The History And Background Of Drug Addiction

How do risk factors such as genetics and environment contribute to adolescents’ susceptibility to substance use and abuse? One study suggests that genetics and environment may actually affect adolescents’ susceptibility to substance abuse in different ways. Silberg, Rutter, D’Onofrio, & Eaves (2003), researchers and authors of Genetic and environmental risk factors in adolescent substance use, conducted a follow-up on the Virginia Twin Study of Adolescent Behavioral Development (VTSABD), “a multi-wave, multi-informant, prospective follow-up study of genetic and environmental influences on the development of psychopathology in children and adolescents” (p. 671). The Researchers analyzed 1439 families with twins ranging from ages 8-16. A direct comorbidity between conduct disturbances and depression amongst both adolescent girls and boys was discovered. Researchers found that conduct disturbances and depression were somewhat mediocrely associated with substance use, yet the correspondence of genetic and environmental risks was different for males and females across the two disorders. The study also revealed genetic factors to be more predominant in girls’ susceptibility to substance use, whereas boys’ use was interceded mainly by shared environmental factors mirroring family dysfunction and deviant peers. The patterns of correlations across the two waves of the study were correlated with conduct disturbance resulting in substance use in both males and females, but depression leading to smoking, drug use and, to a lesser extent, alcohol use in girls. Over more, the study consisted of two main limitations. For one, researchers suggested that it is plausible that there has been a greater selective attrition of dizygotic than mono-zygotic pairs in connection to the total population of twins at birth. Compared with the North Carolina twin sample, which is built upon birth records, the study’s selective attrition is predominately equivalent to findings in other conventional population twin samples. Silberg et al. (2003) argued the following:

Although the attrition could have had a minor effect on estimates of the overall genetic and environmental effects, it is implausible that it could account for the pattern of differences with respect to the two sexes or the phenotypes of depression and contact disturbance. (p. 673).

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Another important limitation was that the findings were more characteristic of early experimental use rather than crucial continuous dependence or abuse in late adolescence or early adulthood; researchers mentioned that it’s important to further analyze this phase. However, it remains an open question whether or not the conclusions will yield the same results in older age periods with more serious substance abuse problems; researchers mentioned that future directions for experimentation includes a follow-up into adult life (Silberg et al., 2003).

How do developmental changes with adolescents correlate with the susceptibility to addiction and alcohol use? In a current study, Cleveland, Feinberg, & Jones, (2012), authors and researchers of Predicting Alcohol Use Across Adolescence: Relative Strength of Individual, Family, Peer, and Contextual Risk and Protective Factors, examined the developmental changes of adolescent in regards to the relative influence of risk and protective factors (RPFs). For example, factors such as individuality, family, peer, school, and community domains were assessed in regards to adolescent alcohol use. Cleveland et al. (2012) utilized and compared the PROSPER sample (Promoting School-University-Community Partnerships to Enhance Resilience) with the ASAPS sample (The Adolescent Substance Abuse Prevention Study). The researchers utilized the Social Development Model (SDM) to analyze associations among RPFs and subsequent-year alcohol use across early- to late-adolescence in two independent samples. Relying on the date collected from 19,200 students in 83 public school districts in the ASAPS sample, the researchers conducted seven survey waves over a 5-year period. Cleveland et al. (2012) assembled risk and protective factor (RPFs) scales into six specific areas. Each of the samples included information that was collected yearly across five years, yet two of the samples differentiated in terms of beginning and ending grades. Building upon previous research with the SDM, Cleveland et al. (2012) tested the following hypothesis:

Hypothesis 1.The influence of the individual domain on adolescent alcohol use will increase linearly from early-to late-adolescence.

Hypothesis 2.The influence of the family and community domains on adolescent alcohol use will decrease linearly from early- to late-adolescence.

Hypothesis 3.The influence of the peer and school domains will increase linearly across early- to late-adolescence. (p. 705).

