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研究生: 廖容瑜
Liao, Jung-Yu
論文名稱: 行動應用程式對於用藥高危險青少年之成效探討
The effectiveness of a smartphone application for illegal drug use prevention among at-risk adolescents
指導教授: 郭鐘隆
Guo, Jong-Long
學位類別: 博士
Doctor
系所名稱: 健康促進與衛生教育學系
Department of Health Promotion and Health Education
論文出版年: 2019
畢業學年度: 107
語文別: 英文
論文頁數: 77
中文關鍵詞: 行動應用程式非法藥物高危險青少年解構式計畫行為理論社會支持
英文關鍵詞: smartphone application, illegal drug use, at-risk adolescents, decomposed theory of planned behavior (DTPB), social support
DOI URL: http://doi.org/10.6345/DIS.NTNU.DHPHE.003.2019.F02
論文種類: 學術論文
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  • 目的:青少年非法藥物濫用預防分三級,對於「高危險群青少年」的預防措施較少。高中職是一重要的轉變期,青少年即將面對升學、就業、結婚等選項,若沒有轉變成功,可能增加非法藥物使用的機率。因此,本研究發展一行動應用程式「QD-Health」應用於藥物濫用預防,使用解構式計畫行為理論評估高危險群學生使用此款行動應用程式之影響因子,並評估其成效,期能促進高危險學生之不用藥健康識能與社會支持,以延緩並預防非法藥物使用的發生。

    方法:本研究招募40名高危險群學生使用QD-Health,共計2個月,參與者需完成三次問卷調查,分別於前測 (第一次使用後)、第一個月追蹤、及第二個月追蹤。資料分析採複迴歸探討影響參與者使用QD-Health意圖之因子;採配對t檢定與效果量評估此行動應用程式對於不用藥健康適能、社會支持與不用藥意圖之成效。

    結果:複迴歸分析結果顯示態度與輔導員影響顯著預測意圖,而知覺有趣性與相容性顯著影響態度。此外,參與者的不用藥意圖、不用藥健康適能與社會支持於使用QD-Health之兩個月當中有所改善,比較前測與第一個月追蹤測的結果,情緒性支持之效果量介於低至中等,其它結果變項為低效果量;比較前測與第二個月追蹤測的結果,情緒性支持之效果量介於中等至高,不用藥健康適能為低至中等之效果量。
    結論:QD-Health是第一個行動應用程式應用於青少年藥物濫用防制,本研究結果認為行動應用程式適合高危險群青少年,且QD-Health對於青少年之情緒性社會支持的改變具潛在成效。

    Aims: Interventions for at-risk adolescents in terms of illegal drug use prevention were less. High school is a critical transition period that they are going to move to the next life stage, such as the college, workforce, or marriage. They may start or restart using drugs as they fail to the transition. Therefore, the study aimed to develop a smartphone app named “QD-Health” on the basic of perspectives of adolescents with experiences of drug use and practitioners who worked with them. The utilization of QD-Health was assessed based on the decomposed theory of planned behavior (DTPB). The effectiveness of QD-Health was assessed on health literacy in drug nonuse, social support and intention not to use drugs.

    Method: A total of 40 at-risk adolescents were recruited in the study. They used QD-Health for two months and completed three measurements at the baseline (after the first-time use), the first-month follow-up, and the second-month follow-up. Multiple regressions were used to identify significant factors based on the DTPB model. Paired-t tests with Bonferroni correction and effect sizes were used to assess the effectiveness of QD-Health on intention not to use drugs, health literacy in drug nonuse, social support, including tangible, emotional and appraisal supports.

    Results: Based on the DTPB model, attitude (satisfaction) and counselors’ influences were found to significantly predict the intention to use QD-Health, accounting for 89.0% of the variance. For satisfaction, perceived playfulness and compatibility were significant predicted factors. Moreover, the magnitude of effect size for emotional support was small to medium when comparing in the first-month follow-up with the baseline. Comparing the second-month follow-up with the baseline, the medium to large effect size was found on emotional support.

