Nancy M. Petry, PhD

In everyday life, financial incentives encourage behaviors of consumers, employees, and even physicians (pay-for-performance). Financial incentives-including direct cash, refunds/rebates, or material goods and services-can also affect patients’ behaviors.

Financial interventions for substance use disorders, often called contingency management, involve provision of monetary-based reinforcers for submission of drug-negative urine specimens. These highly effective interventions are based on the principle that a behavior that is reinforced will increase in frequency. For example, in a nationwide study, 415 patients with stimulant use disorders were randomized to usual care alone or with incentives.

 Patients randomized to incentives evidenced an average of nearly 2 more weeks of continuous abstinence, and 18.7% of incentive patients maintained abstinence throughout the entire 12 weeks versus 4.9% of the usual-care group.

For these interventions to be effective, urine samples (or other objective indices of abstinence) must be collected frequently (eg, 2 to 3 times per week) to detect and rapidly reinforce abstinence. Reinforcers are typically vouchers, exchangeable for retail goods, or chances to draw from a bowl and win prizes worth up to $100. The incentives need to be of sufficient magnitude and increase with sustained abstinence. In voucher systems, patients typically earn up to $1200 over a 12-week period; however, $300 in prize incentives can also be effective.

Incentive interventions are most widely applied for treating stimulant and opioid use disorders, because monitoring abstinence for these drugs is readily aligned with reinforcement principles. Reinforcing smoking or alcohol abstinence is also possible, but Breathalyzers and carbon monoxide devices can only detect use over very short periods. Detection of alcohol use in patients’ natural environments is now possible with devices that monitor alcohol in perspiration or remote Breathalyzers and is effective in reducing drinking and smoking when paired with incentive interventions.

Applicability to other patient populations

Financial incentive interventions are applicable to substance use populations, and they can also be used with patients who have other psychiatric problems. The 

outlines patient behaviors that have been addressed by these interventions.

Treatments for most mental disorders have high rates of attrition. When financially based incentives are provided for coming to substance abuse treatment sessions, attendance increases markedly.

 A low-cost, prize-based approach can be very effective. At an HIV drop-in center for group therapy, $20 per group increased attendance at least two-fold.

Financial incentive interventions can also improve adherence to medications, which is problematic for many patients who have mental health disorders. Typically, this approach involves directly observed adherence, remote monitoring via electronic bottles, or video-recording medication consumption. In one study of dual diagnosis patients, an incentive of £15 for taking depot antipsychotics improved adherence to 85%.

Many psychiatric patients are sedentary and overweight. Incentive interventions are useful in reinforcing adherence to weight loss regimens and exercise. Objective evidence of behavior change (in-person weigh-ins and direct or remote monitoring of physical activity) is necessary. Although the efficacy of these approaches has not been tested explicitly in psychiatric populations, sedentary non-patients randomized to an incentive intervention group met physical activity goals on more than 80% of days compared with 55% of days for the non-incentive group.

Incentive interventions can also be used in diabetes management. For example, blood glucose testing increased from an average of 1.8 to 4.9 times per day among adolescents with poorly controlled type 1 diabetes who received reinforcers for testing-90% completed the recommended 4 or more tests daily.

 These procedures have not been tested directly in psychiatric patients with diabetes, but the guiding principles are generalizable.

Any behavior that can be objectively monitored can be reinforced. If the incentive system is properly designed, it is likely to be effective in altering the behavior targeted for change.

Concerns about financial incentive systems

Although incentive interventions are useful, psychiatrists rarely use them. There are several reasons for this. One relates to familiarity, as few mental health providers are aware of these types of interventions. Second, there is often no method by which providers can be reimbursed for incentives, as they are not covered by Medicaid or private insurers. The Veterans Administration, however, is implementing incentives nationwide in its substance abuse treatment clinics, and many employers use incentives to promote health behaviors-a practice encouraged by the US Affordable Care Act.

Although more information is needed to guide policy, data suggest that incentives are cost-effective.

 Novel methods to apply financial incentives exist, such as arranging for direct access to disability payments or partial rebates on health insurance costs contingent upon meeting specific objectively defined goals.

Potential ethical considerations also arise. Of course, caution must be used when reinforcing adherence to medications because some patients may continue to take the medication even when they experience adverse effects. However, there hasn’t been a single adverse event of incentives documented in the context of substance use disorders. The prize-based system’s effects on gambling have been studied extensively, and it does not intensify gambling behaviors. The criticism that external reinforcers undermine internal motivation to change also has little basis in empirical studies of clinical populations.

There may be an assumption that mental health patients do not understand or respond to contingencies. However, findings indicate that these interventions are highly effective in patients with severe and persistent mental illness.

Some clinicians fear that reinforcement interventions will not engender long-term change. Although effect sizes of incentive interventions are clearly larger during the period they are in effect relative to post-treatment, persistent benefits have been seen in a third of incentive studies.

 Furthermore, there are no data to support the contention that patients who receive incentives have poorer long-term outcomes than those who do not.

