Differential associations of mental health, mild traumatic brain injury and substance use between male and female university students
Department of Psychology, York University, Toronto, Ontario, Canada
Department of Neurology, Division of Movement Disorders, Yale University School of Medicine, New Haven, Connecticut, United States of America
Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, Illinois, United States of America
Department of Psychology, University of the Fraser Valley, Abbotsford, British Columbia, Canada
University of Toronto, CANADA
Abstract
Background
More severe substance use, defined as higher scores on validated measures of problematic use, is increasing within young adult populations. Substance use has been associated with mild traumatic brain injury (mTBI) and elevated symptoms of depression and anxiety. We aimed to understand the relationship between these factors and sex differences in a university sample.
Method
894 university students (372 males and 522 females, aged 18–25 years) self-reported their mTBI history, substance use (Alcohol Use Disorders Identification Test (AUDIT) and the Cannabis Use Disorders Identification Test-Revised (CUDIT-R)), and psychological measures (Patient Health Questionnaire–9 (PHQ-9) and Generalized Anxiety Disorder–7 (GAD-7). Regression analyses examined whether the number of previous mTBIs was associated with increased cannabis (within the past six months) or alcohol use (within the past twelve months) severity. Logistic and linear regression models were used to explore how mTBI history, sex, and mental health symptoms relate to the likelihood and severity of cannabis and alcohol use and were also run separately by sex.
Results
Individuals with multiple mTBIs reported more problematic substance use and a higher number of substances used. Hazardous substance use, as defined by scores above AUDIT and CUDIT-R cut-offs, was associated with both a previous history of mTBI and greater scores on depression and anxiety measures. Individuals with higher scores on an anxiety measure were more likely to use cannabis, especially if they had a history of mTBI. A history of mTBIs and higher current depression scores among cannabis users was associated with more problematic cannabis use. Among alcohol-using individuals, those with higher depression scores in addition to a history of mTBI were more likely to endorse more problematic alcohol use. Finally, males and females were affected differently by mental health and mTBI risk factors.
Conclusion
mTBI history and mental health problems may be associated with hazardous substance use, but these findings highlight the importance of considering sex-specific risk patterns when developing interventions or preventive strategies for young adults with a history of mTBI or elevated anxiety/depression symptoms.
Article notes
Untitled section
Received 2025 May 14; Accepted 2026 Mar 21; Collection date 2026.
Introduction
Substance use is rising and becoming more common among emerging adults, typically defined as those aged 18–29 [1], with half of substance-using Canadian youth engaging in polysubstance use. Use of substances, and in particular alcohol and cannabis, is complex and carries significant treatment and health implications [2–6]. Alcohol and cannabis use and hazardous drug use behaviours, as indicated by higher scores on substance use measures, among emerging adults are associated with negative health outcomes, including poor mental health [7–12]; however, the directionality of this relationship is highly debated [13]. Substance use and mental health disorders share environmental and genetic risk factors, increasing the likelihood of experiencing both [14,15]. For example, the self-medication hypothesis suggests that substance use is a coping mechanism for psychological stressors [14], whereas substance use and its sequelae may also induce additional mental health problems [15].
A history of mild traumatic brain injury(mTBI), as defined as a head injury resulting in loss of consciousness for less than 30 minutes, post-traumatic amnesia lasting less than 24 hours, and a Glasgow Coma Scale score of 13–15, has also been suggested as a predisposing risk factor for substance use and mood problems; however, more research is needed to better understand the mechanisms driving the relationships and their directionality [16–19]. Disruptions to neural pathways resulting from an mTBI may affect frontal brain regions involved in decision-making [20] and emotional regulation [21], which, in turn, may increase vulnerability to substance misuse as well as the increased likelihood of mental health problems. The relationship between mTBI, substance use, and mental health is complex, with prior research demonstrating that both mTBI and mental health uniquely contribute to substance use habits [22]. Further, while disruption of brain regions mediating risk-taking behaviour are proposed to contribute to increased substance use, it is also suggested that mTBI may influence substance use habits indirectly via mood disorders [23]; for example, individuals with mTBI who develop symptoms of depression or anxiety may engage in increased alcohol or cannabis use as a means of coping with emotional distress or physical and cognitive changes.
Untangling the associations between health factors and substance use in young adulthood is critical for early intervention and reducing the likelihood of continued substance use into later adulthood. In developing effective intervention programs, it is also important to consider how these factors may differentially affect males and females. Sex differences have been noted across substance use, mental health problems such as depression and anxiety, and mTBI. For example, adolescent males are more likely to engage in substance use [24] and transition to more risky substance use behaviour, including earlier onset, higher frequency of use, polysubstance use, and use of illicit drugs, than females [24,25], whereas females are more likely to suffer from mental health problems such as depression and anxiety [26]. Females may also have increased vulnerability to sustaining an mTBI [i.e., may be more likely to suffer an mTBI from a similar head impact due to physical differences, such as smaller neck size supporting head during impact, and hormonal differences] and research shows that females typically experience greater symptomology and may have longer recovery trajectory following an mTBI [27–33]. Recent literature has also shown that females with mTBI, especially those with repetitive injuries, reported significantly higher symptom burden, including post-concussive, PTSD, and anxiety symptoms, compared to men [34]. Despite sex differences in these risk factors, there is a lack of individualized treatment for males and females. Current treatment for mTBI typically involves rest, gradual return to activity, and symptom monitoring, but these approaches are generally standardized and do not account for sex-based differences in symptom presentation or recovery trajectories [35].
The aim of this study was to investigate how mental health and mTBI history are associated with recent patterns of substance use using regression models. Given the established sex differences in both substance use patterns and mental health outcomes, as well as possible differences in vulnerability to a recovery from mTBI, it is crucial to examine whether these relationships differ between males and females. To address this, we specifically used sex-based models to explore potential sex-specific variations in these interactions.
Methods
Participants
Ethics was approved by the Human Participants Review Sub-Committee of York University’s Ethics Review Board. Data collection began on September 1, 2025, and written informed consent was obtained through the digital questionnaire. Data were collected from 894 York University students through the undergraduate research participant pool in psychology or kinesiology who received partial course credit for their participation. Participants were eligible if: 1) they were between the ages of 17 and 25 and 2) were registered students in the Introduction to Psychology course.
Measures
Alcohol use disorder identification test (AUDIT).
The AUDIT [36] is a 10-item screening index that was used to assess alcohol use in the past year. This questionnaire was designed for self-administration and is scored by adding each of the 10 items: questions 1–8 are scored on a 0–4 scale, questions 9 and 10 are scored 0, 2 or 4. Total scores of 0–7 indicate low risk, 8–15 indicate medium risk, 16–19 indicate high risk, and 20–40 points indicates likely alcohol addiction. Given that a large proportion of our sample indicated abstinence from alcohol in the past year, participants were considered alcohol users if they indicated any alcohol use in the past year. To better understand factors contributing to the degree of alcohol use, some analyses looked at total AUDIT scores solely within the alcohol use group.
Cannabis use disorder identification test-revised (CUDIT-R).
