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Is marijuana really a gateway drug? A nationally representative test of the marijuana gateway hypothesis using a propensity score matching design

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Abstract

Marijuana use has been proposed to serve as a “gateway” that increases the likelihood that users will engage in subsequent use of harder and more harmful substances, known as the marijuana gateway hypothesis (MGH). The current study refines and extends the literature on the MGH by testing the hypothesis using rigorous quasi-experimental, propensity score-matching methodology in a nationally representative sample. Using three waves of data from the National Longitudinal Study of Adolescent to Adult Health (1994–2002), eighteen propensity score-matching tests of the marijuana gateway hypothesis were conducted. Six of the eighteen tests were statistically significant; however, only three were substantively meaningful. These three tests found weak effects of frequent marijuana use on illicit drug use but they were also sensitive to hidden bias. Results from this study indicate that marijuana use is not a reliable gateway cause of illicit drug use. As such, prohibition policies are unlikely to reduce illicit drug use.

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Notes

  1. Additionally, included wave IV would add a substantial amount of length to the manuscript.

  2. Readers may consult the documentation provided by the Add Health study at their website (see the Appendix 1).

  3. See Appendix 1 for the list of the covariates used in this study. Information on how survey items were measured, response options, and descriptive statistics for each wave are readily available at the Add Health website. Refer to Appendix 1 for appropriate Internet links.

  4. However, it seems that the statistically significant relationships between marijuana use and heavy drug use found in this analysis are differentially affected when considering these missing data. The correlation between recreational marijuana use at wave 1 and heavy illicit drug use at wave 3 reduced from .06 to .03 when missing values on cold relationship with the father were taken into account. This correlation reduced to .045 when missing values on father’s education was taken into account. The correlation between heavy marijuana use at wave 2 and light illicit drug use at wave 3 reduced from .14 to .08 when missing values on condition of the neighborhood were taken into account. The significant results found in Tables 3 and 4 should be interpreted with caution.

  5. Histograms are not recreated here to save space but are available upon request.

  6. ATT = E[{E[Yi\P(Xi),Di = 1] − E[Yi\P(Xi),Di = 0]}\Di = 1]

  7. These findings may be biased due to missing data on cold relationship with the father and father’s education.

  8. The correlation between heavy marijuana use and illicit drug use changes based on missing data according to neighborhood condition. This finding should be interpreted with caution.

  9. Using illicit drugs was a rare event in the sample. The large majority of respondents did not use illicit drugs. As such, there were excessive zeros in the dependent variables. Subsequent analysis on the matched samples examined whether the excessive zeros would bias the results of the propensity score models. The findings from the subsequent analysis were generally similar to those of the propensity score models. However, some differences were observed. Heavy marijuana use was not significantly related to heavy illicit drug use at any wave. Additionally, heavy marijuana use at W1 was weakly associated with light illicit drug use at W2, and having used marijuana at all in the last 30 days at W1 was weakly associated with light illicit drug use at W3. We interpret these results as generally congruent to the results of the propensity score models.

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Authors and Affiliations

  1. Boise State University, University Drive, Mail Stop 1955, Boise, Idaho, 83725-1955, USA

    Cody Jorgensen Ph.D & Jessica Wells Ph.D

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  1. Cody Jorgensen Ph.D
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  2. Jessica Wells Ph.D
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Correspondence to Cody Jorgensen Ph.D.

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Appendix 1. Vector of covariates

Appendix 1. Vector of covariates

Gender

Age

Age squared

Ethnicity

Grade in school

Ever been suspended from school

Mother’s education

Father’s education

Neighborhood condition

Urbanity

Perception of living in a safe neighborhood

How often respondents hang out with friends

Relationship with the mother

Relationship with the father

Frequency of feeling depressed

Drug use in the home

Frequency of tobacco use

Frequency of alcohol use

Ever been high at school

Frequency of vandalism

Importance of religion

Frequency of prayer

Suicidal feelings

Perception of intelligence

Reliance on gut feelings

Frequency of being upset by difficult problems

Perception of having good qualities

Frequency of shoplifting

Frequency of running away from home

Frequency of burglary

Frequency of robbery

Frequency of selling drugs

Frequency of taking part in a group fight

Frequency of theft

Readers are advised to consult the Add Health website to view the survey item wording, response options, and descriptive statistics for each covariate at each wave of data collection. This information can be accessed via the links below:

https://addhealth.cpc.unc.edu/documentation/codebooks/

https://addhealth.cpc.unc.edu/wp-content/uploads/docs/documentations/ACE_Instructions_2015-05-12_scd.pdf

https://addhealth.cpc.unc.edu/documentation/codebook-explorer/#/

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Jorgensen, C., Wells, J. Is marijuana really a gateway drug? A nationally representative test of the marijuana gateway hypothesis using a propensity score matching design. J Exp Criminol 18, 497–514 (2022). https://doi.org/10.1007/s11292-021-09464-z

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