第六十九輯．第一期（Open Access） - 2023-03-31

接觸偏差同儕對偏差行為影響的決策——動機內在歷程分析

An Analysis of Inner Decision Making-Motivational Process Underlying the Effects of Attachment to Deviant Peers on Individual Deviance

作　者：
吳中勤 / Chung-Chin Wu
關鍵字：
中介分析、決策、偏差行為、動機、接觸偏差同儕 / attachment to deviant peers, decision making, deviance, mediation analysis, motivation
  • 摘要
  • 英文摘要
  • 參考文獻
  • 全文下載
青少年偏差行為可能受到偏差同儕、認知—情緒歷程失衡與行為動機的影響。本研究主要目的有二：一、編製信、效度良好的偏差行為趨避動機測量工具。二、整合社會心理學理論與認知神經科學觀點，提出偏差行為的決策－動機歷程模式，釐清該模式是否適合用來解釋青少年從事偏差行為背後的內在歷程。本研究以八年級學生為對象，進行多層次結構方程中介分析發現：一、偏差行為趨避動機測量具有良好的信、效度。二、接觸偏差同儕對偏差行為的效果，除了社會情境具有最大的直接影響外，青少年對接觸偏差同儕或從事偏差行為可能帶來的獲益評估，其影響居次，正、負向情緒也解釋了背後部分的內在歷程，且情緒的影響與獲益評估相當。三、損失評估與趨避動機未能解釋接觸偏差同儕對偏差行為影響的內在歷程。
Juvenile deviance is influenced by the attachment to deviant peers, the unbalanced interplay between cognition and emotion, and behavioral motivation. The purposes of this study are as follows: (1) to develop a reliable and valid measurement for the approach and avoidance motivation of deviance; (2) to propose a decision makingmotivational process model which incorporates sociopsychological and cognitive neuroscience theories to clarify its appropriateness to account for the inner process of juvenile deviance. Eighth-grade students consented to participate in this study, and multilevel mediation SEM analysis was used to analyze the data. The results showed: (1) the measurement of approach and avoidance motivation of deviance demonstrated good reliability and validity; (2) the attachment to deviant peers is the most influential social factor of juvenile deviance, followed by evaluations of potential benefits, as well as positive and negative emotions, with benefits and emotions showing equivalent effects; and (3) the evaluation of losses, approach and avoidance motivation failed to account for the inner process of the effect of attachment to deviant peers on juvenile deviance.

王麗斐、李旻陽、羅明華（2013）。WISER生態系統合作觀的雙師合作策略。輔導季刊，49

　　（3），2-12。

[Wang, L.-F., Li, M.-Y., & Lo, M.-H. (2013). WISER teacher-paired cooperation strategy of ecosystem

　　cooperation viewpoint. Guidance Quarterly, 49(3), 2-12.]

吳中勤（2017）。接觸偏差同儕對偏差行為影響之理論模式的衡鑑。中華輔導與諮商學報，50，

　　63-87。https://doi.org/10.3966/172851862017120050003

[Wu, C.-C. (2017). Evaluating the theoretical model for effects of associated with deviant peer on

　　individual deviance. Chinese Journal of Guidance and Counseling, 50, 63-87. https://doi.org/10.3966/

　　172851862017120050003]

吳中勤（2019）。偏差行為的社會益損評估量表之發展與衡鑑。中華輔導與諮商學報，55，97-

　　121。https://doi.org/10.3966/172851862019050055004

[Wu, C.-C. (2019). Evaluating the theoretical model for effects of associated with deviant peer on

　　individual deviance. Chinese Journal of Guidance and Counseling, 55, 97-121. https://doi.org/10.

　　3966/172851862019050055004]

吳中勤（2021）。探究認知與情緒歷程對青少年偏差行為的影響：雙重系統理論觀點的檢驗與修

　　正。教育學報，49（1），187-209。

[Wu, C.-C. (2021). Investigating the effects of cognitive and emotional process on juvenile deviant

　　behaviors: Examination and revision of dual system theory. Education Journal, 49(1), 187-209.]

