Drug Use and Mental Health Problems Among Adolescents Essay (Critical Writing)

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Updated: Mar 30th, 2024

To identify which substance among alcohol, cannabis and nicotine has a higher likelihood of causing mental disorders in early adolescence, Boys et al (2003) interviewed 2,645 children aged13-15 years. The sample was taken from data collected from the Office for National Statistics (ONS) in a 1999 mental health survey conducted in England, Scotland and Wales involving children aged 5-15 years. Whereas the stratified sampling ensured that the adolescents were interviewed, the group of children belonging to early adolescence (11-12 years) was biased against. This questions the validity of the findings since possible cases of early adolescents were excluded. It is however notable that the sample did not bias against any sex since each sex represented 50% of the sample.

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Farrell et al (2003) examined the comorbidity of psychiatric disorders and drug and substance dependence in a national household survey conducted in England and Wales. Simple stratified random sampling was conducted by selecting one adult (16-64 years) from each identified household. Interviews were conducted on 10,018 adults to assess psychiatric morbidity using Clinical Interview Schedule-Revised (CIS-R). Dependence on nicotine and alcohol was also assessed using questions from the Office of National Statistics. Despite the fact that gender was related to psychological morbidity and drug dependence, the authors of the study failed to consider gender proportions in sampling. The stratified sampling technique however ensured that almost all subgroups (according to age) were captured and the sample size was large, making the results more valid and can be generalized. Since the study revealed that persons aged 16-24 years were mostly alcohol dependents, the study would have reduced bias by considering persons as young as 12 years.

To investigate the relationship between alcohol dependence and major depression, Fergusson, Boden and Horwood (2009) gathered data from 1265 children (635 boys and 630 girls). The birth cohort was selected from persons involved in the Christchurch Health and Development Study and assessments were done at birth, 4 months, 1 year, each year up to age 16 and then at 18, 21, and 25 years. In this study, causal links between alcohol abuse and dependence (ADD) and major depression (MD) were assessed in 1,055 participants at the age of 17-18, 20-21 and 24-25 years. Longitudinal data from this study was prone to confounding and the likelihood of failing to identify the causal directionality for ADD and MD was possible. However, the authors of this study were able to control for confounding to a great extent using fixed-effects regression model. The causal link and directionality is however still prone to confounding due to changes occurring over time of the study thus MD cannot be ruled out as a possible cause of ADD.

The effect of cannabis use on mental health of adolescents was assessed by Rey et al (2002) by interviewing parents and gathering data from adolescents using questionnaires. Data was collected from 1,490 young persons aged between 13 and 17 years who were part of the 1998 National Survey of Mental Health and Well Being in Australia. Households with persons aged below 18 years were identified using a multi-stage probability sampling criteria thus obtaining a representative sample of 4,509. From the 450 Census Collector’s Districts in Australia, clusters of 10 households were selected thus obtaining the sample used in the study. Due to under-sampling of participants aged 16-17 years, it is not valid to conclude that use of cannabis intensified with increase in age. The results are however highly reliable and with minimal bias since the sampled Census Collectors Districts were proportionately distributed thus capturing the target population. Difference in age between the sample and the data from Australian Census carried two years earlier may however have affected the accuracy of the findings.

The occurrence of psychiatric disorders during young adult stage has been linked with psychiatric disorders that occurred during childhood and adolescence. Copeland et al (2009) examines this relationship by studying children aged 9-16 years, 19, and 21 years in western North Carolina. The sample (n=1420) was obtained from a longitudinal study (Great Smoky Mountains Study) that assesses development of psychiatric disorders in youths. By selecting 3 cohorts (9, 11 and 13 years) using stratified sampling method ensured representation of all sub-groups. An initial screening done to parents to assess externalization in children increased the accuracy of the collected data. Moreover, random sampling removed bias despite the fact that confounding is possible due to data being collected during different time periods.

Gibb, Fergusson and Horwood (2010) examine the effect of psychiatric disorders later in young adulthood. By interviewing 950 participants taken from Christchurch Health and Development Study (a longitudinal study) that involves following a birth cohort up to the age of 30 years, the authors of this study identified economic and health burdens to arise at later age. The outcomes were assessed in relation to psychiatric disorders at the age of 18-25 years. The findings are dependable and can be generalized since confounding factors were controlled and the relationship between the extent of psychiatric disorders and the outcomes for living standards and income remained significant (P<0.05).

Assessing and treating mental disorders among adolescents is pertinent since these disorders are disastrous if left unaddressed. Williams et al (2009) look into the benefits of screening for major depression during normal primary care for children aged 7-18 years. Review of past studies was done by carrying out literature searches in Medline, PsycInfo, and the Cochrane Central registry of Controlled Trials among other credible databases and registries. The reviewed studies are credible since they involved controlled trials diagnostic accuracy studies as well as large observational studies. By using relevant key words such as primary care, depression and adolescents, the authors of the study ensured that they retrieved reliable literature. The conclusions can be generalized since they involved meta-analyses as well as systematically reviewed literature. It is however possible to miss some important studies due to limited search criteria and key words.

