Abstract
Background
Depression is associated with substance-related problems that worsen depression-related disability. Marijuana is frequently used by those with depression, yet whether its use contributes to significant barriers to recovery in this population has been understudied.
Method
Participants were 307 psychiatry outpatients with depression; assessed at baseline, 3-, and 6-months on symptom (PHQ-9 and GAD-7), functioning (SF-12) and past-month marijuana use for a substance use intervention trial. Longitudinal growth models examined patterns and predictors of marijuana use and its impact on symptom and functional outcomes.
Results
A considerable number of (40.7%; n = 125) patients used marijuana within 30-days of baseline. Over 6-months, marijuana use decreased (B = −1.20, p < .001), but patterns varied by demographic and clinical characteristics. Depression (B = 0.03, p < .001) symptoms contributed to increased marijuana use over the follow-up, and those aged 50+ (B = 0.44, p < .001) increased their marijuana use compared to the youngest age group. Marijuana use worsened depression (B = 1.24, p < .001) and anxiety (B = 0.80, p = .025) symptoms; marijuana use led to poorer mental health (B = −2.03, p = .010) functioning. Medical marijuana (26.8%; n = 33) was associated with poorer physical health (B = −3.35, p = .044) functioning.
Limitations
Participants were psychiatry outpatients, limiting generalizability.
Conclusions
Marijuana use is common and associated with poor recovery among psychiatry outpatients with depression. Assessing for marijuana use and considering its use in light of its impact on depression recovery may help improve outcomes.
Keywords: anxiety, depression, marijuana, alcohol
1. Introduction
Depression affects approximately 6% (16 million adults) of the U.S. general population and is a leading cause of disability (Substance Abuse and Mental Health Services Administration [SAMHSA], 2015). Studies report that depression is associated with substance use, which can worsen depression-related disability (Davis et al., 2008; Grant et al., 2004). These studies have found depression is associated with a two-fold increase in the rate of alcohol-related problems and a six-fold increase in marijuana-related problems (Grant et al., 2004). Yet clinical outcomes of depression patients who use marijuana are understudied in contrast to alcohol, perhaps due to the larger public health burden associated with depression and alcohol use (Degenhardt & Hall, 2009). However, there is also considerable potential for marijuana to impede the recovery of vulnerable subgroups, including clinical populations. Clinical studies report that marijuana use among depression patients can lead to worse symptoms, more depressive episodes, and impede treatment (Davis et al., 2008; Bricker et al., 2007). These findings suggest that marijuana may be a critical issue for further understanding recovery outcomes in adults with depression.
Differences in demographic, clinical, and marijuana use characteristics are important considerations for the treatment and recovery of persons with depression. Depressed persons who use drugs, including marijuana are often younger, male, divorced or never married and not of Hispanic origin (Davis et al., 2008; Melartin et al., 2002; McDermut et al., 2001). Marijuana and other drug use among depressed persons can lead to worse anxiety, drug use relapse post-treatment, and poor functioning (Hasin et al., 2002; Davis et al., 2008). Whether such findings are present and persist over time in a clinical sample of depressed patients is largely unknown.
This study addresses this important question by examining 6-month patterns of marijuana use and its impact on symptom and functional recovery outcomes for 307 depressed outpatients using and not using marijuana and participating in an alcohol/illicit-drug use intervention. We identified: (1) longitudinal patterns of marijuana use; (2) demographic and clinical predictors of marijuana use; (3) associations between marijuana use, depression and anxiety symptoms, and functioning over the 6-month follow-up.
2. Method
2.1. Participants
Data were collected for a randomized controlled trial of motivational interviewing (MI) in alcohol/drug use treatment for depressed patients, for which the results have been reported (Satre et al., 2016). A total of 307 patients were recruited from Kaiser Permanente Southern Alameda Center Department of Psychiatry in Union City and Fremont, CA. Inclusion criteria were: aged 18 or older; Patient Health Questionnaire score ≥ 5 (PHQ-9: Kroenke et al., 2001); met drug use (illicit/non-prescribed use) or hazardous drinking criteria (≥ 3/≥ 4 drinks/day for women/men) within the past 30-days. A Hazardous drinking standard more conservative than that recommended for the general population was used (Satre et al., 2016). Patients with mania or psychosis were excluded.