Challenges remain to extending the benefits of incentive interventions, but attaining a period of continuous abstinence is critical for long-term success. Incentive interventions have the largest effect size of any psychosocial treatment for substance use disorders in promoting abstinence.

For several years, Dr. Jones has been seeing 25-year-old Matt, who has schizophrenia and stimulant and alcohol use disorders. Matt receives a monthly disability payment of about $1000, which he often spends on drugs-leaving little money for other expenses. His parents buy food and necessities. Matt misses about half of his appointments with Dr. Jones, which results in inefficient use of Dr. Jones’s time, along with reimbursement loss. About 2 or 3 times a year, Matt is hospitalized because of medication non-adherence when he is using drugs.

Dr. Jones sees Matt twice a month, an insufficient frequency with which to monitor and reinforce abstinence. Dr. Jones’s clinic, however, can be reimbursed for more frequent urine sample monitoring. Matt’s parents are already spending hundreds of dollars monthly for their son’s living expenses. Dr. Jones holds a meeting with the family and suggests that the parents provide up to $200 a month contingent on their son’s abstinence. To earn these funds, Matt has to provide a negative breath alcohol and negative cocaine urine sample every Monday and Thursday. For his first set of negative samples, he gets $10, and 2 consecutive negative samples earn him $15. Amounts increase by $5 until they reach a cap of $25 after 2 full weeks of negative samples. A missed or positive sample resets earnings to $5 for the next negative. In total, the system costs no more than $200 per month-less than his parents spend now.

Matt’s parents do not give the money directly to their son. Matt earns money in this manner only with Dr. Jones’s oversight. If Matt relapses and spends all his disability income on drugs, his parents agree to provide food only in their home, or to direct him to a soup kitchen. Unearned funds are returned to the parents. Dr. Jones sets up an accounting system and designates a nurse to deliver the intervention on days he does not see Matt.

Matt is initially skeptical of the plan, but he provides negative breath and urine samples at his first session and receives $10 on the spot. Dr. Jones congratulates Matt and reminds him he could earn $15 on Thursday if he remains abstinent. Dr. Jones asks him what he will do with his earnings. Matt says he will go to Subway for lunch, something he can rarely do. He tests negative on Thursday, and the nurse gives him $15, which he spends on a new T-shirt. Matt gradually increases his earnings to the cap of $25.

After about a month of abstinence, Matt fails to attend an appointment. The nurse, and Dr. Jones, try calling him. He does not answer or re-appear until 2 weeks later when he provides a positive sample. Matt receives no earnings, but Dr. Jones reminds him of all he had gained, tangibly and intangibly, when he was abstinent and encourages him to stop using so that he can test negative later that week and resume earning money.

Matt is hungry and disheveled. The staff refers him to a local soup kitchen, but Matt goes to his parents. They remain firm to their commitment to only provide funds contingent on abstinence. They invite Matt for dinner and tell him they welcome him for every meal until his next testing day; they encourage him to take his medications. Matt comes for dinner the next 2 days. He resumes abstinence and maintains it for years-with only occasional slips and no subsequent psychiatric hospitalizations. Since the program began, he rarely misses appointments with Dr. Jones.

This case exemplifies the successful application of financial incentives. Although not all patients have family willing or able to supply funds, this approach can be useful. Collecting and rapidly screening samples twice weekly allows for frequent monitoring and reinforcement of initial abstinence and appropriate implementation of incentive principles. After sustained periods of abstinence were achieved, Dr. Jones eventually reduced the testing and reinforcement frequency.

This article is based in part on work supported by National Institutes of Health Grants P50-DA09241, P60-AA03510, R01-HD075630, R01-AA021446, DP3 DK097705, and R01-AA023502.

Dr. Petry is Professor of Medicine, University of Connecticut Health Center, Farmington, CT. 

Dr. Petry reports no conflicts of interest concerning the subject matter of this article.

 Petry NM, Peirce JM, Stitzer ML, et al. Effect of prize-based incentives on outcomes in stimulant abusers in outpatient psychosocial treatment programs: a national drug abuse treatment clinical trials network study. 

 Alessi SM, Petry NM. A randomized study of cellphone technology to reinforce alcohol abstinence in the natural environment. 

 Barnett NP, Tidey J, Murphy JG, et al. Contingency management for alcohol use reduction: a pilot study using a transdermal alcohol sensor. 

 Ledgerwood DM, Alessi SM, Hanson T, et al. Contingency management for attendance to group substance abuse treatment administered by clinicians in community clinics. 

 Petry NM, Martin B, Finocche C. Contingency management in group treatment: a demonstration project in an HIV drop-in center. 

 Priebe S, Yeeles K, Bremner S, et al. Effectiveness of financial incentives to improve adherence to maintenance treatment with antipsychotics: cluster randomized controlled trial. 

 Petry NM, Andrade LF, Barry D, Byrne S. A randomized study of reinforcing ambulatory exercise in older adults. 

 Petry NM, Cengiz E, Wagner JA, et al. Testing for rewards: a pilot study to improve type 1 diabetes management in adolescents. 

 Olmstead TA, Petry NM. The cost-effectiveness of prize-based and voucher-based contingency management in a population of cocaine- or opioid-dependent outpatients. 

