Awareness of the potential consequences of alcohol consumption in the context of chronic pain and prescription opioid use

Abstract

Background:

Alcohol and prescription opioid use are highly prevalent among chronic pain populations. One-fifth of individuals prescribed opioids report same-day use of alcohol and opioids. Alcohol use and alcohol/opioid co-use can have deleterious pain management and health outcomes. The extent to which individuals with chronic pain are aware of these deleterious outcomes is considerably understudied.

Objectives:

To explore individuals’ understanding of seven health- and pain-related risks of alcohol/alcohol-opioid use. An exploratory aim was to examine whether greater risk awareness was associated with alcohol/opioid use patterns.

Methods:

Participants included 261 adults age ≥21(36.4% women) endorsing current alcohol use, chronic musculoskeletal pain, and opioid prescription who completed an online survey via Amazon Mechanical Turk.

Results:

Distribution of the total number of items for which a participant endorsed awareness was as follows: zero (10.7%), one (5.0%), two (13.0%), three (13.8%), four (13.8%), five (11.5%), six (10.0%), and seven items (22.2%). Awareness of the health consequences of alcohol/alcohol-opioid use was positively associated with opioid misuse behaviors (β = .525, ΔR² = .251, p < .001), and higher-risk alcohol consumption (β = .152, ΔR² = .021, p = .011).

Conclusion:

Many adults with chronic pain are unaware of the health consequences of alcohol/alcohol-opioid use. Findings of positive covariation between risk awareness and higher-risk alcohol/opioid use suggest that future interventions among this population should go beyond simple risk education and utilize motivational enhancement to help change decisional balance.

Introduction

Chronic musculoskeletal pain (i.e., chronic pain of the muscles, ligaments/tendons, bones, or joints) is a highly prevalent (1) and important public health issue due to its contributions to disability, sickness absence, and healthcare costs (2-4). Alcohol use and chronically painful conditions frequently covary (5-7), and persistent alcohol use may serve as a risk factor for the progression and maintenance of pain over time (7, 8). Cross-sectional evidence further indicates that heavy alcohol consumption (e.g., daily alcohol use, frequent intoxication) is positively associated with the likelihood of reporting chronic or persistent pain (9). It has been proposed that heavy alcohol use may contribute to pain through increased injury risk and musculoskeletal changes (7, 10, 11). Alcohol presents risks for pain treatment outcomes in that it may interfere with endogenous pain modulation via dysregulation of opioid systems (12) and increase the risk of adverse outcomes when using common over-the-counter analgesic medications (stomach bleeding from NSAIDs, liver damage due to acetaminophen) (13).

Alcohol use among individuals with chronic pain is particularly problematic in the context of opioid medication use. Over one-fifth of US adults with chronic pain reported use of prescription opioids in the past three months (14). Despite alcohol use being contra-indicated when taking opioid medications, approximately 20% of individuals prescribed opioids report same-day use of alcohol and opioid medications (15), and 12% report co-use within two hours (16). These data are troubling, given that alcohol interferes with metabolism and effectiveness of opioids (17, 18) and that co-use of alcohol and opioids increases the risk for dangerous health outcomes, including liver damage, respiratory depression, overdose, and death (17, 19).

Despite deleterious health outcomes associated with alcohol consumption in the context of chronic pain and prescription opioid use, the extent to which individuals are aware of these risks has been considerably understudied. Having awareness of the risks associated with a behavior may increase cognitive dissonance and strengthen motivation for behavior change (20, 21). Relevant to intervention development, identifying specific gaps in awareness about negative health consequences can also help optimize targets for psychoeducational components of interventions. Therefore, the goal of this study was to examine awareness of health-related risks of alcohol in the context of chronic pain and prescription opioid use. Specifically, we explored individuals’ understanding and perceptions of the potential deleterious effects of (1) alcohol use in relation to pain-related outcomes and (2) alcohol-opioid co-use. An exploratory goal was to examine whether greater awareness of the potential consequences is associated with patterns of alcohol and opioid use/misuse.

Materials and methods

Participants

Participants included 313 adults who endorsed past-month alcohol use, chronic musculoskeletal pain, and a current opioid prescription, and completed a brief (~25-min) online survey via Amazon Mechanical Turk (mTurk). Chronic pain was assessed with the question, “Do you currently suffer from any type of chronic pain, that is, pain that occurs constantly or flares up frequently? Do not report aches and pain that are fleeting or minor.” Participants were excluded if they endorsed: age <21 years, residing outside the US, or inability to read English. Eligible individuals were then presented with an electronic informed consent form describing study procedures, risks, time commitment, and compensation. All study activities were approved by the Syracuse University IRB.