The present study makes use of secondary data from the previously described trial of MI in alcohol/drug use for depressed patients. In this secondary analysis, we focused on examining the 6-month patterns and predictors of marijuana use and its association with recovery for those using (n = 125) and not using marijuana (n = 182).
2.2. Measures
2.2.1. Marijuana and other substance use
Patients were asked how many days they used marijuana and other substances, including alcohol during the past 30-days at baseline, 3- and 6-months: alcohol, marijuana, cocaine, amphetamine, stimulants, sedatives (other than prescribed), opioids (other than prescribed), heroin, and ecstasy; collapsed as dichotomous (any use = 1; else = 0) due to low frequency. To adjust for non-marijuana substance use in longitudinal analyses a composite was created, where ‘any use’ of the mentioned substances = 1 (except marijuana) and 0 = otherwise. Patients endorsing marijuana use were asked “was the marijuana used in the past 30-days always used for medical purposes, as recommended/prescribed by a provider (medical use =1; otherwise =2)?”
2.2.2. Symptom and functioning recovery outcomes
PHQ-9 depression was measured 2 weeks prior to each interview; higher scores indicate greater depression (9-items, range 0 to 27; score > 5 = at least mild depression) (Kroenke et al., 2001). Generalized Anxiety Disorder scale (GAD-7; Spitzer et al., 2006) anxiety was measured 2 weeks prior to each interview; higher scores indicate greater anxiety (7-items, range 0 to 21; score > 5 = at least mild anxiety) (Spitzer et al., 2006). SF-12 mental health functioning using the MCS-12 subscale was assessed 4 weeks prior to each interview; lower scores indicate worse mental health functioning (12-items, range 0 to 100, M = 50; SD = 10) (Ware et al., 1998). SF-12 physical health functioning using the PCS-12 subscale was assessed 4 weeks prior to each interview (12-items, range 0 to 100, M = 50; SD = 10); lower scores indicate worse physical health functioning (Ware et al., 1998).
2.3. Procedures
Eligibility of the 307 participants was determined by baseline alcohol/drug use measures and PHQ-9 depression. Patient information was collected at baseline and then participants were randomized (MI: 45 minute in-person session followed by two 15-minute boosters; Control: 2-page brochure on substance use risk). Patients were offered $50 gift cards for completing the interviews (baseline, 3-, and 6-month). Of the 307 participants, 296 (96%) completed the 3-month telephone follow-up, 302 (98%) completed 6-month follow-up. Substance use, and participant’s symptoms and functioning were collected at baseline, 3-, and 6-months. The University of California, San Francisco (UCSF) Committee on Human Subjects and the Kaiser Permanente Institutional Review Board approved the procedures. Patients were provided with written informed consent prior to participation.
2.4. Data Analysis
Analyses began by examining baseline differences between patients using and not using marijuana by using χ2 (categorical) and independent sample t (continuous) tests. Longitudinal analyses proceeded using a series of mixed-effects growth models, a form a hierarchical linear modeling for repeated measures data, where multiple measurement occasions are nested within individuals (Raudenbush & Bryk, 2009). Patterns of patients using marijuana were tested using generalized mixed-effects growth models employing penalized-quasi likelihood estimation for computing parameter estimates of binary outcomes. Analyses began with unconditional growth models predicting marijuana use from time (coded: 0 = baseline; 1 = 3-months; 2 = 6-months) to examine overall trajectories of marijuana use. Conditional growth models were computed to examine characteristics that may predict increased use of marijuana. Age, sex, marital status, race/ethnicity, MI, non-marijuana substance use, time-varying psychiatry visits, and time-varying depression were included in conditional models with marijuana use. Predictors were chosen because prior research signaled the variable as related to marijuana use and depression or the variable was significant in prior analyses. GAD-7 anxiety was not included as a predictor with marijuana use outcomes, owing to its high its correlation with PHQ-9 depression. Finally, associations between marijuana use and recovery outcomes were examined. These analyses were conducted with mixed-effects growth models using restricted maximum likelihood estimation for continuous outcomes, predicting symptom and functioning outcomes from time and time-varying marijuana. Rather than discard partial completers (~4.0% of the sample), the expectation maximization approach was used to handle missing data at analysis. Analyses were carried out in R version 2.14.2 (R Development Core Team, 2016). Statistical significance was defined at p < .05.