 Walter KN, Petry NM. Motivation and contingency management treatments for substance use disorders. Curr Top Behav Neurosci. 2016;27:569-581.

 McDonell MG, Srebnik D, Angelo F, et al. Randomized controlled trial of contingency management for stimulant use in community mental health patients with serious mental illness. 

 Petry NM, Alessi SM, Rash CJ. A randomized study of contingency management in cocaine-dependent patients with severe and persistent mental health disorders. 

 Davis DR, Kurti AN, Skelly JM, et al. A review of the literature on contingency management in the treatment of substance use disorders, 2009-2014. 

 Dutra L, Stathopoulou G, Basden SL, et al. A meta-analytic review of psychosocial interventions for substance use disorders. 

Articles

A number of behaviors are improved by financial incentive interventions. Details here.

Financial Incentives for Adherence: Do They Pay?

Obesity has emerged as a significant threat to public health throughout the developed world. The World Health Organization defines overweight as a body mass index of 25.0 to 29.9 kg/m

 Nearly two-thirds of Americans are overweight or obese according to these criteria.

 Numerous health problems, including diabetes, cardiovascular disease, arthritis, and cancer, are associated with obesity. In addition, overweight and obese persons are more likely than their normal-weight peers to have a variety of psychiatric disorders.

In this review, we summarize associations between obesity and psychiatric disorders. We then discuss potential causal pathways, behavioral treatment for obesity, and ways in which psychiatric disorders can complicate obesity treatment. Finally, we provide recommendations for addressing these complications. Several studies cited in this review are based on data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). The findings from the survey are summarized in the 

Associations with mood and anxiety disorders

Epidemiological studies support positive associations between BMI and mood disorders.

 A recent study using NESARC data found increased odds of mood disorder symptoms-including major depression, dysthymia, and manic and hypomanic episodes-among obese and extremely obese persons compared with their normal-weight counterparts.

 Obese individuals were 1.5 times more likely than normal-weight individuals to report lifetime or past-year mood disorder; extremely obese persons were twice as likely. Anxiety disorder rates were elevated not only in the obese and extremely obese but also in those who were only moderately overweight (odds ratio [OR], 1.19 - 2.60). Lifetime and past-year prevalence of generalized anxiety disorder, panic disorder without agoraphobia, and specific phobia were elevated among individuals classified as overweight and obese.

 A greater likelihood of depression and anxiety disorders with increasing BMI has also been observed in epidemiological studies carried out in other countries, including Germany, New Zealand, France, and the Netherlands.

Relationships between elevated body weight and affective disorders appear stronger in women than in men. Obesity was associated with mood and anxiety disorders in both men and women in 1 study, but overweight predicted increased odds of mood and anxiety disorder in women only.

 Other studies have found obesity to be related to depression in women but not in men.

 There is even some evidence that overweight and obesity may be associated with a lower likelihood of attempting or committing suicide among men, although increased BMI is associated with a greater likelihood of suicidal ideation among women.

Because studies to date are cross-sectional, causal pathways between obesity and mood and anxiety disorders have not been identified. It is likely that pathways are bidirectional. Weight-based discrimination is widespread, and being a target of discrimination can lead to anxiety and depression.

 Weight dissatisfaction is more prevalent among women than men, and women are more likely than men to face weight-based discrimination.

Concerns that they will be scrutinized or judged based on weight may contribute to social anxiety in overweight and obese women. In fact, overweight and obese women are at increased risk for social phobia, but BMI is not associated with the likelihood of social phobia among men.

Mood and anxiety disorders can lead to weight gain by interfering with healthy eating or regular exercise.

 Eating may have an anxiolytic effect, although overeating in response to stress varies between individuals.

 Women are more likely than men to eat in response to negative emotions, and women with mood disorders are more likely than men to report increased appetite as a symptom of depression.

Associations between obesity and mood and anxiety disorders may arise from effects of stress on the hypothalamic-pituitary-adrenal (HPA) axis, which responds to stress by releasing cortisol and other hormones that modulate sympathetic nervous system activity. Under conditions of chronic stress, HPA axis activity becomes dysregulated, a state that has been implicated in depression and anxiety disorders as well as in obesity.

 Future prospective studies can further clarify the direction of relationships between obesity and affective disorders.

Associations with substance use disorders

Epidemiological studies of relationships between obesity and substance use disorders yield inconsistent findings. Petry and colleagues

 found higher rates of lifetime alcohol use disorders among overweight, obese, and extremely obese individuals (OR, 1.12 - 1.33). However, when men and women were examined separately, only men showed a positive association between BMI and lifetime alcohol use disorders.

 BMI was not significantly related to lifetime alcohol use disorders among women, but there was a negative relationship between BMI and past-year alcohol use disorders among women. Studies conducted in the US and Germany found obesity to be associated with a decreased likelihood of past-year alcohol use disorders, but these results have not been replicated in other countries.

Significant associations between BMI and illicit drug use disorders have not been identified. However, epidemiological samples include few persons with drug use disorders because of low population base rates.

