a positive relationship between BHS scores and measures of depression, suicidal intent, and current suicidal ideation. Beck et al.39 performed a prospective study of 1,958 outpatients and found that BHS scores were significantly related to eventual completed suicide. A cutoff score of 9 or above identified 16 (94%) of the 17 patients who eventually committed suicide. In a sample of 332 Italian undergraduate students, the BHS had a moderate association with scores on the Reasons for Living Scale (RFL: r = −0.37; P < .001) and the Zung Depression Scale (r = 0.50; P < .001) and sufficient reliability (Cronbach’s alpha = 0.74). The SDS is a 20-item self-report questionnaire with positive and negative items covering affective, psychological, and somatic symptoms associated with depression. Respondents rate each item as it applies to the past week using a 4-point Likert-type scale (1 = none or a little of the time, 4 = most or all the time). A total raw-score, obtained by summing the scores for the items, ranges from 20 to 80. The SDS is valid for identifying patients with depression and dysthymia and discriminating depressed patients from non depressed patients.40−42 Innamorati et al.43 reported sufficient reliability (Cronbach α > 0.70) and a strong correlation with the

convergent measures of depression (mean r = 0.68). Problem drinking and alcohol-related problems were evaluated by the MAST. The MAST consists of 25 true-false items designed to provide a rapid and effective screening for lifetime alcohol-related problems and alcoholism. Benussi et al.44 and Garzotto et al.45 evaluated an Italian adaptation of the MAST and found that a cut-off score of 5 or 6 was the best for discriminating between alcoholism and normalmoderate drinkers. With a cutoff score of 5, sensitivity was 100% and specificity 93.7%; with a cutoff of 6, these values were 98.2% and 95.8%, respectively. The DAST is a 28 item self-report scale designed to provide a brief instrument for clinical screening and treatment evaluation research. Each item has a “yes” or “no” format. Items combine in a total DAST score to yield a quantitative index of problems related to drug misuse. A factor analysis indicated that the DAST is essentially an unidimensional measure. A comprehensive review of the psychometric properties of the measure revealed that the DAST has moderate to high levels of reliability, validity, sensitivity, and specificity, and the DAST yields satisfactory measures of reliability and validity for use as a clinical or research tools.46 The DAST had 85% overall accuracy in classifying patients according to DSM-III abuse or dependence diagnosis, with the 5/6 cut-off being the optimum threshold score.47

RESULTS Respondents reported average scores on the MAST and DAST measures (Table 2), confirming the non-clinical nature of our sample. A 2 (men/women) × 2 (students/employed) × 2 (age groups) multivariate analysis of variance (MANOVA) was performed to investigate the role of sex, occupation, and age on drug and alcohol use patterns (Table 2). The analysis indicated a significant effect of sex and an interaction between age and occupation, with men and the youngest workers reporting higher mean scores on the DAST and the MAST. Thus, both men and young adults between 19 and 24 years of

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TABLE 2. Substances Use and Effects Effect Sex Profession Age Sex∗ Profession Sex∗ Age Profession∗ Age Sex∗ Profession∗ Age Variables DAST

MAST

DAST

Wilks’ λ

F (2;331)

Sig.

Effect size (η2p )

0.96 1.00 0.99 0.99 1.00 0.98 1.00

7.80 0.85 2.54 2.16 0.57 3.98 0.69

0.000 0.43 0.08 0.12 0.57 0.02 0.50

0.05

19- to 24 years old 25 to −30 years old 19 to −24 years old 25 to −30 years old 19 to −24 years old 25 to −30 years old 19 to −24 years old 25 to −30 years old

Mean 2.54 3.46 1.87 4.02 4.65 3.57 3.78 2.00 2.27 3.21 5.31 2.40 4.08 4.46

SD 3.84 4.05 2.84 4.45 4.55 4.33 3.87 3.10 3.38 3.78 4.11 4.34 4.36 5.23

Total Men Women Total Men Women Workers Students

MAST

Workers Students

0.02 F 15.64

Sig. 0.000

Effect Size (η2p ) 0.05

4.69

0.03

0.01

6.54

0.01

0.02

5.85

0.02

0.02

DAST = Drug Abuse Screening Test; MAST = Michigan Alcohol Screening Test.

