研究目的
過去研究已指出憂鬱情緒、對毒品使用效果的預期、拒絕使用毒品的效能、同儕影響、毒品可及性和進出不良場所的頻率等對大學生毒品使用扮演著重要的影響性，並且，過去態度-社會影響-效能模式(Attitude-Social influence-Efficacy model; ASE model)和自我醫療假設模式(Self-medication hypothesis; SMH)被提出說明風險因子之間運作影響毒品使用，如: 態度-社會影響-效能模式(Attitude-Social influence-Efficacy model; ASE model)認為同儕影響和拒用自我效能會直接或間接透過使用意圖影響毒品使用，或正向預期會透過拒用自我效能和同儕影響而預測毒品使用行為。然而，自我醫療假設模式(Self-medication hypothesis; SMH)認為毒品使用和憂鬱之間具有直接的關係，憂鬱情緒會驅使個體直接選擇以使用毒品達到改善負面情緒的目的。目前為止，尚未有研究試圖整合上述兩者模式以解釋憂鬱、正向預期、拒用自我效能、同儕影響和可及性與使用意圖對毒品使用之影響。
為了能清楚地呈現憂鬱、正向預期、自我效能、同儕影響和毒品可及性和毒品使用之間的關係，本研究試圖提出三種假設性模式，分別為(1)主要效果模式:憂鬱、拒用效能、社會影響和意圖可以直接預測毒品使用的行為，正向預期會透過拒用效能或社會影響預測毒品使用，以及拒用效能和社會影響可以透過意圖預測毒品使用;(2)中介效果模式:憂鬱將透過正向預期或社會影響預測毒品使用的行為，拒用效能、社會影響和意圖可以直接預測毒品使用的行為，正向預期會透過拒用效能或社會影響預測毒品使用，以及拒用效能和社會影響可以透過意圖預測毒品使用;(3)調節模式:相較於低憂鬱組，高憂鬱組之調節模式適配度優於低憂鬱組。
因此，本研究目的一為比較目前使用組、過去曾經使用，但目前停止使用組和未曾使用組之憂鬱、正向預期、拒用自我效能、使用意圖、同儕影響、可及性和進出不良場所之頻率等因素對大學生毒品使用的影響，以驗證各自對毒品使用之影響性。目的二在於試圖建構憂鬱、正向預期、拒用自我效能、使用意圖、同儕影響、可及性和進出不良場所之頻率和毒品使用之模式，透過模式的驗證和競爭，呈現從憂鬱情緒到毒品使用之間，正向預期、拒用自我效能、同儕影響和毒品可及性等因素所扮演的角色和歷程。
研究方法
研究設計:本研究資料取自於2005年衛生福利部委託研究計劃-全國大專校院學生藥物使用盛行率與其相關心理社會因素之追蹤研究(Ⅱ)，計畫主持人為柯慧貞教授。本研究採取兩階段的研究設計已完成上述之研究目的。在第一階段裡，為了區辨不同的心理社會因子在毒品使用所扮演的角色，本研究先以橫斷法進行全國大學生的抽樣調查，然後在性別配對下以個案對照法進行心理社會風險因子之檢驗。在第二階段裡，以橫斷法所收集的全國大學生抽樣資料進行假設性心理社會模式之驗證。
研究對象:第一階段裡，在2005年針對全國大專院校進行分層叢集取樣。根據男女性別、四年制與二年制、及北、中、南區等分層，再以系所為單位(叢集)進行抽樣。總共有4,885名研究參與者進行研究，在扣除未參與研究及亂填答之問卷後，有2,758份有效問卷進行研究。研究者再依據參與者所填寫之毒品使用行為，挑選出61位曾經使用或目前仍在使用之參與者作為個案組。依據性別比率和個案對照組1:10的比例隨機抽出610份作為對照組，在扣除未完整填答之問卷後，總計有465份問卷作為對照組資料。個案組再以其毒品使用結果，若其過去曾經使用，但目前已無使用者則歸類至曾經使用，但目前停止使用組(Ex-User)，人數為37人;若其過去曾經使用，且最近這一個月以上仍有使用者則歸類至目前使用組(Current-User)，人數為24人。在第二階段驗證假設性大學生毒品使用之心理社會模式，以第一階段裡所取樣之全國大學生2,758份有效問卷作為模式驗證之資料來源。
研究工具:個人基本資料、毒品使用頻率、憂鬱量表、拒用毒品效能、正向毒品使用預期、負向毒品使用預期、同儕使用毒品程度、同儕對毒品使用的態度、毒品可及性和進出不良場所的頻率等問卷。
研究程序:由受過訓練之研究人員，至所抽樣的大學院校之科系，以班級為單位進行團體施測。施測流程和內容已詳細說明並強調匿名性，填寫研究參與同意書後，開始填寫相關量表，量表回收和建檔數月後，參與者會收到回饋報告書。
統計分析:在第一階段為了辨識心理社會風險因子對毒品使用之角色，本研究以描述統計、多因子變異數分析和Scheff事後比較進行驗證。在第二階段裡以結構方程式作為驗證和比較模式的統計工具。
研究結果
在驗證心理社會風險因子對毒品的影響程度方面，本研究結果顯示目前使用組和曾經使用，但目前停止使用組在憂鬱得分、毒品可及性、同儕對毒品使用的態度和同儕使用毒品的程度是高於對照組。目前使用組和曾經使用，但目前停止使用組在拒用自我效能的得分是低於對照組。最後，曾經使用，但目前停止使用組在進出不良場所的頻率、同儕使用毒品程度和使用意圖方面則低於目前使用組。
在心理社會模式驗證方面，本研究發現在主要效果模式方面，憂鬱、拒用效能和意圖對於毒品使用均能夠對毒品使用有直接的影響，但正向預期卻無法產生直接的效果。在中介模式的驗證方面，則發現憂鬱不僅可以透過正向預期影響毒品使用外，也可以透過社會影響預測毒品的使用。在調節模式裡顯示高憂鬱組ASE模式之適配度優於低憂鬱組ASE模式。在主要效果模式、中介模式和調節模式之模式競爭方面，調節模式具有較佳的競爭模式適配值。
結論
