The Influence of Age on the Perception of Decriminalizing Marijuana - Research Paper Example

?Review of Related Literature This literature review tackles published research during the last seven years on the theme decriminalization of marijuana. The studies included provided significant inputs which enhanced this researcher’s knowledge and awareness about the issue of legalizing marijuana and how various groups of people reacted on the issue. Current discussions and debates pertaining to the subject commenced more than three decades ago, when about a dozen US states decriminalized marijuana possession (McCoun, et al., 2009). Since then, the term decriminalization has gained extensive usage largely with respect to regimes on cannabis policy. Cannabis refers to products which may be obtained from the hemp plant, which is scientifically known as cannabis. Marijuana is obtained from cannabis(Jenkins, 2006). Pacula, et al. (2005) defined the term decriminalization almost literally as the “removal in the criminal status of cannabis possession offenses” (P. 348). However, Pacula, et al. (2005) observed that decriminalization remained undefined in the field of international policy. It is also worth mentioning at this point that a number of countries and sub-jurisdictions who were publicized to have decriminalized marijuana actually just reduced the penalties for offenses pertaining to possession of marijuana or cannabis for amounts specified by law (Pacula, 2005). The following studies were reviewed either for their direct or indirect bearing on the topic of this study: McCoun et al. (2009) suggested that the effect of the law on decriminalization of marijuana varies among age groups. In adult populations, the law has a significant effect on marijuana use. Inversely, youth populations appear to be unfazed by regulations and sanctions (as cited in McCoun, et al. 2009). McCoun, et al. (2009) also argued that the impact of legal sanctions differs significantly depending on the age group being studied. Results of their analysis of Australian cannabis consumption show that the youth have a lower tendency to be swayed by legal sanctions. In contrast, adult subjects are largely influenced by government policies.  The authors expressed concern about immediately concluding that the youth are less sensitive to marijuana-related arrests because young people are more impulsive and prone to risky behavior. The McCoun, et al. (2009) study has the most bearing on the current study in the sense that the study tackled decriminalization of marijuana and that the effect of age was studies as a predictor variable. However, the McCoun (2009) work is different from the present study since the effect of age on prohibition was studied, instead of the effect of age on perceptions about decriminalizing marijuana as proposed in this study.         Reyda and Farley (2006) supports the popular notion about young people and marijuana use. The authors cited evidence revealed in their study that vulnerability of adolescents to be influenced to use marijuana is lessened as they grow older. In addition, it is shown that adolescents are prone to miscalculating risks and developing biases in terms of decision making and judgment than when they grow older. Reyda and Farley’s work has indirect bearing on the study, but nonetheless, their findings bolster this researcher’s position that college students as young people would be supportive of decriminalizing marijuana since marijuana use is tagged to younger people.         Meanwhile, Fetherston and Lenton (2005) investigated public perception on the legalization of cannabis by conducting randomized phone surveys on 809 residents of Western Australia. The respondents were asked regarding their views on cannabis legalization, attitudes towards a proposed legislative model, and their opinion of its perceived effects. Initial participant responses show that majority of respondents share a negative view regarding cannabis. However, most participants consider criminal sanctions against cannabis use as inappropriate and ineffective.         The rest of the observations show that 79 percent of the respondents consider the proposed penalty scheme for cannabis use as a good option, regardless of the respondents’ personal experience, political affiliation, religion, or age of children. Despite being seen as a good idea, 7 out of 10 respondents perceive that the new legislation will not be effective in reducing the levels of cannabis use. In addition 59 percent indicated that the new law will not deter people from obtaining cannabis (Fetherston and Lenton 2005). The Fetherston and Lenton (2005) research has a direct bearing on the present study since it also dealt with public perception regarding the legalization of marijuana. However, the research was conducted in Australia, whereas the present study will be conducted in a southeastern US state. Moreover, age was not considered as key variable in the Fetherston and Lenton (2005), which is the opposite for the current study, where age is being considered as a predictor variable.         