age who were not attending the university were more likely to report drugs related problems. Using the recommended DAST and MAST cut-off score of 6, 14.7% and 24.1% of respondents were classified as at risk drug users and problem drinkers, respectively. Men were overrepresented in the groups of problem drinkers and drug abusers (% drug abusers: Men/Women: 21.8%/9.6%; χ 2 = 9.87; P = .002;  = .17.% problem drinkers: Men/Women: 32.4%/18.2%; χ 2 = 9.13; P = .003;  = .16). Univariate statistics for the SDS and suicidality measures are listed in Table 3. Respondents reported moderate SSS and BHS scores. Only 1.8% reported suicide attempts in the past year, but the prevalence for people with problem drinking and drug use were 3.8% and 4.1%, respectively (for lifetime suicide attempts: overall 1.5%; problem drinkers/drug users: 6.3%/6.1%), and 12.1% of individuals reported a BHS score of 9 or above, indicating a high risk of suicide. Partial correlations controlling for sex, age and profession were carried out between the measures (Table 4). The MAST and the DAST significantly correlated with most of the sui-

cidality dimensions and with SDS scores, although most of the correlations were only in the .20 to .30 range. Thus, alcohol and drug misuse TABLE 3. Descriptive Statistics for Suicidality and Depression Measures

Mean

SD

SSS SSS Part 1 SSS Part 2 RFL SCB RF CC FS FSD MO BHS Feelings about the Future Loss of Motivation Expectations SDS

1.27 0.57 0.70 4.00 4.83 3.62 4.57 2.81 2.16 2.75 4.72 0.76 1.54 2.01 36.92

2.11 1.08 1.20 0.69 0.79 1.11 1.47 1.04 1.11 1.39 2.99 1.01 1.15 1.30 7.68

SSS = Suicide Score Scale; RFL = Reasons for Living Inventory; SCB = Survival and Coping Beliefs; RF = Responsibility to Family; CC = Child Concerns; FS = Fear of Suicide; FSD = Fear of Social Disapproval; MO = Moral Objections; BHS = Beck Hopelessness Scale; SDS = Zung Self-Rating Depression Scale.

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TABLE 4. Partial Correlation (Controlling for Sex, Age, and Profession) Measures

BHS

RFL SCB RF CC FS FSD MO BHS Feelings about the Future Loss of Motivation Expectations SSS SSS Part 1 SSS Part 2 SDS

−.37∗∗ −.44∗∗ −.15∗∗ −.18∗∗ −.02 −.03 −.25∗∗ .75∗∗

Feelings −.41∗∗ −.41∗∗ −.24∗∗ −.22∗∗ −.12∗ −.08 −.32∗∗ .75∗∗

.79∗∗

.49∗∗

.80∗∗ .39∗∗ .38∗∗ .34∗∗ .51∗∗

.41∗∗ .35∗∗ .35∗∗ .30∗∗ .38∗∗

Loss

Expectations

−.21∗∗ −.30∗∗ −.06 −.08 −.01 .08 −.10 .79∗∗ .49∗∗

.45∗∗ .32∗∗ .33∗∗ .27∗∗ .33∗∗

SSS

SSS Part1 SSS Part2

SDS

DAST

MAST

−.26∗∗ −.33∗∗ −.05 −.13∗ .04 −.09 −.21∗∗ .80∗∗ .41∗∗

−.30∗∗ −.42∗∗ −.13∗ −.09 .00 .10 −.14∗∗ .39∗∗ .35∗∗

−.27∗∗ −.39∗∗ −.10 −.07 .00 .12∗ −.14∗∗ .38∗∗ .35∗∗

−.27∗∗ −.38∗∗ −.14∗∗ −.09 .01 .06 −.13∗ .34∗∗ .30∗∗

−.30∗∗ −.41∗∗ −.13∗ −.09 .05 .08 −.20∗∗ .51∗∗ .38∗∗

−.20∗∗ −.19∗∗ −.10 −.14∗∗ −.11∗ .00 −.16∗∗ .21∗∗ .24∗∗

−.18∗∗ −.18∗∗ −.14∗∗ −.07 −.08 −.02 −.11 .23∗∗ .20∗∗

.45∗∗

.32∗∗

.33∗∗

.27∗∗

.33∗∗

.19∗∗

.18∗∗

.26∗∗

.25∗∗ .91∗∗

.24∗∗ .93∗∗ .71∗∗

.43∗∗ .40∗∗ .40∗∗ .35∗∗

.12∗ .34∗∗ .32∗∗ .31∗∗ .24∗∗

.16∗∗ .30∗∗ .28∗∗ .28∗∗ .26∗∗

.26∗∗ .25∗∗ .24∗∗ .43∗∗

.91∗∗ .93∗∗ .40∗∗

.71∗∗ .40∗∗

.35∗∗

∗∗

Correlation is significant at the .01 level (2-tailed);). Correlation is significant at the .05 level (2-tailed). SSS = Suicide Score Scale; RFL = Reasons for Living Inventory; SCB = Survival and Coping Beliefs; RF = Responsibility to Family; CC = Child Concerns; FS = Fear of Suicide; FSD = Fear of Social Disapproval; MO = Moral Objections; BHS = Beck Hopelessness Scale; SDS = Zung Self-Rating Depression Scale; DAST = Drug Abuse Screening Test; MAST = Michigan Alcohol Screening Test.