本研究結果顯示憂鬱情緒、拒絕使用毒品的信心和毒品使用的意圖傾向可能為毒品使用的潛在因子，而同儕使用毒品、毒品可及性和進出不良場所頻率則傾向可能為毒品使用的促發因子，建議未來能以縱貫研究方法驗證其因果關係。其次，模式驗證方面，高憂鬱之大學生更容易受毒品使用的正向預期、拒用自我效能、同儕影響和使用意圖之影響下進而開始使用毒品，因此未來在發展毒品使用者之介入模式時，更需要考慮憂鬱情緒之嚴重度。憂鬱、毒品使用的態度和效能和環境影響之間的關聯性仍需後續縱貫研究或實驗加以驗證。

Background:
Literature illustrated the importance of depression, positive outcome expectancy, refusal self-efficacy, and the effect of peer and availability on illicit drug use. The Attitude-Social influence-Efficacy model (ASE model) assumed that refusal self-efficacy and social influence have direct or indirect impacts on illicit drug use through intention to use; positive outcome expectancies would have an effect on illicit drug use through refusal self-efficacy and social influence; intention has a direct impact on illicit drug use. According to the self-medication hypothesis (SMH), people begin to use illicit drugs in order to alleviate their experience of suffering. However, little study has integrated the ASE model with the SMH model to illustrate a comprehensive psychosocial model of illicit drug use.
In order to clarify the relationships among depression, positive outcome expectancy, refusal self-efficacy, the effect of peer, availability and illicit drug use, the present study proposed three hypothesized models as follow: (1) The main effect model: Depression, refusal self-efficacy, social influence and intention would have direct impacts on illicit drug use. Then, positive outcome expectancy would have indirect effects on illicit drug use through refusal self-efficacy and social influence. Lastly, refusal self-efficacy and social influence would have indirect effects on illicit drug use by intention; (2) The mediation model: Depression would have indirect impacts on illicit drug use through positive outcome expectancy and social influence. Refusal self-efficacy, social influence and intention would have direct impacts on illicit drug use. Then, positive outcome expectancy would have indirect effects on illicit drug use through refusal self-efficacy and social influence. Lastly, refusal self-efficacy and social influence would have indirect effects on illicit drug use through intention; (3) The moderation model: Compared to the lower depression group, the moderated model for the higher depression group would show better model-fit indices.
