Essay Examples - Term Report on Drug Addiction
Substance abuse (i.e. tobacco, alcohol, illicit drugs) is a prevalent and severe issue both domestically and internationally. Within the United States the annual fiscal cost associated with substance abuse is approximately $700 billion (National Institute on Drug Abuse, 2015). Internationally, 230 million people (5 percent of adult population) are estimated to have used illegal drugs as recent as 2010. Potentially adverse issues arising as a result of illegal drug use, include economic, social, and health-related repercussions. Emergent health issues might include HIV spread through needle sharing, and increased morbidity rate (0.2 million per year), (United Nations Office on Drugs and Crime, 2012).
Specifically, illegal drug use cost the healthcare industry approximately $11 billion dollars annually. However, when factoring in costs associated with (i.e. drug related criminal behaviors, lost work productivity, etc.) the approximate annual cost is $193 billion. Over the course of their lifetime a significant number of young people use illegal drugs at least once. Statistically about 20.30 percent of 8th graders, 37.40 percent 10th graders, and 49.10 percent of 12th graders used drugs in 2014 (National Institute on Drug Abuse, 2015).
Also notable is the fact that Americans twelve and older have greater drug use over the last decade. From 8.3 percent in 2002 to 9.4 percent or 24.6 million in 2013. From a gender standpoint men have a drug dependence rate of 3.8 percent versus women at 1.9 percent. Culturally American Indians and Alaska natives represent the highest rate of illicit drug users at 6 percent. African Americans use at a rate of 3.6 percent with Asian Americans on the lower end at 1 percent (Substance Abuse and Mental Health Services Administration, 2014). This informative report will provide scholastic data including (Peer-reviewed journal articles, statistics). It will address various aspects of drug abuse, causative factors, and associated consequences from both a domestic and international perspective.
Tendencies and causative factors of drug addiction
- Analytic descriptive study (Iran)
Comparative to other cultures and groups the ratio of drug addicts in Iran is significantly higher. For example, in most European countries the ratio is 1 drug addict to every 5,000 individuals. In third world countries like Morocco, Egypt, and South Africa the ratio is 1 to 1,000. In contrast, the ratio of drug addicts to non-addicted individuals in Iran is one to 100 (Ahmadali, Hamed, Azizollah, & Azizollah, 2015). Such statistics reveal the dire nature of drug abuse, both in Iran and globally.
In terms of tendencies official records of Iran indicate that there are between 1.2 million to 2 million drug users. About 60 percent of Iranian prisoners are convicted of various drug addictions. Also, an estimated 90 percent of killings, thefts, rapes, incidents of human trafficking, and the contraction of Aids are all associated with drugs. In terms of causative factors, children as young as 9 are becoming addicted based on social and environmental factors. This includes family, social engagement, imitation of adult addicts, and influence by drug abusers (Ahmadali, Hamed, Azizollah, & Azizollah, 2015).
- Probable causative relationship between cannabis use and suicidal thoughts
An examination of suicide reveals three sub-segments including suicidal ideation (SI), suicidal planning (SP), and suicidal attempt (SA). Global statistics of adults reveal that incidents of SI range from 3.1-56 percent, while occurrences of SP ranges from 0.9-19.5 percent. Also, occasions of SA range between 0.4-5.1 percent. There was a multinomial logistic regression analysis that examined SI and SA either with or without a plan (Delforterie, 2015).
To analyze the probable causative relationship between cannabis and suicidal thoughts or behaviors a (SSAGA) Semi-Structured Assessment of the Genetics of Alcoholism took place. Categories ranged from (0) no cannabis use- (3) 3 or more symptoms of use. Final analysis revealed that cannabis involvement was associated with SI regardless of interval (Delforterie, 2015).
It is also notable that even after controlling for other psychiatric disorders and substance association, there remained a causative relationship. In summation, the study is not conclusive as variant samples and confounders should be considered. However, even modest association between cannabis and (SI, SP, or SA) preventative measures should be considered (Delforterie, 2015).
- Probable causative relationship between child abuse and drug use
Drug dependence (especially methamphetamine) has created significant issues in Japan. Designer drugs, cannabis and prescription drug use has also seen a significant increase. Beyond the associated health concerns there are evident social implications. According to one statistic 25 percent of convicted Japanese prisoners have committed crimes under the Stimulant Control law.
Watanabe et al. as cited in (Ogai et al., 2015) has revealed findings that interpersonal relationships (i.e. family, friends) may adversely trigger drug use. Especially among impoverished families child abuse victimization has been frequently identified. Implicit and worth further examination is the role of economics on drug use. (Ogai et al., 2015).