    Conclusion: This is the first study to apply an app to the intervention for adolescent illegal drug use prevention. The findings supported that an app was appropriate for at-risk adolescents and QD-Health had potential influences on health literacy in drug nonuse and emotional support.

    List of Tables VIII List of Figures IX CHAPTER I INTRODUCTION TO THE STUDY 1  Background of the Study 1  Purpose of the Study 4  Research Question(s) 5  Definitions 6 CHAPTER II LITERATURE REVIEW 9  Smartphone and Application 9  Decomposed Theory of Planned Behavior 16  At-risk Adolescents and influential factors related to  behavior change 22 CHAPTER III RESEARCH METHOD 28  Study 1 28  Study 2 30  Study 3 34 CHAPTER IV RESULTS 40  The results of content analysis 40  The app design: QD-Health 45  Demographic information of participants 50  Satisfaction relative to QD-Health 52  QD-Health utilization among participants based on DTPB 53  Effects of QD-Health on outcome indicators 55 CHAPTER V DISCUSSION, RECOMMENDATIONS, AND LIMATATIONS 59  Discussion 59  Recommendations 63  Limitations 66 CHAPTER V CONCLUSIONS 68 REFERENCES 69

    Abroms, L. C., Westmaas, J. L., Bontemps-Jones, J., Ramani, R., & Mellerson, J. (2013). A content analysis of popular smartphone apps for smoking cessation. American Journal of Preventive Medicine, 45(6), 732-736.
    Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
    Armitage, C. J., & Conner, M. (2001). Efficacy of the theory of planned behaviour: A meta‐analytic review. British Journal of Social Psychology, 40(4), 471-499.
    Bachman, J. G., Wadsworth, K. N., O'Malley, P. M., Johnston, L. D., & Schulenberg, J. E. (2013). Smoking, drinking, and drug use in young adulthood: The impacts of new freedoms and new responsibilities. New York, New York: Psychology Press.
    Barnett, L. A. (1991). Characterizing playfulness: Correlates with individual attributes and personality traits. Play and Culture, 4(4), 371-393.
    Bert, F., Giacometti, M., Gualano, M. R., & Siliquini, R. (2014). Smartphones and health promotion: a review of the evidence. Journal of Medical Systems, 38(1), 9995.
    BinDhim, N. F., McGeechan, K., & Trevena, L. (2014). Assessing the effect of an interactive decision-aid smartphone smoking cessation application (app) on quit rates: A double-blind automated randomised control trial protocol. BMJ Open, 4(7), e005371.
    Bricker, J. B., Mull, K. E., Kientz, J. A., Vilardaga, R., Mercer, L. D., Akioka, K. J., & Heffner, J. L. (2014). Randomized, controlled pilot trial of a smartphone app for smoking cessation using acceptance and commitment therapy. Drug and Alcohol Dependence, 143, 87-94.
    Brown III, W., Yen, P. Y., Rojas, M., & Schnall, R. (2013). Assessment of the Health IT Usability Evaluation Model (Health-ITUEM) for evaluating mobile health (mHealth) technology. Journal of Biomedical Informatics, 46(6), 1080-1087.
    Cabin, R. J., & Mitchell, R. J. (2000). To Bonferroni or not to Bonferroni: when and how are the questions. Bulletin of the Ecological Society of America, 81(3), 246-248.
    Cafazzo, J. A., Casselman, M., Hamming, N., Katzman, D. K., & Palmert, M. R. (2012). Design of an mHealth app for the self-management of adolescent type 1 diabetes: a pilot study. Journal of Medical Internet Research, 14(3).
    Chen, C. C., Liao, J. Y., Chang, C. C., & Guo, J. L. (2016). The intervention effectiveness of 3D virtual reality animation on senior high school students with ketamine use [Chinese]. International Journal on Digital Learning Technology, 8(3), 51-69.
    Chen, K. T., Chen, C. J., Fagot-Campagna, A., & Narayan, K. (2001). Tobacco, betel quid, alcohol, and illicit drug use among 13-to 35-year-olds in I-Lan, rural Taiwan: prevalence and risk factors. American Journal of Public Health, 91(7), 1130-1134.