Therefore, two purposes were proposed in the present study. One was to examine the effects of depression, positive outcome expectancy, refusal self-efficacy, peer’s use, availability and illicit drug through a three-group comparison of ex-users, current-users and drug-naïve groups. Another purpose was to propose and examine the psychosocial mode for illicit drug use. Through the evaluation of competing models, including the main effect model, mediation model and moderated model, a proper psychosocial model for depression and illicit drug use was found.
Methods:
Design: The participants were recruited from the “Longitudinal Study on the Prevalence and Psychosocial Risk Factors for Drug Use among College Students (II)” that was funded by the Department of Health in 2005. The project of Principal investigator was Dr. Huei-Chen Ko. (DOH94-NNB-1012).
Two stages were conducted to achieve the two purposes mentioned above. Stage 1 was conducted to differentiate the roles of psychosocial risks for illicit drug use. A nation-wide cross-sectional study was conducted on college students to examine the risk factors of illicit drug use. Furthermore, a case-control study was conducted to examine the roles of psychosocial risks for illicit drug use. In stage 2, a cross-sectional study investigated the hypothesized model of illicit drug use.
Sampling: In stage 1, a national survey was conducted to investigate the risk factors for illicit drug use among college students. 4,588 participants were invited to our study. 2758 participants were enrolled in this study after deleting invalid questionnaires. 61 cases of users and 465 gender-matched controls were sampled to examine the risk factors of illicit drug use. Additionally, the case group was classified into ex-users who had used any kind of illicit drug over the previous year (N=37); and current-users who had ever used any kind of illicit drug in their lifetime (N=24). In stage 2, 2758 questionnaires from the participant recruited from stage 1 were analyzed to examine the hypothesized model for illicit drug use.
Measurements: These participants were assessed by their frequency of illicit drug use, depression, intention to use, positive and negative outcome expectancies, refusal self-efficacy, the effect of peer use, peer’s attitude toward illicit drug use, availability for illicit drug and frequency of visiting high risk places.
Statistics: In stage 1, multiple way analysis of variance (MANOVA) was used to examine the continuous variables among the three groups. Scheffe’s post-hoc comparison test examined the unique effects of risk factors among the three groups. In stage 2, structure equation modeling was conducted to examine the model-fit indices of the main effect, mediation and Dyad models for illicit drug use.
Results:
In stage 1, psychosocial risks showed an increase in depression, accessibility to drug use, peer attitude on drug use, peer drug use, and lower negative outcome expectancies and refusal self-efficacy among current-users and ex-users compared to drug-naïve individuals. Additionally, ex-users reported entering high-risk places less frequently, have lower perceived peer drug use, and intention to use than current-users.
In stage 2, model examination confirmed the main effect of depression, refusal self-efficacy, intention and social influence on illicit drug use except for positive outcome expectancy. In the mediation model, depression indirectly predicted illicit drug use via outcome expectancy and social influence. Lastly, the moderation model showed significant effects of refusal self-efficacy, intention and social influence on illicit drug use when higher levels of depression was experienced. Furthermore, intention did not significantly predict illicit drug use among participants who did not have depression.
Discussion and Conclusions
Our results revealed that depressive mood, refusal self-efficacy and intention were potential factors for illicit drug use. Furthermore, peer use illicit drugs and frequency of visiting high-risk places were provoking factors for illicit drug use. Longitudinal studies should be conducted to examine the causal relationship. Compared with non-depressed people, depressed people may be more likely to have subjective effects of cognition and social influence. Hence, the level of depression should be considered and incorporated when developing intervention programs for illicit drug use. A longitudinal design or experimentation should be applied to examine the relationships among depression, cognition, social influence and illicit drug use in future studies.

Ajzen, I., (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 59, 179-211.
Arendt, M., Rosenberg, R., Fjordback, L., Brandholdt, J., Foldager, L., Sher, L., & Munk-Jorgensen, P. (2007). Testing the self-medication hypothesis of depression and aggression in cannabis-dependent subjects. European Psychiatry, 22, S183.
Arria, A. M., Caldeira, K. M., O’Grady, K. E., Vincent, K. B., Fitzelle, D. B., Johnson, E. P., & Wish, E. D., (2008). Drug exposure opportunities and use patterns among college students: Results of a longitudinal prospective cohort study. Substance Abuse, 29, 19-38.
