Mental and Physical Health-Related Cannabis Motives Mediate the Relationship Between Childhood Trauma and Problematic Cannabis Use Over Time among Emerging Adult Cannabis Users

Abstract

Background:

While growing evidence has identified mental and physical health-related cannabis use motives as significant mechanisms between childhood trauma and problematic cannabis use (PCU) for emerging adults (EA), there is a need to understand the longitudinal stability of these pathways and how they impact PCU as cannabis users age into later adulthood.

Methods:

The current study extends an analysis examining the impact of childhood trauma (e.g., emotional abuse, sexual abuse) on multiple indicators of PCU through a range of cannabis use motives. 339 medical cannabis patient and non-patient EA users from the Los Angeles area were sampled at baseline (mean age=21.23; SD=2.48). The present analysis used four waves of follow-up data collected from 2016 to 2018 (W3, W4) and 2019–2020 (W5, W6).

Results:

Use of cannabis to cope with nausea, sleep, pain, and emotional distress mediated the relationships between some types of childhood abuse and PCU at W4, though most associations attenuated by later adulthood (W6). Specifically, greater emotional distress and nausea motives were associated with greater PCU in models of emotional abuse and neglect and sexual abuse, with emotional distress continuing to mediate at W6. Conversely, sleep and pain motives were associated with lower PCU in models for emotional neglect.

Conclusions:

Mental and physical health-related motives reflect potential intervenable factors that predict PCU in emerging adulthood among EA cannabis users with histories of childhood trauma. Results highlight the importance of and value for assessing a wide range of motives and PCU outcomes to target and address areas for intervention.

Introduction

Cannabis is the most widely used substance among emerging adults (i.e., those ages 18–29) in the U.S. following alcohol, reaching historically high rates in 2020 (Schulenberg et al., 2021). Emerging adults (EA) may be particularly vulnerable to numerous physiological and psychosocial effects of chronic cannabis use given the many developmental changes occurring during this formative period (Burggren et al., 2019; Lisdahl et al., 2014). Regular cannabis use (i.e., defined variably as at least weekly use) in EAs has been linked to increased mental health issues, including depression and anxiety (Gobbi et al., 2019; Leadbeater et al., 2019), increased risk of motor vehicle crashes (Salomonsen-Sautel et al., 2014), emergency room visits and hospitalizations (Vozoris et al., 2022), and poorer employment and educational outcomes (D’Amico et al., 2016; Thompson et al., 2018; Wilhite et al., 2017). Notably, EAs who frequently use cannabis may be at increased risk for developing problematic cannabis use (PCU) compared to those who only report lifetime use (Han et al., 2019).

PCU has been broadly defined as cannabis use that significantly and negatively impacts cognitive and psychosocial functioning, including concerns around substance use or dependence. There have been diverse conceptualizations of PCU in the literature, ranging from psychological worries about one’s cannabis use to clinical indicators of abuse or dependence, highlighting the importance of assessing and differentiating these conceptualizations (Casajuana et al., 2016). It is also noteworthy that prior research of different conceptualizations of cannabis use has been limited among EA populations (Simpson et al., 2021). PCU in EAs has been linked to changes in cognitive functioning (Martin-Rodriguez et al., 2021), poor mental health, including depression and psychosis (Leadbeater et al., 2019; Sorkhou et al., 2021), and poor psychosocial functioning (Meier, 2021). Historically, PCU has been assessed and conceptualized using diagnostic criteria for substance use disorders (e.g., Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; DSM-5 (American Psychiatric Association, 2013), though the use of multiple measures of PCU has been encouraged to more fully account for a range of PCU experiences (Annaheim et al., 2008), particularly in states where medical cannabis is accessible (Sznitman & Room, 2018). As research continues to identify and understand predictors of PCU among EAs, more work is also needed to understand the longitudinal stability of these risk factors and how they impact (i.e., mechanisms) PCU as EAs age, which may lead to crucial efforts in assessment and intervention.

Adverse childhood experiences (ACEs), which encompass abuse and neglect that occurs before age 18, are identified as significant predictors of PCU later in adulthood (Moss et al., 2020). Specifically, research has found trauma-exposed individuals to be at greatest risk for PCU, increased risk for substance use disorders, and greater engagement in substance use for coping with emotional distress (Moss et al., 2020). For instance, a study of Hispanic young adults found that those with four or more ACEs had the highest odds of using cannabis by age 24 compared to those who reported fewer than four ACEs (Forster et al., 2020). Few studies have examined the influence of specific trauma types on cannabis use and PCU specifically, even as growing evidence indicates different types of traumatic experiences may lead to a range of negative outcomes (Wong et al., 2014). Dubowitz and colleagues (2016) examined the effects of unique types of childhood trauma and cannabis use frequency and found that only physical abuse and sexual abuse prior to age 18 was associated with heavy cannabis use (i.e., meeting criteria for cannabis abuse or dependence, using on more than 20 days in the last year, or using more than 10 times in the last month), whereas physical neglect and emotional maltreatment were not. In another recent study, Banducci and colleagues (2018) highlighted that childhood emotional abuse is often overlooked in adolescent and young adult cannabis research, despite its strong association with substance use initiation and severity and found that such trauma contributes significantly to greater cannabis use over time, especially for females.

Furthermore, a growing body of research has implicated cannabis use motives as key mechanisms in the relationship between mental health issues (especially depression, anxiety, trauma symptoms) on substance use problems, including cannabis use problems (Cooper et al., 2016). In their review of cannabis motives literature, Cooper and colleagues (2016) identified that the self-reported motive of using cannabis to cope with emotional distress, negative mood, or mental health symptoms was frequently associated with cannabis use over time. Based on Cox and Klinger’s incentive motivation model (1990), Cooper et al (2016) identified self-focused avoidance motives such as using substances to avoid a negative experience or feeling (i.e., depressed mood, physical pain) as one of the core motives for substance use. Numerous studies have also linked coping-motivated use of cannabis with greater PCU-related problems. Specifically, prior research has indicated that as motives related to managing emotional distress increases, cannabis use-related problem severity and problems with psychosocial functioning also increase (Amiet et al., 2020; Moitra et al., 2021). Further, research has linked these motives to greater cannabis use for individuals with histories of childhood maltreatment or trauma (De la Peña-Arteaga, 2021; Mills et al., 2017). Therefore, it is worthwhile to investigate how motives for use could serve as potential mechanisms for later PCU over time especially among trauma survivors (Meshesha et al., 2019).