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Goodman et al (2000) identified that Strengths and Difficulties Questionnaire (SDQ) is effective in screening for psychiatric disorders. This was based on a study of 7,984 participants aged 11-15 years as retrieved from the 1999 British Child Mental Health Survey. By restricting the study to children aged 11-15 years, the findings of this study become less representative of a large children/adolescent population. This is in fact contrary to the aim of the study which is to study the strength of using SDQ in screening children for psychiatric disorders. This therefore reduces the validity of the conclusion that SDQ are effective in screening psychiatric disorders in children. The sample size is however large enough to strengthen the validity of the findings.

Brent et al (2008) have proposed the use of selective serotonin reuptake inhibitors (SSRI) in combination with cognitive behavioural therapy since it is a promising intervention. By conducting literature searches for studies published between 1990-January 2007 for topics such as antidepressants, psychotherapy and major depressive disorder, Brent et al (2008) were able to obtain highly accurate information. Other than book reviews, reviews were done by searching Medline, PsycINFO and psychological abstracts. By limiting the search to 1990-2007, the review is prone to missing important studies carried out earlier on the topic. However, use of recent literature increased validity of the findings.

Zuckerbrot et al (2007) conducted a 2-stage adolescent depression-identification screen among adolescents aged 13-17 years to identify the possibility of implementing adolescent depression screening in primary care. The study also involved clinicians, nurse practitioners and physicians. Since the outcomes of the study were mainly based on the competence level of the health care provider, it is not likely to see the real feasibility of depression screening in primary care. This is however controlled by training all the involved caregivers on how to assess adolescent depression. Repeat visits also introduce the possibility of confounding thus reducing validity of the findings.

Conclusion

Literature indicates a clear association between drug and substance abuse among adolescents and mental health problems. Problems of validity of findings from the above research are possible due to bias and confounding. However, most studies have controlled for these by using sufficient sample sizes and representative populations. Literature also reflects inadequate focus on screening adolescent depression thus treatment efforts are curtailed. It is important for further research to be done in order to identify whether psychiatric disorders result in drug and substance dependence or whether drug dependence lead to psychiatric disorders.

References

Boys, A. Farrell, M., Taylor, C. and Marsden, J. (2003). Psychiatric morbidity and substance use in young people aged 13–15 years: results from the Child and Adolescent Survey of Mental Health. The British Journal of Psychiatry, 182: 509-517.

Brent, D., Emslie, G., Clarke, G., Wagner, K. D. and Asarnow, J. R. et al. (2008). Switching to another SSRI or to venlafaxine with or without cognitive behavioural therapy for adolescents with SSRI-resistant depression. JAMA, 299(8):901-913.

Copeland, W. E., Shanahan, L., Costello, E. J., and Angold, A. (2009). Childhood and adolescent psychiatric disorders as predictors of young adult disorders. Arch Gen Psychiatry, 66(7):764-772.

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Farrel, M., Howes, S., Bebbington, P., Brugha, T. and Jenkins, R. et al. (2001). Nicotine, alcohol and drug dependence and psychiatric comorbidity. The British Journal of Psychiatry, 179: 432-437

Fergusson, D. M., Boden, J. M. and Horwood, L. J. (2009). Tests of causal links between alcohol abuse or dependence and major depression. Arch Gen Psychiatry, 66(3):260-266.

Gibb, S. J., Fergusson, D. M. and Horwood, L. J. (2010). Burden of psychiatric disorder in young adulthood and life outcomes at age 30. The British Journal of Psychiatry, 197: 122-127.

Goodman, R., Ford, T., Simmons, H., Gatward, R. and Meltzer, H. et al (2000). Using the Strengths and Difficulties Questionnaire (SDQ) to screen for child psychiatric disorders in a community sample. The British Journal of Psychiatry, 177: 534-539.

Rey, J. M., Sawyer, M. G., Raphael, B., Patton, G. C. and Lynskey, M. (2002). Mental health of teenagers who use cannabis. The British Journal of Psychiatry, 180: 216-221.

Williams, S. B., O’Connor, E. A., Eder, M. and Whitlock, E. P. (2009). Screening for child and adolescent depression in primary care settings: a systematic evidence review for the US preventive services task force. PEDIATRICS, 123(4): e716-e735.

Zuckerbrot, R. A., Maxon, L., Pagar, D., Davies, M. and Fisher, P. W. et al. (2007). Adolescent depression screening in primary care: feasibility and acceptability. PEDIATRICS, 119(1): 101-108.

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