Substance use and its association with mental health among Swiss medical students: A cross-sectional study

Abstract

Background: Studies on mental health and substance use among medical students indicated worrying prevalence but have been mainly descriptive.

Aim: To evaluate the prevalence of substance use in a sample of medical students and investigate whether mental health variables have an influence on substance use.

Methods: The data were collected as part of the first wave of the ETMED-L, an ongoing longitudinal open cohort study surveying medical students at the University of Lausanne (Switzerland). N = 886 students were included and completed an online survey including measures of mental health (depression, suicidal ideation, anxiety, stress, and burnout) and use of and risk related with several substances (tobacco, alcohol, cannabis, cocaine, stimulants, sedatives, hallucinogens, opioids, nonmedical prescription drugs, and neuroenhancement drugs). We evaluated the prevalence of use of each substance and then tested the association between mental health and substance use in an Exploratory Structural Equation Modeling framework.

Results: Statistical indices indicated a four-factor solution for mental health and a three-factor solution for substance use. A factor comprising risk level for alcohol, tobacco, and cannabis use - which were the most prevalent substances - was significantly associated with a burnout factor and a factor related to financial situation and side job stress. There was a significant association between a factor comprising depression, anxiety, and suicidal ideation and a factor related to the use of sedatives, nonmedical prescription drugs and neuroenhancement drugs. Although their use was less prevalent, a factor comprising the risk level of stimulants and cocaine use was significantly but more mildly related to the burnout factor. A factor comprising stress related to studies and work/life balance as well as emotional exhaustion was not related to substance use factors.

Conclusion: In this sample of medical students, the prevalence of substance use was substantial and poorer mental health status was related with higher substance use risk levels.

Keywords: Exploratory Structural Equation Modeling; Mental health; medical students; substance use.

Figure 1.

Prevalence of substance use within the collected sample. Note. N = 886. Graph was enlarged for substances more scarcely used in order to show numbers which were otherwise on top of one another. Nonmedical prescription drugs and neuroenhancement drugs use prevalence was not measured with the same scale as the other substances (yearly prevalence versus. ASSIST frequency score, respectively, see methods).

Figure 2.

Exploratory structural equation model. Note. Modeled using maximum likelihood estimation with robust standard errors and oblique geomin rotation. N = 886. RMSEA = 0.022, CFI = 0.983, and SRMR = 0.024. Oval boxes indicate latent variables whereas rectangular boxes indicate observed variables used as indicators of the latent variables. Single-headed arrows from latent to observed indicators constitute the measurement model and reflect the factor loadings, that is, standardized regression coefficients from the latent variables to the observed indicators. Double-sided arrows indicate covariances between exogenous latent variables (i.e. M1–M4) and residual covariances between endogenous latent variables (i.e. S1–S3). Single-headed arrows between mental health latent variables and substance use latent variables indicate regression paths. Figure shows only significant standardized estimates (p < .05). As the nature of data is cross-sectional, significant estimates should not be interpretated as indicating causation. Academic Efficacy is a reversed dimension of burnout.