The population size of the study conducted was one hundred and eleven inpatients and outpatients. The assessment tool used was the (ASI-J) Addiction Severity Index-Japanese version. This ASI-J survey revealed that female participants had the highest rate of child abuse. Naturally those men who experienced abuse (MEA) had a greater predisposition towards drug addiction than their non-abused male counterparts (MNEA). Females who experienced abuse (FEA) had significant family/social dynamics comparative to the non-abused females (FNEA) (Ogai et al., 2015).
Additionally, those men classified as MEA had strained family relationships (especially with fathers), greater anxiety, but less incidents of drug-related arrests than MNEA’s. Those classified as FEA had difficult social engagement including friends, family, life-partners, and psychiatric issues comparative to FNEA’s. This would imply that although there appears to be a causative relationship between drug-dependency and child abuse, there are gender specific behaviors. One suggestion based on the study is the development of gender-based interventions (Ogai et al., 2015). It would also be important to conduct comparative analysis of the same causative variables in different demographic settings and with larger participant groups.
- Probable causative relationship between chronic pain and opioid use
Drug use comes in many forms and prescription opioid dependence is currently on the rise. Therefore, a recent test was conducted with a participant size of 653 individuals. Such individuals were enrolled in the Prescription Opioid Addiction Treatment Study. An initial objective of the study was to ascertain the taxonomy of associated factors associated with use. Identified factors included intrapersonal-environmental and interpersonal determinants. Additionally, there is a greater risk when there are negative psychological issues, adverse emotional instances, or associated social-pressures (Weiss et al., 2014).
Although all participants identified pain relief as the primary reason for opioid use, those with pain did so at a greater rate (83.2 % versus 48.8 %). Following pain relief 13.1 % of those with chronic pain and 39.1 % of those without pain identified getting high as a causative factor. A tertiary reason that is given is psychological or emotional issues like anxiety, depression, or avoidance of undesirable memories. It is also notable that 56.5 % of participants with chronic pain wanted to avoid the symptoms associated with withdrawal (Weiss et al., 2014).
In summation the study reveals a combination of either physical pain or emotional pain/avoidance in all participants. There are similar socio-demographic and clinical characteristics. It is also noteworthy that the study references Marlatt’s taxonomy which classifies precipitants associated with relapse (Weiss et al., 2014). Future studies should consider opioid dependence and probable causative relationships with sub-groups. For example in patients with back pain versus shoulder pain, examination could determine if opioid dependence differed. It would also be important to expand the population size and dynamics. This could include several study’s occurring with similar variables to determine if the outcome would be the same.
- Personalized Feedback Interventions (IPFI’s versus CPFI’s)
A recent article conducted a meta-analysis of Personalized Feedback Interventions (PFI’s). The sub-groups include In-Person (IPFI’s) versus Computer-Delivered Interventions (CPFI’s). Data was collected by examining randomized clinical trials using both methods. Although this study was done specifically for alcohol, the assumption is that the intervention methodologies could also be useful as control mechanisms for drugs (Cadigan et al., 2015).
One observation of the study is that from a cost standpoint CPFI’s offer greater flexibility, are cost-effective, and therefore an appealing alternative to IPFI’s. Another salient point is that IPFI’s require more comprehensive logistics (i.e. trained providers, clinical training, and oversight). Finally, it appears based on the report that both IPFI’s and CPFI’s are feasible intervention strategies (Cadigan et al., 2015). Therefore, future studies could target high-risk drug users to determine probable outcomes. The establishment of a baseline would be also important in the process.
- Technology-based interventions
A recent report examined the potential value of technology-based interventions, especially for college students. Tobacco and other drug use are extremely high among this population. This was a synthesis of 12 studies that involved twenty technology based interventions. This offered researchers an opportunity to understand the value of technology based intervention from a macro perspective (Gulliver et al., 2015).
The majority of the studies reviewed occurred in the United States, with a few being conducted in the Netherlands and Canada. The sample size ranged from 65-517. The studies were randomized both at the individual and institutional level. Of the twenty interventions there was a variety of technology types used. This includes stand-alone computer programs, web, telephone, and mobile (Gulliver et al., 2015).
In terms of outcomes of those nine studies targeting tobacco the principle outcome measured was abstinence. Of the studies that focused on smoking cessation the goal was gradual abstinence. This outcome was measured based on cigarettes smoked per day, intention to quit, and associated quitting activities. There were also a couple of marijuana studies that examined marijuana use within the last month and one study that measured use over the last three months (Gulliver et al., 2015).
Finally, the meta-analysis shows promise of efficacy related to technology-based interventions. In terms of reducing tobacco use among college students this data supports previous studies conducted (i.e. Myung et al). Compared to control groups’ technology-based smoking cessation intervention had a 1.5 times greater success rate. However it is important to ensure that technology based interventions incorporate more frequent communication and accountability (Gulliver et al., 2015).