Wang and Chen (2006) evaluated the effects of cognitive resources and motivation on young and older adults to determine how each group processes variations in the number of persuasive arguments. A two-part experiment was set up wherein younger and older adults were asked to rate their attitudes regarding the legalization of marijuana and capital punishment. After one week, one-half of the group was asked to read either 3 or 9 arguments which support marijuana legalization and capital punishment. This group was assigned as a high involvement group wherein participants were given a chance to discuss the arguments after the survey. Meanwhile, the other half of the respondents are assigned to a low-involvement group.         The second phase involves asking the respondents to rate their attitudes after reading the arguments presented. Results of the study show that young adults belonging to the high-involvement group changed their attitudes regardless of the number of arguments provided to them.  In contrast, young adult respondents from the low-involvement group were shown to be influenced by the number of arguments presented. Argument quantity does not affect older adults from both high and low-involvement groups. Based from these observations it was concluded that working memory as a cognitive mechanism bridges the gap between age and attitude change (Wang and Chen 2006). The finding are important to the present study because the element of cognitive mechanism may be a confounding variable on college students’ attitude regarding marijuana decriminalization. Should the findings of the proposed study support this researcher’s hunch, there will already be a ready recommendation to influence the respondents’ perceptions on legalizing marijuana.         A study performed by Saffer and Chaloupka (as cited in Bates 2004) revealed that the decriminalization of marijuana has increased the likelihood of marijuana use by around 8 percent. However, this is in contrast with the findings of a study conducted by the National Academy of Sciences (as cited in Bates 2004) which shows an insignificant amount of evidence pointing to decriminalization as a factor in the increase of marijuana use. Furthermore, the National Academy of Sciences (as cited in Bates 2004) also concluded that it will cost the State of Alaska more than $24 million per year for enforcement of marijuana prohibition. Considering the high costs and possible increase in crime rates after implementation, marijuana prohibition will more likely lead to failure. This finding supports the legalization of marijuana from an economic point of view which was also considered in the current study.         In Portugal, the decriminalization of cannabis use has been attributed to misconception of the term decriminalization. It was revealed that decriminalization of cannabis was equated to acceptability of illegal drug use which included cannabis. Data from 2001 to 2007 show an increase of lifetime and last year use of cannabis on all age levels above 19 years, which coincided with the decriminalization (as cited in Hughes and Stevens 2010). This study has little but direct bearing on the topic of the current study. The findings point toward the idea that decriminalization is favorable for college students who also use marijuana. In Australia, age is considered as a crucial determinant of marijuana use. In the study conducted by Domrongplasit, Hsiao, and Zhao (2006), the results reveal that young adults in decriminalized states are more likely to become marijuana users. In addition, adults in non-criminalized states are more prone to become marijuana users. It was also observed that the decline of marijuana use as age progresses is attributed to a person’s increased awareness of his or her health and well-being as they grow older. Findings of this study support the thesis of the present study that perception on marijuana legalization are, indeed, influenced by age. Joffe and Yancy (2004) maintained that despite the current focus on adults in terms of legitimizing marijuana use, adolescents will be nonetheless affected by any change on legislation decriminalizing marijuana. The authors hypothesized that marijuana gaining legal status would result to the creation of advertising campaigns which might be directed towards an adolescent audience. In addition, the government might be incapable of regulating marijuana effectively, citing its inability to effectively control alcohol and tobacco use by adolescents in previous years. Moreover, four crucial factors were identified in the prevalence of adolescent marijuana use: perceived risk associated with marijuana, legal sanctions, moral development, and access to marijuana. As the findings suggest, decriminalizing marijuana, or even criminalizing it will affect adolescents, because age is a significant factor. Decriminalization will always be positively perceived by younger people because it is that age where individuals care about personal freedom and carefree behavior. The findings imply support to this researcher’s gut-feel that the proposed study will find an association between age and college students’ perception of the legalization of marijuana. Methodology This section discusses the protocol to be applied in the conduct of the study in sufficient detail that it may be replicated based on the methods and procedures outlined. Specifically, this study will take the pulse of college students in a southeastern state university regarding the decriminalization of marijuana possession and the reasons for their stand on this issue. The hypothesis that there is significant association between age of respondents and their perception on decriminalizing of marijuana will also be tested using non-directional analysis and a 0.05 level of significance. The research methodology describes the research design, sampling design, instrumentation, and the research procedure, which includes the data gathering method and the statistical analysis of the data gathered. 