Limited evidence from clinical samples appears to support an inverse relationship between current substance use disorders and obesity. Persons who seek bariatric surgery for obesity report relatively high rates of lifetime substance use disorders but very low rates of current substance use disorders. This suggests that abstaining from addictive drugs could contribute to obesity.

 Other studies find inverse relationships between BMI and past-year alcohol and marijuana use among women seeking weight loss treatment.

 Among individuals with bipolar disorder, there is an inverse relationship between overweight/obesity and substance use disorders.

Compulsive overeating and addictions to alcohol and other drugs appear to share common psychological and physiological underpinnings. Intake of food or drugs is reinforcing and activates reward circuits in the brain, causing the release of dopamine.

 The reward response to palatable food encourages eating, thus promoting survival; however, substances of abuse activate the system as well.

 Acute substance use leads to increased concentrations of dopamine in the brain. With chronic excessive use, however, the number of dopamine receptors declines, which leads to an eventual reduction in dopamine activity.

 A similar process may occur with overeating.

 used positron emission tomography (PET) to compare concentrations of dopamine D2 receptors in the brains of extremely obese and normal-weight individuals. Obese individuals had significantly fewer D2 receptors than normalweight individuals. Among the obese individuals, D2 receptor concentration declined as body weight increased.

 These findings suggest that overeating, like substance use, may initially stimulate dopamine activity but eventually leads to down-regulation of dopamine receptors and a reduction in dopamine activity.

However, some authors have postulated a preexisting "reward deficiency syndrome" that predisposes one to compulsively engage in rewarding activities, including substance abuse, overeating, gambling, and sexual addiction behavior.

 Variations in genes that govern expression of dopamine D2 receptors lead to individual differences in receptor density. Individuals with fewer D2 receptors are less sensitive to subtle rewards and more prone to anxiety, anger, and dysphoria, which leaves them vulnerable to overindulging in rewarding behaviors in an effort to alleviate negative emotions.

Overeating may thus be one of several behaviors used to compensate for the blunted reward effects of a hypoactive dopamine system. If that is the case, individuals examined by Wang and colleagues

 may have become obese because of a shortage of dopamine receptors rather than a loss of receptors because of overeating. Although there is evidence for a common pathway to obesity or drug addiction, the lack of consistent associations between obesity and substance use disorders in epidemiological samples suggests that any relationship between the two is complex.

Associations with other psychiatric disorders

Obesity is associated with several personality disorders in the NESARC sample.

 Antisocial, avoidant, obsessive-compulsive, paranoid, and schizoid personality disorders are all more prevalent among the obese and extremely obese than in normal-weight persons (OR, 1.31 - 2.55). In addition, extreme obesity is associated with a greater likelihood of dependent personality disorder (OR, 3.04). Antisocial personality disorder (ASPD) is significantly associated with BMI among women.

Obesity has been associated with elevated rates of attention-deficit/hyperactivity disorder (ADHD).

 Children with ADHD and other disruptive behavior disorders are heav-ier than their peers without behav-ioral disorders and are likely to remain overweight into adulthood.

 Impulsivity associated with ADHD may thus contribute to overeating and obesity.

Schizophrenia is not associated with obesity after controlling for other variables.

 However, treatment with antipsychotic medications-particularly olanzapine and clozapine-can lead to substantial weight gain in some patients.

Overall, the accumulated data on obesity and psychiatric disorders indicate that obese persons may face a variety of mental health problems in addition to the physical health problems that often accompany obesity.

In light of the increasing prevalence of overweight and obesity in the general population and elevated prevalence among individuals with a variety of psychiatric disorders, psychiatrists frequently encounter patients who are overweight or obese. They are also quite likely to deal with patients who are experiencing weight gain in response to psychiatric medications.

 There is evidence that most physicians, including psychiatrists, have not received adequate training to counsel patients regarding obesity and options for treatment.

Behavioral treatments for obesity generally include 3 components: dietary change; increased physical activity; and behavior therapy techniques, such as goal-setting, selfmonitoring, stimulus control, and behavioral contracting.

 In addition to weight loss itself, a goal of behavioral interventions is to introduce lifestyle changes that increase the likelihood that weight loss will be maintained.

 A typical behavioral weight loss program includes 12 to 16 lessons that cover specific strategies, such as recording daily food and calorie intake, avoiding triggers for unhealthy eating, increasing physical activity, obtaining social and family support, and modifying thoughts and emotions that undermine weight loss.

 Behavioral interventions generally result in weight losses of about 8% to 10% of initial body weight.

Effect of psychiatric disorders on obesity treatment

Patients with comorbid obesity and psychiatric conditions may have difficulty with adhering to weight loss treatment recommendations. Depression or anxiety may interfere with the ability to adopt new behaviors-particularly those that require effort, such as preparing healthier meals or exercising. There is evidence that weight management patients with major depressive disorder lose less weight than their counterparts without depression.

 Poor impulse control associated with ADHD and ASPD can undermine self-control efforts as well.

Patients who struggle with overweight and obesity may be reluctant to take medications that will further contribute to weight gain, or they may discontinue treatment prematurely if weight gain occurs.

