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Pain Medicine 2014; 15: 541–543 Wiley Periodicals, Inc.
Psychological Dependence and Prescription Opioid Misuse and Abuse
There has been notable concern regarding the rising prevalence of prescription opioid misuse, abuse, and fatal overdoses. A great deal of scholarly activity has been devoted to identifying risk factors for opioid misuse/abuse and less effort on discovering modifiable factors to mitigate risk. In this issue of Pain Medicine, Elander and colleagues [1] conducted an online survey of 112 individuals in the general population who had pain and had used over-the-counter (OTC) and prescription analgesics in the last month. They assessed typical pain factors (frequency, intensity, pain type, and etiology), opioid abuse risk based on a validated risk assessment measure, the Screener and Opioid Assessment for Patients with Pain (SOAPP), mood and anxiety disorders, and frequency and use of OTC and prescription analgesics. In addition, they collected a number of psychological measures, some very novel (alexithymia, mindfulness, self-compassion), along with known possible pain and substance abuse mediators (pain catastrophizing, pain acceptance, pain self-efficacy). Statistical analysis of the relationship between analgesic dependence (based on a modified Leeds Dependence Questionnaire) and the measures of pain, mood, and aberrant drug-related behavior (ADRB) (SOAPP) and other psychological factors revealed that the best single predictor of analgesic dependence was the SOAPP. Other independent factors predictive of dependence were the frequency of analgesic use and the level of acceptance of pain. A number of other interesting psychological variables and interactions were identified. It is not surprising that the SOAPP was the strongest predictor of analgesic dependence as it has probably the best psychometrics of all measures of ADRBs [2], which are considered to be surrogates of possible addiction. However, as noted by the authors, SOAPP scores were not significantly correlated with pain frequency or intensity suggesting that the SOAPP measures the risk of substance dependence independent of pain. The finding that frequent use of analgesics independently predicted dependence is also not intuitively surprising. A study by Edlund et al. [3] evaluated results of a nationally represented survey (N = 9,279) and found that regular users of prescription opioids as compared with nonusers had a higher rate of opioid and nonopioid abuse. The most intriguing results of this study were the significant interactions. For example, more frequent pain increased analgesic dependence when alexithymia was high but decreased dependence when alexithymia (difficulties identifying and describing feelings) was low. Higher pain intensity increased analgesic dependence when pain
acceptance was low but decreased dependence when pain acceptance was high. The authors present a theoretical model of factors that influence the development of analgesic dependence along three pathways. One pathway is the risks inherent of developing substance use disorders (SUDs) in general, irrespective of pain (personal or family history of SUD). A second pathway is the effect of pain intensity mediated by analgesic use (more severe pain increases analgesic use which in turn increases the risk of dependence). The third pathway consists of the psychological factors (pain acceptance, alexithymia, anxiety) that moderate the effects of pain. According to his model, the general risk factors for SUD and the psychological factors can independently increase the risk of analgesic dependence directly or exert influences mediated by increased analgesic use or both. A cautionary note is the use of the term “dependence.” The authors defined psychological dependence based on the Leeds Dependence Questionnaire which measures the graded severity of behavioral and psychological properties of dependence, such as preoccupation, salience, compulsion to start and continue use, etc., extracted from the International Statistical Classification of Diseases-tenth revision and the American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders (DSM) IV criteria for substance dependence. Psychological dependence has also been described as a nonphysiological attachment to the availability of the prescribed opioid which may be related to fear of increased pain or other co-occurring symptoms (sleep disturbance, anxiety, and depression) which the drug is perceived to be controlling if the medication is no longer available to control these symptoms [4]. In the recently released DSM V [5], dependence has been removed from the nosology and replaced with SUD and opioid use disorder (OUD) to more clearly delineate pathological behaviors from a normal adaptive, physiological process. Tolerance and withdrawal are not counted in the criteria to render a diagnosis of SUD if a patient is taking a prescribed medication that can lead to these states. Although this is an improvement from DSM IV, some authors assert that there is still confusion in accurately diagnosing addiction in pain patients using prescribed opioids [6]. As we proceed with research in the area of pain and SUDs, we need to develop and consistently use consensus-based terminology and assessment tools that accurately reflect OUD (addiction) vs misuse, abuse, tolerance, physiological dependence, and pseudoaddiction (under treatment of pain) as to not further 541