Even though cannabis use may lead to some problematic outcomes, research shows that cannabis use can also ameliorate trauma symptoms and associated health-related difficulties, such as insomnia (Ataiants et al., 2021; Sachs-Ericsson et al., 2017), somatic complaints (Oh et al., 2018), and sleep disturbances due to intrusive symptoms (e.g., flashbacks; Bonn-Miller et al., 2013; Kovachy et al., 2013; Shannon & Opila-Lehman, 2016), though evidence may be presently premature for guiding clinical recommendations (Orsolini et al., 2019; Rehman et al., 2021; Sbarski, 2020; Tibbo et al., 2021). Thus, individuals may use cannabis as compensatory strategies or to manage symptoms of trauma (e.g., anxiety, insomnia) that could impact progression toward PCU, highlighting the importance of examining diverse cannabis use motives among EA users. Our prior work has provided some evidence that different trauma types prospectively predicted unique pathways towards PCU based on different motives for cannabis use (e.g., coping for mental health [e.g., inattention] and physical health [e.g., insomnia] reasons; (Brammer et al., 2023). Specifically, among young adults, using cannabis to cope with emotional distress significantly mediated the association between emotional abuse, emotional neglect, physical abuse, physical neglect, and sexual abuse and later PCU. In addition, using cannabis to improve inattention significantly mediated the association between physical neglect and later PCU.

To date, few studies have observed how different types of childhood trauma continue to impact PCU over time for EAs, though this remains an important area of inquiry as it may highlight key opportunities for early intervention. Despite our recent work showing that coping with mental health concerns (i.e., emotional distress, inattention) significantly mediated the association between different childhood trauma types and PCU among young adult cannabis users, limited studies have examined whether such a broad array of motives for cannabis use (i.e., mental and physical health issues) are associated with PCU as cannabis users progress through early adulthood. Furthermore, it would be important to also determine whether such associations tend to be negative (i.e., risky) or positive (i.e., protective). For example, using cannabis to cope with emotional distress due to trauma may confer risk towards the development of PCU (Moss et al., 2020), while using cannabis as way to manage insomnia may lead to reduced risk for PCU (Babson et al., 2017). This knowledge may guide clinicians’ efforts to identify and address developmentally appropriate targets for treatment (Moitra et al., 2021; Sofis et al., 2020).

The current study extends and builds on the previous investigation (Brammer et al., 2023) by examining these motive-mediated pathways from childhood trauma to PCU over the course of later emerging adulthood. Specifically, we address two primary research questions: (1) To what extent do cannabis motives for coping with mental health issues (i.e., using for emotional distress, inattention) and with physical health issues (e.g., using for sleep, pain, and nausea) mediate pathways between different types of childhood trauma (emotional abuse, sexual abuse, physical abuse, physical neglect, and emotional neglect) and later PCU over the course of the subsequent four years that spans a time of many changes, including developmental ones as well as cannabis policy-related ones in California (i.e., recreational cannabis legalization [RCL] in 2016)? (2) What are similarities and differences in these associations over time and relative to what was found in our prior study? Based on our prior findings, we hypothesized that the motives of coping with emotional distress and with inattention would significantly mediate the association between childhood trauma and later PCU at follow-up waves.

Method

This analysis utilized data from a prospective longitudinal study, Cannabis Health and Young Adults (CHAYA) Study, which conducted annual surveys of cannabis-using young adults recruited within the Los Angeles metro area starting in 2014. The study design is described further elsewhere (Lankenau et al., 2018) and was approved by the Institutional Review Boards at (Children’s Hospital Los Angeles) and (Drexel University). The current analysis is a longitudinal extension of a recently published study, which can be referenced for further information about findings from the first two waves of data (W1, W2; Brammer et al., 2023). To address our research questions, we employed two sets of multiple mediation models using four waves of data collected from 2016 to 2018 (W3, W4) and 2019–2020 (W5, W6). We mirror the original analysis (i.e., how W1 motives mediated between childhood trauma and PCU at wave 2) by examining how W3 motives mediated trauma and W4 outcomes and how W5 motives mediated trauma and W6 outcomes.

Sample

Participant recruitment occurred between February 2014 and April 2015. Eligibility criteria included: being between ages 18 and 26 years old; using cannabis (i.e., any generally identified cannabis products) at least four times in the last 30 days; living in the Los Angeles metro area; and being able to speak/read English. Participants were stratified based upon whether they had a current medical cannabis recommendation issued by a California-based physician or had never obtained a recommendation card: medical cannabis patients (MCP=210) or non-patient users (NPU = 156). Demographic information is presented in Table 1. With the exception of W3, which was collected via face-to-face interviews, the rest of the waves were collected using the Research Electronic Data Capture (REDCap) interface via personalized survey links sent to participants’ emails.

Table 1.

Descriptive Statistics (n = 251).