Armitage, C. J., & Conner, M. (2001). Efficacy of the theory of planned behaviour: A meta‐analytic review. British journal of social psychology, 40, 471-499.
Bandura, A., (1997) Self-efficacy: the exercise of control. New York: W. H. Freeman and Company.
Bandura, A., (1993). Perceived self-efficacy in cognitive development and functioning. Educational Psychologist, 28,117-148.
Beck, A. T., Ward, C.H., Mendelson, M., Mock, J., & Erbaugh, J. (1961). An inventory for measuring depression. Archives of General Psychiatry (now JAMA Psychiatry), 4, 561-571.
Beevers, C. G., Rohde, P., Stice, E., & Nolen-Hoeksema, S. (2007). Recovery from major depressive disorder among female adolescents: A prospective test of the scar hypothesis. Journal of Consulting and Clinical Psychology, 75, 888-900.
Benjet, C., Borges, G., Medina‐Mora, M. E., Fleiz, C., Blanco, J., Zambrano, J., et al (2007). Prevalence and socio‐demographic correlates of drug use among adolescents: results from the Mexican Adolescent Mental Health Survey. Addiction, 102, 1261-1268.
Benthin, A., Slovic, P., & Severson, H. (1993). A psychometric study of adolescent risk perception. Journal of Adolescence, 16, 153-168.
Borsari, B., & Carey, K. B. (2001). Peer influences on college drinking: a review of the research. Journal of Substance Abuse, 13, 391-424.
Bosker, W. M., Kuypers, K. P. C., & Conen, S., (2010) Dose-related effects of MDMA on psychomotor function and mood before, during, and after a night of sleep loss. Psychopharmacology, 209, 69-76.
Bolton, J., Cox, B., Clara, I., & Sareen, J. (2006). Use of alcohol and drugs to self-medicate anxiety disorders in a nationally representative sample. The Journal of nervous and mental disease, 194, 818-825.
Bovasso, G. B. (2001). Cannabis abuse as a risk factor for depressive symptoms. American Journal of Psychiatry, 158, 2033-2037.
Brechwald, W. A., & Prinstein, M. J. (2011). Beyond homophily: A decade of advances in understanding peer influence processes. Journal of Research on Adolescence, 21, 166-179.
Breslau. N., Peterson, E. L., Schultz, L. R., Chilcoat, H. D., & Andreski, P., (1998) Major depression and stage of smoking. Archie of General Psychiatry, 55, 161-166.
Chang, C. H., Ko, H. C., Wu, J. Y. W., & Cheng, C. P., (2007) Social cognitive determinants of betel quid chewing among college students in southern Taiwan: A revised Attitude- Social influence- Efficacy Model. Addictive Behaviors, 32, 2345-2350.
Chen, W. J., Fu, T. C., Ting, T. T., Huang, W. L., Tang, G. M., Hsiao, C. K., & Chen, C. Y. (2009). Use of ecstasy and other psychoactive substances among school-attending adolescents in Taiwan: national surveys 2004–2006. BMC Public Health, 9, 27.
Choi, H. J., Krieger, J. L., & Hecht, M. L. (2013). Reconceptualizing efficacy in substance use prevention research: refusal response efficacy and drug resistance self-efficacy in adolescent substance use. Health communication, 28, 40-52.
Chou, P., Liu, MY., Lai, MY., Hsiao, ML., & Chang, HJ., (1999). Time trend of substance use among adolescent students in Taiwan, 1991-1996. Journal of the Formosan Medical Association, 98, 827-831.
Chong, M. Y., Chan, K. W., & Cheng, A. T. A. (1999). Substance use disorders among adolescents in Taiwan: prevalence, sociodemographic correlates and psychiatric co-morbidity. Psychological medicine, 29, 1387-1396.
Chiu, S. H., Ko, H. C., & Wu, J. Y. (2007). Depression moderated the effect of exposure to suicide news on suicidality among college students in Taiwan. Suicide and Life-Threatening Behavior 37:58-592.
Clark, H. K., Ringwalt, C. L., & Shamblen, S. R., (2011) Predicting adolescent substance use: the effect of depressed mood and positive expectancies. Addictive Behaviors, 36, 488-493.