The CUDIT-R [37] is an 8-item screening index used to assess cannabis use in the past six months that can be administered to individuals who indicate cannabis use within the last six months. This questionnaire was designed for self-administration and is scored by adding each of the 8 items: questions 1–7 are scored on a 0–4 scale, question 8 is scored 0, 2, or 4. Scores of 8 or more indicate hazardous cannabis use, while scores of 12 or more indicate a possible cannabis use disorder for which further intervention may be required. Participants were considered cannabis users if they indicated any use of cannabis in the past six months. To better understand factors contributing to the degree of cannabis use, some analyses looked at total CUDIT-R scores solely within the cannabis use group.
Substance use history.
Participants answered questions about their substance use history, which inquired about current use of various substances in the past year (“Have you ever used ____” and “How often have you used ____ in the past year”) including tobacco/nicotine (including vaporizers), prescribed opioids/opioids in general, stimulants (e.g., cocaine, Adderall), steroids, and “other”. To provide data for an exploratory analysis of “polysubstance use”, the number of categories of substances used was included as a variable by summing the number of different types of substances used in the past year, including the above categories as well as cannabis and alcohol.
Patient health questionnaire-9 item (PHQ-9).
The PHQ-9 [38] is a screening tool derived from the Patient Health Questionnaire. The PHQ-9 is a brief self-report measure that evaluates 9 criteria for depressive disorders based on DSM-IV criteria. This self-administered tool assesses how often individuals were bothered by items over the last two weeks. Questions are scored on a 4-point ordinal scale (0; not at all, 1; several days, 2; more than half the days, 3; nearly every day). Total scores of 0–4 indicate none, 5–9 indicate mild depression, 10–14 indicate moderately severe depression, and 20–47 indicate severe depression. Possible major depressive disorder (MDD) was characterized by 5 or more items endorsed at least “more than half the days” or if items 1 or 2 are endorsed as at least “more than half the days”.
Generalized anxiety disorder-7 item (GAD-7).
The GAD-7 [39] is a well-validated, 7-item questionnaire to assess self-reported anxiety. This self-administered tool assesses how often individuals were bothered by items over the last two weeks. Questions are scored on a 4-point ordinal scale (0; not at all, 1; several days, 2; more than half the days, 3; nearly every day). Total scores of 0–4 indicate minimal anxiety, 5–9 indicate mild anxiety, 10–14 indicate moderate anxiety, and 15–21 indicate severe anxiety.
mTBI history.
Participants were asked questions about their mTBI history. An operational definition of a concussion was provided, as follows, “For this section, we define a concussion as a blow to the head or whiplash that caused any one or more of the following: witnessed loss of consciousness (LOC) (being “knocked out”, and someone saw it), loss of memory for events immediately before and/or after the injury (PTA), or feeling dazed and confused for at least 30 seconds. Participants indicated whether they had sustained zero, one, two, three, four, or five or more mTBIs. Participants provided dates (month and year) for each injury. Each identified injury was followed up by a series of questions asking: i) Did someone see you lose consciousness? ii) Were you dazed and confused? iii) Did you have no memory for events immediately after the injury? iv) Did you go to the hospital? v) Were you medically diagnosed with a concussion or brain injury? vi) Did you miss any school or work because of this injury? vii) Did you have symptoms for more than 24 hours? viii) Did you have symptoms for more than one week? ix) Did you have symptoms for more than one month?
Clinical history.
Information was also collected about years of education, endorsement of any previous diagnoses of anxiety, or depression, all through self-report. Rates of Attention-deficit/hyperactivity disorder (ADHD) and learning disorders were also collected but not included in main analyses.
Procedures
Substance use measures, mental health measures, as well as information about mTBI and sport history, and demographic information were collected via an online survey (Redcap). Data were collected from September 2022 to November 2022 as part of the fall course requirement. Individuals who agreed to participate were required to complete the survey in a quiet, distraction-free environment.
Statistical analyses
Data were analyzed using the Statistical Package for the Social Sciences (SPSS) version 28 (IBM Corp. Released, 2015). Although our questionnaire targeted mTBI history, some participants may have reported more severe injuries. We identified such cases (i.e., endorsement of both LOC and PTA, LOC and admission to the hospital, or LOC and an injury occurring due to a motor vehicle accident (n = 82)) and compared substance use outcomes with those reporting less severe mTBIs. As no group differences emerged, all participants were included in analyses. Independent t-tests were run where homogeneity of variance was met. T-tests and chi-square tests were used to analyze sex differences in AUDIT, CUDIT-R, GAD-7, and PHQ-9 scores and to compare differences between GAD-7 and PHQ-9 scores in females and males with and without a history of mTBI.
Binary regressions were used to compare mTBI history and cannabis use or alcohol use. Substance use and mental health was compared in those with one versus multiple mTBIs and linear regression was used to determine if sustaining one, two, or three or more mTBIs compared to no mTBIs, was significantly associated with increased scores on the CUDIT-R or AUDIT among cannabis and alcohol users group, or with the number of different types of substances used in the past year.
Binary regressions were used to compare mTBI history and cannabis use or alcohol use as well as hazardous and non-hazardous use and to compare mTBI in hazardous users with co-occurring moderate anxiety or depression scores.
A binary logistic regression model was used to look at whether endorsement of past mTBIs (none versus any), sex at birth, current psychological symptoms of depression or anxiety (PHQ-9, GAD-7 total scores) and the their interactions (i.e., mTBI history with sex, depression scores, or anxiety scores) were associated with the likelihood of use versus non-use of cannabis or alcohol (yes/no) among all participants. The same predictors were used in a linear regression to examine their relationship with total CUDIT-R and AUDIT scores among the cannabis and alcohol users group. The binary logistic regression models described above were run separately for males and females to identify substance use factors that may be obscured in combined models.
For each analysis, we investigated the extent to which the data met the assumptions of linearity, normality, and homoscedasticity of errors, as well as whether there was multicollinearity where relevant. Histograms and plots of studentized residuals were examined, and some mild violations were noted but did not warrant corrections or prevent the analyses. No participants were excluded for missing data.
Results
Sample characteristics
Demographic information is shown in Table 1. This sample was made up of 894 individuals. Sex at birth was 72.9% (N = 652) female, which was used in all analyses as our sample did not allow for a more in-depth sample of gender identity. Three hundred and twenty mTBIs were reported among 200 participants. Clinical information is shown in Table 2.