董旭英（2009）。生活壓迫事件、社會支持、社會心理特質與台灣都會區國中生偏差行為之關係。

　　青少年犯罪防治研究期刊，1（1），129-164。

[Tung, Y.-Y. (2009). Relationships among coercion, social support, social-psychological

　　characteristics and delinquency of junior high school students in Taiwan metropolitan areas. Journal

　　of Research in Delinquency and Prevention, 1(1), 129-164.]

謝曜任（2013）。從WISER模式談專任輔教師的角色與功能。輔導季刊，49（3），13-18。

[Hsieh, Y.-J. (2013). Talking about role and function of counselling teachers through WISER model.

　　Guidance Quarterly, 49(3), 13-18.]

Agnew, R. (1991). A longitudinal test of social control theory and delinquency. Journal of Research in

　　Crime and Delinquency, 28(2), 126-156. https://doi.org/10.1177/0022427891028002002

Agnew, R. (1992). Foundation for a general strain theory of crime and delinquency. Criminology, 30(1),

　　47-88. https://doi.org/10.1111/j.1745-9125.1992.tb01093.x

Agnew, R. (1993). Why do they do it? An examination of the intervening mechanisms between “social-

　　control” variables and delinquency. Journal of Research in Crime and Delinquency, 30(3), 245-266.

　　https://doi.org/10.1177/0022427893030003001

Agnew, R. (2001). Building on the foundation of general strain theory: Specifying the types of strain most

　　likely to lead to crime and delinquency. Journal of Research in Crime and Delinquency, 38(4), 319-

　　361. https://doi.org/10.1177/0022427801038004001

Agnew, R., & Brezina, T. (2019). General strain theory. In M. D. Krohn, N. Hendrix, G. P. Hall, & A. J.

　　Lizotte (Eds.), Handbook on crime and deviance (pp. 145-160). Springer.

Akers, R. L., & Jennings, W. G. (2019). The social learning theory of crime and deviance. In M. D. Krohn,

　　N. Hendrix, G. P. Hall, & A. J. Lizotte (Eds.), Handbook on crime and deviance (pp. 113-129).

　　Springer.

Akers, R. L., & Sellers, C. S. (2009). Criminological theories: Introduction, evaluation, and application.

　　Oxford.

Andrews, J. L., Ahmed, S. P., & Blakemore, S. J. (2021). Navigating the social environment in

　　adolescence: The role of social brain development. Biological Psychiatry, 89(2), 109-118. https://

　　doi.org/10.1016/j.biopsych.2020.09.012

Arnett, P. A., Smith, S. S., & Newman, J. P. (1997). Approach and avoidance motivation in psychopathic

　　criminal offenders during passive avoidance. Journal of Personality and Social Psychology, 72(6),

　　1413-1428. https://doi.org/10.1037/0022-3514.72.6.1413

Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of

　　Marketing Science, 16(1), 74-94. https://doi.org/10.1007/BF02723327

Bechara, A., & Damasio, A. R. (2005). The somatic marker hypothesis: A neural theory of economic

　　decision. Games and Economic Behavior, 52(2), 336-372. https://doi. org/10.1016/j.geb.2004.06.010

Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994). Insensitivity to future consequences

　　following damage to human prefrontal cortex. Cognition, 50(1-3), 7-15. https://doi.org/10.1016/0010-

　　0277(94)90018-3

Bechara, A., Damasio, H., Damasio, A. R., & Lee, G. P. (1999). Different contributions of the human

　　amygdala and ventromedial prefrontal cortex to decision-making. Journal of Neuroscience, 19(13),