Clark, A. E., & Loheac, Y. (2007). “It wasn’t me, it was them!” Social influence in risky behavior by adolescents. Journal of health economics, 26, 763-784.
Cooper, M. L., Frone, M. R., Rusell, M., & Mudar, P., (1995) Drinking to regulate positive and negative emotions: a motivational model of alcohol use. Journal of Personality and Social Psychology, 69, 990-1050.
Degenhardt, L., & Hall, W. (2012). Extent of illicit drug use and dependence, and their contribution to the global burden of disease. The Lancet, 379, 55-70.
Degenhardt, L., Hall, W., Warner-Smith, M., & Lynskey, M. (2004). Illicit drug use. Comparative quantification of health risks: global and regional burden of disease attributable to selected major risk factors. World Health Organization, Geneva, 1, 1109-1176.
Devlin, R. J., & Henry, J. A. (2008). Clinical review: Major consequences of illicit drug consumption. Critical Care, 12, 202.
De Vries, H., & Mudde, A. H., (1998) Predicting stage transitions for smoking cessation applying the attitude-social influence-efficacy model. Psychology & Health, 13, 369-385.
De Vries, H., & Backbier, E. (1994). Self-efficacy as an important determinant of quitting among pregnant women who smoke: the Ø-pattern. Preventive medicine, 23, 167-174.
Devaney, M. L., Reid, G., & Baldwin, S., (2007) Prevalence of illicit drug use in Asia and the Pacific. Drug and Alcohol Review, 26, 97-102.
De Weert-Van Oene, G. H., Brateler, M. H., Schippers, G. M., & Schrijvers, A. J. (2000). The validity of the self-efficacy list for drug users (SELD). Addictive Behaviors, 25, 599-605.
de Win, M. M., Reneman, L., Reitsma, J. B., den Heeten, G. J., Booij, J., & van den Brink, W. (2004). Mood disorders and serotonin transporter density in ecstasy users—the influence of long-term abstention, dose, and gender. Psychopharmacology, 173, 376-382.
Durdle, H., Lundahl, L., Johanson, C., & Tancer, M. (2008). Major depression: the relative contribution of gender, MDMA, and cannabis use. Depression & Anxiety, 25, 241-247. doi:10.1002/da.20297
Faul, F., Erdfelder, E., Buchner, A., & Lang, A. G. (2007). G*Power 3.1: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39,175-191.
Fergusson, D. M., Boden, J. M., & Horwood, L. J. (2008). The developmental antecedents of illicit drug use: evidence from a 25-year longitudinal study. Drug and Alcohol Dependence, 96, 165-177.
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Reading, MA: Addison Wesley.
Galvan, A., Hare, T., Voss, H., Glover, G., & Casey, B. J. (2007). Risk‐taking and the adolescent brain: who is at risk?. Developmental science, 10, F8-F14.
Giletta, M., Scholte, R. H. J., Prinstein, M. J., Engels, R. C., Ragalietti, E., & Burk, W. J., (2012) Friendship context matters: examining the domain specificity of alcohol and depression socialization among adolescents. Journal of Abnormal Children Psychology, 40, 1027-1043.
George, A. M., Olesen, S., Tait, R. J., (2013) Ecstasy use and depression: a 4 year longitudinal study among an Australian general community sample. Psychopharmacology, 229, 713-721.
Hall, D. H., & Queener, J. E. (2007). Self-medication hypothesis of substance use: testing Khantzian's updated theory. Journal of psychoactive drugs, 39, 151-158.
Han, B., Gfroerer, J. C., & Colliver, J. D. (2010). Associations between duration of illicit drug use and health conditions: results from the 2005-2007 national surveys on drug use and health. Annual of Epidemiology, 20, 289-297.
Harder, V. S., Morral, A. R., & Arkes, J. (2006). Marijuana use and depression among adults: testing for causal associations. Addiction, 101, 1463-1472.
Hayaki, J., Herman, D. S., Hagerty, C. E., De Dios, M. A., Anderson, B. J., & Stein, M. D. (2011). Expectancies and self-efficacy mediate the effects of impulsivity on marijuana use outcomes: An application of the acquired preparedness model. Addictive behaviors, 36, 389-396.