| Variable | |
|---|---|
| Age in years M(SD) | 19.0 (1.5) |
| Range | 17-25 |
| Gender n (%) | |
| Female | 647 (72%) |
| Male | 241(27%) |
| Non-binary | 3 (0.3%) |
| Prefer to self-describe or not disclose | 2 (0.2%) |
| Female sex at birth n (%) | 652 (72.9%) |
| Male sex at birth n (%) | 242 (27.1%) |
| Race | |
| Asian | 364 (40.72%) |
| White | 217 (24.27%) |
| Middle Eastern | 104 (11.63%) |
| Black or African American | 85 (9.51%) |
| South Asian | 49 (5.48%) |
| Mixed Ethnicity | 30 (3.36%) |
| Hispanic, Latino, or Latina | 29 (3.24%) |
| American Indian or Alaska Native | 3 (0.34%) |
| Native Hawaiian or Pacific Islander | 2 (0.22%) |
| Prefer to not disclose | 11 (1.23%) |
| Years of university education M (SD) Range | 1.63 (.86) 1-6 |
| Cannabis use past six months n (%) | 233 (26.05%) | |
|---|---|---|
| CUDIT-R total M(SD) | 2.07 (4.55) | |
| Range | 0-32 | |
| Hazardous cannabis use (over 8) n (%) | 101 (11.30%) | |
| Alcohol use past year n (%) | 481 (53.80%) | |
| AUDIT-C total M(SD) | 1.99 (3.38) | |
| Range | 0-23 | |
| Hazardous alcohol use (over 8) n (%) | 72 (8.05%) | |
| PHQ9 total M(SD) | 9.65 (6.33) | |
| Range | 0-27 | |
| PHQ9 mild or above n (%) | 687 (76.85%) | |
| PHQ9 moderate or above n (%) | 407 (45.53%) | |
| Possible MDD based on PHQ9 n (%) | 369 (41.28%) | |
| GAD7 total M(SD) | 8.45 (5.87) | |
| Range | 0-21 | |
| GAD7 mild or above n (%) | 619 (69.34%) | |
| GAD moderate or above n (%) | 351 (39.26%) | |
| Hazardous cannabis use and PHQ9 moderate or above | 59 (6.6%) | |
| Hazardous cannabis use and GAD7 moderate or above | 51 (5.7%) | |
| Hazardous alcohol use and PHQ9 moderate or above | 43 (4.8%) | |
| Hazardous alcohol use and GAD7 moderate or above | 41 (4.6%) | |
| Previous diagnosis of anxiety n (%) | 166 (18.57%) | |
| Previous diagnosis of depression n (%) | 116 (12.98%) | |
| Tobacco use this year n (%) | 231 (25.84%) | |
| Opioid use this year n (%) | 12 (1.34%) | |
| Simulant use this year n (%) | 27 (3.02%) | |
| Steroid use this year n (%) | 7 (0.78%) | |
| Other drug use this year n (%) | 39 (4.36%) | |
| Number of substances used this year n (%) | 0 | 338 (37.81%) |
| 1 | 257 (28.75%) | |
| 2 | 160 (17.90%) | |
| 3 | 112 (13.31%) | |
| 4 | 19 (2.13%) | |
| 5 | 7 (0.78% | |
| 6 | 1 (0.11%) | |
| Number of mTBIs endorsed across the lifetime n (%) | 0 | 694 (77.62%) |
| 1 | 125 (13.98%) | |
| 2 | 47 (5.26%) | |
| 3 | 16 (1.79%) | |
| 4 | 7 (0.78%) | |
| 5 or more | 5 (0.56%) | |
| Time since last injury in years M(SD) | 3.74(3.84) | |
| Range | 0-18 | |
| ADHD n (%) | 48 (5.37%) | |
| Learning disorder n (%) | 39 (4.36%) | |
Associations between mTBI and mental health on substance use outcomes by sex
There were no significant differences in the proportions of males and females who used cannabis (X2([1], N = 894) =.487, p = [.485]), alcohol (X2([1], N = 894) =.877, p = [.349])), in overall CUDIT-R or AUDIT scores (t(892) = −.094, p = .925; t(892) =.893, p = .372), or whether they endorsed a history of mTBI (X2([1], N = 894) =.862, p = [.353]). However, females had significantly higher symptoms of depression and anxiety than males (t(892) = 7.428, p = .004; t(892) = 8.309, p = < .001; See Table 3). Additionally, current depression and anxiety symptom scores were significantly higher in females who endorsed a history of mTBI (M = 12.93, SD = 6.91; M = 11.50, SD = 6.07) compared to those who did not (M = 9.87, SD = 6.04; M = 8.78, SD = 5.70; t(650) = −5.276, p = .001; t(650) = −5.057, p = < .001). Whereas current depression and anxiety symptom scores did not differ for males with a history of mTBI (M = 8.37, SD = 5.77; M = 6.92, SD = 4.68), versus those without (M = 6.83, SD = 5.37; M = 5.60, SD = 5.04); t(240) = −1.763, p = .079; t(240) = −1.658, p = .099).
| Female | Male | p-value | |
|---|---|---|---|
| Cannabis use N(%) | 174 (26.7%) | 59 (24.4%) | .485 |
| CUDIT-R total M(SD) | 2.06 (4.49) | 2.10 (4.71) | .925 |
| Alcohol use N(%) | 357 (54.8%) | 124 (51.2%) | .349 |
| AUDIT total M(SD) | 2.36 (3.37) | 2.14 (3.16) | .372 |
| mTBI history N(%) | 151 (23.2%) | 49 (20.2%) | .353 |
| PHQ9 total M(SD) | 10.57 (6.38) | 7.14 (5.48) | .004** |
| GAD7 total M(SD) | 9.41 (5.89) | 5.87 (4.99) | <.001*** |
Associations between mTBI on substance use outcomes
Binary logistic regressions indicated that mTBI history was not a significant predictor of cannabis use, (, SE = 0.178, Wald(1) = 1.576, p = .209, odds ratio = 1.25) and that mTBI history significantly as associated with a greater likelihood of alcohol use (, SE = 0.163, Wald(1) = 3.963, p = .047, odds ratio = 1.38). Among those with previous mTBI, participants with a history of two or more mTBIs (n = 75) versus only one mTBI (n = 125) reported significantly higher scores on cannabis use (CUDIT: M = 4.04 vs. 2.31; t(198) = –2.05, p = .042), alcohol use (AUDIT: M = 3.75 vs. 2.39; t(198) = –2.37, p = .019), anxiety symptoms (GAD-7: M = 12.55 vs. 9.07; t(198) = –4.06, p < .001), and depressive symptoms (PHQ-9: M = 14.39 vs. 10.27; t(198) = –4.24, p < .001).
To investigate further whether the number of past mTBIs (i.e., one, two, or three or more), is associated with the severity of substance use within users, separate regressions were run for cannabis users (N = 233) and alcohol users (N = 481). Among cannabis users, having two (b = .194, t(229) = 3.01, p = .003) or three or more mTBIs (b = .162, t(229) = 2.52, p = .013), but not one (b = .093, t(229) = 1.43, p = .154), was associated with increased cannabis use. For alcohol users, only those with three or more mTBIs showed higher alcohol use (b = .208, t(477) = 4.61, p < .001). Exploratory analyses, showed that sustaining two sustaining two (b = .067, t(890) = 2.02, p = .044) or three or more mTBIs (b = .180, t(890) = 5.44, p < .001), was associated with a greater number of different substances used.
Those with hazardous cannabis use were also more likely to report moderate or greater anxiety and depression (GAD-7: 50.5% vs. 37.8%, χ²(1, N = 894) = 6.03, p = .014; PHQ-9: 58.4% vs. 43.9%, χ²(1, N = 894) = 7.63, p = .006). Similarly, individuals with hazardous alcohol use were more likely to report moderate or greater anxiety and depression (GAD-7: 56.9% vs. 37.7%, χ²(1, N = 894) = 10.27, p = .001; PHQ-9: 59.7% vs. 44.3%, χ²(1, N = 894) = 6.36, p = .012). Binary logistic regressions show that mTBI history was significantly associated with hazardous cannabis use (, SE = 0.233, Wald(1) = 4.473, p = .034, odds ratio = 1.64), and hazardous alcohol use (, SE = 0.267, Wald(1) = 4.053, p = .044, odds ratio = 1.71).