Cheatle obscure the distinction between a pain sufferer appropriately using opioids and a patient abusing opioids. Although this study had methodological issues including a small sample size and a sample that is unrepresentative of high-risk pain patients (mostly OTC use, episodic pain), the results underscore that patients with chronic pain are complex, and those who are at risk for misusing or abusing prescription analgesics are even more so. A personal history of substance abuse has been the most reliable, and evidence-based predictor, of prescription opioid abuse [7]. While identifying this risk factor can alert clinicians to be more vigilant when prescribing opioids, it is not amenable to modification to mitigate risk. In this study, pain acceptance was an independent predictor of analgesic dependence, whereas anxiety, alexithymia, and acceptance were psychological factors that moderated the effect of pain. There is a persuasive literature that supports the efficacy and cost-effectiveness of cognitive behavioral therapy and acceptance and commitment therapy in addressing these possible mediators/ moderators of pain [8–11] and also SUDs [12,13]. Further studies like Elander et al. [1] are needed to distinguish risk factors that can be identified early, are dynamic, and susceptible to interventions to prevent the development of opioid misuse/abuse. A final challenge is access to these needed services to mitigate risk, as oftentimes, the number of patients that require specialty care far exceeds the number of specialists, or services are unavailable due to insurance constraints or the patients are living in a rural location. Novel delivery systems (telemedicine, Internetbased CBT, and smart phone applications) show promise in the areas of pain and SUD [14–17] but require additional research. MARTIN D. CHEATLE, PhD Center for Studies of Addiction, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA References 1 Elander J, Duarte J, Maratos F, Gilbert P. Predictors of painkiller dependence among people with pain in the general population. Pain Med 2014;15:613– 24. 2 Passik SD, Kirsh KL, Caspar D. Addiction-related assessment tools and pain management: Instruments for screening, treatment planning, and monitoring compliance. Pain Med 2008;9:S145–66. 3 Edlund MJ, Sullivan M, Steffick D, Harris KM, Wells KB. Do users of regularly prescribed opioids have higher rates of substance use problems than nonusers? Pain Med 2007;8(8):647–56. 4 Cheatle MD, Savage SR. Informed consent in opioid therapy: A potential obligation and opportunity. J Pain Symptom Manage 2012 Jul;44(1):105–16. 542
5 American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 5th edition. Arlington, VA: American Psychiatric Publishing; 2013. 6 Ballantyne JC, Stannard C. New addiction criteria: Diagnostic challenges persist in treating pain with opioids. ISAP Pain Clin Updat 2013;21(5):1–7. 7 Turk DC, Swanson KS, Gatchel RJ. Predicting opioid misuse by chronic pain patients: A systematic review and literature synthesis. Clin J Pain 2008;24(6):497– 508. 8 Vowles K, Witkiewitz K, Sowden G, Ashworth J. Acceptance and commitment therapy for chronic pain: Evidence of mediation and clinically significant change following an abbreviated interdisciplinary program of rehabilitation. J Pain 2014;15(1):101– 13. 9 Lamb SE, Hansen Z, Lall R, et al. Group cognitive behavioral treatment for low-back pain in primary care: A randomized controlled trial and costeffectiveness analysis. Lancet 2010;375(9718):916– 23. 10 Linton SJ. A 5-year follow-up evaluation of the health and economic consequences of an early cognitive behavioral intervention for back pain: A randomized, controlled trial. Spine 2006;31(8):853–8. 11 Thieme K, Flor H, Turk D. Psychological pain treatment in fibromyalgia syndrome: Efficacy of operant behavioral and cognitive behavioral treatments. Arthritis Res Ther 2006;8(4):R121. 12 Osilla KC, Hepner KA, Muñoz RF, Woo S, Watkins K. Developing an integrated treatment for substance use and depression using cognitive-behavioral therapy. J Subst Abuse Treat 2009;37(4):412– 20. 13 Dutra L, Stathopoulou G, Basden SL, et al. A metaanalytic review of psychosocial interventions for substance use disorders. Am J Psychiatry 2008;165: 179–87. 14 Kay-Lambkin FJ, Baker AL, Lewin T, Carr VJ. Computer-based psychological treatment for comorbid depression and problematic alcohol and/or cannabis use: A randomized controlled trial of clinical efficacy. Addiction 2009;104(3):378–88. 15 Dear BF, Titov N, Perry KN, et al. The pain course: A randomised controlled trial of a clinician-guided Internet-delivered cognitive behaviour therapy program for managing chronic pain and emotional wellbeing. Pain 2013;154(6):942–50. 16 Kristjánsdóttir OB, Fors EA, Eide E, et al. A smartphone-based intervention with diaries and
Editorial therapist-feedback to reduce catastrophizing and increase functioning in women with chronic widespread pain: Randomized controlled trial. J Med Internet Res 2013;15(1):e5.
17 Vardeh D, Edwards RR, Jamison R, Eccleston C. There’s an app for that: Mobile technology is a new advantage in managing chronic pain. ISAP Pain Clinical Updates 2013;21(6):1–7.