Variable	Total n (%) or Mean (SD)
	Baseline (n = 366)	Wave 3 (n = 322)	Wave 4 (n = 302)	Wave 5 (n = 260)	Wave 6 (n = 251)
Demographic Variables
Assigned Sex at Birth, Male (vs. Female)	225 (66.4%)	–	–	–	–
Gender Identity
Male	224 (66.3%)	–	–	–	–
Female	113 (33.4%)	–	–	–	–
Other	1 (.3%)	–	–	–	–
Race-Ethnicity
Non-Hispanic White	86 (25.8%)	–	–	–	–
Non-Hispanic Black/African-American	63 (18.9%)	–	–	–	–
Non-Hispanic Multiracial	20 (6.0%)	–	–	–	–
Non-Hispanic Asian/Pacific Islander	13 (3.9%)	–	–	–	–
Hispanic/Latino	151 (45.3%)	–	–	–	–
Days of Cannabis Use in Past 90 Days	69.15 (26.57)	–	–	–	–
Covariates
Age	21.21 (2.47)	23.18 (2.46)	24.21 (2.46)	26.16 (2.45)	27.19 (2.47)
Socioeconomic Status
Grew up in lower income household	104 (30.8%)	–	–	–	–
Grew up in middle income household	163 (48.2%)	–	–	–	–
Grew up in middle/upper income household	62 (18.3%)	–	–	–	–
Grew up in upper income household	9 (2.7%)	–	–	–	–
Medical or Recreational User
Exclusively medical (no recreational uses)	13 (3.6%)	14 (3.8%)	–	21 (5.7%)	–
Primarily medical (some recreational uses)	76 (20.8%)	51 (13.9%)	–	44 (12%)	–
Equally medical and recreational uses	134 (36.6%)	109 (29.8%)	–	69 (18.9%)	–
Primarily recreational (some medical uses)	94 (25.7%)	77 (21.0%)	–	63 (17.2%)	–
Exclusively recreational (no medical uses)	49 (13.3%)	41 (11.2%)	–	29 (7.9%)	–
Perceived Stress	–	–	16.57 (6.54)	–	17.64 (5.92)
Predictors
Childhood Trauma (assessed at W2)	41.34 (14.21)	–	–	–	–
Emotional Abuse	8.99 (4.48)	–	–	–	–
Emotional Neglect	10.92 (5.30)	–	–	–	–
Physical Abuse	7.64 (3.56)	–	–	–	–
Physical Neglect	7.83 (3.40)	–	–	–	–
Sexual Abuse	6.43 (3.51)	–	–	–	–
Mediators
Cannabis Use Motives
Emotional Distress	–	1.96 (0.91)	–	2.21 (0.99)	–
Attention	–	2.05 (1.07)	–	2.14 (1.16)	–
Sleep	–	3.11 (1.25)	–	2.98 (1.21)	–
Pain	–	2.67 (1.26)	–	2.67 (1.19)	–
Nausea	–	1.89 (1.09)	–	2.07 (1.10)	–
Outcomes
Severity of Dependence Scale	0.50 (0.68)	–	2.89 (2.94)	–	2.91 (3.10)
DSM Cannabis Use Disorder Symptoms	–	–	2.14 (2.58)	–	1.54 (2.13)

Measures

Childhood Trauma.

The Childhood Trauma Questionnaire (CTQ), a 28-item measure which rates the self-reported traumatic impact of a range of ACEs that occurred prior to age 18 (Bernstein, 1998), was administered at W2 only to capture self-reported childhood trauma history. This measure exhibited reliability and validity in community and adolescent populations (Bernstein et al., 1997). CTQ scores within this sample were similar to other ethnically and racially diverse urban young adult samples (Liebschutz et al., 2018). Each subscale contains 5-items reported on a 5-point scale ranging from “Never True” to “Very Often True” with all the items on the Emotional Neglect subscale reverse scored (e.g., a score of ‘1’ is recoded as ‘5’; Bernstein et al, 2003). We computed sum composites of the following scales: emotional abuse (e.g., “People in my family called me things like ‘stupid,’ ‘lazy,’ or ‘ugly’ ”; α=.84), emotional neglect (e.g., “I knew there was someone to take care of me and protect me”; α=.90), and sexual abuse (e.g., “Someone tried to touch me in a sexual way or tried to make me touch them”; α=.91; Scher et al., 2001) based on the present analyses.

Cannabis Use Motives.

The Comprehensive Marijuana Motives Questionnaire (CMMQ; (Lee et al., 2009; Lee et al., 2007), a 36-item instrument comprised of 17 subscales with 3-items per subscale rated on a 5-point scale (i.e., almost never/never to almost always/always), was assessed at each wave of data collection to assess motives for using cannabis. In the current analyses, we used five of these motives collected at W3 and W5: to cope with emotional distress (e.g., “To forget your problems”; α=.78; .78, respectively); to sleep (e.g., “Because you are having problems sleeping”; α=.89; .87); to relieve pain (e.g., “To relieve aches and pains”‘; α=.85; .83); to relieve nausea (e.g., “To keep me from vomiting”; α=.87; .88); and to increase focus/attention (e.g., “To keep me focused when I’m distracted”; α=.89; .92). The last three subscales (i.e., pain, nausea, focus/attention) and their items were added to the original CMMQ to include other mental and physical health-oriented motives for use and were developed with the study’s Community Advisory Board, including current young adult users, medical cannabis industry professionals, public health officials, and law enforcement. Prior psychometric analysis of this modified measure was found to have acceptable-to-good fit and congruence with the original CMMQ items (Wong, 2016). Specifically, a sequence of Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were conducted to determine the latent factor structure of the items (i.e., substantiating the subscales) and to ascertain these factors cohere as a whole measure. The final CFA model with the original CMMQ items and the newly created items showed acceptable-to-good fit (Chi²=2193.3, df=1088, p<.001, CFI=.90; TFI=.89; RMSEA=.05; Wong et al., 2016).

Problematic Cannabis Use (PCU).

PCU has been most prominently based on criteria for cannabis use disorder (CUD) using the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5; APA, 2013), which focuses on cannabis use’s impact on functioning, challenges with cravings, and symptoms of withdrawal or dependence. Previous literature has supported the use of the DSM-5 criteria for substance use disorders in research (Hasin et al., 2020). An 11-item measure based on DSM-5 criteria for CUD to assess functional impairment, such as spending a lot of time getting, using, and recovering from cannabis use (e.g., “Give up or cut down on activities that were important to you in order to use marijuana—like work, school, or associating with friends or relatives?”), negative consequences due to use (e.g., “Continue to use marijuana even though you knew it was causing you trouble with your family or friends?”), and physical cravings or urges (e.g., “Have a craving or a strong desire or urge to use marijuana?”), was introduced in W3 and administered at each following wave (α= 0.84, 0.81 for W4 and W6, respectively). Participants responded ‘yes’ or ‘no’ to items which were then summed with higher scores reflecting greater CUD symptoms (Hasin et al., 2013). Moreover, recent psychometric evaluation of the measure generally found agreement between moderate/severe CUD with DSM-IV dependence criteria and has supported its use among adult users (Livne et al., 2021).