3. Results
3.1. Prevalence and characteristics of depression patients using marijuana
A considerable number of depressed patients were using marijuana at baseline, with 125 (40.7%) of the 307 patients reporting use in the prior 30 days (Table 1). Overall, few differences existed between those using and not using marijuana. Marijuana using patients were younger, less likely to be married, and more likely to use tobacco than those not using the drug (Table 1).
Table 1.
Characteristics of patients with depression using and not using marijuana.
| Variable | Patients using Marijuana n = 125 (40.7%) |
Patients not using Marijuana n = 182 (59.2%) |
Pa |
|---|---|---|---|
| M (SD) | M (SD) | ||
| Demographic Characteristics | |||
| Race/ethnicity | |||
| —n (% White) | 49 (39.2) | 68 (37.3) | .836 |
| —n (% Black) | 23 (18.4) | 42 (23.0) | .399 |
| —n (% Hispanic) | 32 (25.6) | 35 (19.2) | .253 |
| —n (% Asian) | 16 (12.8) | 27 (14.8) | .735 |
| —n (% other/unknown) | 5 (4.0) | 10 (5.4) | .743 |
| Age | 33.59 (12.82) | 39.68 (12.89) | <.001 |
| Sex—n (% female) | 82 (65.6) | 134 (73.6) | .165 |
| Marital Status—n (% married) | 43 (34.4) | 86 (47.2) | .033 |
| Employment—n (% employed) | 81 (64.8) | 123 (67.5) | .700 |
| Income—n (% ≥ 50k) | 60 (48.0) | 103 (56.5) | .399 |
| Clinical Characteristics | |||
| PHQ-9 Depressionb score | 14.30 (5.84) | 13.64 (5.41) | .316 |
| GAD-7 Anxietyc score | 11.21 (5.42) | 10.56 (4.97) | .289 |
| SF-12 Mental Healthd | 29.12 (9.72) | 29.82 (9.46 | .534 |
| Functioning score | |||
| SF-12 Physical Healthe | 49.31 (10.64) | 49.38 (10.13) | .956 |
| Functioning score | |||
| Medical marijuana use—n(% use) | 33 (26.8) | – | – |
| Alcohol use—n (% alcohol use) | 111 (88.8) | 172 (94.5) | .106 |
| Tobacco use—n(% tobacco use) | 54 (43.2) | 49 (26.9) | <.004 |
| Opioid use—n (% opioid use) | 12 (8.0) | 8 (5.0) | .406 |
| Sedative use—n (% sedative use) | 8 (5.3) | 8 (5.0) | .492 |
| Amphetamine use—n (% amphetamine use) | 2 (1.3) | 5 (3.1) | – |
| Stimulant use—n (% stimulant use) | 2 (1.3) | 5 (3.1) | – |
| Cocaine use—n (% cocaine use) | 3 (2.0) | 2 (1.2) | – |
| Ecstasy use—n (% ecstasy use) | 5 (3.3) | 4 (2.5) | – |
| Treatment Characteristics | |||
| Psychiatry visits (average visitsf) | 1.49 (2.85) | 1.83 (2.84) | .302 |
| MI treatment condition—n (% MI) | 65 (52.0) | 89 (48.9) | .676 |
Note. MI = motivational interviewing treatment condition; − = insufficient data were available to compute p-values.
Bivariate analyses were computed using χ2 (categorical) or independent sample t-tests (continuous) variables. Between-group comparisons were not computed for substance use variables because drug and alcohol use variables are not mutually exclusive.
