Risk Factors of Marijuana, Research Paper Example

Marijuana is the most widely used illicit drug among U.S. adolescents, with 14.2% of tenth-graders reporting a past 30-day use in 2008. Adolescent marijuana use has been linked to adverse outcomes including elevated depression, conduct problems, and low educational achievement, as well as well as increased risks for dependence compared to those who initiated usage later in life (Farhat, Siomons-Morton, & Luk, 2011). Previously published studiesindicate that marijuana use is associated with a multitude of risk factors, including psychological,family, peer, and school variables. Most risk factor studies have focused on a single aspect of the development of marijuana involvement, usually lifetime use or initiation of experimentation. However, it is poorly understood to what extent well-established risk factors are associated with different stages of marijuana involvement (Van Den Bree & Pickworth, 2005). Evaluateing a wide range of relevant risk factors to provide well-funded evidence for their relative importance in predicting development of marijuana usage may enable predictions in the development of marijuana involvement based on a variety of risk factors.

Cross-cultural comparisons of risk factors for drug use enable researchers to understand how current knowledge of drug use can be generalized across cultures and over time. Such findings can help clarify the nature of the interventions needed to reduce or prevent the development of drug use in different cultures and during different stages of development.In the area of delinquency and drug use, there have been several studies comparing the risk factors using a prospective, longitudinal design in different countries. Recent research indicates that high rates of drug abuse or dependence is associated with antisocial personality disorder, depression, and certain family variables such as punitive discipline tactics and authoritarian or permissive parenting styles.In addition to family variables, peer deviance was also important in predicting adolescent marijuana use; with one of the most robust predictors of subsequent marijuana use being the  adolescent’s own use of legal drugs (tobacco and alcohol) (Brook, Brook, Arencibia-Mireles, Richter,&Whiteman, 2001). Health outcomes of marijuana use in adolescents can be associated with respiratory issues, increased heart rate, disruptions in normal brain functioning, and dependency.  Although the effects of marijuana on the brain of adolescents require further investigation, recent studies indicate a strong correlation between marijuana use and dependency on other drugs (NIDA, 2012). Further research using a mixed sample, cross-cultural population may be able to help clarify how genetic variables play a role in various risk factors in relation to environmental risk factors.

At least 1.5 million people worldwide are suffering from multidrug-resistant tuberculosis.  Failure to treat and manage MDR-TB effectively condemns patients to almost certain death, fuels transmission of drug-resistant TB to others, and contributes to the emergence of even more resistant and deadly strains (Partners in Health, nd). Several psychosocial factors may also challenge the ability ofpatients to adhere to treatment. Previous treatment failures leave many patients susceptible to depressive disorders. Due to the complex difficulties faced by patients, the development of successful strategies tosupport patients is essential to ensure treatment adherence and, consequently, to effectively control the MDR-TB epidemic (Acha, Sweetland, Guerra, Chalco, Castillo, & Palacios, 2010).

The impact of the psychosocial support groups can be assessed in relation to treatment outcomes and depressive symptoms using four interests groups. These groups consist of ten patients suffering from TB with depression who took part in psychosocial support groups, ten patients with no depressive symptoms who receive psychosocial support, ten patients with depression who did not receive psychosocial support, and ten patients with no depressive symptoms who did not receive psychosocial support. General summaries will be recorded after each session and will consist of patient attitudes, with response levels to medical interventions being included.Data will be analyzed to compare life quality of TB patients suffering from depression verses those with no depressive symptoms. Those who received psychosocial support will be compared to those with and without depressive symptoms who did not receive any psychosocial support. Common themes will be analyzed comparing the data available from group summaries, field notes from the participant observer, and patient medical records (Acha, Sweetland, Guerra, Chalco, Castillo, & Palacios, 2010).

Treatment adherence is central to the control of the TB epidemic. In order to achieve a cure, as well aslimit the spread of disease and prevent the development of further drug resistance, multiple aspects of intervention and support is needed to improve patient life-quality. The constellation of difficulties faced by patients requires innovation on the part of care providers in order to find ways to support patients in overcoming these challenges. Numerous studies examining the factors thatcontribute to non-adherence among patients with drug-resistant TB implicateside effects and psychosocial factors. Treatment adherence is central to the control of the TB epidemic, to achieve cure,limit the spread of disease, and prevent the development of further drugresistance. As both side effects andpsychosocial difficulties are significantly more complex for patients with drug-resistant TB, it is clear that more research is needed to examinethe impact of these factorsand to explore innovative strategies intended to help patients adhere to difficult medication regimens(Acha, Sweetland, Guerra, Chalco, Castillo, & Palacios, 2010).

References

Acha, J., Sweetland, A., Guerra, D., Chalco, K., Castillo, H., & Palacios, E. (2010). Psychosocial support groups for patients with multidrug-resistanttuberculosis: Five years of experience. Global Public Health, 2: 4, 404 — 417

Brook, J. S., Brook, D. W., Arencibia-Mireles, O., Richter, L., & Whiteman, M. (2001). Risk factors for adolescent marijuana use across cultures and across time. The Journal of Genetic Psychology, 162(3), 357-74.

Farhat, T., Simons-Morton, & Luk, J.W. (2011). Psychosocial correlates of adolescent marijuana use: Variations by status of marijuana use. Addictive Behaviors, 36, 404-407

NIDA. (2012). Marijuana. The Science Behind Drug Abuse. Retrieved December 15, 2012 from http://teens.drugabuse.gov/facts/facts_mj1.php

Partners in Heatlh. (nd). Time to step up the fight against MDR- and XDR-TB. Retrieved December 15, 2012 from http://model.pih.org/files/MDR-TB%20brochure%20rev2%20spreads.pdf

Van Den Bree, M.B.M., Ph.D., & Pickworth, W.B., Ph.D. (2005). Risk Factors Predicting Changes in Marijuana Involvement in Teenagers.Arch Gen Psychiatry. 2005;62(3):311-319.