A post-hoc analysis showed that individuals with both hazardous alcohol use and moderate or greater anxiety (GAD-7; n = 41) were more likely to report a history of mTBI (41.5%) than those without co-occurring challenges (21.5%; χ²(1, N = 894) = 9.02, p = .003). A similar pattern was found for those with hazardous alcohol use and moderate or greater depression (PHQ-9; n = 43; 41.9% vs. 21.4%; χ²(1, N = 894) = 9.88, p = .002). In contrast, hazardous cannabis use combined with moderate or greater anxiety (GAD-7; n = 51) was not linked to higher mTBI rates. However, those with hazardous cannabis use and moderate or greater depression (PHQ-9; n = 59) were more likely to report mTBI (33.9% vs. 21.6%; χ²(1, N = 894) = 4.83, p = .028).
Associations between mTBI, mental health and sex on substance use outcomes
Binary logistic regressions were conducted to examine whether mTBI history (none versus any), sex, GAD-7 scores, PHQ-9 scores, and their interactions with mTBI were associated with cannabis or alcohol use versus non-use (see Table 4). For cannabis use, (χ2(7) = 22.72, p = .002), higher anxiety scores were associated with greater likelihood of cannabis use (OR= 1.056, 95% CI [1.008, 1.107], p = .022). A significant interaction term between mTBI history and anxiety indicated that higher anxiety was more strongly associated with cannabis use among individuals without an mTBI compared to those with an mTBI (OR=.016, 95% CI [.799,.977], p = .016; see Fig 1). None of these variables showed a relationship with alcohol use (χ2(7) = 12.578, p = .083). Table 4 summarizes estimates of the unstandardized parameters, standard errors, along with the associated Wald statistics, p-values, odds ratios and 95% confidence intervals.
| Predictors | B(SE) | Wald | p-value | OR | 95%CI OR | R 2 |
|---|---|---|---|---|---|---|
| Model 1: Cannabis use versus non-use | .025 | |||||
| mTBI history | .326(.437) | 0.556 | .456 | 1.385 | 0.588, 3.260 | |
| Sex | −.064(.207) | 0.096 | .757 | 0.938 | 0.625, 1.408 | |
| Depression symptoms | .006(.022) | 0.068 | .794 | 1.006 | 0.963, 1.051 | |
| Anxiety symptoms | .055(.024) | 5.266 | .022* | 1.056 | 1.008, 1.107 | |
| mTBI history x sex | .013(.441) | 0.001 | .977 | 1.013 | 0.427, 2.406 | |
| mTBI history x depression symptoms | .086(.045) | 3.663 | .056 | 1.090 | 0.998, 1.191 | |
| mTBI history x anxiety symptoms | −.124(.051) | 5.820 | .016* | 0.883 | 0.799, 0.977 | |
| Constant | −1.560(.206) | 57.480 | <.001 | 0.210 | ||
| Observations | 894 | |||||
| Model 2: Alcohol use versus non-use | .014 | |||||
| mTBI history | .595(.387) | 2.365 | .124 | 1.814 | 0.849, 3.873 | |
| Sex | .036(.176) | 0.041 | .840 | 1.036 | 0.734, 1.463 | |
| Depression symptoms | .023(.020) | 1.275 | .259 | 1.023 | 0.983, 1.064 | |
| Anxiety symptoms | .016(.021) | 0.587 | .444 | 1.016 | 0.975, 1.060 | |
| mTBI history x sex | −.011(.396) | 0.001 | .978 | 0.989 | 0.455, 2.150 | |
| mTBI history x depression symptoms | −.007(.040) | 0.031 | .861 | 0.993 | 0.919, 1.073 | |
| mTBI history x anxiety symptoms | −.028(.045) | 0.385 | .535 | 0.973 | 0.891, 1.061 | |
| Constant | −.278(.171) | 2.637 | .104 | 0.758 | ||
| Observations | 894 | |||||
The same variables were used to look at the association with CUDIT-R total scores in cannabis users and AUDIT scores among alcohol users. See Table 5 for estimates of the unstandardized parameters, along with the associated t statistics, p-values and 95% confidence intervals. For cannabis users, the model (R 2 of.098 (F(7,225) = 3.486, p = .001)) showed significant associations with mTBI (b = .438, t(225) = 2.69, p = .008) and depression scores (b = 301, t(225) = 2.80, p = .006) indicating that individuals with prior mTBI or higher depression scores endorsed more severe cannabis use. For alcohol users, the model (R 2 of.050 (F(7,473) = 3.584, p < .001)) revealed a significant interaction between mTBI history and depression scores (b = .328, t(473) = 2.05, p = .041), such that increased symptoms of depression were associated with more problematic alcohol use among those with an mTBI history.
| Predictors | Unstandardized estimate | 95% CI | t-statistic | p-value |
|---|---|---|---|---|
| Model 1: Total CUDIT-R scores in users | ||||
| (Intercept) | 5.702 | 3.647,7.757 | 5.468 | <.001 |
| mTBI history | 5.754 | 1.534, 9.975 | 2.687 | .008** |
| Sex | −1.398 | −3.380, 0.583 | −1.391 | .166 |
| Depression symptoms | 0.286 | 0.085, 0.486 | 2.803 | .006** |
| Anxiety symptoms | −0.038 | −0.233, 0.157 | −0.383 | .702 |
| mTBI history x sex | 0.298 | −3.679, 4.274 | 0.148 | .883 |
| mTBI history x depression symptoms | −0.349 | −0.816, 0.118 | −1.474 | .142 |
| mTBI history x anxiety symptoms | 0.062 | −0.460, 0.585 | 0.235 | .815 |
| Observations | 233 | |||
| Model 2: Total AUDIT scores in users | ||||
| (Intercept) | 3.332 | 2.491, 4.173 | 7.784 | <.001 |
| mTBI history | 0.180 | −1.584, 1.944 | 0.201 | .841 |
| Sex | 0.177 | −0.666, 1.019 | 0.412 | .680 |
| Depression symptoms | 0.040 | −0.054, 0.134 | 0.833 | .405 |
| Anxiety symptoms | 0.025 | −0.071, 0.122 | 0.516 | .606 |
| mTBI history x sex | −1.712 | −3.444, 0.020 | −1.943 | .053 |
| mTBI history x depression symptoms | 0.187 | 0.008, 0.367 | 2.052 | .041* |
| mTBI history x anxiety symptoms | −0.059 | −0.259, 0.140 | −0.585 | .559 |
| Observations | 481 | |||
Four binary logistic regressions tested whether mTBI history (none versus any), depression, anxiety scores, and their interactions were associated with substance use or non-use separately for females and males. For females (χ2(5) = 21.14, p < .001), those with higher anxiety scores were more likely to endorse cannabis use (OR= 1.088, 95% CI [1.032, 1.148], p = .022). Interaction effects showed that, higher depression scores were associated with greater likelihood of cannabis use among those with a history of mTBI (OR=1.126, 95% CI [1.017, 1.246], p = .022; see Fig 2A), whereas higher anxiety scores were associated with greater likelihood of cannabis use for those without a mTBI (OR=.843, 95% CI [0.753, 0.945], p = .003; see Fig 2B). For males, (χ2(5) = 8.28, p = .141), higher depression scores were associated with greater likelihood of cannabis use (OR= 1.112, 95% CI [1.007, 1.228], p = .036).