In addition, PCU is recommended to be assessed by measures not tied to contextual factors or specific consequences of use, such as self-perceived concerns about one’s cannabis dependence, which may capture more of the psychological aspects of PCU (Annaheim et al., 2008; Blevins et al., 2018; Sznitman & Room, 2018). The Severity of Dependence Scale (SDS; (Martin et al., 2006) is a screener for cannabis dependence which focuses on psychological worries or concerns about one’s cannabis use. This measure of PCU reflects a participant-centered definition of problematic use, which has been associated actual attitudes and behaviors related to substance use (Annaheim et al., 2008; Blevins et al., 2018; Sznitman & Room, 2018). It has shown strong reliability and validity over time in adolescent and young adult samples (Piontek et al., 2008). It includes 5 items (e.g., “Did you ever think your use of marijuana was out of control,” “Did the prospect of missing a smoke make you very anxious or worried”) rated on a scale 0 to 3 (never or almost never, sometimes, often, always or almost always for items 1, 2, and 4; not at all, a little, quite a lot, a great deal for item 3, and not difficult, quite difficult, very difficult, impossible for item 5). Items are summed with higher scores indicating greater PCU (α= 0.83; 0.86, W4 and W6 respectively). This measure was assessed at each wave.

Socio-demographic Factors and Cannabis Related Covariates

Key socio-demographic factors (age, sex assigned-at-birth, race/ethnicity) and cannabis-related covariates (e.g., patient status [i.e., having a medical cannabis recommendation], orientation towards primarily medical vs. recreational use) were assessed using structured questions. Only orientation towards medicinal and recreational use, which was assessed on a 5-point scale ranging from exclusively/primarily medicinal to equally medicinal/recreational use to exclusively/primarily recreational use, was retained as a covariate in the final models given its association with outcomes. In addition, current perceived stress, assessed using the Perceived Stress Scale (PSS), a widely utilized 10-item measure of self-perceived stress level (Kamarck et al., 1983), was included as a covariate. The PSS is assessed at each wave and was included in the models concurrent with the outcome (e.g., W4 PSS in W4 SDS/DSM-5 outcome). Prior literature has linked higher perceived stress with greater cannabis use and PCU (Ketcherside & Filbey, 2015). Finally, W1 level of SDS (α = 0.82) was included as a covariate, concordant with models from the initial study; however, W1 DSM-5 was not included as a covariate as this measure was not included in the study until W3 (Brammer et al., 2023). Still, the inclusion of W1 SDS is considered sufficient given the strong, but moderate correlation between the SDS and DSM-5 at W3–6 (Spearman’s ρ ranges from .50 at W6 to .62 at W4).

Data Analysis

Between W1 and W6, the overall sample size decreased by 31.4%. We generally did not observe statistically significant differences across demographics, orientation towards medicinal or recreational cannabis use, or any of the outcome variables when examined between baseline and W6 sample based on attrition and between W3 and W6 based on attrition across each wave. Between W3–6, attrition was only associated with greater emotional distress motive (p<.01) and greater DSM-5 scores (p=.05). Attrition between W1 and W6 was also associated with slightly higher scores on the CTQ sexual abuse subscale (p<.01), meaning that there was greater attrition among individuals who reported greater impact of childhood sexual abuse. Still, based on these findings, the final sample at W6 was found to be generally representative of the initial sample. In addition, tests to ensure the assumption of collinearity indicated that multicollinearity was not a concern (VIF for all motives < 3).

As noted above, all models controlled for orientation towards medicinal or recreational use, W1 SDS, and W4 or W6 perceived stress (concurrent with W4 or W6 outcome, respectively), given their association with PCU outcomes. All cannabis motives were entered into every model concurrently to estimate their composite and independent indirect effects from trauma on PCU.

We utilized the multiple mediation PROCESS macro (Hayes, 2013) to assess whether cannabis motives at W3 and W5 mediated the association of childhood trauma exposure on SDS and DSM-5 at W4 and W6, respectively. We utilized the same approach as our initial analysis with W1 and W2 data (Brammer et al., 2023). Analyses incorporated bootstrapping that non-parametrically re-samples a dataset 5000 times and derives percentages from calculated distributions to estimate 95% bias corrected and accelerated (BCa) confidence intervals (CI) and associated indirect effects. The PROCESS macro accommodates missing data through listwise deletion. Bootstrapping is statistically more powerful that more traditional measurement approaches and accommodates skewed data (MacKinnon et al., 2000; Preacher & Hayes, 2008; Zhao et al., 2010). The current models provide temporally-ordered predictors, mediators, and outcomes, given the retrospective report of trauma, consistent with recommendations for investigating causal mediation (Kraemer et al., 2001). Mediation is theorized to follow a “stage sequence” process in which the predictor impacts the mediator, which then affects the outcome (Collins et al., 1998); given that these effects can often suppress one another, mediation models no longer include any requirement for direct effects (Zhao et al., 2010). Furthermore, bootstrapping estimates of indirect effects can still be statistically significant if one or both of individual a and b pathways are non-significant (Hayes, 2022). In this analysis, separate models examined whether W3 or W5 cannabis motivations mediated the association of trauma subscales with W4 or W6 SDS and DSM-5, respectively.