Steps were taken to promote data quality based on best practices for mTurk research (22-24). Specifically, the study inclusion criteria were disguised during recruitment, reducing the incentive for disingenuous responding (22, 23). The recruitment post gave only a general description of the purpose of the study: “to better understand different aspects of pain, health, and substance use behaviors.” After survey completion, responses with duplicate IP addresses (n = 19) were discarded. Responses located outside the United States based on a review of latitude and longitude were also discarded (n = 22). Finally, two response accuracy checks (e.g., “Please respond with a two for this item”) placed near the beginning and end of the survey were used to exclude participants who responded incorrectly to either item (n = 12). These exclusions totaled n = 52 participants and the final sample comprised N = 261 participants. Qualitative data on the use of mTurk in addictions research indicate that participants report greater comfort disclosing potentially stigmatized substance use behaviors online versus interview with a researcher (23).

Measures

Awareness of the health-related consequences of alcohol use in the context of chronic pain and prescription opioid use

To assess awareness of the potential consequences of alcohol use in the context of chronic pain and prescription opioid use, seven items were generated by the authors, who bring expertise in the areas of pain and substance use (7, 25, 26) (see Table 2). Specifically, four items assessed the potential consequences of alcohol use on pain and the benefits of quitting or reducing alcohol use (items 1, 2, 3, and 5). These items were informed by an established body of literature indicating that alcohol use can lead to the onset, progression, and worsening of pain (9, 27-30) and that quitting/reducing alcohol use can improve pain and pain-related function (12, 31). In addition, three items assessed awareness of the potential consequences of alcohol-opioid co-use (items 4, 6, and 7). These items were informed by an established literature on negative health outcomes associated with concurrent use of alcohol and prescription opioids, including slowed opioid metabolism, liver damage, and overdose (32-35). We summed the number of items for which each participant reported awareness (i.e., responded “yes”), with higher scores (possible range: 0–7) indicating greater awareness of the health consequences of alcohol use in the context of chronic pain and prescription opioid use.

Table 2.

Participant awareness of the risks of alcohol consumption in the context of chronic pain and prescription opioid use (N = 261).

Item	Yes	No	Don’t Know
	n (%)	n (%)	n (%)
Can drinking alcohol cause chronic pain?	161 (61.7%)	73 (28.0%)	27 (10.3%)
Can drinking alcohol make pain worse over time?	159 (60.9%)	87 (33.3%)	15 (5.7%)
Can drinking alcohol make it more difficult to function physically despite pain?	148 (56.7%)	92 (35.2%)	21 (8.0%)
Can drinking alcohol reduce effectiveness of opioid medications?	144 (55.2%)	82 (31.4%)	35 (13.4%)
Can quitting drinking alcohol help improve pain and physical functioning?	138 (52.9%)	89 (34.1%)	34 (13.0%)
Can drinking alcohol while taking prescription opioid medications cause dangerous health effects?	156 (59.8%)	85 (32.6%)	20 (7.7%)
Can drinking alcohol slow down the metabolism of opioids and increase the risk for overdose?	139 (53.3%)	86 (33.0%)	36 (13.8%)

Hazardous alcohol use

The Alcohol Use Disorders Identification Test (AUDIT) (36) includes 10 items that are summed to generate a total score assessing hazardous alcohol use. Three subscale scores are also generated: quantity/frequency of alcohol consumption (“Consumption”), symptoms of dependence (“Dependence”), and use resulting in physical/mental health consequences (“Harmful Use”). Cronbach’s α in the present sample was good for AUDIT Total scores (α = .850), AUDIT Dependence subscale scores (α = .771), and AUDIT Harmful Use subscale scores (α = .724), while AUDIT Consumption subscale scores showed poor reliability (α = .536).

Opioid misuse behaviors

The Prescription Opioid Misuse Index (POMI) (37) is a valid and reliable 6-item measure which assesses prescription opioid medication misuse (e.g., exceeding the prescribed dose, seeking early refills) (37). Items are summed for a total score ranging from 0 to 6, with greater scores indicative of greater opioid medication misuse-related behaviors. Cronbach’s α in the present sample was good (α = .743).

