教師關懷、社團影響、學校活動與青少年偏差行為之研究

Teacher Caring, Influence of Student Societies, School Activities and Delinquency

10.7014/SRMA.2022040002

盧名瑩(Ming-Ying Lu)；張楓明(Feng-Ming Chang)；郭玲玲(Ling-Ling Kueh)；董旭英(Yuk-Ying Tung)

青少年偏差行為 ； 社會控制理論 ； 零膨脹負二項迴歸模型 ； delinquency ； social control theory ； zero-inflated negative binomial regression

調查研究-方法與應用

48期（2022 / 04 / 01）

47 - 91

繁體中文

本研究旨在探討教師關懷、社團影響及學校活動，與青少年偏差行為的發生與否及發生頻率間之關聯性。研究數據取自臺灣教育長期追蹤資料庫2007年針對臺灣高中職、五專學生所進行的第四波調查資料，有效樣本為4,056名學生；使用零膨脹負二項迴歸模型進行分析，以了解教師關懷等因素是否影響青少年偏差行為的發生及發生頻率。研究結果顯示：教師關懷、社團影響及學校活動雖非偏差行為發生與否的影響因素，但卻能降低偏差行為的發生頻率。換言之，教師關懷等因素均非青少年偏差行為發生與否的觸發因素；但感受較多的教師關懷、社團正向影響或學校活動投入，將使青少年偏差行為發生頻率隨之降低。背景變項中，性別同時影響偏差行為發生與否及發生頻率，即男生出現偏差行為的機率及頻率高於女生；相較於都市，城鎮地區青少年發生偏差行為機率較低；就讀綜合學程的青少年，偏差行為發生頻率比普通學程更高。最後，依據研究結果提出建議，以供學校、教師作為實際輔導工作及未來研究之參考。

Hirschi's social control theory implies that when students lack a sense of attachment or identity, or dislike participating in school activities, deviations or criminal behavior might occur. We hypothesize that the effects of school factors should play important roles in the explanation of youth delinquency. If teenagers have negative relationships with teachers, or dislike going to school, these are likely to result in the occurrence of deviant behavior. Few empirical studies have analyzed the influencing factors that trigger the ＂occurrence＂ of delinquency, and whether relevant factors have an effect on the ＂frequency＂ of the occurrence of deviant behavior. Therefore, this study attempted to examine the impact and influence which teacher caring, student societies and school activities have on the occurrence and frequency of delinquent behavior by using the zero-inflated negative binomial regression model. Adopting the dynamic change development and life course interpretation perspective allowed us to explore the causes of various developmental aspects of adolescents' deviant behavior. The study utilized data collected from 4,056 high school, technical high school and five-year junior college program students in Taiwan under the Taiwan Education Panel Survey (TEPS) published in 2007. The database was planned and funded by Academia Sinica and the Ministry of Education in Taiwan. TEPS was the first database in Taiwan to sample and collect long-term data from junior high school, high school, vocational high school and five-year junior college students across the country. Deviant behavior usually occurred beyond normality and routine. The actual situation was much more complex and unlikely to present itself in a normal statistical distribution. The occurrence of deviant behavior in a group is relatively rare. Consequently, it tends to be unique and occur in complex situations, rather than being normal or routine; as a result, it is difficult to identify in normal statistical distributions. Therefore, the use of behavioral types or continuous values cannot reflect the true situation of deviation behavior. In order to overcome the excessive dispersion and heterogeneity caused by a large number of ＂zeros＂ in the data, this study utilized the zero-inflated negative binomial regression model (ZINB) in statistical analysis. Through ZINB analysis, first, based on the number of occurrences of deviant behavior among adolescents, students were divided into susceptible groups and non-susceptible groups. Then, for the susceptible groups, a negative binomial regression model was further used to test the impact of independent variables on deviant behavior. The major findings of this study were as follows: (1) The influence which teacher caring, student societies and school activities had on students was not significantly associated with the occurrence of delinquency. However, students who experienced a higher level of teacher caring and more positive experiences in student societies and school activities appeared to have a lower frequency of delinquency. (2) Gender was significantly associated with the occurrence and frequency of delinquency, such that male students showed higher levels of occurrence and frequency of delinquency than female students. (3) Students from townships showed a lower level of occurrence of delinquent behavior than those from cities. (4) Students from comprehensive high schools showed a higher level of frequency of delinquent behavior than those from normal high schools. Based on the research results, this paper concludes with suggestions of applied counseling work references for schools and teachers and possible directions that future research may take.

