Validation of the General Decision Making in the Substance Use Instrument among Secondary School Students in Malaysia

Authors

  • Ahmad Jazimin Jusoh Universiti Pendidikan Sultan Idris Author
  • Mohammad Khatim Hasan Universiti Kebangsaan Malaysia Author
  • Raja Jamilah Raja Yusof Universiti Malaya Author
  • Helmi Norman Universiti Kebangsaan Malaysia Author
  • Suzaily Wahab Universiti Kebangsaan Malaysia Author

DOI:

https://doi.org/10.24036/ijplc.v2i4.32

Keywords:

Confirmatory Factor Analysis, Exploratory Factor Analysis, Decision Making, Substance Abuse, Drug Education

Abstract

The current research aimed to assess the validity of the decision-making process in the substance use instrument among secondary school students in Malaysia. This research used a survey research design. The current research participants were 211 secondary school students in Johor, Selangor, and Kedah, Malaysia. Two procedures were used to analyse the data: exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). EFA with comprehensive techniques that compromise parallel analysis and minimum average partial (MAP) yielded a 5-factor solution: avoidant decision making, rational decision making, spontaneous decision making, dependent decision making, and intuitive decision making. Furthermore, the factors attain a minimum standard of Communalities (.30 to 1.0) and factor loading (>.50). The structure of the instrument was then confirmed through Confirmatory factor analysis (CFA) with adequate fit indices such as RMSEA (<06 to .08), CFI, TLI (.80), and CMIN (<5). The instrument validation and reliability were tested through AVE, CR, and Cronbach's alpha.

References

Adam, N. F. M., Rusli, N. F. M., Salleh, N. S., Mokhtar, W. K. W., & Abdullah, S. (2022). Kensiu language preservation: An analysis based on the typological framework of language threats. Jundishapur Journal of Microbiology, 15(1), 2640-2659.

Alavi, M., Watson, R., Thapa, D. K., Hunt, G. E., Watson, R., & Cleary, M. (2020). Chi-square for model fit in confirmatory factor analysis. Journal of Advanced Nursing, 76(9), 2209–2211. https://doi.org/10.1111/jan.14399

Amemori, K., & Graybiel, A. M. (2012). Localised microstimulation of primate pregenual cingulate cortex induces negative decision-making. Nature Neuroscience, 15(5), 776–785. https://doi.org/10.1038/nn.3088

Anderson, C. (2003). The psychology of doing nothing: Forms of decision avoidance result from reason and emotion. Psychological Bulletin, 129(1), 139–167. https://doi.org/10.1037/0033-2909.129.1.139

Anderson, K., & Minke, K. M. (2007). Parent involvement in education: toward an understanding of parents’ decision making. Journal of Educational Research, 100(5), 311–323. https://doi.org/10.3200/joer.100.5.311-323

Anwar, M. (2018). Business model innovation and SMEs performance — does competitive advantage mediate? International Journal of Innovation Management, 22(07), 1850057. https://doi.org/10.1142/s1363919618500573

Auerswald, M., & Moshagen, M. (2019). How to determine the number of factors to retain in exploratory factor analysis: A comparison of extraction methods under realistic conditions. Psychological Methods, 24(4), 468–491. https://doi.org/10.1037/met0000200

Banseng, S., Sandai, R., & Rasool, S. (2021). Language of strata and expression in construction of sampi amongst iban community in malaysia. International Journal of Education, Information Technology, and Others, 4(3), 417-427. https://doi.org/10.5281/zenodo.5169017

Caron, P. (2019). Minimum average partial correlation and parallel analysis: The influence of oblique structures. Communications in Statistics - Simulation and Computation, 48(7), 2110–2117. https://doi.org/10.1080/03610918.2018.1433843

Chen, S., Yang, P., Chen, T., Su, H., Jiang, H., & Zhao, M. (2020). Risky decision-making in individuals with substance use disorder: A meta-analysis and meta-regression review. Psychopharmacology, 237(7), 1893–1908. https://doi.org/10.1007/s00213-020-05506-y

Credé, M., & Harms, P. D. (2019). Questionable research practices when using confirmatory factor analysis. Journal of Managerial Psychology, 34(1), 18–30. https://doi.org/10.1108/jmp-06-2018-0272

Currie, J., & MacLeod, W. B. (2020). Understanding doctor decision making: the case of depression treatment. Econometrica, 88(3), 847–878. https://doi.org/10.3982/ecta16591

Dash, G., & Paul, J. (2021). CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting. Technological Forecasting and Social Change, p. 173, 121092. https://doi.org/10.1016/j.techfore.2021.121092.