Results

Descriptive data for the current sample are summarized in Table 1. Within each set of models (i.e., W3 mediator/W4 outcome and W5 mediator/W6 outcome models) below, we present the independent associations of trauma type with each motive, followed by the associations of each motive with SDS and DSM-5, after controlling for covariates. We then review the bootstrapped indirect effects of trauma type on SDS and DSM-5 through each motive. Results regarding the total effect of trauma type (i.e., the effect of trauma type on SDS or DSM-5 without control of all motives in the model) and direct effect of trauma type on SDS or DSM-5 (i.e., the effect of trauma type on SDS or DSM-5 after accounting for all motives and covariates in the model) are reviewed in Table 2. See Table 2 for full details of models and Figures 1a–c and 2a–c for significant mediation models. Of note, for conciseness and focus on our primary research question, the models for which there was significant mediation are presented here (i.e., models for emotional abuse, emotional neglect, and sexual abuse) whereas the final models for physical abuse and physical neglect are available for review in supplementary material (Table 3).

Table 2.

Total effects, direct effects, and specific indirect effects of mediation models.

Path	Predictor →Wave 3 Motives→ Wave 4 Outcomes			Predictor →Wave 5 Motives→ Wave 6 Outcomes
	a B (SE)	b B (SE)	Indirect B (SE)	a B (SE)	b B (SE)	Indirect B (SE)
Associations by Severity Dependence Scale (SDS)
Emotional Abuse on SDS via
Wave 3/5 Emotional Distress	0.04 (0.01)**	0.50 (0.23)*	0.02 (0.01)*	−0.01 (0.02)	0.58 (0.29)*	−0.01 (0.01)
Wave 3/5 Attention	0.00 (0.02)	0.18 (0.21)	0.00 (0.00)	−0.02 (0.02)	0.24 (0.32)	−0.01 (0.01)
Wave 3/5 Sleep	0.01 (0.02)	−0.23 (0.18)	0.00 (0.01)	−0.02 (0.02)	−0.02 (0.28)	0.00 (0.01)
Wave 3/5 Pain	0.02 (0.02)	−0.54 (0.20)**	−0.01 (0.01)	−0.01 (0.02)	0.10 (0.32)	0.00 (0.01)
Wave 3/5 Nausea	0.01 (0.02)	0.38 (0.22)	0.01 (0.01)	−0.02 (0.02)	0.04 (0.32)	0.00 (0.01)
Total effect	–	–	0.02 (0.02)	–	–	−0.01 (0.02)
Total direct effect	–	–	−0.04 (0.04)	–	–	0.02 (0.06)
Emotional Neglect on SDS via
Wave 3/5 Emotional Distress	0.01 (0.01)	0.41 (0.22)	0.00 (0.01)	0.01 (0.02)	0.48 (0.28)	0.00 (0.01)
Wave 3/5 Attention	−0.01 (0.01)	0.21 (0.21)	0.00 (0.00)	0.02 (0.02)	0.21 (0.32)	0.00 (0.01)
Wave 3/5 Sleep	−0.01 (0.01)	−0.21 (0.18)	0.00 (0.00)	0.00 (0.02)	0.00 (0.28)	0.00 (0.01)
Wave 3/5 Pain	−0.02 (0.01)	−0.53 (0.20)**	0.01 (0.01)*	0.02 (0.02)	0.04 (0.33)	0.00 (0.01)
Wave 3/5 Nausea	−0.01 (0.01)	0.37 (0.21)	0.00 (0.01)	0.01 (0.02)	0.10 (0.32)	0.00 (0.01)
Total effect	–	–	0.01 (0.01)*	–	–	0.01 (0.02)
Total direct effect	–	–	0.05 (0.03)	–	–	0.05 (0.05)
Sexual Abuse on SDS via
Wave 3/5 Emotional Distress	0.02 (0.01)	0.46 (0.22)*	0.01 (0.01)*	−0.01 (0.02)	0.54 (0.29)	0.00 (0.01)
Wave 3/5 Attention	0.01 (0.02)	0.23 (0.21)	0.00 (0.01)	0.00 (0.03)	0.19 (0.32)	0.00 (0.01)
Wave 3/5 Sleep	0.05 (0.02)*	−0.14 (0.18)	−0.01 (0.01)	0.01 (0.03)	−0.05 (0.29)	0.00 (0.01)
Wave 3/5 Pain	0.03 (0.02)	−0.54 (0.20)**	−0.01 (0.01)	−0.02 (0.03)	0.17 (0.34)	0.00 (0.01)
Wave 3/5 Nausea	0.05 (0.02)**	0.36 (0.22)	0.02 (0.01)*	−0.01 (0.02)	0.03 (0.32)	0.00 (0.01)
Total effect	–	–	0.01 (0.02)	–	–	−0.01 (0.02)
Total direct effect	–	–	−0.06 (0.05)	–	–	−0.06 (0.07)
Associations by Cannabis Use Disorder Symptoms (DSM-5)
Emotional Abuse on DSM-5 via
Wave 3/5 Emotional Distress	0.03 (0.01)**	0.28 (0.20)	0.01 (0.01)	0.01 (0.01)	0.30 (0.16)	0.00 (0.01)
Wave 3/5 Attention	0.00 (0.01)	0.04 (0.18)	0.00 (0.00)	−0.01 (0.02)	0.05 (0.17)	0.00 (0.00)
Wave 3/5 Sleep	0.01 (0.02)	−0.10 (0.15)	0.00 (0.00)	−0.01 (0.02)	0.10 (0.15)	0.00 (0.00)
Wave 3/5 Pain	0.01 (0.02)	−0.29 (0.17)	0.00 (0.01)	0.01 (0.02)	−0.16 (0.18)	0.00 (0.00)
Wave 3/5 Nausea	0.01 (0.01)	0.38 (0.19)*	0.00 (0.01)	0.00 (0.02)	−0.01 (0.18)	0.00 (0.00)
Total effect	–	–	0.01 (0.01)	–	–	0.00 (0.01)
Total direct effect	–	–	0.03 (0.04)	–	–	0.04 (0.03)
Emotional Neglect on DSM-5 via
Wave 3/5 Emotional Distress	0.00 (0.01)	0.29 (0.19)	0.00 (0.00)	0.03 (0.01)*	0.31 (0.16)*	0.01 (0.01)*
Wave 3/5 Attention	−0.01 (0.01)	0.04 (0.18)	0.00 (0.00)	0.02 (0.01)	0.04 (0.17)	0.00 (0.00)
Wave 3/5 Sleep	−0.01 (0.01)	−0.12 (0.15)	0.00 (0.00)*	0.02 (0.01)	0.09 (0.15)	0.00 (0.00)
Wave 3/5 Pain	−0.03 (0.01)*	−0.28 (0.17)	0.01 (0.01)*	0.03 (0.01)	−0.14 (0.18)	0.00 (0.01)
Wave 3/5 Nausea	−0.01 (0.01)	0.39 (0.19)*	0.00 (0.01)	0.02 (0.01)	0.00 (0.18)	0.00 (0.00)
Total effect	–	–	0.00 (0.01)	–	–	0.01 (0.01)
Total direct effect	–	–	0.04 (0.03)	–	–	−0.02 (0.03)
Sexual Abuse on DSM-5 via
Wave 3/5 Emotional Distress	0.02 (0.01)	0.33 (0.20)	0.01 (0.01)	0.00 (0.02)	0.27 (0.16)	0.00 (0.01)
Wave 3/5 Attention	0.01 (0.02)	0.06 (0.18)	0.00 (0.00)	0.01 (0.02)	0.00 (0.17)	0.00 (0.00)
Wave 3/5 Sleep	0.04 (0.02)*	−0.04 (0.15)	0.00 (0.01)	0.02 (0.02)	0.08 (0.15)	0.00 (0.00)
Wave 3/5 Pain	0.02 (0.02)	−0.29 (0.36)	−0.01 (0.01)	0.00 (0.02)	−0.10 (0.18)	0.00 (0.00)
Wave 3/5 Nausea	0.04 (0.02)*	0.36 (0.19)	0.01 (0.01)*	0.01 (0.02)	−0.03 (0.18)	0.00 (0.00)
Total effect	–	–	0.01 (0.01)	–	–	0.00 (0.01)
Total direct effect	–	–	−0.02 (0.04)	–	–	0.00 (0.04)