Pain Intensity

Pain intensity was assessed using the Characteristic Pain Intensity (CPI) subscale of the Graded Chronic Pain Scale (GCPS) (38). The GCPS-CPI score is the sum of three NRS items assessing current, past-3-month worst, and past-3-month average pain intensity (0 “no pain” to 10 “pain as bad as it could be”). GCPS-CPI scores demonstrated good internal consistency in the present sample (Cronbach’s α = .818).

Data analytic plan

To examine awareness of the health-related consequences of alcohol in the context of chronic pain and prescription opioid use, we computed the percent of participants who responded “yes” (i.e., indicated awareness) to each of the seven items. We then examined the total number of items for which each participant reported awareness (possible range: 0–7). Separate hierarchical linear regressions were conducted to explore associations between awareness of health risks (i.e., total number of items to which participants responded “yes”), hazardous alcohol use (AUDIT total and subscale scores), and prescription opioid misuse behaviors (POMI total scores). Hierarchical regression was selected to allow for examination of the variance in AUDIT and POMI scores attributable to awareness of health risks after accounting for other relevant variables. Age, education, pain intensity, gender identity, and racial identity were entered in Step 1 of each model. Age, education, and pain intensity were retained as covariates in all regression models due to positive correlations with POMI scores (p < .001). Gender identity and race (dichotomized due to small numbers of participants endorsing non-White racial identities) were included as covariates due to previously observed associations with hazardous drinking/opioid misuse (39, 40). Awareness of health risks (count of items endorsed) was entered at Step 2 of each model. All analyses were conducted using IBM SPSS Statistics 27 (41).

Results

Participant characteristics

Participants (N = 261; 36.4% identifying as women, 81.6% White, M_age = 38.6) reported consuming an average of 2.0 drinks per day (SD = 2.3), with mean AUDIT scores (20.0; SD = 7.7) indicating a high level of hazardous drinking (36). For “How often do you have a drink containing alcohol?” (AUDIT_1), the response distribution was “Monthly or less” (23.8%), “2–4 times a month” (49.0%), “2–3 times a week” (23.0%) and “4 or more times a week” (4.2%). Responses to “How many standard drinks containing alcohol do you have on a typical day?” (AUDIT_2) were distributed as follows: “1 or 2” (36.4%), “3 or 4” (44.4%), “5 or 6” (15.3%), “7 to 9” (2.7%), “10 or more” (1.1%). Responses to “How often do you have six or more drinks on one occasion?” (AUDIT_3) were distributed as follows: “Never” (8.0%), “Less than monthly” (15.3%), “Monthly” (29.1%), “Weekly” (37.2%), and “Daily or almost daily” (10.3%). The mean POMI score was 3.8 (SD = 1.9), which is above the clinical cutoff (≥2) for probable opioid misuse (37). Opioid medications most commonly endorsed were hydrocodone (37.2%), oxycodone (33.0%), and tramadol (31.0%). Additional sociodemographic information is displayed in Table 1.

Table 1.

Sociodemographic, alcohol use, and pain characteristics (N = 261).

	Total N = 261
	n (%)
Gender
Woman	95 (36.4%)
Race/Ethnicity/Origin
Asian	10 (3.8%)
Black or African American	36 (13.8%)
White	213 (81.6%)
Hispanic/Latino	11 (4.2%)
Middle Eastern/North African	3 (1.1%)
Native Hawaiian/Pacific Islander	4 (1.5%)
Other race, ethnicity, or origina	3 (1.1%)
Marital Status
Married	227 (87.0%)
Single	33 (12.6%)
Income
$0–$24,999	38 (14.6%)
$25,000–$49,999	77 (29.5%)
$50,000–$74,999	92 (35.2%)
More than $75,000	54 (20.7%)
Education
High school or high school equivalency	5 (1.9%)
Some college	14 (5.4%)
Technical school/Associate’s degree	5 (1.9%)
Four-year college degree	178 (68.2%)
Some school beyond four-year college degree	25 (9.6%)
Professional degree	34 (13.0%)
Primary Pain Location
Back/Neck	95 (36.4%)
Head/Face	75 (28.7%)
Upper Extremities	42 (16.1%)
Lower Extremities	18 (6.9%)
Chest/Breast	9 (3.4%)
Stomach/Abdomen	22 (8.4%)
Frequency of Co-Use
Same-Day
Never	27 (10.3%)
1–9 Days/Month	182 (69.7%)
10–24 Days/Month	48 (18.4%)
Daily or Almost Daily	4 (1.5%)
Within 2 Hours
Never	42 (16.1%)
1–9 Days/Month	134 (51.3%)
10–24 Days/Month	84 (32.3%)
Daily or Almost Daily	1 (0.4%)
	M (SD)
Age	38.58 (11.85)
Pain Intensityb	19.93 (5.39)
AUDIT-Total Scorec	24.19 (8.58)

^aParticipants who endorsed “Some other race, ethnicity, or origin”

^bGraded Chronic Pain Scale – Characteristic Pain Intensity

^cAlcohol Use Disorders Identification Test.