Department of Statistics Malaysia Official Portal. (2022). https://www.dosm.gov.my/v1/

Duarte, P., Palmeira, L., & Pinto-Gouveia, J. (2020). The three-factor eating questionnaire-r21: a confirmatory factor analysis in a Portuguese sample. Eating and weight disorders-studies on anorexia bulimia and obesity, 25(1), 247–256. https://doi.org/10.1007/s40519-018-0561-7

Finch, W. H. (2020). Using fit statistic differences to determine the optimal number of factors to retain in an exploratory factor analysis. Educational and Psychological Measurement, 80(2), 217–241. https://doi.org/10.1177/0013164419865769

Fisher, A., Mills, K. L., Teesson, M., & Marel, C. (2021). Shared decision‐making among people with problematic alcohol/other drug use and co‐occurring mental health conditions: A systematic review. Drug and Alcohol Review, 40(2), 307–324. https://doi.org/10.1111/dar.13149

Fooladvand, K., Borjali, A., Sabet, F. H., & Delavar, A. (2017). Decision-making styles and attitude towards substances: predictors of potential addiction in adolescents. Practice in Clinical Psychology. https://doi.org/10.18869/acadpub.jpcp.5.2.91

Goretzko, D., Pham, T., & Bühner, M. (2021). Exploratory factor analysis: Current use, methodological developments and recommendations for good practice. Current Psychology, 40(7), 3510–3521. https://doi.org/10.1007/s12144-019-00300-2

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

Hafnidar, H., Harniati, I., & Hailemariam, M. (2021). Students self-regulation: An analysis of exploratory factors of self-regulation scale. Spektrum: Jurnal Pendidikan Luar Sekolah (PLS), 9(2), 220-225. https://doi.org/10.24036/spektrumpls.v9i2.112589

Handrianto, C., Rahman, M. A., & Nengsih, Y. K. (2024). Bridging Theory and Practice: Crafting Blended Learning Communities for Empowering ELT Professionals in Indonesia in Education, Character, and Humanistic Pedagogy: Concept, Theory, and Applications. PT Mafy Media Literasi Indonesia.

Intahphuak, S., Lorga, T., & Tipwareerom, W. (2022). Community health nurses' perspective on the introduced rational drug use policy in primary care settings in Thailand: a descriptive qualitative study. Tropical Medicine and Infectious Disease, 7(10), 304. https://doi.org/10.3390/tropicalmed7100304

Jain, J. C., Walia, N., Kaur, M., & Singh, S. (2021). Behavioural biases affecting investors’ decision-making process: a scale development approach. Management Research Review, 45(8), 1079–1098. https://doi.org/10.1108/mrr-02-2021-0139

Kerwin, M. E., Kirby, K. C., Speziali, D., Duggan, M., Mellitz, C., Versek, B., & McNamara, A. (2015). What can parents do? A review of state laws regarding decision making for adolescent drug abuse and mental health treatment. Journal of Child & Adolescent Substance Abuse, 24(3), 166–176. https://doi.org/10.1080/1067828x.2013.777380

Knekta, E., Runyon, C. R., & Eddy, S. L. (2019). One size doesn’t fit all: using factor analysis to gather validity evidence when using surveys in your research. CBE- Life Sciences Education, 18(1), rm1. https://doi.org/10.1187/cbe.18-04-0064

Lim, S., & Jahng, S. (2019). Determining the number of factors using parallel analysis and its recent variants. Psychological Methods, 24(4), 452–467. https://doi.org/10.1037/met0000230

Lorenzo-Seva, U., & Ferrando, P. J. (2020). Unrestricted factor analysis of multidimensional test items based on an objectively refined target matrix. Behavior Research Methods. https://doi.org/10.3758/s13428-019-01209-1

Mata, D., Korpak, A. K., Macaulay, T., Dodge, B., Mustanski, B., & Feinstein, B. A. (2022). Substance use experiences among bisexual, pansexual, and queer (bi+) male youth: a qualitative study of motivations, consequences, and decision making. Archives of Sexual Behavior. https://doi.org/10.1007/s10508-022-02447-9

Matt, D. G. F., Banseng, S., & Gerry, D. (2022). Effect of wordwall in teaching malay literature component amongst form one students. International Journal of Education, Technology and Science, 2(3), 279-287.