Researchers discovered that RPFs and alcohol use were equivocal amongst all parallel measures. Alcohol use was found to be similar amongst the PROSPER and ASAPS samples. For example, in the PROSPER sample, 11% of sixth grade admitted to using alcohol in the previous month, yet that number rose to 40% when students reached the tenth grade. In the ASAPS sample, 15% of students in the seventh grade reported using alcohol in the past month, yet that number rose to 45% when students reached the eleventh grade. In both samples, the level of alcohol use amongst adolescents had increased drastically and with greater stability as adolescents advanced in grade levels. In regards to individuality risks, it was confirmed that adolescents’ tendency for alcohol use corroborates with early and late adolescence. Findings also indicate that risky behavior decreased amongst adolescents with adequate family involvement and negative associations with risky behavior. Yet, the findings suggested an overestimation of peer influence on alcohol use amongst adolescents. Nonetheless, there were a few limitations to the study. For one, there were persistent developmental dissimilarities in regards to the influence of individuality, peer influence, and familial protection. In addition, the PROSPER and ASAPS samples comprised of differences in gender and ethnicity, which could have possibly led to the inability to account for differences amongst the two samples. Future directions for research may include examination of other dimensions of alcohol use in consolidation with other critical factors, which may yield more accurate clarification of adolescent alcohol use (Cleveland et al., 2012).

ZimiA‡ and JukiA‡ (2012), researchers and authors of Familial Risk Factors Favoring Drug Addiction Onset, conducted a study between 2008 and 2009 on 146 addicts and 134 control subjects in order to determine whether familial risk factors favored drug addiction onset. In addition, the goal of the study was to examine the find differences between families dealing with addiction and families dealing with similar issues. According to ZimiA‡ and JukiA‡ (2012), “The addict group was comprised of a total of 146 drug addicts; there were 92 men, 51 women and three individuals who neglected to state their gender who were aged 18 to 46?(p. 177). The control group on the other hand, “was comprised of a total of 134 individuals; there were 88 men, 45 women and one individual who neglected to state his/her gender who were aged 17 to 44?( ZimiA‡ & JukiA‡, 2012, p. 177). ZimiA‡ and JukiA‡ (2012) gave both groups a 67-variabale questionnaire, which focused on the following three essential features for the study:

aˆ? Developmental features: separation from the parents early in life (i.e. prior to the age of seven), parental divorce or death of one of the parents during the subject’s childhood and adolescence, self-perception of one parent as more attentive and more caring, psychological trauma and stressful events in childhood and adolescence, lack of parental surveillance and support;

aˆ? Interaction features: emotional relations with the parents established in childhood and existent at the present moment, relations with the siblings, interparental relations, distribution of power within the family, communication with the parents, and support given by the family;

aˆ? Sociological features: family migrations taking place in the subject’s childhood and adolescence, familial sociopathology such as harassment and domestic violence, alcohol abusing and mentally challenged parents, religious beliefs and attitudes, criminal offences committed by family members, etc. (p. 177).

ZimiA‡ and JukiA‡ (2012) mentioned that statistically, the results failed to show a considerable socio-demographic difference in regards to addicts’ and controls’ groups immediate families. And even though the groups differed socio-demographically, researchers mentioned that familial sociological features exhibited the most profound distinction amongst the controls and addicts. In addition, researchers discovered that 39% of addicts had a greater tendency to have alcohol abuse and mental disorders due to parental divorce or death of a parent, whereas 21% of such cases occurred in the control group (p. 182). Researchers mentioned that there were some limitations to the study. For one, educational backgrounds seen across the control group tended to be higher than that of the addicts. In addition, there was a significant difference in religious upbringing across the two groups. It was said that further implications for research may consist of more extensive research into familial affiliations of addicts as well as a more therapeutic approach for addicts and their families as a whole (ZimiA‡ & JukiA‡, 2012).

How do psychological factors impact an adolescent’s susceptibility to addiction and substance use? Malmberg et al. (2010), authors and researchers of Substance use risk profiles and associations with early substance use in adolescence, conducted a study on 3783 adolescent (aged 11-15) to determine whether psychological factors such as sensation seeking, desperation, anxiety, impressionability, and hopelessness would yield drug and polysubstance use in early adolescence. The data that the researchers collected was part of a larger national school prevention program. The researchers began their study by visiting participating schools to collect data from children whom parents agreed to let them participate in the study. Participants were asked questions regarding their personality traits along with alcohol, cannabis, and tobacco use. In regards to Reports indicated that

Malmberg et al. (2010) stated the following in regards to their hypothesis of the study;

we hypothesize sensation seekers to have an increased risk for an early initiation of alcohol, tobacco, and cannabis use. Hence, we expected to find that anxiety sensitive adolescents have an increased risk for an early onset of alcohol use, adolescents reporting higher levels of hopelessness to have an increased risk for an early onset of alcohol and tobacco use, and impulsive adolescents to have an increased risk for an early onset of alcohol and cannabis use.

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