Higher mean scores indicate worse depression severity.
Higher mean scores indicate worse anxiety severity.
Lower mean scores indicate worse mental health functioning.
Lower mean scores indicate worse physical health functioning.
Average number of psychiatry department visits within 30-days of baseline.
3.2. Longitudinal patterns and predictors of marijuana use and the impact of marijuana on symptom and functional outcome
After finding few baseline differences between the marijuana using and non-marijuana using groups, the patterns and predictors of marijuana use over 6-months were investigated. As reported in Table 2, the unconditional growth model results showed that the number of patients using marijuana significantly declined over time. Depression symptoms were associated with significantly increased rates of marijuana over 6-months. Marijuana use significantly increased for those aged 50+ over 6-months compared to the youngest age group, although patients aged 50+ were less likely to use marijuana at baseline (Table 2).
Table 2.
Longitudinal predictors of marijuana use among patients with depression (N = 307).
| Variable | Marijuana Use
|
|||
|---|---|---|---|---|
| B | 95%CI | SE | p | |
|
| ||||
| Time | Unconditional Growth Model | |||
| −1.20 | −1.924, −0.492 | 0.36 | <.001 | |
| Conditional Growth Model with Depressive Symptomsa | ||||
| Ageb | ||||
| 30–39 | −0.79 | −1.335, −0.251 | 0.27 | .004 |
| 40–49 | −0.80 | −1.430, −0.183 | 0.32 | .011 |
| 50+ | −1.35 | −1.908, −0.804 | 0.28 | <.001 |
| Female | −0.39 | −0.843, 0.053 | 0.23 | .087 |
| Whitec | −0.30 | −0.796, 0.205 | 0.25 | .235 |
| Married | −0.31 | −0.746, 0.119 | 0.22 | .163 |
| MI Treatment | −0.15 | −0.563, 0.243 | 0.20 | .458 |
| Non-Marijuana Substance Used | 0.17 | −0.601, 0.942 | 0.39 | .668 |
| Time | −0.69 | −1.281, −0.008 | 0.18 | <.001 |
| Time × Ageb | ||||
| Time × 30–39 | 0.12 | −0.191, 0.455 | 0.16 | .441 |
| Time × 30–39 | 0.13 | −0.240, 0.504 | 0.18 | .485 |
| Time × 50+ | 0.44 | 0.126, 0.783 | 0.16 | <.001 |
| Time × Female | 0.16 | −0.102, 0.437 | 0.13 | .238 |
| Time × Whitec | 0.20 | −0.106, 0.499 | 0.15 | .189 |
| Time × Married | 0.23 | −0.019, 0.492 | 0.13 | .073 |
| Time × MI Treatment | 0.07 | −0.174, 0.307 | 0.12 | .567 |
| Time × Non Marijuana | −0.06 | −0.632, 0.499 | 0.29 | .818 |
| Substance Used | ||||
| Psychiatry Visitse | −0.01 | −0.057, 0.019 | 0.01 | .329 |
| Depressive Symptomsf | 0.03 | 0.014, 0.060 | 0.01 | <.001 |
Note. B = beta coefficient; SE = standard error; 95% CI = confidence intervals; p = p-values < .05 are presented in boldface; MI Treatment = Motivation interviewing treatment condition.
Conditional growth models were fit using penalized quasi likelihood estimation.
reference = ages 18 – 29.
reference = otherwise (Hispanic, Asian, Black, Other); collapsed as dichotomous for longitudinal analysis.
reference = any non-marijuana substance use (alcohol, tobacco, opioid, sedative, stimulant, cocaine, amphetamine, and/or ecstasy); collapsed as a composite variable for longitudinal analysis.
Psychiatry visits = Time-varying covariate estimating the number of psychiatry visits prior to each interview.
PHQ-9 total score; higher scores indicate greater depression severity.