    Cheon, J., Lee, S., Crooks, S. M., & Song, J. (2012). An investigation of mobile learning readiness in higher education based on the theory of planned behavior. Computers & Education, 59(3), 1054-1064.
    Chu, P. S., Saucier, D. A., & Hafner, E. (2010). Meta-analysis of the relationships between social support and well-being in children and adolescents. Journal of Social and Clinical Psychology, 29(6), 624-645.
    Cohen, J. (1988). Statistical power analysis for the behavioural sciences. Hillsdale, New Jersey: Erlbaum.
    Cohen, S. (2004). Social relationships and health. American Psychologist, 59(8), 676-684.
    Cohen, S., & Wills, T. A. (1985). Stress, social support, and the buffering hypothesis. Psychological Bulletin, 98(2), 310.
    Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319-340.
    Degenhardt, L., & Hall, W. (2012). Extent of illicit drug use and dependence, and their contribution to the global burden of disease. The Lancet, 379(9810), 55-70.
    Demanet, J., & Van Houtte, M. (2012). School belonging and school misconduct: The differing role of teacher and peer attachment. Journal of Youth and Adolescence, 41(4), 499-514.
    Erickson, K. G., Crosnoe, R., & Dornbusch, S. M. (2000). A social process model of adolescent deviance: Combining social control and differential association perspectives. Journal of Youth and Adolescence, 29(4), 395-425.
    Evans, S. R. (2010). Clinical trial structures. Journal of Experimental Stroke & Translational Medicine, 3(1), 8.
    Free, C., Phillips, G., Watson, L., Galli, L., Felix, L., Edwards, P., . . . Haines, A. (2013). The effectiveness of mobile-health technologies to improve health care service delivery processes: A systematic review and meta-analysis. PLoS Medicine, 10(1), e1001363.
    Frison, E., & Eggermont, S. (2015). The impact of daily stress on adolescents’ depressed mood: The role of social support seeking through Facebook. Computers in Human Behavior, 44, 315-325.
    Garamszegi, L. Z. (2006). Comparing effect sizes across variables: Generalization without the need for Bonferroni correction. Behavioral Ecology, 17(4), 682-687.
    Grunbaum, J. A., Tortolero, S., Weller, N., & Gingiss, P. (2000). Cultural, social, and intrapersonal factors associated with substance use among alternative high school students. Addictive Behaviors, 25(1), 145-151.
    Guo, J. L., Lee, T. C., Liao, J. Y., & Huang, C. M. (2015). Prevention of illicit drug use through a school-based program: Results of a longitudinal, cluster-randomized controlled trial. Journal of Adolescent Health, 56(3), 314-322.
    Guo, J. L., Liao, J., Chang, L., Wu, H., & Huang, C. (2014). The effectiveness of an integrated multicomponent program for adolescent smoking cessation in Taiwan. Addictive Behaviors, 39(10), 1491-1499.
    Heffner, J. L., Vilardaga, R., Mercer, L. D., Kientz, J. A., & Bricker, J. B. (2015). Feature-level analysis of a novel smartphone application for smoking cessation. The American Journal of Drug And Alcohol Abuse, 41(1), 68-73.
    Hirschi, T. (2017). Causes of delinquency. New York, New York: Routledge.
    Holt-Lunstad, J., & Uchino, B. (2015). Social support and health. Health behavior: Theory, Research and Practice, 183-204.
    House, J. S., Umberson, D., & Landis, K. R. (1988). Structures and processes of social support. Annual Review of Sociology, 14(1), 293-318.
    Hsieh, P.-J. (2015). Physicians’ acceptance of electronic medical records exchange: An extension of the decomposed TPB model with institutional trust and perceived risk. International Journal of Medical Informatics, 84(1), 1-14.
    Hsu, M. H., & Chiu, C. M. (2004). Predicting electronic service continuance with a decomposed theory of planned behaviour. Behaviour & Information Technology, 23(5), 359-373.