 Sensitivity to these concerns can allow psychiatrists to anticipate challenges and barriers to effective treatment of psychiatric conditions. Bariatric surgery is becoming an increasingly popular treatment for severe obesity. Psychiatric evaluations to assess patients' ability to adhere to the behavioral changes required to benefit from surgery are an important part of the treatment process.

Treating obese patients with psychiatric disorders

Behavioral assessment of obese patients can identify psychiatric conditions that might interfere with treatment.

 Experts recommend treating depression before starting patients on a weight loss program, although there is also evidence that successful treatment of obesity can lead to significant improvement in mood.

 Exercise can improve mood, and it is a vital component of a successful weight loss intervention. Thus, introducing exercise during treatment for depression can give patients a head start on improving health before they begin a weight loss program.

Patients with anxiety disorders may become alarmed by the physical sensations they experience during exercise. Many require a gradual increase in exercise intensity to learn that heart rate and respiration will return to normal after exertion. Anxious patients may also need encouragement and even gradual exposure to overcome avoidance of behaviors that trigger anxiety, such as weighing themselves or keeping records of weight or food intake.

Patients with ADHD are likely to have difficulty adopting many weight loss strategies, particularly those like self-monitoring of food intake that rely on the ability to keep organized records and make entries on a regular basis. It may be necessary to work with these patients to develop routines for planning meals, finding time for regular exercise, and organizing food diaries and other self-monitoring materials.

Concern about the increased prevalence and negative health effects of obesity continues to grow. Greater understanding of psychiatric comorbidity may facilitate the development of more effective prevention and treatment interventions.

Obesity: Preventing and Managing the Global Epidemic.

 Hedley AA, Ogden CL, Johnson CL, et al. Prevalence of overweight and obesity among US children, adolescents, and adults, 1999-2002. 

 Barry D, Pietrzak RH, Petry NM. Gender differences in associations between body mass index and DSM-IV mood and anxiety disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. 

 Baumeister H, HÃ¤rter M. Mental disorders in patients with obesity in comparison with healthy probands. 

 Petry NM, Barry D, Pietrzak RH, Wagner JA. Overweight and obesity are associated with psychiatric disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions.

 Scott KM, Bruffaerts R, Simon GE, et al. Obesity and mental disorders in the general population: results from the world mental health surveys. 

 Carpenter KM, Hasin DS, Allison DB, Faith MS. Relationships between obesity and DSM-IV major depressive disorder, suicide ideation, and suicide attempts: results from a general population study. 

 Magnusson PK, Rasmussen F, Lawlor DA, et al. Association of body mass index with suicide mortality: a prospective cohort study of more than one million men. 

 Carr D, Friedman MA. Is obesity stigmatizing? Body weight, perceived discrimination, and psychological well-being in the United States. 

 Kessler RC, Mickelson KD, Williams DR. The prevalence, distribution, and mental health correlates of perceived discrimination in the United States. 

 DiGioacchino RF, Sargent RG, Topping M. Body dissatisfaction among White and African American male and female college students. 

 Andreyeva T, Puhl RM, Brownell KD. Changes in perceived weight discrimination among Americans, 1995-1996 through 2004-2006. 

 Jones F, O’Connor DB, Conner M, et al. Impact of daily mood, work hours, and iso-strain variables on self-reported health behaviors. 

 Kaplan HI, Kaplan HS. The psychosomatic concept of obesity. 

 Greeno CG, Wing RR. Stress-induced eating. 

 Larsen JK, van Strien T, Eisinga R, Engels RC. Gender differences in the association between alexithymia and emotional eating in obese individuals. 

 Bornstein SR, Schuppenies A, Wong ML, Licinio J. Approaching the shared biology of obesity and depression: the stress axis as the locus of gene-environment interactions. 

 Barry D, Petry NM. Associations between body mass index and substance use disorders differ by gender: results from the National Epidemiologic Survey on Alcohol and Related Conditions. 

 John U, Meyer C, Rumpf HJ, Hapke U. Relationships of psychiatric disorders with overweight and obesity in an adult general population. 

 Kalarchian MA, Marcus MD, Levine MD, et al. Psychiatric disorders among bariatric surgery candidates: relationship to obesity and functional health status. 

 Kleiner KD, Gold MS, Frost-Pineda K, et al. Body mass index and alcohol use. 

 Warren M, Frost-Pineda K, Gold M. Body mass index and marijuana use. 

 McIntyre RS, McElroy SL, Konarski JZ, et al. Substance use disorders and overweight/obesity in bipolar I disorder: preliminary evidence for competing addictions. 

 Volkow ND, Fowler JS, Wang GJ. The addicted human brain: insights from imaging studies. 

 Comings DE, Blum K. Reward deficiency syndrome: genetic aspects of behavioral disorders. 

 Wang GJ, Volkow ND, Logan J, et al. Brain dopamine and obesity. 

 Blum K, Cull JG, Braverman ER, Comings DE. Reward Deficiency Syndrome. 

 Goldstein RB, Dawson DA, Stinson FS, et al. Antisocial behavioral syndromes and body mass index among adults in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions. 