1. 翁健力, Chien-li(2018)。生命歷程犯罪學的回首與展望。犯罪學期刊，20(2)，3-28。
   連結：
2. 張雲龍, Yun-lung(2016)。家庭與學校知覺影響高中職生偏差行為之探討。輔導與諮商學報，38(1)，61-82。
   連結：
3. 郭玲玲, Ling-ling,洪瑄, Hsuan,董旭英, Yuk-ying(2021)。青少年偏差行為發生與否及發生頻率之模型建構。教育研究集刊，67(1)，29-63。
   連結：
4. 郭銘峰, Ming-feng,王鼎銘, Ding-ming,丁太平, Tai-ping(2016)。中國大陸基層治理與社區維權：零膨脹負二項計數模型之分析。人文及社會科學集刊，28(4)，581-622。
   連結：
5. 蕭孟平, Meng-ping,黃國彰, Kuo-chang(2020)。青少年偏差行為成因探討及防範。諮商與輔導，418，35-38+63。
   連結：
6. 譚子文, Tzyy-wen,范書菁, Shu-ching(2010)。依附關係、參與傳統活動、社會緊張因素與台灣地區青少年外向性偏差行為及內向性偏差行為關性之研究。輔導與諮商學報，32(1)，17-42。
   連結：
7. 譚子文, Tzyy-wen,張楓明, Feng-ming(2013)。依附關係、低自我控制及接觸偏差同儕與青少年偏差行為關係之研究。當代教育研究季刊，21(4)，81-120。
   連結：
8. Akers, Ronald L.,Sellers, C. S.,Jennings, W. G.(2016).Criminological Theories: Introduction, Evaluation, and Application.New York:Oxford University.
9. Britt, Chester L.,Rocque, M.,Zimmerman, G. M.(2018).The Analysis of Bounded Count Data in Criminology.Journal of Quantitative Criminology,34(2),591-607.
10. Cameron, A. Colin,Trivedi, Pravin K.(2013).Regression Analysis of Count Data.Cambridge:Cambridge University Press.
11. Cretacci, Michael A.,Rivera, Craig,Gao, Yandong,Zheng, Liu(2018).Bonding to Bamboo: A Social Control Explanation of Chinese Crime.International Journal of Criminal Justice Sciences,13(1),122-136.
12. Erdmann, Anke,Reinecke, Jost(2019).What Influences the Victimization of High-Level Offenders? A Dual Trajectory Analysis of the Victim-Offender Overlap from the Perspective of Routine Activities with Peer Groups.Journal of Interpersonal Violence
13. Evans, Sara Z.,Simons, Leslie G.,Simons, Ronald L.(2016).Factors that Influence Trajectories of Delinquency Throughout Adolescence.Journal of Youth & Adolescence,45(1),156-171.
14. Fisher, Benjamin W.,Gardella, Joseph H.,Tanner-Smith, Emily E.(2019).Social Control in Schools: The Relationships between School Security Measures and Informal Social Control Mechanisms.Journal of School Violence,18(3),347-361.
15. Garay, Aldo M.,Hashimoto, Elizabeth M.,Ortega, Edwin M. M.,Lachos, Victor H.(2011).On Estimation and Influence Diagnostics for Zero-inflated Negative Binomial Regression Models.Computational Statistics & Data Analysis,55(3),1304-1318.
16. Gomes, Hugo S.,Farrington, David P.,Maia, Angela,Krohn, Marvin D.(2019).Measurement Bias in Self-reports of Offending: A Systematic Review of Experiments.Journal of Experimental Criminology,15(3),313-339.
17. Greene, William H.(1994).NYU Working PaperNYU Working Paper,未出版
18. Han, Yoonsun,Kim, Heejoo,Lee, Dong Hun(2016).Application of Social Control Theory to Examine Parent, Teacher, and Close Friend Attachment and Substance Use Initiation among Korean Youth.School Psychology International,37(4),340-358.
19. Hirschi, Travis(1969).Causes of delinquency.Berkeley:University of California Press.
20. Jones, Adrian M.(2017).When in Rome: Testing the Moderating Influence of Neighborhood Composition on the Relationship between Self-Control and Juvenile Offending.Crime & Delinquency,63(7),759-785.
21. Kleiber, Christian,Zeileis, Achim(2016).Visualizing Count Data Regressions Using Rootograms.The American Statistician,70(3),296-303.
22. Lambert, Diane(1992).Zero-inflated Poisson Regression, with an Application to Defects in Manufacturing.Technometrics,34(1),1-14.
23. Lanza, Stephanie T.,Cooper, Brittany R.,Bray, Bethany C.(2014).Population Heterogeneity in the Salience of Multiple Risk Factors for Adolescent Delinquency.Journal of Adolescent Health,54(3),319-325.