Hendershot, C. S., Witkiewitz, K., George, W. H., & Marlatt, G. A. (2011). Relapse prevention for additive behaviors. Substance Abuse Treatment, Prevention, and Policy, 6, 1-17.
Hutton, F. (2010). Kiwis, clubs and drugs: Club cultures in Wellington, New Zealand. Australian & New Zealand Journal of Criminology, 43, 91-111.
Huizink, A. C., Ferdinand, R. F., van den Ende, J., & Verhulst, F. C. (2006). Symptoms of anxiety and depression in childhood and use of MDMA: prospective, population based study. BMJ, 332,825-828.
Isralowitz, R., & Rawson, R. (2006). Gender differences in prevalence of drug use among high risk adolescents in Israel. Addictive Behaviors, 31, 355-358.
Iwamoto, D., William, C., Carl, L., & MacPherson, L., (2014) College men and alcohol use: positive alcohol expectancies as a mediator between distinct masculine norms and alcohol use. Psychology of Men & Masculinity, 15, 29-39.
Johnston, L. D., O’Malley, P. M., Bachman, J. G. (2007). Monitoring the Future. National Survey Results on Drug Use 1975-2006: Volume II: College Students & Adults Ages 19-45. (NIH Publication No. 07-6206), Bethesda, MD: National Institute on Drug Abuse.
Katz E. C., Fromme, K., & D’Amico, E. J. (2000). Effects of outcome expectancies and personality on young adults’ illicit drug use, heavy drinking, and risky sexual behavior. Cognitive Therapy and Research, 24, 1-22.
Khantzian, E. J. (1997). The self-medication hypothesis of substance use disorders: a reconsideration and recent applications. Harvard review of psychiatry, 4, 231-244.
King, C. A., Knox, M. S., Henninger, N., Nquyen, T. A., Ghaziuddin, N., Maker, A., & Hanna, G. L., (2006) Major depressive disorder in adolescents: family psychiatric history predicts severe behavioral disinhibition. Journal of Affective Disorder. 90, 111-121.
Khantzian, E. J., (1974) Opiate addiction: A crique of theory and some implications for treatment. American Journal of Psychotherapy, 28, 59-77.
Lee, S. K. H., Bowen, S., Oei, T. P. O., & Yen, C. F., (2012). An expanded self-medication hypothesis based on cognitive-behavioral determinants for heroin abusers in Taiwan: a cross-sectional study. American Journal on Addictions, 21, S43-48.
Lee, K. H., Yeh, Y. C., Yang, P. C., Lin, H. C., Wang, P. W., Liu, T. L., & Yen, C. F. (2012). Individual and peer factors associated with ketamine use among adolescents in Taiwan. European Child & Adolescent Psychiatry, 21, 553-558.
Lee, K. H., Bowen, S., & Bai, A. F., (2011). Psychosocial outcomes of mindfulness-based relapse prevention in incarcerated substance abusers in Taiwan: A preliminary study. Journal of Substance Use, 16, 476-483.
Liu, S. F., Lee, P. C., Lu, ML., Tsay, WL., & Li, JH., (2006) A survey on substance abuse in the Greater Taipei area. Taiwan Journal of Public Health, 25, 274-282.
Liang, W., Lenton, S., Allsop, S., & Chikritzhs, T. (2011). Does availability of illicit drugs mediate the association between mental illness and substance use? Substance use & misuse, 46, 1304-1308.
Lynskey, M. T., Agrawal, A., Henders, A., Nelson, E. C., Madden, P. A., & Martin, N. G. (2012). An Australian twin study of cannabis and other illicit drug use and misuse, and other psychopathology. Twin Research and Human Genetics, 15, 631-641.
Macleod, J., Oakes, R., Copello, A., Crome, I., Egger, M., Hickman, M., et al. (2004). Psychological and social sequelae of cannabis and other illicit drug use by young people: a systematic review of longitudinal, general population studies. The Lancet, 363, 1579-1588.
Madden, T. J., Ellen, P. S., & Ajzen, I. (1992). A comparison of the theory of planned behavior and the theory of reasoned action. Personality and social psychology Bulletin, 18, 3-9.
Martins, S. S., Storr, C. L., Alexandre, P. K., & Chilcoat, H. D. (2008). Adolescent ecstasy and other drug use in the National Survey of Parents and Youth: The role of sensation-seeking, parental monitoring and peer's drug use. Addictive Behaviors, 33, 919-933.