For alcohol use in females (χ2(5) = 10.71, p = .057) none of the predictors were associated with likelihood of use. For males (χ2(5) = 10.82, p = .055), higher depression scores were associated with greater likelihood of alcohol use (OR= 1.121, 95% CI [1.026, 1.224], p = .012). Interaction effects showed that, males with higher depression scores were less likely to use alcohol if they had a history of mTBI (OR=.832, 95% CI [0.694, 0.997], p = .046; see Fig 2C), whereas higher anxiety scores were associated with greater likelihood of alcohol use among males with a history of mTBI (OR= 1.258, 95% CI [1.010, 1.568], p = .041; See Fig 2D). Table 6 summarizes estimates of the unstandardized parameters (B), standard errors (SE), along with the associated Wald statistics, p-values, odds ratios (OR) and 95% confidence intervals (CI) for all of the above models.
| Predictors | B(SE) | Wald | p-value | OR | 95%CI OR | R 2 |
|---|---|---|---|---|---|---|
| Model 1: Cannabis use versus non-use in females | .032 | |||||
| mTBI history | .464(.461) | 1.016 | .313 | 1.591 | 0.645, 3.925 | |
| Depression symptoms | −.021(0.26) | 0.681 | .409 | 0.979 | 0.931, 1.030 | |
| Anxiety symptoms | .085(.027) | 9.600 | .002** | 1.088 | 1.032, 1.148 | |
| mTBI history x depression symptoms | .118(.052) | 5.258 | .022* | 1.126 | 1.017, 1.246 | |
| mTBI history x anxiety symptoms | −.170(.058) | 8.575 | .003** | 0.843 | 0.753, 0.945 | |
| Constant | −1.628(.216) | 56.944 | <.001 | 0.196 | ||
| Observations | 652 | |||||
| Model 2: Cannabis use versus non-use in males | .034 | |||||
| mTBI history | −.020(.710) | 0.001 | .978 | 0.981 | 0.244, 3.946 | |
| Depression symptoms | .106(.051) | 4.378 | .036* | 1.112 | 1.007, 1.228 | |
| Anxiety symptoms | −.057(.056) | 1.046 | .306 | 0.944 | 0.846, 1.054 | |
| mTBI history x depression symptoms | −.033(.098) | 0.113 | .737 | 0.968 | 0.799, 1.172 | |
| mTBI history x anxiety symptoms | .069(.119) | 0.342 | .559 | 1.072 | 0.850, 1.352 | |
| Constant | −1.635(.295) | 30.614 | <.001 | 0.195 | ||
| Observations | 242 | |||||
| Model 3: Alcohol use versus non-use in females | .016 | |||||
| mTBI history | .692(.415) | 2.776 | .096 | 1.997 | 0.885, 4.507 | |
| Depression symptoms | −.003(.023) | 0.017 | .897 | 0.997 | 0.953, 1.043 | |
| Anxiety symptoms | .045(.025) | 3.390 | .066 | 1.046 | 0.997, 1.098 | |
| mTBI history x depression symptoms | .038(.045) | 0.731 | .393 | 1.039 | 0.952, 1.134 | |
| mTBI history x anxiety symptoms | −.088(.050) | 3.074 | .080 | 0.916 | 0.831, 1.010 | |
| Constant | −.241(.178) | 1.839 | .175 | 0.786 | ||
| Observations | 652 | |||||
| Model 4: Alcohol use versus non-use in males | .044 | |||||
| mTBI history | .314(.597) | 0.276 | .599 | 1.369 | 0.425, 4.407 | |
| Depression symptoms | .114(.045) | 6.363 | .012* | 1.121 | 1.026, 1.224 | |
| Anxiety symptoms | −.086(.048) | 3.177 | .075 | 0.918 | 0.836, 1.009 | |
| mTBI history x depression symptoms | −.184(.092) | 3.990 | .046* | 0.832 | 0.694, 0.997 | |
| mTBI history x anxiety symptoms | .230(.112) | 4.191 | .041* | 1.258 | 1.010, 1.568 | |
| Constant | −.330(.240) | 1.903 | .168 | 0.719 | ||
| Observations | 242 | |||||
Discussion
This study aimed to examine the relationship between mTBI history with substance use (cannabis use within the past six months and alcohol use within the past year), as well as to understand the contribution of mental health to this relationship and sex related differences in these associations. Similar to prior research, we found an association between mTBI history and substance use in the past 6-months to one year [18]. Risk-taking behaviour such as problematic substance use is common following mTBI [40–42] and may be related to underlying neuropathology following head injury [42]. Our study suggests that the number of past injuries was an important factor to consider when examining problematic use of these substances It may be that while sustaining one injury is associated with current substance use in general, more severe use is associated with individuals who sustained multiple injuries. Specifically, sustaining one injury was not significantly associated with more severe current substance use in our study, however, sustaining two or more prior mTBIs was associated with more severe cannabis use and sustaining three or more previous injuries was associated with more severe alcohol use among users. Similarly to other studies [17,43], we found that sustaining multiple injuries was associated with a greater number of substances being used over the course of the past year. We also found that individuals with hazardous cannabis or alcohol use were more likely to have a history of mTBI and endorse current (i.e., within the last two weeks) moderate to severe depression and anxiety scores.
The relationship between increased risk of mental health problems following mTBI has been shown consistently in the literature [44–46], with a recent meta-analysis indicating that individuals with a history of mTBI, including both civilians and service members, are more than three times as likely to experience depression [47]. Furthermore, sustaining multiple mTBIs may place individuals at an even greater risk of experiencing depression [48]. The relationship between mTBI and depression is complex and likely affects substance use behaviours, while substance use also likely impacts mental health [13,17]. Recent research suggests that mTBI exposure has both direct and indirect effects on substance use via depression [23]. Similarly, our study showed that both endorsement of a previous mTBI and higher current depression scores were independently associated with more problematic cannabis use in cannabis users. Additionally, when examining problematic use in alcohol users, there was a small but significant interaction where increased depression scores in individuals with a past mTBI were associated with more problematic alcohol use. It may be that mTBI may interact by disrupting neural circuits involved in mood regulation, increasing vulnerability to depression and anxiety. These emotional difficulties may, in turn, contribute to substance use as individuals attempt to self-medicate or cope with negative affect.
The relationship between mTBI and anxiety has been less studied, but current findings show that college athlete alumni who have a history of mTBI endorse greater long-term anxiety symptoms [49] and one study examining adults following mTBI suggested that in the first few months following an mTBI, anxiety may be more prevalent than depression symptoms [50]. In fact, another recent study following adults who experienced mTBI shows that over 30% of individuals met the criteria for one or more anxiety disorders within a year of sustaining an mTBI and those with pre-injury anxiety were even more susceptible [51]. While anxiety and the use of alcohol and cannabis have been suggested to be associated via the self-medication model and the substance-induced model [52], additional endorsement of a previous mTBI may affect these models and may do so differently for these disorders. Consistent with previous literature, higher current anxiety symptoms were associated with an increased likelihood of cannabis use in our sample. Furthermore, anxiety symptoms interacted with mTBI history: among females, those with a history of mTBI exhibited significantly higher anxiety scores than those without a history of mTBI. Males showed the same pattern, despite not reaching significance. However, in individuals without a history of mTBI, higher anxiety scores were associated with greater likelihood of cannabis use. This aligns with other research showing associations between cannabis use and anxiety [53]. However, it also suggests a more nuanced relationship: anxiety is associated with cannabis use in individuals without an mTBI history, whereas in those with a history of mTBI, both anxiety and the injury itself may be linked to cannabis use. It should be noted that prior mental health diagnoses were not included in these models, which limits conclusions about the influence of pre-existing conditions on post-TBI outcomes.