- Examination of screening and diagnostic instruments used to assess cannabis dependency
There was a study that examined thirty-five reports to understand the efficacy of twenty-five previously used instruments. The overall goal of reliable screening and assessment tools is to mitigate cannabis use. Globally cannabis has been identified as the most frequently used drug. For example, approximately 80.5 million Europeans have used it at least once in their lifetime. Further, there is an identified correlation between cannabis use and psychiatric, physical, and social impairment (Lopez-Pelayo, Batalla, Balcells, Colom, & Gual, 2015.
The 25 instruments used to evaluate cannabis use and resultant issues were divided into four categories. Those included cannabis scales, drug scales, structured interviews, and tools for enumerating cannabis use. The strength of the various instruments included revealing good psychometric properties. However, further development needs to occur before an instrument can be considered a gold standard. Future diagnostic tools must also evaluate organic consequences of cannabis. Hazardous patterns of use must also be considered and determined in future developments (Lopez-Pelayo, Batalla, Balcells, Colom, & Gual, 2015.
- Examination of outcomes of POAT (Prescription Opioid Addiction Treatment) studies
A recent study examined treatment of individuals reliant on prescription opioids and also associated long-term responses. The 9 month trial was labeled (POAT) Prescription Opioid Addiction Treatment study. The criteria for the POAT’s study included individuals who had either used heroin, had a dependence on Opioid, or a combination of both. It’s also noteworthy that the adaptive treatment design was divided into a two-phase strategy (Weiss et al., 2015).
The first phase was (SMM) standard medical management. The other phase was SMM plus (ODC) individual opioid drug counseling. The three and a half year study revealed marked improvement as a result of SMM and ODC. Finally, the long-term treatment appears to have marked improvement comparative to the short term studies (Weiss et al., 2015).
- Physician interventions
There was a study conducted in 2010 that examined the preparedness and experience of medical students regarding tobacco counseling. There were 10 medical schools from the United States involved in the survey. Survey questions covered topics including tobacco counseling, perception regarding physician influence on smokers, and understanding of tobacco treatments. Smoking was evaluated primarily based on it being the primary cause of preventable morbidity (Xiao et al., 2015). Future studies would need to determine the experience level of medical students regarding drug counseling.
Results indicate that approximately half (50.4%) of medical students had at least some tobacco counseling prior to medical school. Such consoling included clinical 5A tobacco counseling. The best identified approach to tobacco counseling included a combination of behavioral counseling and pharmacotherapy. This view was purported by approximately 86-92 % of medical students regardless of their previous counseling experience (Xiao et al., 2015).
Finally, there were approximately ten smoking cessation treatments identified. These included printed health education materials, physician counseling, nicotine replacement products, behavioral counseling, and tobacco treatment combined with behavioral counseling. Additionally, internet based programs, hypnosis, acupuncture, Chantix, and wellbutrin, were also identified as cessation treatments. Also noteworthy is the fact that student engagement with those dependent on nicotine varied. Therefore, it is difficult to ascertain the efficacy of long-term cessation counseling. Future studies should include information about duration, types and quality of student’s experiences with cessation counseling (Xiao et al., 2015).
In conclusion this report had identified various facts associated with substance abuse. While focusing primarily on drug abuse it has also included information on other substance abuse factors. The associated costs are significant and therefore it’s imperative that the United States and other countries address it. From a macro perspective the primary concern is the socio-economic impact that affects multiple industries including (law enforcement, and healthcare). From a micro or more granular perspective drug use is an epidemic that affects individuals as young as 9 and as old as 99.
Although there may be a disparity in the level of impact based on social factors, demographics, and cultural influences it affects all cultures. One insight gleaned from the study is that drug and substance use is often triggered by external causative factors. This could include abusive relationships, unhealthy modeling by drug-users, and early exposure. This could also include avoidance of emotional and or psychological issues. Often drug use is viewed primarily as an issue for those from a lower socio-economic background. However, drug and substance abuse is not based on a specific caste or social system.
In fact, drug and substance abuse is often a result of dependence on medication that is designed to cure pain. In these instances the issue becomes multi-faceted. Not only can the pain medication become an entry point to more serious drugs, it also can create unhealthy dependence. Therefore, patients have indicated a resistance to eliminating use for fear of withdrawal symptoms. This would affirm many of the studies which purported the value of combined intervention that includes counseling and education.
The range of available interventions includes surveys, various technology based interventions, and In-Person. The main focus of any intervention should be targeting substance abusers at the early stage. Clinical trials for example indicated the Pros and Cons of IPFI’s versus CPFI’s. These are factors necessary to combat substance abuse. Factors like logistics required to implement intervention is important. It would also be important for there to be pilot studies conducted prior to rolling out a comprehensive program. Especially in instances where technology intervention is leveraged, working out any issues is paramount.