543
Pain Medicine 2014; 15: 541–543 Wiley Periodicals, Inc.
Psychological Dependence and Prescription Opioid Misuse and Abuse
There has been notable concern regarding the rising prevalence of prescription opioid misuse, abuse, and fatal overdoses. A great deal of scholarly activity has been devoted to identifying risk factors for opioid misuse/abuse and less effort on discovering modifiable factors to mitigate risk. In this issue of Pain Medicine, Elander and colleagues [1] conducted an online survey of 112 individuals in the general population who had pain and had used over-the-counter (OTC) and prescription analgesics in the last month. They assessed typical pain factors (frequency, intensity, pain type, and etiology), opioid abuse risk based on a validated risk assessment measure, the Screener and Opioid Assessment for Patients with Pain (SOAPP), mood and anxiety disorders, and frequency and use of OTC and prescription analgesics. In addition, they collected a number of psychological measures, some very novel (alexithymia, mindfulness, self-compassion), along with known possible pain and substance abuse mediators (pain catastrophizing, pain acceptance, pain self-efficacy). Statistical analysis of the relationship between analgesic dependence (based on a modified Leeds Dependence Questionnaire) and the measures of pain, mood, and aberrant drug-related behavior (ADRB) (SOAPP) and other psychological factors revealed that the best single predictor of analgesic dependence was the SOAPP. Other independent factors predictive of dependence were the frequency of analgesic use and the level of acceptance of pain. A number of other interesting psychological variables and interactions were identified. It is not surprising that the SOAPP was the strongest predictor of analgesic dependence as it has probably the best psychometrics of all measures of ADRBs [2], which are considered to be surrogates of possible addiction. However, as noted by the authors, SOAPP scores were not significantly correlated with pain frequency or intensity suggesting that the SOAPP measures the risk of substance dependence independent of pain. The finding that frequent use of analgesics independently predicted dependence is also not intuitively surprising. A study by Edlund et al. [3] evaluated results of a nationally represented survey (N = 9,279) and found that regular users of prescription opioids as compared with nonusers had a higher rate of opioid and nonopioid abuse. The most intriguing results of this study were the significant interactions. For example, more frequent pain increased analgesic dependence when alexithymia was high but decreased dependence when alexithymia (difficulties identifying and describing feelings) was low. Higher pain intensity increased analgesic dependence when pain
acceptance was low but decreased dependence when pain acceptance was high. The authors present a theoretical model of factors that influence the development of analgesic dependence along three pathways. One pathway is the risks inherent of developing substance use disorders (SUDs) in general, irrespective of pain (personal or family history of SUD). A second pathway is the effect of pain intensity mediated by analgesic use (more severe pain increases analgesic use which in turn increases the risk of dependence). The third pathway consists of the psychological factors (pain acceptance, alexithymia, anxiety) that moderate the effects of pain. According to his model, the general risk factors for SUD and the psychological factors can independently increase the risk of analgesic dependence directly or exert influences mediated by increased analgesic use or both. A cautionary note is the use of the term “dependence.” The authors defined psychological dependence based on the Leeds Dependence Questionnaire which measures the graded severity of behavioral and psychological properties of dependence, such as preoccupation, salience, compulsion to start and continue use, etc., extracted from the International Statistical Classification of Diseases-tenth revision and the American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders (DSM) IV criteria for substance dependence. Psychological dependence has also been described as a nonphysiological attachment to the availability of the prescribed opioid which may be related to fear of increased pain or other co-occurring symptoms (sleep disturbance, anxiety, and depression) which the drug is perceived to be controlling if the medication is no longer available to control these symptoms [4]. In the recently released DSM V [5], dependence has been removed from the nosology and replaced with SUD and opioid use disorder (OUD) to more clearly delineate pathological behaviors from a normal adaptive, physiological process. Tolerance and withdrawal are not counted in the criteria to render a diagnosis of SUD if a patient is taking a prescribed medication that can lead to these states. Although this is an improvement from DSM IV, some authors assert that there is still confusion in accurately diagnosing addiction in pain patients using prescribed opioids [6]. As we proceed with research in the area of pain and SUDs, we need to develop and consistently use consensus-based terminology and assessment tools that accurately reflect OUD (addiction) vs misuse, abuse, tolerance, physiological dependence, and pseudoaddiction (under treatment of pain) as to not further 541