 Altfas JR. Prevalence of attention deficit/hyperactivity disorder among adults in obesity treatment. 

 Holtkamp K, Konrad K, MÃ¼ller B, et al. Overweight and obesity in children with Attention-Deficit/Hyperactivity Disorder. 

 Anderson SE, Cohen P, Naumova EN, Must A. Relationship of childhood behavior disorders to weight gain from childhood into adulthood. 

 Susce MT, Villanueva N, Diaz FJ, de Leon J. Obesity and associated complications in patients with severe mental illnesses: a cross-sectional survey. 

 Allison DB, Mentore JL, Heo M, et al. Antipsychotic-induced weight gain: a comprehensive research synthesis. 

 Stunkard AJ, Faith MS, Allison KC. Depression and obesity.

 Jay M, Gillespie C, Ark T, et al. Do internists, pediatricians, and psychiatrists feel competent in obesity care? Using a needs assessment to drive curriculum design.

 Fabricatore AN. Behavior therapy and cognitive-behavioral therapy of obesity: is there a difference? 

 Diabetes Prevention Program (DPP) Research Group. The Diabetes Prevention Program (DPP): description of lifestyle intervention. 

 Friedman MA, Brownell KD. A comprehensive treatment manual for the management of obesity. In: Van Hasselt VB, Hersen M, eds. 

Sourcebook of Psychological Treatment Manuals for Adult Disorders.

 Wadden TA, Osei S. The treatment of obesity: an overview. In: Wadden TA, Stunkard AJ, eds. 

 Pagoto S, Bodenlos JS, Kantor L, et al. Association of major depression and binge eating disorder with weight loss in a clinical setting. 

 Fava M. Weight gain and antidepressants. 

 Walfish S, Vance D, Fabricatore AN. Psychological evaluation of bariatric surgery applicants: procedures and reasons for delay or denial of surgery. 

 Wadden TA, Phelan S. Behavioral assessment of the obese patient. In: Wadden TA, Stunkard AJ, eds. 

Obesity has emerged as a significant threat to public health throughout the developed world. The World Health Organization defines overweight as a body mass index of 25.0 to 29.9 kg/m2 and obesity as a BMI of 30.0 kg/m2 or greater.1 Nearly two-thirds of Americans are overweight or obese according to these criteria.2 Numerous health problems, including diabetes, cardiovascular disease, arthritis, and cancer, are associated with obesity. In addition, overweight and obese persons are more likely than their normal-weight peers to have a variety of psychiatric disorders.

Obesity and Psychiatric Disorders

Contingency management (CM) treatments are based upon a simple behavioral principle -- if a behavior is reinforced or rewarded, it is more likely to occur in the future. These behavioral principles are used in everyday life. For example, parents use allowances or dessert to encourage their children to make their beds or eat their dinners. Employers use salaries and bonuses to reward good job performance. In the case of substance abuse treatment, drug abstinence, as well as other behaviors consistent with a drug-free lifestyle, can be reinforced using these principles.

Substance abuse treatment, however, is often aversive in nature. Because many drugs are illegal, society considers substance users to engage in illegal behaviors, and the courts and legal systems may mandate or coerce them into treatment. Thus, rather than reinforcing substance abusers for their progress and attempts at remaining abstinent, some clinics utilize confrontation techniques when patients are suspected of "using" or discharge patients when they are not adhering to program rules. While these negative reinforcement techniques may be effective in altering some behaviors, they also result in an unpleasant environment and context for recovery. Importantly, not all aspects of substance abuse treatment are aversive. Many treatment programs routinely use some forms of reinforcement, such as take-home methadone privileges for patients who maintain long periods of abstinence or pins and leadership status in Alcoholics Anonymous meetings.

The premise behind CM is to utilize these and other reinforcement procedures systematically to modify behaviors of substance abusers in a positive and supportive manner (Petry, 2000). For example, in many CM treatments, patients leave urine specimens multiple times each week and receive explicit rewards for each specimen that tests negative for drugs. These rewards often consist of vouchers that have a monetary basis and can be exchanged for retail goods and services such as restaurant gift certificates, clothing, sports equipment, movie theater tickets and electronics.

A series of studies demonstrated that CM is efficacious in retaining patients in treatment and reducing substance use. Higgins et al. (1993) randomly assigned cocaine-dependent outpatients to 12-step-oriented treatment or a CM treatment in which they received individual behavioral therapy in conjunction with vouchers every time they provided a drug-free urine specimen. Patients assigned to the CM group remained in treatment significantly longer and reduced cocaine use relative to patients in the 12-step group. A subsequent trial evaluated whether it was the provision of the contingent vouchers, as opposed to the behavioral therapy, that engendered the improved outcomes (Higgins et al., 1994). This study provided intensive behavioral therapy to another sample of cocaine-dependent outpatients, but one group received vouchers contingent upon drug abstinence while the other group did not. Three-quarters of the patients in the voucher condition completed treatment, compared with 40% of patients who received the same behavioral therapy without the vouchers. Over half the patients who received vouchers achieved at least 10 weeks of continuous cocaine abstinence versus 15% in the non-voucher condition. 