　　5473-5481. https://doi.org/10.1523/JNEUROSCI.19-13-0547.1999

Bechara, A., Dolan, S., Denburg, N., Hindes, A., Anderson, S. W., & Nathan, P. E. (2001). Decision-

　　malting deficits, linked to a dysfunctional ventromedial prefrontal cortex, revealed in alcohol and

　　stimulant abusers. Neuropsychologia, 39(4), 376-389. https://doi. org/10.1016/s0028-3932(00)00

　　136-6

Bechara, A., Tranel, D., Damasio, H., & Damasio, A. R. (1996). Failure to respond autonomically to

　　anticipated future outcomes following damage to prefrontal cortex. Cerebral Cortex, 6(2), 215-225.

　　https://doi.org/10.1093/cercor/6.2.215

Burdick, J. D., Roy, A. L., & Raver, C. C. (2013). Evaluating the Iowa Gambling Task as a direct

　　assessment of impulsivity with low-income children. Personality and Individual Differences, 55(7),

　　771-776. https://doi.org/10.1016/j.paid.2013.06.009

Burnett, S., Bault, N., Coricelli, G., & Blakemore, S. J. (2010). Adolescents’ heightened riskseeking in a

　　probabilistic gambling task. Cognitive Development, 25(2), 183-196. https:// doi.org/10.1016/j.

　　cogdev.2009.11.003

Burt, C. H., Simons, R. L., & Simons, L. G. (2006). A longitudinal test of the effects of parenting and the

　　stability of self-control: Negative evidence for the general theory of crime. Criminology, 44(2), 353-

　　396. https://doi.org/10.1111/j.1745-9125.2006.00052.x

Carver, C. S., Sutton, S. K., & Scheier, M. F. (2000). Action, emotion, and personality: Emerging

　　conceptual integration. Personality and Social Psychology Bulletin, 26(6), 741-751. https://doi.org/

　　10.1177/0146167200268008

Casey, B. J., Getz, S., & Galvan, A. (2008). The adolescent brain. Developmental Review, 28(1), 62-77.

　　https://doi.org/10.1016/j.dr.2007.08.003

Cauffman, E., Shulman, E. P., Steinberg, L., Claus, E., Banich, M. T., Graham, S., & Woolard, J. (2010).

　　Age differences in affective decision making as indexed by performance on the Iowa Gambling Task.

　　Developmental Psychology, 46(1), 193-207. https://doi.org/10.1037/a0016128

Church, W. T., Wharton, T., & Taylor, J. K. (2008). Examination of differential association and social

　　control theory: Family systems and delinquency. Youth Violence and Juvenile Justice, 7(1), 3-15.

Ciranka, S., & van den Bos, W. (2019). Social influence in adolescent decision-making: A formal

　　framework. Frontiers in Psychology, 10, 1915. https://doi.org/10.3389/fpsyg.2019.01915

Coyle, S., Cipra, A., & Rueger, S. Y. (2021). Bullying types and roles in early adolescence: Latent classes

　　of perpetrators and victims. Journal of School Psychology, 89(2), 51-71. https://doi.org/10.1016/j.jsp.

　　2021.09.003

Corr, P. J., & McNaughton, N. (2012). Neuroscience and approach/avoidance personality traits: A two stage

　　(valuation-motivation) approach. Neuroscience and Biobehavioral Reviews, 36(10), 2339-2354. https:

　　//doi.org/10.1016/j.neubiorev.2012.09.013

De Pascalis, V., Cozzuto, G., Caprara, G. V., & Alessandri, G. (2013). Relations among EEGalpha

　　asymmetry, BIS/BAS, and dispositional optimism. Biological Psychology, 94(1), 198-209. https://

　　doi.org/10.1016/j.biopsycho.2013.05.016

Defoe, I. N., Dubas, J. S., Figner, B., & van Aken, M. A. G. (2015). A meta-analysis on age differences in

　　risky decision making: Adolescents versus children and adults. Psychological Bulletin, 141(1), 48-84.