Nasution, M. I., Fahmi, M., Jufrizen, Muslih, & Prayogi, M. A. (2020). The quality of small and medium enterprises performance using the Structural Equation Model-Part Least Square (SEM-PLS). Journal of Physics: Conference Series, 1477(5), 052052. https://doi.org/10.1088/1742-6596/1477/5/052052

O’Malley, P. (2019). Consuming risks: harm minimisation and the government of 'drug-users.’ Routledge EBooks, pp. 191–214. https://doi.org/10.4324/9780429427114-8

Ogunsanya, O. A., Aigbavboa, C., Thwala, D., & Edwards, D. (2019). Barriers to sustainable procurement in the Nigerian construction industry: an exploratory factor analysis. The International Journal of Construction Management, 22(5), 861–872. https://doi.org/10.1080/15623599.2019.1658697

Ramadhani, D., Kenedi, A. K., & Rafli, M. F. (2022). Advancement of STEM-based digital module to enhance HOTS of prospective elementary school teachers. Jurnal Pendidikan Progresif, 12(2), 981-993. http://dx.doi.org/10.23960/jpp.v12.i2.202245

Reyna, V. F., & Farley, F. (2006). Risk and rationality in adolescent decision making: Implications for theory, practice, and public policy. Psychological science in the public interest, 7(1), 1-44.

Rohe, K., & Zeng, M. (2020). Vintage Factor Analysis with Varimax Performs Statistical Inference. ArXiv (Cornell University). http://export.arxiv.org/pdf/2004.05387

Schildkamp, K. (2019). Data-based decision-making for school improvement: Research insights and gaps. Educational Research, 61(3), 257–273. https://doi.org/10.1080/00131881.2019.1625716

Schlag, A. K. (2020). Percentages of problem drug use and their implications for policy making: A review of the literature. Drug Science, Policy and Law, 6, 205032452090454. https://doi.org/10.1177/2050324520904540

Schreiber, J. B. (2021). Issues and recommendations for exploratory factor analysis and principal component analysis. Research in Social & Administrative Pharmacy, 17(5), 1004–1011. https://doi.org/10.1016/j.sapharm.2020.07.027

Scott, S. I., & Bruce, R. A. (1995). Decision-making style: the development and assessment of a new measure. Educational and Psychological Measurement, 55(5), 818–831. https://doi.org/10.1177/0013164495055005017

Shiv, B., Loewenstein, G., & Bechara, A. (2005). The dark side of emotion in decision-making: When individuals with decreased emotional reactions make more advantageous decisions. Cognitive Brain Research, 23(1), 85–92. https://doi.org/10.1016/j.cogbrainres.2005.01.006

Shrestha, N. (2021). Factor analysis as a tool for survey analysis. American Journal of Applied Mathematics and Statistics, 9(1), 4–11. https://doi.org/10.12691/ajams-9-1-2

Sung, H., & Richter, L. (2007). Rational choice and environmental deterrence in the retention of mandated drug abuse treatment clients. International Journal of Offender Therapy and Comparative Criminology, 51(6), 686–702. https://doi.org/10.1177/0306624x07299226

Taherdoost, H., Sahibuddin, S., & Jalaliyoon, N. (2014). Exploratory Factor Analysis; Concepts and Theory. HAL (Le Centre Pour La Communication Scientifique Directe).

Tavakol, M., & Wetzel, A. P. (2020). Factor Analysis: a means for theory and instrument development in support of construct validity. International Journal of Medical Education, 11, 245–247. https://doi.org/10.5116/ijme.5f96.0f4a

Wipulanusat, W., Panuwatwanich, K., & Stewart, R. A. (2017). Exploring leadership styles for innovation: an exploratory factor analysis. Engineering Management in Production and Services, 9(1), 7–17. https://doi.org/10.1515/emj-2017-0001

Yamamoto, D. J., Woo, C., Wager, T. D., Regner, M. F., & Tanabe, J. (2015). Influence of dorsolateral prefrontal cortex and ventral striatum on risk avoidance in addiction: A mediation analysis. Drug and Alcohol Dependence, 149, 10–17. https://doi.org/10.1016/j.drugalcdep.2014.12.026

Yoo, J., & Chon, K. (2008). Factors affecting convention participation decision-making: developing a measurement scale. Journal of Travel Research, 47(1), 113–122. https://doi.org/10.1177/0047287507312421

Zachry, J. E., Johnson, A. J., & Calipari, E. S. (2019). Sex differences in value-based decision making underlie substance use disorders in females. Alcohol and Alcoholism, 54(4), 339–341. https://doi.org/10.1093/alcalc/agz052

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Published

2025-12-31

How to Cite

Validation of the General Decision Making in the Substance Use Instrument among Secondary School Students in Malaysia. (2025). International Journal of Pedagogy and Learning Community (IJPLC), 2(4), 186-199. https://doi.org/10.24036/ijplc.v2i4.32