To further isolate the effects of the vouchers, Higgins et al. (2000) compared a group of cocaine-dependent outpatients who received vouchers contingent upon negative urinalysis results to another group who received the same amount of vouchers regardless of their urinalysis results. Significantly more of the patients in the contingent condition were able to achieve long periods of cocaine abstinence throughout the study, and the beneficial effects of the contingent condition persisted throughout a one-year follow-up period.

These beneficial effects of CM treatments extend beyond cocaine-dependent outpatients. Studies have shown improved outcomes when CM techniques are applied to clients dependent on marijuana (Budney et al., 2000), cigarettes (Roll et al., 1996), alcohol (Petry et al., 2000), opioids (Bickel et al., 1997), benzodiazepines (Stitzer et al., 1992) and multiple drugs (Petry and Martin, in press; Piotrowski et al., 1999). 

Not only can abstinence be reinforced using these CM techniques, but variations of these procedures are effective in modifying other behavior patterns of substance abusers. Reinforcement can be provided for attendance at therapy sessions (Carey and Carey, 1990), for prosocial behaviors within the clinic (Petry et al., 1998) or for compliance with goal-related activities (Bickel et al., 1997; Iguchi et al., 1997; Petry et al., 2000). In terms of this latter category, clients may decide upon three discrete activities each week that are related to their treatment goals. These may be attending a medical appointment if the goal is to improve health, going to the library with their child if the goal is to improve parenting or filling out a job application if the goal is to obtain employment. If clients successfully accomplished these activities and provided objective verification of their completion via receipts (Petry et al., 2001b), they received rewards. In one study at an HIV drop-in center, we found that providing reinforcement increased attendance at groups from an average of less than one patient per week to over seven per week and that reinforcing compliance with goal-related activities increased compliance rates from less than 30% to over 65% (Petry et al., 2001a). Similarly, Silverman et al. (2001) described a vocational training program in which substance abusers receive paid training opportunities contingent upon drug abstinence, and Milby et al. (2000) have a program that provides housing to homeless cocaine abusers that is contingent upon abstinence. Focusing on behaviors that can derive reinforcement from the natural environment, such as is apparent with housing and employment, may result in persistence of the behavior pattern even after participation in the research study is completed. 

These techniques can also be used to encourage adherence to medication in substance abusers. Preston et al. (1999) found that providing vouchers significantly enhanced adherence to naltrexone (ReVia) in recently detoxified heroin-dependent patients, and Rigsby et al. (2000) reported similar beneficial effects of CM techniques with adherence to anti-retrovirals among HIV-positive patients. 

Despite the efficacy of CM in enhancing drug abstinence and improving other psychosocial problems, some logistical concerns have hindered its dissemination, the primary of which is cost. The voucher amounts escalate as the number of consecutive negative urine samples increases, such that the first negative sample earns $2.50, the second $3.75, the third $5 and so on. Typically, successful voucher programs (Higgins et al., 2000; 1994; 1993; Silverman et al., 1996) have allowed for earnings exceeding $1,000 during a 12-week treatment period, and average earnings are about $600 per patient. 

A way to reduce the costs of CM is to provide only a proportion of the behaviors with a tangible reinforcer. In one outpatient treatment program, alcohol-dependent patients earned the chance to draw from a bowl and win prizes of varying magnitudes for submitting negative breath-alcohol samples and completing steps toward their treatment goals (Petry et al., 2000). The prizes available ranged from $1 prizes (choice of a bus token or fast-food coupon), $20 prizes (choice of a personal tape player, watch or phone card) and $100 prizes (choice of television or stereo). Chances of winning were inversely related to prize costs, such that chances of winning a $1 prize were approximately 1 in 2, while chances of winning a $100 prize were 1 in 250. This intermittent schedule of reinforcement may be an inexpensive expansion of vouchers, as average cost per client was under $200. The beneficial effects of this technique were replicated in cocaine-abusing methadone patients (Petry and Martin, in press). 

The time or money associated with obtaining prizes, however, may still exceed the resources available to many treatment providers. To further reduce costs, clinics may consider having both monetary and non-monetary prizes available (e.g., lunches and special parking spots for a week or take-home doses or rapid dosing lines in methadone clinics). Clinics may solicit donations of some prizes or write for small grants ($5,000) that may cover the costs of prizes for a year. Nevertheless, if the magnitude of the rewards becomes too low, or if the prizes available are not desired by the patients, the procedure is unlikely to produce its desired effects (Petry, 2000). 

Contingency management procedures that provide any form of monetary-based incentives are clearly going to be more costly than standard treatment. However, the costs of the CM approach, which can be accompanied by dramatic reductions in substance use, may be small in contrast to those associated with continued drug use, including emergency department visits, inpatient stays or medical care for an individual who contracts HIV (Holder and Blose, 1991). Thus, CM interventions may ultimately save money through reduced hospitalizations, medical care, criminal justice system costs and public assistance payments and through increased productivity. These treatments may also have direct beneficial effects to the treatment programs, i.e., if clients are retained in treatment longer, the reimbursements provided to the clinic may increase. The potential cost-savings effects of CM from both programmatic as well as societal perspectives have yet to be studied. If found to be cost-effective, General Assistance programs and managed care companies may find the upfront costs of CM programs to be modest with respect to their long-term cost offsets. Creative adaptation of these techniques by community providers may assist in disseminating CM techniques for improving the treatment of substance abusers. 