^*p ≤ .05.

^**p ≤ .01.

Figure 1a.

Emotional Distress Motive Mediates the Association Between Emotional Abuse and W4 SDS Outcome. Bolded mediators indicate significant mediation (p<.05).

Figure 2a.

Sleep and Pain Motives Mediate the Association Between Emotional Neglect and W4 DSM-5 Outcome. Bolded mediators indicate significant mediation (p<.05).

Predictions of Problematic Cannabis Use (PCU) as indicated by SDS

Emotional Abuse

W4 Results.

Emotional abuse significantly positively predicted only W3 emotional distress motive. W3 emotional distress motive positively predicted W4 SDS, whereas pain motive negatively predicted W4 SDS. Results showed that W3 emotional distress motive significantly mediated the effect of emotional abuse on W4 SDS (See Figure 1a). W6 Results. Emotional abuse was unrelated to any W5 motives, while W5 emotional distress motive positively predicted W6 SDS. Bootstrapping estimates found no significant mediation of W5 motives in the association between emotional abuse and W6 SDS.

Emotional Neglect

W4 Results.

Emotional neglect was not associated with any W3 motives. W3 pain motive significantly negatively predicted W4 SDS. Bootstrapping analyses indicated that only W3 pain motive emerged as a significant mediator of the effect of emotional neglect on W4 SDS (See Figure 1b). In this model, there was a significant total effect of emotional neglect on W4 SDS without controlling for the effect of covariates or W3 motives. W6 Results. Emotional neglect was unrelated to all W5 motives, and no motives were associated with W6 SDS. Bootstrapping identified no significant mediation.

Figure 1b.

Pain Motive Mediates the Association Between Emotional Neglect and W4 SDS Outcome. Bolded mediators indicate significant mediation (p<.05).

Sexual Abuse

W4 Results.

Sexual abuse significantly positively predicted W3 sleep and nausea motives. Emotional distress motive significantly and positively predicted W4 SDS; whereas W3 pain motive significantly negatively predicted W4 SDS. Bootstrapping estimated that both emotional distress and nausea motives significantly mediated the effect of sexual abuse on W4 SDS (See Figure 1c). W6 Results. Sexual abuse was unrelated to all W5 motives, and no motives were associated with W6 SDS. Bootstrapping estimates indicated no significant mediation.

Figure 1c.

Emotional Distress and Nausea Motives Mediate the Association Between Sexual Abuse and W4 SDS Outcome. Bolded mediators indicate significant mediation (p<.05).

Predictions of Wave 4 PCU as indicated by the DSM-5

Emotional Abuse

W4 Results.

Emotional abuse significantly positively predicted only W3 emotional distress and W3 nausea motive significantly and positively predicted W4 DSM-5. Bootstrapping estimates indicated that no motives significantly mediated the effect of emotional abuse on W4 DSM-5. W6 Results. Emotional abuse was unrelated to any W6 motives and no W5 motives were associated with W6 DSM-5 outcome. No motives emerged as significant mediators.

Emotional Neglect

W4 Results.

Emotional neglect was significantly and negatively associated with only W3 pain motive. Only W3 nausea motive was significantly positively associated with W4 DSM-5. Both sleep and pain motives emerged as significant mediators of the effect of emotional neglect on W4 DSM-5 through bootstrapping (See Figure 2a). W6 Results. Emotional neglect positively predicted W5 emotional distress motive and W5 emotional distress motive significantly and positively predicted W6 DSM-5. Bootstrapping estimates indicated W5 emotional distress motive significantly mediated the association between emotional neglect and W6 DSM-5 (see Figure 2b).

Figure 2b.

Emotional Distress Motive Mediates the Association Between Emotional Neglect and W6 DSM-5 Outcome. Bolded mediators indicate significant mediation (p<.05).

Sexual Abuse

W4 Results.