    Huang, C. M., Lin, L. F., Lee, T. C., & Guo, J. L. (2013). Proximal to distal correlates of the patterns of illicit drug use among night school students in Taiwan. Addictive Behaviors, 38(1), 1481-1484.
    Huang, C. M., Chien, L. Y., Cheng, C. F., & Guo, J. L. (2012). Integrating life skills into a theory‐based drug‐use prevention program: Effectiveness among junior high students in Taiwan. Journal of School Health, 82(7), 328-335.
    Igbaria, M., Iivari, J., & Maragahh, H. (1995). Why do individuals use computer technology? A Finnish case study. Information & Management, 29(5), 227-238.
    Kay, M., Santos, J., & Takane, M. (2011). mHealth: New horizons for health through mobile technologies. World Health Organization, 64(7), 66-71.
    Kazemi, D. M., Borsari, B., Levine, M. J., Lamberson, K. A., & Dooley, B. (2018). REMIT: Development of a mHealth theory-based intervention to decrease heavy episodic drinking among college students. Addiction Research & Theory, 26(5), 377-385.
    Kazemi, D. M., Borsari, B., Levine, M. J., Li, S., Lamberson, K. A., & Matta, L. A. (2017). A systematic review of the mHealth interventions to prevent alcohol and substance abuse. Journal of Health Communication, 22(5), 413-432.
    Kelley, K., & Preacher, K. J. (2012). On effect size. Psychological Methods, 17(2), 137-152.
    Kickbusch, I., & Nutbeam, D. (1998). Health promotion glossary. Geneva: World Health Organization, 14.
    Kraus, L., & Nociar, A. (2016). ESPAD report 2015: Results from the European school survey project on alcohol and other drugs: European Monitoring Centre for Drugs and Drug Addiction.
    Krippendorff, K. (2004). Reliability in content analysis. Human communication research, 30(3), 411-433.
    Lau, A. S. (2011). Hospital-based nurses’ perceptions of the adoption of Web 2.0 tools for knowledge sharing, learning, social interaction and the production of collective intelligence. Journal of Medical Internet Research, 13(4), e92.
    Liang, D., Han, H., Du, J., Zhao, M., & Hser, Y. I. (2018). A pilot study of a smartphone application supporting recovery from drug addiction. Journal of Substance Abuse Treatment, 88, 51-58.
    Liao, J. Y., Huang, C. M., Lee, C. T. C., Hsu, H. P., Chang, C. C., Chuang, C. J., & Guo, J. L. (2018). Risk and protective factors for adolescents’ illicit drug use: A population-based study. Health Education Journal, 0017896918763462.
    Linas, B. S., Latkin, C., Genz, A., Westergaard, R. P., Chang, L. W., Bollinger, R. C., & Kirk, G. D. (2015). Utilizing mHealth methods to identify patterns of high risk illicit drug use. Drug and Alcohol Dependence, 151, 250-257.
    McManama O'Brien, K. H., LeCloux, M., Ross, A., Gironda, C., & Wharff, E. A. (2017). A pilot study of the acceptability and usability of a smartphone application intervention for suicidal adolescents and their parents. Archives of Suicide Research, 21(2), 254-264.
    Miech, R. A., Schulenberg, J. E., Johnston, L. D., Bachman, J. G., O'Malley, P. M., & Patrick, M. E. (2017). National Adolescent Drug Trends in 2017: Findings Released. Retrieved from http://www.monitoringthefuture.org.
    Monney, G., Penzenstadler, L., Dupraz, O., Etter, J. F., & Khazaal, Y. (2015). mHealth app for cannabis users: Satisfaction and perceived usefulness. Frontiers in Psychiatry, 6, 120.
    NIDA. (2003). Preventing drug use among children and adolescents (In Brief). Retrieved from https://www.drugabuse.gov/publications/preventing-drug-use-among-children-adolescents-in-brief.
    NIDA. (2017). Health consequences of drug misuse. Retrieved from https://www.drugabuse.gov/related-topics/health-consequences-drug-misuse.