Interventions must also be appropriate for their targeted population. For instance a web or computer based intervention would be appropriate for college students but maybe not for the senior population. In contrast, the senior population may be more inclined to respond to one-on-one intervention from a physician. It would be equally important to assess desired outcomes. For example the tobacco studies in the report established abstinence as a desired outcome. If future proposed interventions establish abstinence as a goal then appropriate timeframes should be considered.
Finally, while this report does not assume that intervention will be pursued by all demographics it offers relevant data. Failure to aptly implement intervention strategies could have significant consequences. Those consequences could adversely affect individuals and society. Therefore, if intervention is considered then early intervention is preferable, as it provides the greatest opportunity for successful treatment. It is also noteworthy that medical schools should allow intervention studies to inform present and future curriculum development.
Ahmadali, R., Hamed, S., Azizollah, A., & Azizollah, M. (2015, January). The Most Common Reasons and Incentives of Tendency to Addiction in Prisons and Rehabilitation Centers of Zahedan (Iran). Global Journal of Health Science, 7(4), 329-334.
Cadigan, J. M., Haeny, A. M., Martens, M. P., Weaver, C. C., Takamatsu, S. K., & Arterberry, B. J. (2015, April). Personalized Drinking Feedback: A Meta-Analysis of In-Person Versus Computer-Delivered Interventions. American Psychological Association, 83(2), 430-437.
Delforterie, M. J., Lynskey, M. T., Huizink, A. C., Creemers, H. E., Grant, J. D., Few, L. R., Glowinski, A. L., Statham, D. J., Trull, T. J., Bucholz, K. K., Madden, P. A., Martin, N. G., Heath, A. C., & Agrawal, A. (2015). The relationship between cannabis involvement and suicidal thoughts and behaviors. Drug and Alcohol Dependence, 150(1), 98-104.
Gulliver, A., Farrer, L., Chan, J. K., Tait, R. J., Bennett, K., Calear, A. L., & Griffiths, K. M. (2015, February 24). Technology-based interventions for tobacco and other drug use in university and college students: a systematic review and meta-analysis. Addiction Science & Clinical Practice, 10(1), 5-14. doi:10.1186/s13722-015-0027-4
Lopez-Pelayo, H., Batalla, A., Balcells, M. M., Colom, J., & Gual, A. (2015, April). Assessment of cannabis use disorders: a systematic review of screening and diagnostic instruments. Psychological Medicine, 45(6), 1121-1133.
National Institute on Drug Abuse. (2015). Monitoring the Future Study: Trends in Prevalence of Various Drugs. Retrieved from http://www.drugabuse.gov/trends-statistics/monitoring-future/monitoring-future-study-trends-in-prevalence-various-drugs
National Institute on Drug Abuse. (2015). Trends and Statistics. Retrieved from http://www.drugabuse.gov/related-topics/trends-statistics
Ogai, Y., Senoo, E., Gardner, F. C., Haraguchi, A., Saito, T., Morita, N., & Ikeda, K. (2015, March). Association between Experience of Child Abuse and Severity of Drug Addiction Measured by the Addiction Severity Index among Japanese Drug-Dependent Patients. International Journal of Environmental Research and public health, 12(3), 2781-2792.
Substance Abuse and Mental Health Services Administration. (2014, October 10). Alcohol, Tobacco, and Other Drugs. Retrieved from http://www.samhsa.gov/atod
Tang, J., Liao, Y., He, H., Deng, O., Zhang, G., Qi, C., Cui, H., Jiao, B., Yang, M., Feng, Z., Chen, X., Hao, W., & Liu, T. (2015). Sleeping problems in Chinese illicit drug dependent subjects. BMC Psychiatry, 15(1), 28-35.
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Weiss, R. D., Potter, J. S., Griffin, M. L., McHugh, K. R., Haller, D., Jacobs, P., Gardin, J., Fischer, D., & Rosen, K. D. (2014, August). Reasons for opioid use among patients with dependence on prescription opioids: The role of chronic pain. Journal of Substance Abuse Treatment, 47(2), 140-145.
Weiss, R. D., Potter, J. S., Griffin, M. L., Provost, S. E., Fitzmaurice, G. M., McDermott, K. A., Srisarajivakul, E. N., Dodd, D. R., Dreifuss, J. A., McHugh, K. R., & Carroll, K. M. (2015, May). Long-term outcomes from the National Drug Abuse Treatment Clinical Trials Network Prescription Opioid Addiction Treatment Study. Drug and Alcohol Dependence, 150(1), 113-119.
Xiao, R. S., Hayes, R. B., Waring, M. E., Geller, A. C., Churchill, L. C., Okuyemi, K. S., Adams, M., Huggett, K. N., & Ockene, J. K. (2015). Tobacco counseling experience prior to starting medical school, tobacco treatment self-efficacy and knowledge among first-year medical students in the United States. Preventive Medicine, 73(1), 119-124.