Sexual abuse significantly positively predicted W3 nausea and sleep motives, while no W3 motives were associated with W4 DSM-5. Bootstrapping estimates determined that only the W3 nausea motive significantly mediated the association between sexual abuse and W4 DSM-5 (see Figure 2c). W6 Results. Sexual abuse was unrelated to any W5 motives nor were any motives associated with W6 DSM-5. No motives emerged as significant mediators of sexual abuse on W6 DSM-5.

Figure 2c.

Nausea Motive Mediates the Association Between Sexual Abuse and W4 DSM-5 Outcome. Bolded mediators indicate significant mediation (p<.05).

Discussion

The present study addressed a gap in the literature examining whether and to what extent mental and physical health-related cannabis use motives (i.e., emotional distress, inattention, sleep, pain, nausea) persist in mediating the association between the negative impact of specific types of childhood trauma (i.e., emotional abuse, sexual abuse, physical abuse, physical neglect, and emotional neglect) and two indicators of PCU (i.e., the DSM-5 and SDS) during emerging adulthood. The current study extends an earlier analysis identifying the mediational pathways of cannabis use motives on the relationship between types of childhood trauma experiences and PCU among young adult medical cannabis patient and non-patient users, which found that using cannabis for emotional coping and inattention significantly mediated the association between different childhood trauma types and greater PCU, though there were no observed associations for other health-related motives (Brammer et al., 2023). In our analysis, we found that both mental and physical health-related coping mediated the pathways between the impact of types of childhood trauma and PCU, but these associations varied over time and by each outcome measure. As our childhood trauma measure assesses the impact of exposure, our findings indicate that certain childhood trauma exposures perceived as more impactful by participants were associated with greater maladaptive motives for cannabis and, consequently, greater PCU. However, other motives were associated with less PCU, indicating perhaps a buffering or protective effect. Further, in employing multiple indicators of PCU to capture a range of maladaptive behavioral symptoms and negative consequences of cannabis use cannabis abuse/dependence, including worries or concerns about one’s cannabis use, and functional impairment, such as missing work or family obligations, we observed nuances in these mediational pathways towards PCU.

Our results showed that the use of cannabis to cope with emotional distress was associated with PCU into emerging adulthood (three years post-baseline at W4); however, this pathway appeared to be mostly attenuated by later adulthood (five years post-baseline at W6). Specifically, and similar to what we found in the original study, W3 emotional distress motive significantly mediated the pathway from emotional abuse and sexual abuse to W4 SDS outcome; however, we did not find this by W6. In these models, the effect reflected those who endorsed greater use of cannabis for emotional distress at W3 reporting greater SDS scores at W4. Further, those who endorsed greater impact of childhood emotional abuse were also more likely to report using cannabis for emotional distress at W3. In contrast, W5 emotional distress motive mediated the pathway between emotional neglect and W6 DSM-5 outcome solely. In this model, the effect reflected those who endorsed greater impact of childhood emotional neglect were more likely to endorse using cannabis for emotional distress at W5 and those using cannabis for emotional distress at W5 reporting greater CUD symptoms at W6. This was also the only significant mediation effect between trauma with either indicator of PCU by W6. These results highlight that childhood sexual abuse and emotional abuse may have lingering effects that motivates individuals to use cannabis to cope with distress, contributing to PCU. However, while the pathway from using cannabis to cope with trauma-related emotional distress leading to later PCU seems to attenuate as these EAs mature, the impact of emotional neglect emerges. Though this type of childhood trauma is much less explored in the literature, this finding may reflect a different aspect of emotional abuse that becomes more apparent as EAs age and reflects an area for further exploration.

In line with prior research, our findings suggest that for EAs impacted by childhood emotional and sexual abuse, engaging in cannabis use as a means of coping with emotional distress may reflect a maladaptive response to avoid unpleasant feelings and alleviate negative affect (Cooper et al., 2016; Glodosky & Cuttler, 2020; Lucke et al., 2021), leading to chronic or problematic use as these symptoms escalate and avoidance is no longer an effective strategy (Colder et al., 2019; Moitra et al., 2021). Further, in their study, Lucke and colleagues (2021) found that while emotion dysregulation alone was not related to cannabis consumption, individuals with greater emotion dysregulation were more likely using cannabis to cope with negative emotions. For EAs with trauma histories, experiencing greater emotion dysregulation, a common sequelae of trauma exposure, may increase risk of using cannabis to cope with negative affect and thus, increase risk of developing PCU later (Lucke et al., 2021).

In comparison with our initial analyses in which participants were in late adolescence/early young adulthood (Brammer et al., 2023), we observed a change in the mediational relationships as participants transitioned into later emerging adulthood. Notably, we no longer found that using cannabis to increase attention/focus predicted greater PCU. This was an unexpected finding and may reflect changes in EAs’ cannabis motives as they age. In other words, as participants transitioned out of the college age and into different roles, motives for managing inattention may have attenuated, while other motives associated with physical health concerns emerged (e.g., pain, nausea, sleep issues). While a recent review found that many cannabis users with inattention symptoms generally report use of cannabis also to manage sleep problems and physical pain (Hernandez & Levin, 2022), this was contrary to our current findings. Though EA in our study may have expressed greater inattention motives earlier in young adulthood (during waves 1 and 2), this motive may have been less strong for these cannabis users compared to sleep and pain motives by later emerging adulthood. Further research is needed to understand the trajectory of how this motive may evolve in EA with trauma histories across developmental stages; specifically, cannabis-seeking EA who may or may not be diagnosed with attention deficit/hyperactivity disorder (ADHD) and receiving treatment for inattention related to ADHD or traumatic stress. As our sample is non-clinical, our initial findings about inattention may reflect inattention motives more generally among young adults impacted by trauma, but this finding may not translate to EA with ADHD.