Manchikanti, L., Manchukonda, R., Pampati, V., Damron, K. S., Brandon, D. E., Cash, K. A., & McManus, C. D. (2006). Does random urine drug testing reduce illicit drug use in chronic pain patients receiving opioids?. Pain Physician, 9, 123.
McCardle, K., Luebbers, S., Carter, J. D., Croft, R. J., & Stough, C. (2004). Chronic MDMA (ecstasy) use, cognition and mood. Psychopharmacology , 173, 434-439.
McMillan, B., & Conner, M. (2003). Applying an Extended Version of the Theory of Planned Behavior to Illicit Drug Use among Students. Journal of Applied Social Psychology, 33, 1662-1683.
Melchior, M., Chastang, J. F., Goldberg, P., Fombonne, E. (2008). High prevalence rates of tobacco, alcohol and drug use in adolescents and young adults in France: results from the GAZEL youth study. Addictive Behaviors, 33,122-133.
Moore, T. H., Zammit, S., Lingford-Hughes, A., Barnes, T. R., Jones, P. B., Burke, M., & Lewis, G. (2007). Cannabis use and risk of psychotic or affective mental health outcomes: a systematic review. The Lancet, 370, 319-328.
Mohler-Kuo, M., Lee, J. E., & Wechsler, H. (2003) Trends in marijuana and other illicit drug use among college students: results from a Harvard School of Public Health College Alcohol Study surveys: 1993-2001. Journal of American College Health, 52, 17-24.
Niaura, R. (2000). Cognitive social learning and related perspectives on drug craving. Addiction, 95, S155-S163.
Nuňo-Gutiérrez, B. L., Rodriguez-Cerda, O., & Álvarez-Nemegyei, J., (2006) Why do adolescents use drugs? A common sense explanatory model from the social actor’s perspective. Adolescent, 41, 649-665.
Oei, T. P. S., & Morawska, A., (2004). A cognitive model of binge drinking: the influence of alcohol expectancies and drinking refusal self-efficacy. Addictive Behavior, 29, 159-179.
Palmer, R. H. C., Young, S. E., Hopfer, C. J., Corley, R. P., Stallings, M. C., Crowley, T. J., & Hewitt, J. K. (2009). Developmental epidemiology of drug use and abuse in adolescence and young adulthood: Evidence of generalized risk. Drug and Alcohol Dependence, 102, 78-87.
Peters, G. J., Kok, G., & Abraham, C. (2007). Social cognitive determinants of ecstasy use to target in evidence-based interventions: a meta-analytical review. Addiction, 103, 109-118.
Ramo, D. E., Prochaska, J. J., & Myers, M. G. (2010). Intentions to quit smoking among youth in substance abuse treatment. Drug and alcohol dependence, 106, 48-51.
Rohde, P., Lewinsohn, P. M., & Seeley, J. R. (1994). Are adolescents changed by an episode of major depression? Journal of the American Academy of Child and Adolescent Psychiatry, 33, 1289-1298.
Rogojanski, J., Vettese, L. C., & Antony, M. M. (2011). Coping with cigarette cravings: comparison of suppression versus mindfulness-based strategies. Mindfulness, 2, 14-26.
Schafer, J., & Brown, S. A. (1991). Marijuana and cocaine effect expectancies and drug use pattern. Journal of Consulting and Clinical Psychology, 59, 558-565.
Simple English Wikipedia. 31 / May / 2014, cited from http://simple.wikipedia.org/wiki/2014
Sheeran, P., (2002) Intention-Behavior relations: a conceptual and empirical review. European Review of Social Psychology, 12, 1-36.
Simons-Morton, B. (2007). Social influences on adolescent substance use. American Journal of health behavior, 31, 672-684.
Stephens, P. C., Sloboda, Z., Stephens, R. C., Teasdale, B., Grey, S. F., Hawthorne, R. D., & Williams, J. (2009). Universal school-based substance abuse prevention programs: Modeling targeted mediators and outcomes for adolescent cigarette, alcohol and marijuana use. Drug and alcohol dependence, 102, 19-29.
Stone, A. L., Becker, L. G., Huber, A. M., & Catalano, R. F. (2012). Review of risk and protective factors of substance use and problem use in emerging adulthood. Addictive behaviors, 37, 747-775.