The sex gap in the proportion of individuals with substance use disorders is narrowing [54] and women may be particularly at risk of experiencing higher rates of psychiatric disorders co-occurring with substance use disorders, which further complicates treatment [55]. Several studies have shown that women who use cannabis tend to report higher anxiety symptoms during treatment and withdrawal from use [56,57]. While research shows that depression strongly co-occurs with cannabis use, results investigating sex differences in depression among cannabis users are more mixed [58]. In our sample, females had significantly greater current mental health symptoms compared to males, and interactions between mental health and mTBI on cannabis use were observed exclusively in females. More specifically, in females, cannabis use was associated with both a prior mTBI history and higher current depression symptoms, while higher current anxiety symptoms appeared to be associated with cannabis use in those without an injury history. In contrast, higher current depression symptoms in males were associated with cannabis use. No associations between anxiety and cannabis use were observed in males in our sample. Our findings suggest that there may be differential relationships between mental health symptoms and cannabis use between sexes.
Furthermore, in our male sample, we observed that current mental health scores and mTBI history were associated with alcohol use. Alcohol use and risky use have become more normative particularly among university students [59], with about half our sample partaking in alcohol within the past year. The co-occurrence of anxiety and alcohol use [60] and depression and alcohol use [10,61], and increased susceptibility to depression following mTBI have been well established [62,63]. Likewise, in our sample, both depression and anxiety scores were higher—though not significantly—in males with mTBI compared to males without mTBI. However, higher anxiety scores, in addition to a history of mTBI were associated with greater alcohol use in males. Whereas none of these predictors were associated with alcohol use in females in our sample. This suggests that other factors including peer influencing, social norms, and coping styles among others, may contribute to alcohol use in females, whereas alcohol use in males might be related to their mental health and history of mTBI.
There are several limitations to this study. First, the participant pool was limited to psychology and kinesiology students at a single institution, which may affect the generalizability of these findings. Additionally, we cannot assume temporal causality with any of these relationships. Despite examining “past” mTBI and “current” substance use, we cannot control for the possibility of lifetime substance use that preceded any injuries. While self-reported prior mental health diagnoses were collected, we lacked details on the timing, duration, and severity of these conditions, limiting our ability to interpret their potential impact on substance use outcomes. As such, these findings should be interpreted as reflecting associations between these factors rather than causal relationships. The identification of mTBI history was based on a self-report questionnaire, and although a definition of mTBI was provided to participants, it is possible that this measure also captured more significant injuries. We attempted to address this by examining the characteristics of the reported injuries (see Analysis section) and found no differences in outcome measures for those who may have exhibited more significant signs or symptoms (e.g., LOC and PTA). Similarly, our study relied on self-reported substance use habits, which may be subject to reporting bias. Additionally, the smaller sample size of male participants led to wider confidence intervals and reduced statistical power, which may have limited our ability to detect significant effects in males and could have biased results toward patterns observed in the larger female sample.
Conclusion
In conclusion, this study aimed to better understand the associations between mTBI and mental health on alcohol and cannabis use among young adults and to explore how these factors may be associated differently in males and females. We found that while mTBI and mental health were not significantly associated with alcohol use patterns over the past year in females, mTBI history in combination with either depression or anxiety symptoms was associated with cannabis use in females. In contrast, depression symptoms and mTBI history were correlated with alcohol and cannabis use in males. Our findings suggest that males and females may use substances for different reasons. Females may be more likely to use cannabis as a coping mechanism for anxiety, whereas depression may predispose males to alcohol or cannabis use in general. Additionally, individuals with mTBI tend to report more mental health problems. By recognizing these different factors in males and females, our findings support the need for more individualized treatment approaches for young adults.
Acknowledgments
The authors would like to acknowledge the York University Undergraduate Research Participation Pool team for their assistance with recruitment.
Data Availability
The underlying data contain sensitive participant information, and our Research Ethics Board (REB) did not approve the release of a fully de-identified open-access dataset. Therefore, the dataset cannot be made publicly available. However, the data can be made available upon request under appropriate ethical and institutional agreements. Interested researchers can contact Dr. Magdalena Wojtowicz, senior author (magdawoj@yorku.ca), or Alison Collins-Mrakas, Director, Research Ethics department, York University (Integrityacollins@yorku.ca) to request access. Data requests will be considered for institutions that obtain REB approval or have a mutual ethics agreement with our institution. This approach ensures compliance with ethical and legal obligations while enabling qualified researchers to access the data for replication or further study.
Funding Statement
The author(s) received no specific funding for this work.
References
Untitled section
References
- 1.Arnett JJ, Žukauskienė R, Sugimura K. The new life stage of emerging adulthood at ages 18-29 years: implications for mental health. Lancet Psychiatry. 2014;1(7):569–76. doi: 10.1016/S2215-0366(14)00080-7
- 2.Zuckermann AME, Williams G, Battista K, de Groh M, Jiang Y, Leatherdale ST. Trends of poly-substance use among Canadian youth. Addict Behav Rep. 2019;10:100189. doi: 10.1016/j.abrep.2019.100189
- 3.Compton WM, Valentino RJ, DuPont RL. Polysubstance use in the U.S. opioid crisis. Mol Psychiatry. 2021;26(1):41–50. doi: 10.1038/s41380-020-00949-3
- 4.Konefal S, Sherk A, Maloney-Hall B, Young M, Kent P, Biggar E. Polysubstance use poisoning deaths in Canada: an analysis of trends from 2014 to 2017 using mortality data. BMC Public Health. 2022;22(1):269. doi: 10.1186/s12889-022-12678-z
- 5.Crummy EA, O’Neal TJ, Baskin BM, Ferguson SM. One Is Not Enough: Understanding and Modeling Polysubstance Use. Front Neurosci. 2020;14:569. doi: 10.3389/fnins.2020.00569
- 6.Volkow ND, Blanco C. Substance use disorders: a comprehensive update of classification, epidemiology, neurobiology, clinical aspects, treatment and prevention. World Psychiatry. 2023;22(2):203–29. doi: 10.1002/wps.21073
- 7.Hines LA, Freeman TP, Gage SH, Zammit S, Hickman M, Cannon M, et al. Association of High-Potency Cannabis Use With Mental Health and Substance Use in Adolescence. JAMA Psychiatry. 2020;77(10):1044–51. doi: 10.1001/jamapsychiatry.2020.1035
- 8.Moore THM, Zammit S, Lingford-Hughes A, Barnes TRE, Jones PB, Burke M, et al. Cannabis use and risk of psychotic or affective mental health outcomes: a systematic review. Lancet. 2007;370(9584):319–28. doi: 10.1016/S0140-6736(07)61162-3
- 9.Gobbi G, Atkin T, Zytynski T, Wang S, Askari S, Boruff J, et al. Association of Cannabis Use in Adolescence and Risk of Depression, Anxiety, and Suicidality in Young Adulthood: A Systematic Review and Meta-analysis. JAMA Psychiatry. 2019;76(4):426–34. doi: 10.1001/jamapsychiatry.2018.4500
- 10.McHugh RK, Weiss RD. Alcohol Use Disorder and Depressive Disorders. Alcohol Res. 2019;40(1):arcr.v40.1.01. doi: 10.35946/arcr.v40.1.01
- 11.Grant BF, Stinson FS, Dawson DA, Chou SP, Dufour MC, Compton W, et al. Prevalence and co-occurrence of substance use disorders and independent mood and anxiety disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Arch Gen Psychiatry. 2004;61(8):807–16. doi: 10.1001/archpsyc.61.8.807
- 12.Degenhardt L, Stockings E, Patton G, Hall WD, Lynskey M. The increasing global health priority of substance use in young people. Lancet Psychiatry. 2016;3(3):251–64. doi: 10.1016/S2215-0366(15)00508-8
- 13.Esmaeelzadeh S, Moraros J, Thorpe L, Bird Y. Examining the Association and Directionality between Mental Health Disorders and Substance Use among Adolescents and Young Adults in the U.S. and Canada-A Systematic Review and Meta-Analysis. J Clin Med. 2018;7(12):543. doi: 10.3390/jcm7120543
- 14.Khantzian EJ. The self-medication hypothesis of substance use disorders: a reconsideration and recent applications. Harv Rev Psychiatry. 1997;4(5):231–44. doi: 10.3109/10673229709030550
- 15.Sadock BJ, Sadock VA, Ruiz P. Kaplan and Sadock’s concise textbook of clinical psychiatry. 4th ed. Kluwer W. Philadelphia, PA. 2016.
