Psychosocial distress is a stronger correlate of psychiatric symptom burden than cannabis dependence in young adults: a functional connectome and structural equation modeling study
Abstract
IntroductionCannabis is widely used among young adults and often viewed as a primary driver of adverse psychiatric and neural outcomes, yet the psychosocial and socioeconomic context in which use occurs is rarely modeled jointly with neural and behavioral measures.MethodsUsing the Human Connectome Project young-adult sample (analytic N = 1,010–1,016), we employed structural equation modeling to estimate the relative contributions of cannabis, latent psychosocial distress, socioeconomic status, and familial psychiatric risk to three indices of psychiatric symptom burden, while adjusting for polysubstance, alcohol, and nicotine exposure and for family clustering. Cannabis exposure was operationalized in parallel as DSM-IV dependence and as heavy use. Resting-state functional connectomes were examined using graph metrics and network-based statistics, and finite mixture models were used to test for discrete vulnerable subgroups.ResultsPsychosocial distress was the dominant predictor of psychiatric symptom burden across all three outcomes (standardized β = 0.41–0.70), substantially exceeding that of cannabis (total β = 0.05–0.19), which reached significance for only one outcome under the dependence definition. Larger unadjusted group differences (Cohen's d = 0.28–0.75) attenuated sharply once distress and demographic factors were modeled. Lower socioeconomic status and greater familial psychiatric risk were each associated with elevated distress, whereas cannabis was not (all indirect β ≤ 0.01, all confidence intervals spanning zero). Neither graph metrics nor the network-based statistic revealed an association between cannabis dependence and the functional connectome, despite approximately 80% power to detect d≈ 0.30, and the fitted finite mixture models did not identify a robust and interpretable cannabis-vulnerable subgroup.DiscussionIn a large young-adult sample, psychosocial context rather than cannabis exposure accounted for most of the explained variance in psychiatric symptom burden, and no cannabis-related signature was detectable in the functional connectome. The cross-sectional design cannot establish causal ordering, and because the distress and symptom measures share self-report method variance that the coarse binary exposure measures do not, the relative magnitudes should not be interpreted as a comparison of aetiological importance. These findings nonetheless suggest that risk models and neuroimaging analyses that omit psychosocial context may attribute to cannabis variance shared with distress, disadvantage, and familial risk.
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BibTeX
@article{mattie2026psychosocial,
title = {{Psychosocial distress is a stronger correlate of psychiatric symptom burden than cannabis dependence in young adults: a functional connectome and structural equation modeling study}},
author = {David Mattie and Jacob Levman},
journal = {Frontiers in Neuroscience},
year = {2026},
month = oct,
doi = {10.3389/fnins.2026.1922823},
url = {https://www.frontiersin.org/articles/10.3389/fnins.2026.1922823},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Psychosocial distress is a stronger correlate of psychiatric symptom burden than cannabis dependence in young adults: a functional connectome and structural equation modeling study
AU - David Mattie
AU - Jacob Levman
PY - 2026
DA - 2026/10/28
JO - Frontiers in Neuroscience
DO - 10.3389/fnins.2026.1922823
UR - https://www.frontiersin.org/articles/10.3389/fnins.2026.1922823
AB - IntroductionCannabis is widely used among young adults and often viewed as a primary driver of adverse psychiatric and neural outcomes, yet the psychosocial and socioeconomic context in which use occurs is rarely modeled jointly with neural and behavioral measures.MethodsUsing the Human Connectome Project young-adult sample (analytic N = 1,010–1,016), we employed structural equation modeling to estimate the relative contributions of cannabis, latent psychosocial distress, socioeconomic status, and familial psychiatric risk to three indices of psychiatric symptom burden, while adjusting for polysubstance, alcohol, and nicotine exposure and for family clustering. Cannabis exposure was operationalized in parallel as DSM-IV dependence and as heavy use. Resting-state functional connectomes were examined using graph metrics and network-based statistics, and finite mixture models were used to test for discrete vulnerable subgroups.ResultsPsychosocial distress was the dominant predictor of psychiatric symptom burden across all three outcomes (standardized β = 0.41–0.70), substantially exceeding that of cannabis (total β = 0.05–0.19), which reached significance for only one outcome under the dependence definition. Larger unadjusted group differences (Cohen's d = 0.28–0.75) attenuated sharply once distress and demographic factors were modeled. Lower socioeconomic status and greater familial psychiatric risk were each associated with elevated distress, whereas cannabis was not (all indirect β ≤ 0.01, all confidence intervals spanning zero). Neither graph metrics nor the network-based statistic revealed an association between cannabis dependence and the functional connectome, despite approximately 80% power to detect d≈ 0.30, and the fitted finite mixture models did not identify a robust and interpretable cannabis-vulnerable subgroup.DiscussionIn a large young-adult sample, psychosocial context rather than cannabis exposure accounted for most of the explained variance in psychiatric symptom burden, and no cannabis-related signature was detectable in the functional connectome. The cross-sectional design cannot establish causal ordering, and because the distress and symptom measures share self-report method variance that the coarse binary exposure measures do not, the relative magnitudes should not be interpreted as a comparison of aetiological importance. These findings nonetheless suggest that risk models and neuroimaging analyses that omit psychosocial context may attribute to cannabis variance shared with distress, disadvantage, and familial risk.
SN - 1662-453X
ER -