Our results indicated that pain motive significantly mediated the effect of emotional neglect on PCU as indicated by the SDS, with the effect indicating those that use cannabis for pain reported less PCU at W4. Pain motive also mediated the effect of emotional neglect on PCU as indicated by the DSM-5 at W4, with the effect also reflecting those who endorse using cannabis for pain reported less PCU. In other words, using cannabis for pain was associated with lower PCU, suggesting that this motive may reduce risk of negative cannabis-related consequences. We also found that using cannabis for sleep mediated the association between emotional neglect and W4 DSM-5, with the effect reflecting those who use cannabis for sleep reporting fewer CUD symptoms. This association of greater pain and sleep motives and lower PCU was observed across the majority of models, suggesting that such motives may be adaptive, acting as a protective buffer for EA cannabis users with physical health concerns (Babson et al., 2017; Shorey Fennell et al., 2022). Further, these motives were negatively associated with the impact of childhood emotional neglect (though these associations were not significant) and may not reflect management of trauma-related symptoms.

Finally, using cannabis to manage nausea significantly mediated the pathway between childhood sexual abuse and both indicators of PCU at W4, with the effect reflecting those who endorsed greater impact of sexual abuse being significantly more likely to use cannabis for nausea, leading to greater PCU. In contrast to the models with other physical health-related motives (i.e., pain, sleep), this model appears to indicate greater nausea motive among those reporting being more affected by childhood sexual abuse and suggests use for management of trauma-related symptoms. Prior research has documented greater experiences of gastrointestinal distress, including nausea and vomiting, among survivors of childhood sexual abuse (Bonomi et al., 2008).

These findings regarding physical health-related motives are particularly salient given that approximately two-thirds of our sample are medical cannabis patients, and one-third of the sample reports using cannabis exclusively or primarily for medicinal reasons. Research has found that while medical cannabis users tend to report greater frequency of use owing to their health-related motives, such use is not generally associated with problematic cannabis use or abuse (Lin et al., 2016). Moreover, greater prevalence of medical conditions and norms related to medical cannabis use may have impacted our findings, such that participants were more likely to engage in medicinal cannabis use for certain physical health-related issues but were not more likely to develop negative cannabis-related consequences. Our research provides continued evidence that EAs may use cannabis for both mental and physical health reasons and that such use is not always associated with negative outcomes; especially, if they are using to manage sleep and pain issues. However, we found that the motive of using cannabis to cope with emotional distress remained associated with greater PCU, even into later emerging adulthood.

Limitations and Future Directions

We note several limitations in the present work. While our sample is heterogenous in many ways, the data was collected from 18–26-year-old cannabis users who were living in the Los Angeles area at the start of the study in 2014, which has implications for generalizability to young adults in other geographic locations. The data is based on retrospective self-report, which could result in recall bias, particularly regarding childhood trauma; thus, future studies would benefit from the use of multi-informant report to reduce such bias. Further, we did not account for different modes of administration or product types in our analyses, which may have biased their responses on the SDS in particular which asks pointed questions about “missing a smoke”; however, smoking has remained the most popular and prevalent mode of administration for this sample over time such that the influence of this bias is assumed to be limited. We also did not examine other specific life stressors outside of childhood abuse, such as recent types of traumas or discrimination (Okamoto et al., 2009), or other factors (e.g., mental health conditions) that may have contributed to cannabis use, though we did control for the influence of current perceived stress. In addition, our analyses did not account for the potential influence of access to mental health treatment or other factors that might attenuate the relationship between childhood trauma and PCU in adulthood, such as social support. While outside the scope of the present study, these limitations reflect areas for future research to examine other potential factors that may increase risk or buffer against the development of PCU for adult survivors of childhood trauma and abuse. Finally, as noted in our results, we did not find any significant mediational pathways in the models for physical abuse and neglect, which is not consistent with prior literature among adolescents and young adults, including our prior analysis (e.g., Brammer et al., 2023; Dubowitz, 2016), and may reflect changes in the impact of this specific type of childhood trauma as young adults age into later emerging adulthood. As such, future exploration of these changes in the impact of trauma over time and its influence on EA cannabis use is suggested.

Given more recent national data indicating limited public health and national efforts to address PCU despite rising prevalence of such issues among U.S. EAs (Cerdá et al., 2019; Hall & Lynskey, 2020; Mennis, 2021), our findings suggest unique pathways for DSM-5 CUD symptoms and concerns about cannabis-related consequences among EAs with childhood trauma histories. Further, our results highlight the importance of and value for assessing a wide variety of motives, including mental and physical health-related coping, particularly among those with histories of sexual abuse and emotional abuse. Moreover, these results demonstrated potential risk for PCU associated with using cannabis to cope with emotional distress and nausea, though using for pain or sleep may buffer against such deleterious outcomes. Of note, among the eight significant mediational pathways, half were observed with the SDS outcome and the other half with the DSM-5 symptom outcome, suggesting both were capturing PCU, respectively. Though the SDS and DSM-5 tap into the underlying construct of PCU, the former is anchored in the last 12 months and the latter in the last 3 months, which may have contributed to some of the differences in findings. Nonetheless, our findings also suggest the importance of employing multiple measures of PCU to capture the range of negative consequences that may be experienced by frequent cannabis users, beyond traditional assessment of clinical symptoms which may overlook other vital indicators of problematic use.

The impact of ACEs on health disparities in adulthood, particularly among under-resourced communities and communities of color, has been an area of increasing inquiry, with studies demonstrating that such early life stress can lead to complex issues with sleep, pain, gastrointestinal issues, and emotional distress, which may be associated with maladaptive cannabis use as a means of self-treatment (Hyman & Sinha, 2009; Maultsby et al., 2021). Research has identified several evidence-based treatments for problematic substance use, such as cognitive behavioral and motivation enhancement therapies (Sabioni & Le Foll, 2019), though there remains a lack of understanding around strategies to address cannabis use motives as a mechanism of change. Our findings highlight a vital area for future research regarding targeted intervention in addressing PCU. Specifically, future efforts should be directed towards assessing and treating negative emotion, emotional distress, and avoidance among EA cannabis users, particularly those impacted by childhood emotional abuse, neglect, and sexual abuse (Davis et al., 2005; Heng et al., 2018).