　　https://doi.org/10.1037/a0038088

Durkin, K. F., Wolfe, T. W., & Clark, G. A. (2005). College students and binge drinking: An evaluation of

　　social learning theory. Sociological Spectrum, 25(3), 255-272. https://doi.org/10.1080/

　　027321790518681

Dyer, N. G., Hanges, P. J., & Hall, R. J. (2005). Applying multilevel confirmatory factor analysis

　　techniques to the study of leadership. The Leadership Quarterly, 16(1), 149-167. https://doi.

　　org/10.1016/j.leaqua.2004.09.009

Elliot, A. J., & Church, M. A. (1997). A hierarchical model of approach and avoidance achievement

　　motivation. Journal of Personality and Social Psychology, 72(1), 218-232. https://doi.org/10.

　　1037//0022-3514.72.1.218

Eitle, T. M., Eitle, D., & Johnson-Jennings, M. (2013). General strain theory and substance use among

　　American indian adolescents. Race Justice, 3(1), 3-30. https://doi.org/10.1177/2153368712460553

Elliot, A. J., & Thrash, T. M. (2002). Approach-avoidance motivation in personality: Approach and

　　avoidance temperaments and goals. Journal of Personality and Social Psychology, 82(5), 804-818.

　　https://doi.org/10.1037/0022-3514.82.5.804

Figner, B., Mackinlay, R. J., Wilkening, F., & Weber, E. U. (2009). Affective and deliberative processes in

　　risky choice: Age differences in risk taking in the Columbia Card Task. Journal of Experimental

　　Psychology: Learning Memory and Cognition, 35(3), 709-730. https://doi.org/10.1037/a0014983

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and

　　measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.2307/3151312

Froggio, G. (2007). Strain and juvenile delinquency: A critical review of Agnew’s general strain theory.

　　Journal of Loss & Trauma, 12(4), 383-418. https://doi.org/10.1080/15325020701249363

Gao, Y., Wong, D. S. W., & Yu, Y. (2016). Maltreatment and delinquency in China: Examining and

　　extending the intervening process of general strain theory. International Journal of Offender

　　Therapy and Comparative Criminology, 60(1), 38-61. https://doi.org/10.1177/0306624X14547495

Gardner, M., & Steinberg, L. (2005). Peer influence on risk taking, risk preference, and risky decision

　　making in adolescence and adulthood: An experimental study. Deviant Psychology, 41(4), 625-635.

　　https://doi.org/10.1037/0012-1649.41.4.625

Gupta, R., Koscik, T. R., Bechara, A., & Tranel, D. (2011). The amygdala and decision-making.

　　Neuropsychologia, 49(4), 760-766. https://doi.org/10.1016/j.neuropsychologia.2010.09.029

Grant, S., Contoreggi, C., & London, E. D. (2000). Drug abusers show impaired performance in a

　　laboratory test of decision making. Neuropsychologia, 38(8), 1180-1187. https://doi.org/10.1016/

　　s0028-3932(99)00158-x

Hair, J. F., William, C. B., Babin, B. J., & Rolph, E. A. (2009). Multivariate data analysis (7thed.). Prentice

　　Hall.

Heck, R. H., & Thomas, S. L. (2009). An introduction to multilevel modeling techniques (2nded.).

　　Routledge.

Higgins, G. E., & Tewksbury, R. (2007). Sports fan binge drinking: An examination using low self-control

　　and peer association. Sociological Spectrum, 27(4), 389-404. https://doi.org/10.1080/0273217070131

　　3472

Hirschi, T. (1969). Causes of delinquency. University of California Press.

Hirschi, T. (2002). Causes of delinquency. Transaction.

Hollist, D. R., Hughes, L. A., & Schaible, L. M. (2009). Adolescent maltreatment, negative emotion, and

　　delinquency: An assessment of general strain theory and family-based strain. Journal of Criminal

　　Justice, 37(4), 379-387. https://doi.org/10.1016/j.jcrimjus.2009.06.005

Hox, J. J. (2010). Multilevel analysis: Techniques and applications. Routledge.

Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis:

　　Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1-55. https://doi.

　　org/10.1080/10705519909540118

Intravia, J., Jones, S., & Piquero, A. R. (2012). The roles of social bonds, personality, and perceived costs:

　　An empirical investigation into Hirschi’s “new” control theory.

International Journal of Offender Therapy and Comparative Criminology, 56(8), 1182-1200. https://doi.org

　　/10.1177/0306624X11422998

Jöreskog, K. G., & Sörbom, D. (1993). LISREL 8: Structural equation modeling with the

　　SIMPLIS command language. Scientific Software International.

Kim, Y. S. (2016). Examination of the relative effects of neighborhoods and schools on juvenile

　　delinquency: A multilevel cross-classified model approach. Deviant Behavior, 37(10), 1196-1214.

　　https://doi.org/10.1080/01639625.2016.1170537

Lilly, J. R., Cullen, F. T., & Ball, R. A. (2007). Crime in American society: Anomie and strain theories.

　　Sage.

Lüdtke, O., Marsh, H. W., Robitzsch, A., Trautwein, U., Asparouhov, T., & Muthén, B. O. (2008).

　　The multilevel latent covariate model: A new, more reliable approach to group-level effects in

　　contextual studies. Psychological Methods, 13(3), 203-229. https://doi.org/10.1037/ a0012869

Marsh, H. W., Muthen, B., Asparouhov, T., Ludtke, O., Robitzsch, A., Morin, A. J. S., & Trautwein, U.

　　(2009). Exploratory structural equation modeling, integrating CFA and EFA: Application to

　　students’ evaluations of university teaching. Structural Equation Modeling, 16(3), 439-476. https:

　　//doi.org/10.1080/10705510903008220

Matsueda, R. L., & Heimer, K. (1987). Race, family structure, and delinquency: A test of differential

　　association and social control theories. American Sociological Review, 52(6), 826-840. https://

　　doi.org/10.2307/2095837

Matsueda, R. L., Kreager, D. A., & Huizinga, D. (2006). Deterring delinquents: A rational choice model of

　　theft and violence. American Sociological Review, 71(1), 95-122. https://doi.org/10.1177/0003122406

　　07100105

Mazas, C. A., Finn, P. R., & Steinmetz, J. E. (2000). Decision-making biases, antisocial personality, and

　　early-onset alcoholism. Alcoholism-Clinical and Experimental Research,24(7), 1036-1040. https://

　　doi.org/10.1097/00000374-200007000-00014

Mehta, P. D., & Neale, M. C. (2005). People are variables too: Multilevel structural equations modeling.

　　Psychological Methods, 10(3), 259-284. https://doi.org/10.1037/1082-989x.10.3.259

Muthén, B., & Asparouhov, T. (2015). Causal effects in mediation modeling: An introduction with

　　applications to latent variables. Structural Equation Modeling, 22(1), 12-23. https://doi.org/10.

　　1080/10705511.2014.935843

Muthén, B. O., & Satorra, A. (1995). Complex sample data in structural equation modeling. Sociological

　　Methodology, 25, 267-316.

O’Brien, L., Albert, D., Chein, J., & Steinberg, L. (2011). Adolescents prefer more immediate rewards

　　when in the presence of their peers. Journal of Research on Adolescence, 21(4), 747-753. https://

　　doi.org/10.1111/j.1532-7795.2011.00738.x

Petry, N. M., Bickel, W. K., & Arnett, M. (1998). Shortened time horizons and insensitivity to future

　　consequences in heroin addicts. Addiction, 93(5), 729-738. https://doi.org/10.1046/j.1360-0443.