∗

TABLE 5. Multiple Regression (Stepwise) Criterion: SSS Step 1 2 3

4

Model 1 2 3 4

Predictors SCB SCB SDS SCB SDS DAST SCB SDS DAST Loss of Motivation

Beta Std −.43 −.31 .29 −.28 .26 .23 −.25 .23 .21 .13

t −8.41 −5.79 5.48 −5.25 4.90 4.62 −4.76 4.25 4.29 2.55

Sig.

Multicollinearity Tolerance

.000 .000 .000 .000 .000 .000 .000 .000 .000 .01

1.000 .833 .833 .815 .814 .930 .790 .774 .915 .840

Adjusted R2

F

Sig.

R2 Change

F Change

Sig. F Change

0.18 0.25 0.30 0.31

70.77 53.67 45.24 36.16

0.000 0.000 0.000 0.000

0.19 0.07 0.05 0.01

70.77 29.94 21.31 6.48

0.000 0.000 0.000 0.01

was related to decreased reasons for living and increased hopelessness, suicidal behavior, and depression. To identify the best predictors of the SSS total score as a measure of suicidal risk, we inserted several demographic variables (age, living alone, sex, occupation, and relatives unemployment), and clinical variables (RFL

dimensions, BHS dimensions, SDS, DAST, and MAST) as predictors in a stepwise multiple regression analysis. The analysis resulted in four models predictive of suicide risk, explaining from 18% to 31% of the SSS variance (Table 5). At step 1, the model contained only one negative predictor/protective factor—Survival and Coping Beliefs. At step 2, the model contained two

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predictors—the Survival and Coping Beliefs and the SDS as predictors of suicide risk. At step 3, the model contained another predictor of suicide risk—the DAST. Finally, the last model contained four predictors—the DAST, the SDS, and Loss of Motivation as positive predictors of suicide risk and Survival and Coping Beliefs as a negative predictor or protective factor.

DISCUSSION The current results support research reporting a “firm footing” in the society for recreational drug use.4 The results are consistent with those of Ramsay et al.11 and O’Malley and Johnston.12 Although our prevalence rates are lower, the difference may be a result of the way in which the variables measured. Ramsay et al.11 measured the prevalence rates of illicit drug use, and O’Malley and Johnston12 reported data on the prevalence rates of “heavy drinking,” whereas our study focused on problem drinking and drug use (i.e., the use of alcohol and drugs associated with adverse consequences). The results confirm differences reported in the prevalence patterns of recreational drug use among young adults.12,13 Both sex and the interaction between age and profession had significant effects on the substances use of Italian young adults, with men and the youngest workers reporting more problem drinking and drug use. This is consistent with the report from Poelen et al.,48 who studied alcohol misuse in young adults in the Netherlands. They reported two main findings: alcohol use increased with age until the age of 25, after which it decreased; and men exceeded women on most aspects of alcohol use, with exception of the youngest age group and lifetime alcohol use. When controlling for anamnestic variables, problem drinking and drug use were associated with depression, suicide risk, and hopelessness. Our results are consistent with studies reporting an increase in self-harm and suicide risk in individuals at risk for substances abuse,19−21 and reinforce the evidence for the potential adverse effects, both direct and indirect, associated with recreational drug use in young adults.

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We identified four predictors of suicide risk in young adults: problem drug use, depression, and loss of motivation (as measured by the BHS) as positive predictors of suicide risk and survival and coping beliefs (on the RFL) as a protective factor. As reported by Murphy et al.49 and Canapary et al.,50 not one of these risk factors will signal the highest risk for suicide. Clinicians have to be aware that, only when considered in combination, suicidal risk factors can be cumulatively and interactively useful and increase the predictive validity of their assessment. The results also support the need for comprehensive programs directed to people at risk for problem drug use and drinking. The programs should be specific and directed to adolescents at risk and younger adults. Pitkanen51 reported that future problem drinkers, compared with other drinking style groups, have lower states of psychological well-being during their adolescence, which become more pronounced during the transition to young adulthood. Thus, only early intervention, especially if structured with long-term repeated booster programs, will be effective and prevent late psychological and behavioral problems.52 When selecting people at risk for problem drinking and drug use for preventive interventions, the presence of severe psychiatric symptoms and suicide risk must be assessed to screen for individuals needing more structured interventions. The current study did have some limitations. First, the assessment of clinical variables was conducted using only self-report measures and the respondents may have not been completely honest.53 Second, the sample size was limited and the respondents were not evaluated for important covariates, such as psychiatric diagnosis. However, both “indirect” (the RFL and the BHS) and direct (the SSS) measures of suicidality were used, and the results were consistent with previous research. Future research is planned using larger samples and alternative methodologies to explore the reliability of the present findings. REFERENCES 1. Kessler RC, Borges G, Walters EE. Prevalence and risk factors for lifetime suicide attempts in the National Comorbidity Survey. Arch Gen Psychiatry. 1999;56:617–26.

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