1. Substance and alcohol use, internet addiction and mental stress among university students. A study in Algeria, France and Hungary J Ladner 1,2, A Lukacs 3, N Boussouf 4, MP Tavolacci 1,2, B Varga 5, S Grigioni 1,2, P Déchelotte 1,2 1 Rouen University Hospital, Rouen (France) 2 INSERM Unit 1073, ADEN, Rouen University Hospital, Rouen 3 Faculty of Health Care, Miskolc (Hungary) 4 Batna University Hospital, Batna (Algeria) 5 Faculty of Economics, Miskolc joel.ladner@univ-rouen.fr

2. Alcohol, tobacco and cannabis consumption are well recognized as important public health topics in university students Prevalence of Internet addiction, mental stress and eating and disorders are regularly growing Background

3. Objectives To study the prevalence and identify risk comportments of alcohol, tobacco and cannabis use, Internet addiction and eating disorders risks, perceived mental stress in students in higher education in 3 countries (Algeria, France and Hungary)

4. Methods (1) Batna, Algeria Miskolc, HungaryRouen, France

5. Anonymous auto-questionnaires Papers questionnaires in Batna and Miskolc Paper and online questionnaires in Rouen (www.tasanteenunclic.org) Methods (2) Questionnaire

6. www.tasanteenunclic.org

7. Age, gender, to get a job in parallel, study grant holder) Alcohol consumption (binge drinking) Smoking habits Cannabis experimentation Psychotropic drugs consumption (anxiolytics, antidepressant drugs) SCOFF questionnaire: screening test of eating disorders risk Methods (3) Data collection

8. Assess global perception of stress 10 questions, 5-Lickert scale PPS score ranges from 0 to 40 Methods (3) The Perceived Stress Scale (PPS) of Cohen

9. 9 questions, scored 0 or 1 Measure the risk to become Net addicted Three levels of Internet addiction –From 0 to 3: very little tendancy to become Net addicted (low risk) –From 4 to 6: a risk to become Net addicted (risk) –From 7 to 9: a high risk to become Net addicted (high risk) Methods (4) The Internet Stress Scale (Orman test)

10. Results (1) A total of 2,102 students included SD: standard deviation

11. Results (2) Smoking prevalence and cannabis experimentation SD: standard deviation; R=range

12. Results (3) Alcohol consumption in men and women (%) Batna (n=345) Miskolc (n=275) Rouen (n=1,482) MWpMWpMWp Alcohol consumption >2 x/week 00-27.63.80.02532.332.90.93 Never BG93.61000.4515.739.3<10 -4 12.634.0<10 -4 At least 1 BG in the last month 6.400.7838.28.2<10 -4 41.312.6<10 -4 At least >1 drunkeness in the last 12 months 2.700.8982.356.70.0182.937.80.001 BG: binge drinking

13. Results (4) Risk of eating disorders

14. Results (5) Perceived mental stress (mean value)

15. Results (6) Psychotropic drugs consumption (%) Batna (n=345) Miskolc (n=275) Rouen (n=1,482) MWpMWpMWp Anxiolytic dugs 2.010.2<10 -4 2.94.20.461.35.70.13 Antidepressant drugs 1.13.90.0103.40.501.31.40.98

16. Results (7) Prevalence of risk of Internet addiction (%) Batna (n=345) Miskolc (n=275) Rouen (n=1,482) MWpMWpMWp Low risk 48.752.5 73.581.3 62.571.2 Medium risk 26.630.80.08 11.810.00.07 31.025.50,001 High risk24.716.714.78.76.53.3

17. Main findings –Higher prevalence of smoking in French and Hungarian students –As well as cannabis consumption in French students (around 50%) –High level of alcohol consumption in French men and women students –Difference of alcohol consumption between men and women in Hungarian students –Very high level of stress in Hungarian students –Very high risk of cyberaddiction in Algerian students; in women, the risk remains significant in the 3 populations Conclusion (1)

18. New problematic and comportments Difference of substances use et risk comportments between men and women These findings stress the need to develop investigations on these topics in students population, to have a better understanding There is also an urgent need for public health practitioners and clinicians working in university campuses New research areas needed, especially the impact of these risk behaviours on the professional career and future life Conclusion (2)

21. Results (7) Risks of Internet addiction

22. Results (8) Factors associated to Internet addiction (logistic regression) Adjusted on sex, marital status, binge drinking, anxiolytics drug consumption, sleep quality