Cheatle obscure the distinction between a pain sufferer appropriately using opioids and a patient abusing opioids. Although this study had methodological issues including a small sample size and a sample that is unrepresentative of high-risk pain patients (mostly OTC use, episodic pain), the results underscore that patients with chronic pain are complex, and those who are at risk for misusing or abusing prescription analgesics are even more so. A personal history of substance abuse has been the most reliable, and evidence-based predictor, of prescription opioid abuse [7]. While identifying this risk factor can alert clinicians to be more vigilant when prescribing opioids, it is not amenable to modification to mitigate risk. In this study, pain acceptance was an independent predictor of analgesic dependence, whereas anxiety, alexithymia, and acceptance were psychological factors that moderated the effect of pain. There is a persuasive literature that supports the efficacy and cost-effectiveness of cognitive behavioral therapy and acceptance and commitment therapy in addressing these possible mediators/ moderators of pain [8–11] and also SUDs [12,13]. Further studies like Elander et al. [1] are needed to distinguish risk factors that can be identified early, are dynamic, and susceptible to interventions to prevent the development of opioid misuse/abuse. A final challenge is access to these needed services to mitigate risk, as oftentimes, the number of patients that require specialty care far exceeds the number of specialists, or services are unavailable due to insurance constraints or the patients are living in a rural location. Novel delivery systems (telemedicine, Internetbased CBT, and smart phone applications) show promise in the areas of pain and SUD [14–17] but require additional research. MARTIN D. CHEATLE, PhD Center for Studies of Addiction, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA References 1 Elander J, Duarte J, Maratos F, Gilbert P. Predictors of painkiller dependence among people with pain in the general population. Pain Med 2014;15:613– 24. 2 Passik SD, Kirsh KL, Caspar D. Addiction-related assessment tools and pain management: Instruments for screening, treatment planning, and monitoring compliance. Pain Med 2008;9:S145–66. 3 Edlund MJ, Sullivan M, Steffick D, Harris KM, Wells KB. Do users of regularly prescribed opioids have higher rates of substance use problems than nonusers? Pain Med 2007;8(8):647–56. 4 Cheatle MD, Savage SR. Informed consent in opioid therapy: A potential obligation and opportunity. J Pain Symptom Manage 2012 Jul;44(1):105–16. 542
5 American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 5th edition. Arlington, VA: American Psychiatric Publishing; 2013. 6 Ballantyne JC, Stannard C. New addiction criteria: Diagnostic challenges persist in treating pain with opioids. ISAP Pain Clin Updat 2013;21(5):1–7. 7 Turk DC, Swanson KS, Gatchel RJ. Predicting opioid misuse by chronic pain patients: A systematic review and literature synthesis. Clin J Pain 2008;24(6):497– 508. 8 Vowles K, Witkiewitz K, Sowden G, Ashworth J. Acceptance and commitment therapy for chronic pain: Evidence of mediation and clinically significant change following an abbreviated interdisciplinary program of rehabilitation. J Pain 2014;15(1):101– 13. 9 Lamb SE, Hansen Z, Lall R, et al. Group cognitive behavioral treatment for low-back pain in primary care: A randomized controlled trial and costeffectiveness analysis. Lancet 2010;375(9718):916– 23. 10 Linton SJ. A 5-year follow-up evaluation of the health and economic consequences of an early cognitive behavioral intervention for back pain: A randomized, controlled trial. Spine 2006;31(8):853–8. 11 Thieme K, Flor H, Turk D. Psychological pain treatment in fibromyalgia syndrome: Efficacy of operant behavioral and cognitive behavioral treatments. Arthritis Res Ther 2006;8(4):R121. 12 Osilla KC, Hepner KA, Muñoz RF, Woo S, Watkins K. Developing an integrated treatment for substance use and depression using cognitive-behavioral therapy. J Subst Abuse Treat 2009;37(4):412– 20. 13 Dutra L, Stathopoulou G, Basden SL, et al. A metaanalytic review of psychosocial interventions for substance use disorders. Am J Psychiatry 2008;165: 179–87. 14 Kay-Lambkin FJ, Baker AL, Lewin T, Carr VJ. Computer-based psychological treatment for comorbid depression and problematic alcohol and/or cannabis use: A randomized controlled trial of clinical efficacy. Addiction 2009;104(3):378–88. 15 Dear BF, Titov N, Perry KN, et al. The pain course: A randomised controlled trial of a clinician-guided Internet-delivered cognitive behaviour therapy program for managing chronic pain and emotional wellbeing. Pain 2013;154(6):942–50. 16 Kristjánsdóttir OB, Fors EA, Eide E, et al. A smartphone-based intervention with diaries and
Editorial therapist-feedback to reduce catastrophizing and increase functioning in women with chronic widespread pain: Randomized controlled trial. J Med Internet Res 2013;15(1):e5.
17 Vardeh D, Edwards RR, Jamison R, Eccleston C. There’s an app for that: Mobile technology is a new advantage in managing chronic pain. ISAP Pain Clinical Updates 2013;21(6):1–7.
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