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CONCLUSIONS
This dissertation explores a growing problem in society with regard to prescription drugs. The study was unique in that it chose to focus on prescription stimulants, rather than the opioids which has been the focus of most recent research in this field of study. This dissertation is the first study of its kind to attempt to address the issue of prescription stimulant abuse by
developing techniques to identify individuals attempting to inappropriately access stimulants. Two different techniques were explored in this study: the first used administrative claims data to classify individual stimulant users using a latent class analysis; and the second attempted to develop a short subtle scale called the Subtle ADHD Malingering Screener (SAMS) for administration in the primary care provider’s office to identify individuals malingering symptoms of ADHD with the intentions of obtaining prescriptions of stimulants for misuse or diversion.
The specific goal of this dissertation was to help develop strategies that can be used in the prevention of abuse of prescription psychostimulants. The combination of techniques
developed/tested in this dissertation provide a health policy analyst with tools, such as the SAMS, and the prescription claims based latent classes, required to develop these strategies. These tools still need several rounds of further research before they can be used in strategies tailored for drug abuse prevention, but this dissertation will hopefully serve as the platform for the development and refinement of these tools. The conclusions from each of the three papers are
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discussed below, along with directions for future research and the clinical implications of this dissertation.
Concluding Comments on Paper One
This paper developed a deeper understanding of the differences in stimulant use behaviors between abusers and non-abusers, using a latent class analysis to first classify individuals according to their behaviors. It is one of the first studies to attempt to exclusively characterize stimulant use behaviors, and validate the developed latent classes using stimulant abuse diagnoses identified from administrative claims data. The use of administrative claims data to identify misusers of prescription stimulants revealed critical insights that can help future research in this area. This study was also the first to use a combination of Medicaid
administrative claims data and PMP data to comprehensively capture all use of stimulants while estimating the risk behaviors.
This study developed a 2-class model with 4.1% of the sample in the one class, and 95.9% of the sample in the other class. The 2-class model, however, was not predictive of a diagnosis of dependent or nondependent stimulant abuse. It is possible that many individuals classified in Class 1 were in fact abusing prescription stimulants, but had not been diagnosed; Unfortunately, there was no way to know their true misuse status from the data. Hence the
findings of the prediction of stimulant misuse using latent classes need to be treated with caution. It is possible that alternative validation mechanisms with more reliable identification of misusers might have discovered a correlation with the latent classes obtained in this study. It is possible that any combination of these reasons was responsible for the non-significant finding obtained in this study. The latent classes obtained in this study might still be indicative of stimulant misuse,
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but further research into the stimulant use behavior, perhaps using alternative validation techniques, is needed. This study demonstrated the value of latent class techniques to help identify variations in patterns of stimulant use, while also displaying the limitations of administrative claims databases in capturing true misuse status.
Concluding comments on Paper Two
This study is the first of its kind to attempt to develop a scale to identify malingering in the context of ADHD. A ten-item, two-factor solution was obtained for the SAMS in this study. The sum scale score was used to calculate the total score for the SAMS in order to preserve ease of scoring, and reduce time of administration in the physician’s office. Each individual SAMS item was also found to significantly differentiate all three groups in the study, and not just the ADHD group and the Malingerer group. The mean scores on both the psychological and academic factor follow patterns predicted in the Accuracy of Knowledge framework.
The SAMS presents an innovative approach to identify malingering of ADHD symptoms, reduce overdiagnosis of ADHD, and for early identification of prescription stimulant abuse directly in the clinical setting. It is designed to be short, inexpensive, and does not need
additional training for administration, scoring, or evaluation, which makes it a valuable resource for primary care providers. There is a need to focus on the needs of malingerers identified by this scale, and to develop interventions that can help malingerers cope with their stressors and
address potential addiction problems. Finally, this study successfully demonstrates the methodology of developing a subtle scale with the application of a theoretical framework for item development. This technique can be applied in other areas in such as the early identification
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of opioid abusers, injection drug users, to implement early targeted interventions. Further research required on the SAMS was conducted as part of paper three, as presented below.
Concluding comments on Paper Three
This study provides critical research for the further development of the Subtle ADHD Malingering Scale (SAMS) and builds value for its use in the clinical setting. The study used data collected in paper two to develop a cut-off score for SAMS and estimate its classification accuracy. Using CART analysis, a cut off score was developed for the SAMS. Respondents were classified as malingerers if their psychological subscale score was greater than 15 and the
academic subscale score was greater than 7. This classification provided a sensitivity of 90.3% and a specificity of 80.1%. The SAMS also showed significantly higher sensitivity than the PAI. Being classified as a ‘malingerer’ by the SAMS at a physician’s office should signal the need for additional testing, or a referral to a specialist, in the case of primary care providers.
The SAMS presents immense potential for use in the clinical setting to help identify malingering of ADHD. It is tailored toward malingering of ADHD symptoms, and has
demonstrated satisfactory sensitivity, specificity, and high resistance to malingering. Physicians evaluating patients for ADHD are recommended to administer the SAMS, pending further
research, to help validate the veracity of the patient’s claims. Patients flagged as ‘malingerers’ by the SAMS are recommended for additional testing or referral to a specialist to identify if they truly have ADHD. There is a need for further research testing the SAMS directly in the clinical setting and in diverse populations. There is also a need to develop interventions for patients identified as ‘malingerers’ by the SAMS. These individuals may need help for drug dependence and counseling to help them cope with the stressors that have encouraged drug-seeking behavior.
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IMPLICATIONS
Implications for Research & Practice
This dissertation was carried out with the goal of making a change in the healthcare system that contributes to millions of cases of prescription stimulant abuse every year. The latent classes developed in paper one, with further refinement, can provide a tool to payers such as commercial insurance companies or Medicaid to help identify individuals who are in need of intervention for drug abuse, and to help curtail others who may be diverting their prescriptions. Once the identification of these individuals can be accomplished with reasonable accuracy, tailored interventions need to be developed that involve a combination of lock-in programs to prevent further drug diversion, and medical intervention to help treat possible drug abuse
problems. Further research is needed to develop validation tools that can estimate if latent classes using behavioral risk factors can perform reliably at identifying individuals who are misusing or diverting stimulant prescriptions.
Papers two and three serve a different purpose in the prevention of drug abuse. They used a college student population, to help develop a tool for use in the physician’s office to help identify malingerers of ADHD symptoms. This can help address overdiagnosis of ADHD, and over-prescribing of stimulants. The SAMS displayed potential for clinical use with high levels of sensitivity and specificity.. A true estimate of prevalence of malingering in various settings needs to be estimated to calculate a positive and negative predictive value that can help direct
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including children under the age of 18 years, and adults not enrolled in colleges is required before the SAMS can be recommended in the clinical setting.
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