- 16.Alcock B, Gallant C, Good D. The relationship between concussion and alcohol consumption among university athletes. Addict Behav Rep. 2018;7:58–64. doi: 10.1016/j.abrep.2018.02.001
- 17.Rosenthal SR, Sonido PL, Sammartino C, Swanberg JE, Noel JK. Brain Injury and Substance Use in Young Adults: The Need for Integrating Care. R I Med J (2013). 2023;106(3):17–22.
- 18.Olsen CM, Corrigan JD. Does Traumatic Brain Injury Cause Risky Substance Use or Substance Use Disorder?. Biol Psychiatry. 2022;91(5):421–37. doi: 10.1016/j.biopsych.2021.07.013
- 19.Adams Nejatbakhsh N, Dawson D, Hutchison M, Selby P. Association between pediatric TBI and mental health and substance use disorders: A scoping review. Brain Inj. 2023;37(6):525–33. doi: 10.1080/02699052.2023.2184871
- 20.Shaw NA. The neurophysiology of concussion. Prog Neurobiol. 2002;67(4):281–344. doi: 10.1016/s0301-0082(02)00018-7
- 21.van der Horn HJ, Liemburg EJ, Aleman A, Spikman JM, van der Naalt J. Brain Networks Subserving Emotion Regulation and Adaptation after Mild Traumatic Brain Injury. J Neurotrauma. 2016;33(1):1–9. doi: 10.1089/neu.2015.3905
- 22.Wilson A, Gicas K, Wojtowicz M. Influence of Mild Traumatic Brain Injury History and Mental Health Status on Alcohol and Cannabis Use in University Athletes. Clin J Sport Med. 2023;33(2):145–50. doi: 10.1097/JSM.0000000000001110
- 23.Newman SD, Grantz JG, Brooks K, Gutierrez A, Kawata K. Association between History of Concussion and Substance Use Is Mediated by Mood Disorders. J Neurotrauma. 2020;37(1):146–51. doi: 10.1089/neu.2019.6550
- 24.Skidmore CR, Kaufman EA, Crowell SE. Substance Use Among College Students. Child Adolesc Psychiatr Clin N Am. 2016;25(4):735–53. doi: 10.1016/j.chc.2016.06.004
- 25.Choi HJ, Lu Y, Schulte M, Temple JR. Adolescent substance use: Latent class and transition analysis. Addict Behav. 2018;77:160–5. doi: 10.1016/j.addbeh.2017.09.022
- 26.Piccinelli M, Wilkinson G. Gender differences in depression. Br J Psychiatry. 2000;177(6):486–92. doi: 10.1192/bjp.177.6.486
- 27.Covassin T, Swanik CB, Sachs ML. Sex Differences and the Incidence of Concussions Among Collegiate Athletes. J Athl Train. 2003;38(3):238–44.
- 28.Gessel LM, Fields SK, Collins CL, Dick RW, Comstock DR. Concussions on U.S. high school and collegiate athletes. J Athl Train. 2007;42(4):495–503.
- 29.Covassin T, Schatz P, Swanik CB. Sex differences in neuropsychological function and post-concussion symptoms of concussed collegiate athletes. Neurosurgery. 2007;61(2):345–50; discussion 350-1. doi: 10.1227/01.NEU.0000279972.95060.CB
- 30.Preiss-Farzanegan SJ, Chapman B, Wong TM, Wu J, Bazarian JJ. The relationship between gender and postconcussion symptoms after sport-related mild traumatic brain injury. PM R. 2009;1(3):245–53. doi: 10.1016/j.pmrj.2009.01.011
- 31.Zuckerman SL, Apple RP, Odom MJ, Lee YM, Solomon GS, Sills AK. Effect of sex on symptoms and return to baseline in sport-related concussion. J Neurosurg Pediatr. 2014;13(1):72–81. doi: 10.3171/2013.9.PEDS13257
- 32.Bazarian JJ, Blyth B, Mookerjee S, He H, McDermott MP. Sex differences in outcome after mild traumatic brain injury. J Neurotrauma. 2010;27(3):527–39. doi: 10.1089/neu.2009.1068
- 33.Gupte R, Brooks W, Vukas R, Pierce J, Harris J. Sex Differences in Traumatic Brain Injury: What We Know and What We Should Know. J Neurotrauma. 2019;36(22):3063–91. doi: 10.1089/neu.2018.6171
- 34.Starkey NJ, Duffy B, Jones K, Theadom A, Barker-Collo S, Feigin V, et al. Sex differences in outcomes from mild traumatic brain injury eight years post-injury. PLoS One. 2022;17(5):e0269101. doi: 10.1371/journal.pone.0269101
- 35.McCrory P, Meeuwisse W, Dvořák J, Aubry M, Bailes J, Broglio S, et al. Consensus statement on concussion in sport—the 5th international conference on concussion in sport held in Berlin, October 2016. Br J Sports Med. 2017;51(11):838–47.
- 36.Babor TF, de la Fuente JR, Saunders J, Grant M. AUDIT The Alcohol Use Disorders Identification Test: Guidelines for use in Primary Health Care. Prim Care. 2001.
- 37.Adamson SJ, Kay-Lambkin FJ, Baker AL, Lewin TJ, Thornton L, Kelly BJ, et al. An improved brief measure of cannabis misuse: the Cannabis Use Disorders Identification Test-Revised (CUDIT-R). Drug Alcohol Depend. 2010;110(1–2):137–43. doi: 10.1016/j.drugalcdep.2010.02.017
- 38.Kroenke K, Spitzer RL. The PHQ-9: A new depression diagnostic and severity measure. Psychiatr Ann. 2002;32(9):509–15.