Dr. Petry's research is supported by the National Institutes of Health (R01-DA13444, R01-MH60417, R01-MH60417-suppl, R29-DA12056, P50-DA09241, P50-AA03510 and M01-RR06192).

 Bickel WK, Amass L, Higgins ST et al. (1997), The effects of adding behavioral treatment to opioid detoxification with buprenorphine. J Consult Clin Psychol 65(5):803-810.
 

 Budney AJ, Higgins ST, Radonovich KJ, Novy PL (2000), Adding voucher-based incentives to coping skills and motivational enhancement improves outcomes during treatment for marijuana dependence. J Consult Clin Psychol 68(6):1051-1061.
 

 Carey KB, Carey MP (1990), Enhancing the treatment attendance of mentally ill chemical abusers. J Behav Ther Exp Psychiatry 21(3):205-209.
 

 Higgins ST, Budney AJ, Bickel WK et al. (1993), Achieving cocaine abstinence with a behavioral approach. Am J Psychiatry 150(5):763-769.
 

 Higgins ST, Budney AJ, Bickel WK et al. (1994), Incentives improve outcome in outpatient behavioral treatment of cocaine dependence. Arch Gen Psychiatry 51(7):568-576.
 

 Higgins ST, Wong CJ, Badger GJ et al. (2000), Contingent reinforcement increases cocaine abstinence during outpatient treatment and 1 year of follow-up. J Consult Clin Psychol 68(1):64-72.
 

 Holder HD, Blose JO (1991), Typical patterns and cost of alcoholism treatment across a variety of populations and providers. Alcohol Clin Exp Res 15(2):190-195.
 

 Iguchi MY, Belding MA, Morral AR et al. (1997), Reinforcing operants other than abstinence in drug abuse treatment: an effective alternative for reducing drug use. J Consult Clin Psychol 65(3):421-428.
 

 Milby JB, Schumacher JE, McNamara C et al. (2000), Initiating abstinence in cocaine abusing dually diagnosed homeless persons. Drug Alcohol Depend 60(1):55-67.
 

 Petry NM (2000), A comprehensive guide to the application of contingency management procedures in clinical settings. Drug Alcohol Depend 58(1-2):9-25.
 

 Petry NM, Bickel WK, Tzanis E et al. (1998), A behavioral intervention for improving verbal behaviors of heroin addicts in a treatment clinic. J Appl Behav Anal 31(2):291-297.
 

 Petry NM, Martin B (in press), Lower cost contingency management for treatment cocaine and opioid abusing methadone patients. J Consult Clin Psychol.
 

 Petry NM, Martin B, Cooney JL, Kranzler HR (2000), Give them prizes and they will come: contingency management for treatment of alcohol dependence. J Consult Clin Psychol 68(2):250-257.
 

 Petry NM, Martin B, Finocche C (2001a), Contingency management in group treatment: a demonstration project in an HIV drop-in center. J Subst Abuse Treat 21(2):89-96.
 

 Petry NM, Tedford J, Martin B (2001b), Reinforcing compliance with non-drug related activities. J Subst Abuse Treat 20(1):33-44.
 

 Piotrowski NA, Tusel DJ, Sees KL et al. (1999), Contingency contracting with monetary reinforcers for abstinence from multiple drugs in a methadone program. Exp Clin Psychopharmacol 7(4):399-411.
 

 Preston KL, Silverman K, Umbricht A et al. (1999), Improvement in naltrexone treatment compliance with contingency management. Drug Alcohol Depend 54(2):127-135.
 

 Rigsby MO, Rosen MI, Beauvais JE et al. (2000), Cue-dose training with monetary reinforcement: pilot study of an antiretroviral adherence intervention. J Gen Intern Med 15(12):841-847.
 

 Roll JM, Higgins ST, Badger GJ (1996), An experimental comparison of three different schedules of reinforcement of drug abstinence using cigarette smoking as an exemplar. J Appl Behav Anal 29(4):495-504; quiz 504-505.
 

 Silverman K, Higgins ST, Brooner RK et al. (1996), Sustained cocaine abstinence in methadone maintenance patients through voucher-based reinforcement therapy. Arch Gen Psychiatry 53(5):409-415.
 

 Silverman K, Svikis D, Robles E et al. (2001), A reinforcement-based therapeutic workplace for the treatment of drug abuse: six-month abstinence outcomes. Exp Clin Psychopharmacol 9(1):14-23.
 

 Stitzer ML, Iguchi MY, Felch LJ (1992), Contingent take-home incentive: effects on drug use of methadone maintenance patients. J Consult Clin Psychol 60(6):927-934.

Contingency management provides tangible reinforcement to modify patients' behaviors and has been found to reduce substance abuse across a number of clinical populations and settings. What types of tangible reinforcements are most effective?

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