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Paper ID:IJSREM66382

DETERMINANTS AND STRUCTURAL PATHWAYS OF AWARENESS ON DRUG ABUSE PREVENTION AMONG COLLEGE STUDENTS: A MULTIPLE REGRESSION, STRUCTURAL EQUATION MODELLING AND GARRETT RANKING ANALYSIS — A STUDY IN ERODE DISTRICT OF TAMIL NADU

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM66382

Volume:

10 |

7 |

Jul 2026

Pages:

1-10

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM66382

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

Dr.K.Gunasundari

Dr.K.Gunasundari

Department of B.Com(E-Commerce)

Vellalar College for Women(Autonomous), Erode, Tamilnadu, India

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Dr.P.Parimaladevi

Dr.P.Parimaladevi

Department of B.Com(E-Commerce)

Vellalar College for Women(Autonomous), Erode, Tamilnadu, India

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Abstract

While general awareness of drug abuse is widely reported among college students, the specific socio-economic determinants of awareness regarding prevention and control measures, and the causal pathways linking these determinants to overall awareness, remain comparatively under-examined in the Indian context. This study models these pathways among college students in Erode District, Tamil Nadu, using data collected from 600 respondents selected through stratified random sampling from engineering, arts and science, medical, pharmacy, polytechnic, and teacher-education colleges. Multiple Regression Analysis, Structural Equation Modelling (SEM), and the Henry Garrett Ranking Technique were applied to identify predictors, model structural relationships, and rank the perceived reasons behind student drug use, respectively. The regression model explains 57.2 per cent of the variation in awareness on prevention and control measures (R = 0.756, R² = 0.572, F = 71.26, p < 0.001), with stream of study, educational qualification of parents, monthly family income, and parental occupation emerging as the strongest predictors; gender and family size were statistically non-significant. The SEM model demonstrated good fit (CMIN/df = 2.684, GFI = 0.928, CFI = 0.947, RMSEA = 0.054), confirming significant structural pathways from socio-economic factors through awareness on causes and effects to prevention measures and overall awareness, with the prevention-to-overall-awareness path showing the strongest standardised estimate (β = 0.792). The Garrett Ranking analysis identified peer pressure/friends' influence (mean score 77.13) and stress/exam pressure (mean score 73.10) as the two most important perceived reasons for drug use initiation among students. The study concludes that awareness-building interventions are most effective when they combine socio-economic targeting with structured peer- and stress-focused prevention content, and recommends a layered, evidence-based model for designing college-based drug abuse prevention programmes.

KEYWORDS

Drug Abuse Prevention Structural Equation Modelling Multiple Regression Henry Garrett Ranking College Students Erode District Awareness Substance Abuse

Cite This Article

Dr.K.Gunasundari, Dr.P.Parimaladevi, "DETERMINANTS AND STRUCTURAL PATHWAYS OF AWARENESS ON DRUG ABUSE PREVENTION AMONG COLLEGE STUDENTS: A MULTIPLE REGRESSION, STRUCTURAL EQUATION MODELLING AND GARRETT RANKING ANALYSIS — A STUDY IN ERODE DISTRICT OF TAMIL NADU," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 7, pp. 1-10, Jul 2026. https://doi.org/10.55041/IJSREM66382

Full Article/Conclusion

This study moves beyond descriptive assessment to model the determinants and structural pathways underlying awareness on drug abuse prevention among college students in Erode District. The Multiple Regression Analysis confirms that stream of study, parental education, family income, and parental occupation are the strongest socio-economic predictors of prevention-related awareness, while the Structural Equation Model validates a sequential, mediated pathway in which awareness of causes and effects together shape prevention-focused awareness, which in turn is the strongest driver of students' overall awareness level. The Henry Garrett Ranking Technique further clarifies that, from students' own perspective, peer pressure and academic stress — not the mere availability of drugs — are the dominant reasons behind drug use initiation. Taken together, these findings suggest that the most effective prevention strategies for college students in the district will be those that combine socio-economically targeted outreach with structured, staged awareness-building content and psychosocial interventions addressing peer influence and stress, rather than generic, availability-focused, or one-time awareness campaigns.

References

1.      Ardra, P.P., Ranalin, V. P., Raga Jyothi (2025), “Alcohol and Drug Abuse Among Youth: Causes, Effects, and Control”, TIJER – International Research Journal, Vol.12, Issue 3, pp.123-126. 2.      Hemamalini, M., E. Elamathi, S. Rajathi and K. Narayanasamy (2025), “Impact of Substance Abuse among Adolescents: A Narrative Review”, International Journal of Community Medicine and Public Health, Vol.12, No.10, pp.4812-4818. 3.      Sakshi Sharma, Safira Kabir, Hilal Ahmad Dar, Azra Qureshi, Naila Kousar (2024), “Drug Abuse among Youth: A Socio-Demographic Analysis of Patients at D-Dwari De-Addiction Center, Samba District, Jammu”, Frontiers in Health Informatics, Vol.13, Issue 3, pp.5383-5395. 4.      Bentler, P. M. (1990), Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246. 5.      Byrne, B. M. (2016), Structural equation modeling with AMOS: Basic concepts, applications, and programming (3rd ed.). Routledge. 6.      Chandra, P. S., Sarkar, S., Ambekar, A., & Basu, D. (2019). Substance use disorders among youth in India: Current status and future directions. Indian Journal of Psychiatry, 61(Suppl 4), S780–S787. 7.      Garrett, H. E., & Woodworth, R. S. (1969). Statistics in psychology and education. Vakils, Feffer & Simons. 8.      Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019), Multivariate data analysis (8th ed.). Cengage Learning. 9.      Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis. Structural Equation Modeling, 6(1), 1–55. 10.   Kumar, V., & Sekar, K. (2018), Socio-demographic correlates of substance use awareness among adolescents in Tamil Nadu. Indian Journal of Social Psychiatry, 34(2), 145–151.

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Publication Date

7/28/2026

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