With respect to the 6-month recovery trajectories, findings revealed that patients using marijuana demonstrated significantly less improvement with regards to their depression (B = 1.24 [95% CI = 0.466—2.015], p = <.001) and anxiety (B = 0.80 [95% CI = 0.101—1.509], p = .025) symptomatology, as well as mental health functioning (B = −2.03 [95% CI = −3.587— −0.472], p = .010) than those not using marijuana. No evidence of a significant difference was found between those using and not using marijuana and physical health functioning (p > .05).
Post-hoc analyses using mixed-effect growth models were employed in the marijuana use subsample (n = 125) to investigate whether recovery outcome differences existed between those who used the drug recreationally or medicinally. No significant differences were found between those who reported recreational or medicinal use on the symptom or mental health functioning outcomes (p’s > .05), indicating comparable impairment in these domains. However, compared to those reporting recreational marijuana use (B = −3.35 [95% CI = −6.603— −0.096], p = .044), those reporting medicinal use of the drug had significantly poorer physical health functioning.
4. Discussion
This study examined 307 depression outpatients using and not using marijuana on their recovery and marijuana outcomes over 6 months. Baseline findings revealed those who used marijuana were younger and less likely to be married. Reported rates of marijuana use were the highest within 30 days of baseline and then declined overall; however, patterns varied by patient characteristics. Higher depressive symptoms placed patients at risk for continued marijuana use, and patients aged 50+ were at high risk for increased marijuana use. Ongoing marijuana use led to poorer symptom and mental health functioning; medical marijuana was associated with poorer physical health functioning. Results suggest marijuana use is common and associated with poor recovery among psychiatry outpatients with depression.
4.1. Clinical Implications
This work provides further support that marijuana use can be clinically problematic for psychiatry patients and suggests that on-going efforts to improve education around the adverse health effects of marijuana use are important (Volkow et al., 2014). For example, if depression patients were more aware that ongoing symptom distress is linked to marijuana use, they might be more likely to consider treatment options to cut back. Many adults with depression try to stop using marijuana (Shi, 2014) suggesting these patients may be more willing to try interventions with demonstrated efficacy such as MI (Satre et al., 2016). Marijuana prevention and treatment strategies also should target younger age groups, since use is high and associated with adverse consequences in adolescents and young adults (Fergusson & Boden, 2008; Volkow et al., 2014). We found marijuana users were largely comprised of younger adults, but additionally that those age 50+ increased their use over time, suggesting the potential for adverse consequences among older adults and treatment needs for them. Education efforts about the adverse impact marijuana use can have on depression are needed, with a focus on subgroups (i.e., young people and older adults, high depression severity patients) at risk for poor outcome. Together, our results warrant replication and indicate a need for providers to ask depressed patients about their marijuana use, to inform those using marijuana of its potential risks and determine treatment needs.
4.2. Study Limitations
Patients were participants in a randomized controlled trial of alcohol and drug use among psychiatry outpatients and had PHQ-9 depression of ≥ 5, limiting generalizability. Patients were using substances other than marijuana, limiting our ability to draw firm conclusions, although all models adjusted for non-marijuana use. Substance use data were self-report and subject to recall bias. Models were unadjusted for patient’s premorbid functioning/marijuana use, which could have impacted the results. Substance use variables were dichotomized due to low frequency, reducing statistical power, our ability to determine quantity/frequency, and our understanding of patterns over time. We do not know how patients used marijuana (i.e., oral, smoked, ingested, etc.), whether problems were associated with use, or the primary reason/condition for medical use. Longitudinal analyses are limited to a 6-month follow-up, suggesting further research will be needed over longer periods of time.
5. Conclusions
This study found that marijuana use was common and associated with poor recovery among psychiatry outpatients with depression. Our findings signal the need for conducting marijuana use assessments in the context of outpatient psychiatry treatment and considering its use for at risk subgroups (i.e., young people and older adults, high depression severity patients) in light of its impact on recovery.
Highlights.
Marijuana use decreased among depression patients but patterns varied by characteristics.
Older psychiatry patients were at high risk for increasing marijuana use over time.
Marijuana was associated with worse symptoms and mental health functioning.
Marijuana use should be assessed and addressed in the context of depression treatment.
Footnotes
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