24. MacDonald, John M.,Lattimore, P. K.(2010).Count Models in Criminology.Handbook of Quantitative Criminology,New York, NY:
25. Regan, Timothy,Tubman, Jonathan G.,Schwartz, Seth J.(2020).Relations among Externalizing Behaviors, Alcohol Expectancies and Alcohol Use Problems in a Multi-Ethnic Sample of Middle and High School Students.Substance Abuse: Research and Treatment,14,1-11.
26. Ridout, Martin,Hinde, John,Demétrio, Clarice G. B.(2001).A Score Test for Testing a Zero-inflated Poisson Regression Model against Zero-inflated Negative Binomial Alternatives.Biometrics,57(1),219-223.
27. Rydberg, Jason,Carkin, Danielle M.(2017).Utilizing Alternate Models for Analyzing Count Outcomes.Crime & Delinquency,63(1),61-76.
28. Simons, Jeffrey S.,Neal, Dan J.,Gaher, Raluca M.(2006).Risk for Marijuana-related Problems among College Students: An Application of Zero-inflated Negative Binomial Regression.The American Journal of Drug and Alcohol Abuse,32(1),41-53.
29. Stogner, John,Gibson, Chris L.(2011).The influence of health strain on the initiation and frequency of substance use in a national sample of adolescents.Journal of Drug Issues,41(1),69-93.
30. Vuong, Quang H.(1989).Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses.Econometrica,57,307-333.
31. Wagner, Brandie,Riggs, Paula,Mikulich-Gilbertson, Susan K.(2015).The Importance of Distribution-choice in Modeling Substance Use Data: A Comparison of Negative Binomial, Beta Binomial, and Zero-inflated Distributions.American Journal of Drug Alcohol Abuse,41(6),489-497.
32. Yang, Si,Harlow, Lisa L.,Puggioni, Gavino,Redding, Colleen A.(2017).A Comparison of Different Methods of Zero-inflated Data Analysis and an Application in Health Surveys.Journal of Modern Applied Statistical Methods,16(1),518-543.
33. 司法院，2019，少年事件處理法（https://law.moj.gov.tw/LawClass/LawAll.aspx?pcode=C0010011，取用日期：2021 年 7 月 31 日）。（Judicial Yuan, ROC (Taiwan), 2019, “Juvenile Justice Act.” https://law.moj.gov.tw/LawClass/LawAll.aspx?pcode=C0010011 (Date visited: July 31, 2021.)）
34. 行政院，2021，少年偏差行為預防及輔導辦法（https://law.moj.gov.tw/LawClass/LawAll.aspx?pcode=D0080209，取用日期：2021 年 7 月 31 日）。（Executive Yuan, ROC (Taiwan), 2021, “Plans for Counseling and Prevention of Juvenile Delinquency.” https://law.moj.gov.tw/LawClass/LawAll.aspx?pcode=D0080209 (Date visited: July 31,2021.)）
35. 吳武典, Wu-tien(1992)。偏差行為的診斷與輔導。現代教育，7(1)，17-26。
36. 周愫嫻, Sus-yan(2001)。愛上學的孩子，不會變壞嗎？論學校因素與青少年偏差行為之關係。應用心理研究，11，93-115。
37. 張琦, Chi(2018)。零膨脹次數資料分析在 R 程式的應用。教育研究月刊，290，114-126。
38. 許春金, Chuen-jim,吳奕嫺,Yi-xian,莊宜佳, Yi-chia,陳玉書, Yu-shu(2018)。家庭、機會與青少年偏差行為。青少年犯罪防治研究期刊，9(2)，57-117。
39. 郭玲玲, Ling-ling,董旭英, Yuk-ying(2020)。緊張因素、利社會行為與青少年偏差行為之研究。教育學報，48(2)，157-180。
40. 陳貞吟, Chen-yin,張楓明, Feng-ming,郭俊豪, Chun-hao(2018)。高中生知覺教師教學效能、學業自我效能與班級偏差行為關聯性之探討。青少年犯罪防治研究期刊，10(2)，1-42 42。
41. 游玉英, Yu-Ying,許全守, Chuan-Shou(2019)。從社會控制理論之觀點探討國中學生中輟預防之研究。犯罪與刑事司法研究，31，1-33。
42. 馮莉雅, Li-yia(1997)。國中學生偏差行為與社會控制因素之間相關研究—以高雄市為例。教育資料文摘，39(2)，171-192。
43. 齊力（編）, Li,董旭英（編）, Yuk-ying(2003).臺灣青少年偏差行為之剖析.高雄=Kaohsiung:復文=Fu Wen Books.
44. 劉俊良, Chun-liang(2019)。青少年依附關係與偏差行為之相關研究。樹德科技大學學報，21(2)，91-116。
45. 劉俊良, Chun-liang,張弘遠, Hong-yuan,陳意文, Yi-wen(2019)。父母管教方式與青少年偏差行為之相關研究。致理學報，39，419-458。
46. 蔡德輝, Te-hui,楊士隆, Shu-lung(2003).少年犯罪—理論與實務.臺北=Taipei:五南圖書=Wu Nan.