Awareness of potential health consequences of alcohol/alcohol-opioid use

The distribution of the total number of items for which a participant endorsed awareness was as follows: zero items (10.7%), one item (5.0%), two items (13.0%), three items (13.8%), four items (13.8%), five items (11.5%), six items (10.0%), and seven items (22.2%). For each of the seven health consequences assessed, greater than one-third of participants were not aware that consequences could occur (Table 2). For example, over one-third of participants were not aware that drinking alcohol can contribute to the onset and worsening of chronic pain, and nearly half did not know that quitting drinking can improve pain and physical functioning. Moreover, 45% of participants were not aware that drinking alcohol can reduce the effectiveness of opioid pain medications, 40% did not know that co-use of alcohol and opioids can lead to dangerous health effects, and 46% did not know that co-use can increase the risk of overdose. Overall, only 22.2% of participants were aware of all seven health risks of alcohol consumption in the context of chronic pain and prescription opioid use. In other words, 77.8% were unaware of at least one of the potential health consequences of alcohol consumption in the context of pain and prescription opioid use.

As shown in Table 3, greater awareness of potential health consequences of drinking was positively associated with higher-risk alcohol consumption (AUDIT total scores; β = .152, ΔR² = .021, p = .011) and reported negative consequences from alcohol use (AUDIT Harmful Use scores; β = .202, ΔR² = .037, p = .001), but not with alcohol consumption or dependence symptoms (ps > .05). Awareness of the potential consequences was also positively associated with prescription opioid misuse (Table 3; β = .525, ΔR² = .251, p < .001).

Table 3.

Associations between awareness of risks and alcohol/opioid use/misuse (N = 261).

Variable	Hazardous Drinking Patternsb			Opioid Misuse Behaviorsc
	β	t	p	β	t	p
Age	.052	.860	.391	.126	2.370	.019*
Education (Reference = “Professional degree”)	.185	3.236	.001*	.163	3.233	.001*
Pain intensitya	.291	4.812	<.001**	.051	.956	.340
Gender (Reference = “Man”)	.062	1.071	.285	−.029	−.562	.574
Race (Reference = “Non-White”)	.018	.301	.764	.000	−.010	.992
Awareness of Risks	.152	2.573	.011*	.525	10.051	<.001**
R2		.194			.369
ΔR2		.021			.251
F for ΔR2		6.621*			101.017**

Variable	AUDIT – Consumption			AUDIT – Dependence			AUDIT – Harmful Use
	β	t	p	β	t	p	β	t	p
AUDIT Subscale Scores
Age	.062	1.032	.303	.026	.430	.668	.049	.789	.431
Education (Reference = “Professional degree”)	.110	1.935	.054	.250	4.344	<.001**	.121	2.040	.042*
Pain intensitya	.338	5.609	<.001**	.287	4.686	<.001**	.184	2.925	.004*
Gender (Reference = “Man”)	.060	1.046	.296	.033	.562	.575	.065	1.080	.281
Race (Reference = “Non-White”)	.093	1.604	.110	.017	.285	.776	−.026	−.421	.674
Awareness of Risks	.097	1.649	.100	.057	.956	.340	.202	3.287	.001*
R2	.200			.177			.126
ΔR2	.009			.003			.037
F for ΔR2	2.721			.913			10.807*

^aGraded Chronic Pain Scale – Characteristic Pain Intensity

^bAlcohol Use Disorders Identification Test (AUDIT) total score

^cPrescription Opioid Misuse Index (POMI) total score.

^*p < .05

^**p < .001.

Discussion

The current study demonstrates that many individuals remain unaware of evidence that alcohol consumption can contribute to the onset and worsening of chronic pain and increase the risk for dangerous health outcomes when combined with opioid analgesics (5-7, 17, 18). In a sample of adults with chronic pain who were prescribed an opioid pain medication, we observed varying levels of awareness regarding the potential health effects of alcohol consumption in the context of chronic pain and prescription opioid use. Notably, only 22% of participants were aware of all of the health risks assessed.