Suh, J. J., Ruffins, S., Robins, C. E., Albanese, M. J., & Khantzian, E. J. (2008). Self-medication hypothesis: Connecting affective experience and drug choice. Psychoanalytic psychology, 25, 518.
Swendsen, J. D., Tennen, H., Carney, M. A., Affleck, G., Willard, A., & Hromi, A. (2000). Mood and alcohol consumption: an experience sampling test of the self-medication hypothesis. Journal of abnormal psychology, 109, 198.
Tominaga, M., Kawakami, N., Ono, Y., Nakane, Y., Nakamura, Y., Tachimori, H., et al. (2009). Prevalence and correlates of illicit and non-medical use of psychotropic drugs in Japan. Social psychiatry and psychiatric epidemiology, 44, 777-783.
Tomlinson, K. L., Tate, S. R., Anderson, K. G., McCarthy, D. M., & Brown, S. A. (2006). An examination of self-medication and rebound effects: Psychiatric symptomatology before and after alcohol or drug relapse. Addictive Behaviors, 31, 461-474.
Urberg, K. A., Luo, Q., Pilgrim, C., & Degirmencioglu, S. M. (2003). A two-stage model of peer influence in adolescent substance use: individual and relationship-specific differences in susceptibility to influence. Addictive Behaviors, 28,1243-1256.
Van Amsterdam, J. G., van Laar, M., Brunt, T. M., & van den Brink, W. (2012). Risk assessment of gamma-hydroxybutyric acid (GHB) in the Netherlands. Regulatory Toxicology and Pharmacology, 63, 55-63
Van Es, S. M., Nagelkerke, Ad. F., Colland, V. T., Scholten, Ron. J. P. M., & Bouter, Lex. M., (2001) An intervention programme using the ASE-model aimed at enhancing adherence in adolescents with asthma. Patient Education and Counseling, 44, 193-203
Van Havere, T., Vanderplasschen, W., Lammertyn, J., Broekaert, E., & Bellis, M. (2011). Drug use and nightlife: more than just dance music. Substance Abuse Treatment, Prevention and Policy, 6, 1899-1915.
Wang, S. H., Lin, I. C., Chen, C. Y., Chen, D. R., Chan, T. C., & Chen, W. J., (2013): Availability of convenience stores and adolescent alcohol use in Taiwan: a multilevel analysis of national surveys. Addiction, 108, 2081-2088.
Wang, P. W., Lin, H. C., Yeh, Y. C., Liu, T. L., & Yen, C. F. (2012). The relation of substance use with different levels of depressive symptoms and the moderating effect of sex and age in Taiwanese adolescents. Comprehensive Psychiatry, 53, 1013-1020.
Wagner, G. A., Stempliuk Vde, A., Zilberman, M. L., Barroso, L. P., & de Andrade, A. G. (2007). Alcohol and drug use among university students: gender differences. Revista Brasileira de Psiquiatria, 29, 123-129.
Webb, T. L., & Sheeran, P. (2006). Does changing behavioral intentions engender behavior change? A meta-analysis of the experimental evidence. Psychological Bulletin, 132,249-268.
Witkiewitz, K., & Marlatt, G. A. (2004). Relapse prevention for alcohol and drug problems: that was Zen, this is Tao. American Psychologist, 59, 224.
Wu, P., Goodwin, R. D., Fuller, C., Liu, X., Comer, J. S., Cohen, P., & Hoven, C. W. (2010). The relationship between anxiety disorders and substance use among adolescents in the community: specificity and gender differences. Journal of Youth and Adolescence, 39, 177-188.
Yang, MS., Yang, MJ., Liu, YH., Ko, YC., (1998). Prevalence and related risk factors of licit and illicit drug substances use by adolescent students in Southern Taiwan. Public Health, 112, 347-352.
Young, R. M. Connor, J. P., Ricciardelli, L. A., & Saunders, J. B. (2006). The role of alcohol expectancy and drinking refusal self-efficacy beliefs in university student drinking. Alcohol & Alcoholism, 41, 70-75.
Yu, R. L., & Ko, H. C. (2006). Cognitive determinants of MDMA use among college students in Southern Taiwan. Addictive Behaviors, 31, 2199-2211.