　　998.9357298.x

Pratt, T. C., & Cullen, F. T. (2000). The empirical status of Gottfredson and Hirschi’s general theory of

　　crime: A meta-analysis. Criminology, 38(3), 931-964. https://doi.org/10.1111/j.1745-9125.2000.

　　tb00911.x

Pratt, T. C., Cullen, F. T., Sellers, C. S., Winfree, L. T., Madensen, T. D., Daigle, L. E., Fearn, N E., & Gau,

　　J. M. (2010). The empirical status of social learning theory: A meta-analysis.Justice Quarterly, 27(6),

　　765-802. https://doi.org/10.1080/07418820903379610

Preacher, K. J. (2011). Multilevel SEM strategies for evaluating mediation in three-level data. Multivariate

　　Behavioral Research, 46(4), 691-731. https://doi.org/10.1080/00273171.2011.589280

Preacher, K. J., Zyphur, M. J., & Zhang, Z. (2011). Alternative methods for assessing mediation in

　　multilevel data: The advantages of multilevel SEM. Structural Equation Modeling, 18(2), 161-182.

　　https://doi.org/10.1080/10705511.2011.557329

Rebellon, C. J. (2012). Differential association and substance use: Assessing the roles of discriminant

　　validity, socialization, and selection in traditional empirical tests. European Journal of Criminology,

　　9(1), 73-96. https://doi.org/10.1177/1477370811421647

Sigfusdottir, I. D., Kristjansson, A. L., & Agnew, R. (2012). A comparative analysis of general strain theory.

　　Journal of Criminal Justice, 40(2), 117-127. https://doi.org/10.1016/j.jcrmjus.2012.01.001

Steinberg, L. (2008). A social neuroscience perspective on adolescent risk-taking. Developmental Review,

　　28(1), 78-106. https://doi.org/10.1016/j.dr.2007.08.002

Sun, I. Y., & Longazel, J. G. (2008). College students’ alcohol-related problems: A test of competing

　　theories. Journal of Criminal Justice, 36(6), 554-562. https://doi.org/10.1016/j.jcrimjus.2008.09.007

Telzer, E. H., van Hoorn, J., Rogers, C. R., & Do, K. T. (2018). Social influence on positive youth

　　development: A developmental neuroscience perspective. Advances in Child Development and

　　Behavior, 54, 215-258. https://doi.org/10.1016/bs.acdb.2017.10.003

van Hoorn, J., McCormick, E. M., Rogers, C. R., Ivory, S. L., & Telzer, E. H. (2018). Differential effects of

　　parent and peer presence on neural correlates of risk taking in adolescence. Social Cognitive and

　　Affective Neuroscience, 13(9), 945-955. https://doi.org/10.1093/scan/nsy071

van Hoorn, J., Shablack, H., Lindquist, K. A., & Telzer, E. H. (2019). Incorporating the social context into

　　neurocognitive models of adolescent decision-making: A neuroimaging metaanalysis. Neuroscience &

　　Biobehavioral Reviews, 101, 129-142. https://doi.org/10.1016/j.neubiorev.2018.12.024

Wang, J., & Wang, X. (2012). Structural equation modeling: Application using Mplus. Wiley.

Ward, B. W., & Gryczynski, J. (2009). Social learning theory and the effects of living arrangement on

　　heavy alcohol use: Results from a national study of college students. Journal of Studies on Alcohol

　　and Drugs, 70(3), 364-372. https://doi.org/10.15288/jsad.2009.70.364

Yang, F., Nelson-Gardell, D., & Guo, Y. (2018). The role of strains in negative emotions and bullying

　　behaviors of school-aged children. Children and Youth Services Review, 94, 290-297. https://doi.org/

　　10.1016/j.childyouth.2018.10.016

Zimmerman, G. M. (2010). Impulsivity, offending, and the neighborhood: Investigating the person-context

　　nexus. Journal of Quantitative Criminology, 26(3), 301-332. https://doi.org/10.1007/s10940-010-9096

　　-4

 

全文下載