Many participants were not aware that alcohol can lead to poorer pain outcomes, including greater pain and impaired physical function. One particularly concerning finding was that up to 47% of participants were not aware of several health risks associated with drinking alcohol while taking prescription opioids (e.g., increased risk for overdose). These findings are broadly consistent with prior estimates of knowledge of overdose risk factors among chronic pain patients prescribed opioids, which found that <50% correctly identified any of nine overdose risk factors, and <20% knew about risks of combining opioids with sedatives (42). The present study adds to this growing literature by indicating that substantial proportions of individuals with chronic pain who drink alcohol are not fully cognizant of the risks that alcohol use/alcohol-opioid co-use pose to both general health and pain management.

Greater awareness of the potential consequences of alcohol consumption in the context of pain and prescription opioid use was positively associated with higher-risk alcohol consumption (AUDIT total scores) and reported negative consequences from alcohol use (AUDIT Harmful Use scores), as well as opioid misuse. This finding was surprising, as it is in contrast with prior research which has shown negative associations between perceptions of substance-related risk and heavier use of alcohol (43) and non-medical use of prescription opioids (44). One possible explanation for this pattern of findings is that individuals with heavier alcohol/opioid use may have had more opportunities for direct learning about the negative consequences of such use and/or may have received more psychoeducation from providers. Additionally, it has been proposed that individuals with knowledge of co-use risks may also tend to hold knowledge that co-use can increase intoxication, which in turn could motivate co-use behaviors (45). This hypothesis is consistent with prior research among heroin overdose survivors demonstrating that those with knowledge of a specific overdose risk factor (e.g., concurrent use with other substances) were more likely to have engaged in that same risk behavior (45).

Several important limitations should be noted. First, these cross-sectional findings do not allow for conclusions about the directionality or causality of the relationships examined. Future research should examine temporal relationships between alcohol-opioid co-use behaviors and perceptions of negative health effects. Second, the sample had a high level of hazardous drinking (mean AUDIT score = 20.0, SD = 7.7). Despite the high prevalence of hazardous drinking often observed among chronic pain populations (7, 12), these results may not generalize to individuals who drink less heavily. Third, the sample was highly educated (>90% reporting at least a 4-year college degree), and majority White (82%) and male (66%), which may limit the generalizability of the present findings. Samples recruited via MTurk are typically more highly educated and have a higher proportion of White respondents, relative to the general population (46), further highlighting the need for replication in larger and more diverse participant samples. Fourth, data were collected via self-report in an online survey. Despite the use of recommended procedures to reduce disingenuous response (e.g., masked inclusion criteria) (24), replication in samples recruited via other methods is needed. Additional steps to promote data quality may include verification of prescription status (e.g., researchers reviewing prescription bottles), and exclusion of data from participants with improbable/inconsistent response patterns (e.g., straight-lining, inconsistencies among multiple reports of substance use frequency). Fifth, only risk-related perceptions were assessed. Given that both risk and benefit perceptions are thought to drive decision-making (47), future research should investigate the perceived benefits of alcohol-opioid co-use among this population. Sixth, participant perceptions may have been overestimated due to social desirability bias (48).

These findings may ultimately inform interventions aimed at reducing alcohol use among chronic pain populations, which have received increasing interest (49, 50). Further research is needed to fully explicate the clinical implications of these findings. First, in the present sample, greater awareness of risks was, somewhat counterintuitively, associated with greater hazardous drinking and opioid misuse scores. However, perceived likelihood of and personal susceptibility to given risks have also been shown to be an important predictor of behavior (51). Future work should test how estimation of the likelihood of/personal susceptibility to health risks of alcohol-opioid co-use may be related to hazardous drinking and opioid use patterns. Second, an important next step is to test the role of other cognitive and affective constructs that were not assessed in the present study but are theorized and empirically supported as key predictors of health behavior change. These may also include analgesia expectancies for alcohol/alcohol-opioid co-use (25), pain catastrophizing (26), perceived behavioral control, positive attitudes toward/perceptions of alcohol use and alcohol-opioid co-use, and subjective social norms (52, 53).

Nonetheless, identification of gaps in awareness regarding pain-alcohol-opioid interrelations is an important first step in the development of tailored and personalized interventions. Education can be provided on the negative consequences of alcohol/alcohol-opioid use in the context of pain, increasing risk awareness and highlighting the discrepancy between individuals’ current behavior and their health and pain management goals. The present findings highlighted knowledge gaps, particularly in relation to positive pain- and health-related outcomes of quitting drinking and deleterious alcohol-opioid interactions (e.g., increased overdose risk, reduced medication effectiveness).