    NIDA. (2018, July). Drugs, brains, and behavior: The science of addiction. Retrieved from https://www.drugabuse.gov/publications/drugs-brains-behavior-science-addiction/preface.
    Pretlow, R. A., Stock, C. M., Allison, S., & Roeger, L. (2015). Treatment of child/adolescent obesity using the addiction model: a smartphone app pilot study. Childhood Obesity, 11(3), 248-259.
    Ray, J. W., & Shadish, W. R. (1996). How interchangeable are different estimators of effect size? Journal of Consulting and Clinical Psychology, 64(6), 1316-1325.
    Research2Guidance. (2017). mHealth App Economics 2017: Current Status and Future Trends in Mobile Health. Berlin, Germany: Research2guidance.
    Ritterband, L. M., Gonder-Frederick, L. A., Cox, D. J., Clifton, A. D., West, R. W., & Borowitz, S. M. (2003). Internet interventions: In review, in use, and into the future. Professional Psychology: Research and Practice, 34(5), 527-534.
    Ritterband, L. M., Thorndike, F. P., Cox, D. J., Kovatchev, B. P., & Gonder-Frederick, L. A. (2009). A behavior change model for internet interventions. Annals of Behavioral Medicine, 38(1), 18-27.
    Robbins, R., Krebs, P., Jagannathan, R., Jean-Louis, G., & Duncan, D. T. (2017). Health app use among US mobile phone users: Analysis of trends by chronic disease status. JMIR mHealth and uHealth, 5(12), e197.
    Rogers, E. M. (1962). Diffusion of innovations. New York: Free Press of Glencoe.
    Rogers, E. M. (2010). Diffusion of innovations (4th Ed.). New York: Simon and Schuster.
    Rostosky, S. S., Owens, G. P., Zimmerman, R. S., & Riggle, E. D. (2003). Associations among sexual attraction status, school belonging, and alcohol and marijuana use in rural high school students. Journal of Adolescence, 26(6), 741-751.
    Sørensen, K., Van den Broucke, S., Fullam, J., Doyle, G., Pelikan, J., Slonska, Z., & Brand, H. (2012). Health literacy and public health: a systematic review and integration of definitions and models. BMC Public Health, 12(1), 80.
    Sambucini, V. (2015). Comparison of single-arm vs. randomized phase II clinical trials: a Bayesian approach. Journal of Biopharmaceutical Statistics, 25(3), 474-489.
    Sullivan, G. M., & Feinn, R. (2012). Using effect size—or why the P value is not enough. Journal of Graduate Medical Education, 4(3), 279-282.
    Taylor, S., & Todd, P. (1995). Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International Journal of Research In Marketing, 12(2), 137-155.
    Valente, T. W., Ritt‐Olson, A., Stacy, A., Unger, J. B., Okamoto, J., & Sussman, S. (2007). Peer acceleration: effects of a social network tailored substance abuse prevention program among high‐risk adolescents. Addiction, 102(11), 1804-1815.
    Volkow, N. D., Swanson, J. M., Evins, A. E., DeLisi, L. E., Meier, M. H., Gonzalez, R., . . . Baler, R. (2016). Effects of cannabis use on human behavior, including cognition, motivation, and psychosis: A review. JAMA Psychiatry, 73(3), 292-297.
    Wang, M. T., Brinkworth, M., & Eccles, J. (2013). Moderating effects of teacher–student relationship in adolescent trajectories of emotional and behavioral adjustment. Developmental Psychology, 49(4), 690-705.
    Whittaker, R., McRobbie, H., Bullen, C., Rodgers, A., & Gu, Y. (2016). Mobile phone‐based interventions for smoking cessation. Cochrane Database of Systematic Reviews (4). doi:10.1002/14651858.CD006611.pub4.
    World Health Organization. (2009). Process of translation and adaptation of instruments. Retrieved from https://www.who.int/substance_abuse/research_tools/translation/en/.
    World Health Organization. (2018). Health promotion-Track 2: Health literacy and health behaviour. Retrieved from https://www.who.int/healthpromotion/conferences/7gchp/track2/en/.

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