- 39.Spitzer RL, Kroenke K, Williams JBW, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166(10):1092–7. doi: 10.1001/archinte.166.10.1092
- 40.McKinlay A, Corrigan J, Horwood LJ, Fergusson DM. Substance abuse and criminal activities following traumatic brain injury in childhood, adolescence, and early adulthood. J Head Trauma Rehabil. 2014;29(6):498–506. doi: 10.1097/HTR.0000000000000001
- 41.Lawrence DW, Foster E, Comper P, Langer L, Hutchison MG, Chandra T, et al. Cannabis, alcohol and cigarette use during the acute post-concussion period. Brain Inj. 2020;34(1):42–51. doi: 10.1080/02699052.2019.1679885
- 42.Merkel SF, Cannella LA, Razmpour R, Lutton E, Raghupathi R, Rawls SM, et al. Factors affecting increased risk for substance use disorders following traumatic brain injury: What we can learn from animal models. Neurosci Biobehav Rev. 2017;77:209–18. doi: 10.1016/j.neubiorev.2017.03.015
- 43.Kort-Butler LA. Head Injury and Substance Use in Young Adults. Subst Use Misuse. 2017;52(8):1019–26. doi: 10.1080/10826084.2016.1268632
- 44.Delmonico RL, Theodore BR, Sandel ME, Armstrong MA, Camicia M. Prevalence of depression and anxiety disorders following mild traumatic brain injury. PM R. 2022;14(7):753–63. doi: 10.1002/pmrj.12657
- 45.Chrisman SPD, Richardson LP. Prevalence of diagnosed depression in adolescents with history of concussion. J Adolesc Health. 2014;54(5):582–6. doi: 10.1016/j.jadohealth.2013.10.006
- 46.Scholten AC, Haagsma JA, Cnossen MC, Olff M, van Beeck EF, Polinder S. Prevalence of and Risk Factors for Anxiety and Depressive Disorders after Traumatic Brain Injury: A Systematic Review. J Neurotrauma. 2016;33(22):1969–94. doi: 10.1089/neu.2015.4252
- 47.Hellewell SC, Beaton CS, Welton T, Grieve SM. Characterizing the Risk of Depression Following Mild Traumatic Brain Injury: A Meta-Analysis of the Literature Comparing Chronic mTBI to Non-mTBI Populations. Front Neurol. 2020;11:350. doi: 10.3389/fneur.2020.00350
- 48.Strain J, Didehbani N, Cullum CM, Mansinghani S, Conover H, Kraut MA, et al. Depressive symptoms and white matter dysfunction in retired NFL players with concussion history. Neurology. 2013;81(1):25–32. doi: 10.1212/WNL.0b013e318299ccf8
- 49.Meehan WP 3rd, Taylor AM, Berkner P, Sandstrom NJ, Peluso MW, Kurtz MM, et al. Division III Collision Sports Are Not Associated with Neurobehavioral Quality of Life. J Neurotrauma. 2016;33(2):254–9. doi: 10.1089/neu.2015.3930
- 50.Barker-Collo S, Theadom A, Jones K, Starkey N, Kahan M, Feigin V. Depression and anxiety across the first 4 years after mild traumatic brain injury: findings from a community-based study. Brain Inj. 2018;32(13–14):1651–8. doi: 10.1080/02699052.2018.1540797
- 51.Lamontagne G, Belleville G, Beaulieu-Bonneau S, Souesme G, Savard J, Sirois M-J, et al. Anxiety symptoms and disorders in the first year after sustaining mild traumatic brain injury. Rehabil Psychol. 2022;67(1):90–9. doi: 10.1037/rep0000422
- 52.Vorspan F, Mehtelli W, Dupuy G, Bloch V, Lépine J-P. Anxiety and substance use disorders: co-occurrence and clinical issues. Curr Psychiatry Rep. 2015;17(2):4. doi: 10.1007/s11920-014-0544-y
- 53.Crippa JA, Zuardi AW, Martín-Santos R, Bhattacharyya S, Atakan Z, McGuire P, et al. Cannabis and anxiety: a critical review of the evidence. Hum Psychopharmacol. 2009;24(7):515–23. doi: 10.1002/hup.1048
- 54.Keyes KM, Grant BF, Hasin DS. Evidence for a closing gender gap in alcohol use, abuse, and dependence in the United States population. Drug Alcohol Depend. 2008;93(1–2):21–9. doi: 10.1016/j.drugalcdep.2007.08.017
- 55.Conway KP, Compton W, Stinson FS, Grant BF. Lifetime comorbidity of DSM-IV mood and anxiety disorders and specific drug use disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. J Clin Psychiatry. 2006;67(2):247–57. doi: 10.4088/jcp.v67n0211
- 56.Foster KT, Li N, McClure EA, Sonne SC, Gray KM. Gender Differences in Internalizing Symptoms and Suicide Risk Among Men and Women Seeking Treatment for Cannabis Use Disorder from Late Adolescence to Middle Adulthood. J Subst Abuse Treat. 2016;66:16–22. doi: 10.1016/j.jsat.2016.01.012
- 57.Cuttler C, Mischley LK, Sexton M. Sex Differences in Cannabis Use and Effects: A Cross-Sectional Survey of Cannabis Users. Cannabis Cannabinoid Res. 2016;1(1):166–75. doi: 10.1089/can.2016.0010
- 58.Calakos KC, Bhatt S, Foster DW, Cosgrove KP. Mechanisms Underlying Sex Differences in Cannabis Use. Curr Addict Rep. 2017;4(4):439–53. doi: 10.1007/s40429-017-0174-7
- 59.Karam E, Kypri K, Salamoun M. Alcohol use among college students: an international perspective. Curr Opin Psychiatry. 2007;20(3):213–21. doi: 10.1097/YCO.0b013e3280fa836c
- 60.Smith JP, Randall CL. Anxiety and alcohol use disorders: comorbidity and treatment considerations. Alcohol Res. 2012;34(4):414–31. doi: 10.35946/arcr.v34.4.06
- 61.Boden JM, Fergusson DM. Alcohol and depression. Addiction. 2011;106(5):906–14. doi: 10.1111/j.1360-0443.2010.03351.x
- 62.Stein MB, Jain S, Giacino JT, Levin H, Dikmen S, Nelson LD, et al. Risk of Posttraumatic Stress Disorder and Major Depression in Civilian Patients After Mild Traumatic Brain Injury: A TRACK-TBI Study. JAMA Psychiatry. 2019;76(3):249–58. doi: 10.1001/jamapsychiatry.2018.4288
- 63.Rapoport MJ, McCullagh S, Streiner D, Feinstein A. The clinical significance of major depression following mild traumatic brain injury. Psychosomatics. 2003;44(1):31–7. doi: 10.1176/appi.psy.44.1.31
Associated Data
Data Availability Statement
The underlying data contain sensitive participant information, and our Research Ethics Board (REB) did not approve the release of a fully de-identified open-access dataset. Therefore, the dataset cannot be made publicly available. However, the data can be made available upon request under appropriate ethical and institutional agreements. Interested researchers can contact Dr. Magdalena Wojtowicz, senior author (magdawoj@yorku.ca), or Alison Collins-Mrakas, Director, Research Ethics department, York University (Integrityacollins@yorku.ca) to request access. Data requests will be considered for institutions that obtain REB approval or have a mutual ethics agreement with our institution. This approach ensures compliance with ethical and legal obligations while enabling qualified researchers to access the data for replication or further study.