1.0 Research Design This study will adopt the descriptive-quantitative research technique using survey methodology. The descriptive method of research is deemed most appropriate for this scholastic inquiry because the objective of the proposed study is to shed light on current issues, which in this case is, how college students stand on the legalization of marijuana in the state locale (Fox and Bayat, 2007). Moreover, descriptive research methods permit “objective, reliable and scientifically valid descriptions of what people think, say and do” (Mitchell and Jolley, 2010, P. 104). The study will be conducted among college students in a southeastern state university using stratified random sampling design and a researcher-constructed research instrument. Descriptive and inferential measures will be used in data analysis, particularly frequency and percentage distributions, a measure of central tendency (the weighted mean), a measure of dispersion (standard deviation), simple ranking and one-way analysis of variance. Use of quantitative techniques was chosen for the possibility of replication. As explained by Cohen, Manion, and Morrison (2007), replication involves applying the same methods on a similar sample should generate the same results. Additionally, only quantitative methods support hypothesis testing. 2.0. Sampling Design The population identifies for the study is the college student enrollees in a southeastern state university. According to the 2010 figures from the Board of Regents of the state university system, the total college enrollment in the research locale is 5693. A Web-based sample size calculator was used to compute for the minimum required sample, based on the following parameters: (1) margin of error, 5%; (2) confidence level, 95%; (3) population size, 5693; and (4) response distribution, 50. The minimum required sample size generated by the Web-based calculation was 360. A screenshot of the output is presented in Appendix 2. For contingency, this number will be increased by 10% and rounded off to the nearest tens to cover for unretrieved survey questionnaires or invalid / incompletely answered questionnaire. Hence, a total of 400 questionnaires will be floated among the college students in the research locale. Using stratified random sampling design, the 400 questionnaires will be randomly distributed to the intended respondents based on their year level strata. In stratified random sampling, the population is divided into non-overlapping segments of the population or the strata. A random sample is extracted from each population. Black (2010) maintained that the primary advantage of adopting a stratified random sampling design is its potential to reduce sampling error. The stratified sampling distribution of respondents in the study is shown in Table 1. Table 1. Distribution of Respondents in the Study by Year Level Year Level Population (N=5693) Percentage of the Total Population Minimum Required Sample Per Year Level (n=400) Freshman Sophomore Junior Senior 2186 1238 1089 1180 38.40 21.75 19.13 20.72 154 87 76 83 To ensure random sampling per level during the administration of the questionnaire, a list of the names and class schedules of the college students will be obtained from the registrar’s office. The names will be inputted in MS Excel (2003) and the students will be sorted by year level per column. Across each name will be assigned random numbers automatically generated by MS Excel (2003). The random numbers will be arranged from highest to lowest per year level. The top 154 from the freshmen, top 87 from the sophomores, top 76 from the juniors and the top 83 from the seniors will be contacted through their class schedules and invited to participate in the study as voluntary respondents and will be given the schedule when and where the questionnaires will be administered. Those who wish to be reminded an hour before the scheduled administration of the survey will be requested to provide their mobile phones. 3.0. Variables in the Study. Variables involved in this study includes perceptions of the students regarding the decriminalization of marijuana, the reasons which prompted such perceptions, and the profile variables, gender, age, year level ethnicity and course. Perception represented the understanding or awareness on information pertaining to the legalization of marijuana and will be described in terms of level of support by the respondents. It is an ordinal variable based on the study design, and is also the dependent variable in the study. Reasons for such perceptions will be described in terms of the levels of their importance, and hence are also ordinal variable. On the other hand, age is a scale variable and will be the independent variable of this study. Age was grouped as shown in the research instrument (Appendix 1). Level of support and level of importance will be discussed in more detail under Instrumentation. The other profile variables will simply be descriptors of the demographic characteristics of the respondents. Meanwhile, decriminalization of marijuana was discussed at length in the review of literature. 4.0. Instrumentation The researcher-constructed instrument consists of a two-page 13-item questionnaire divided into two sections: (1) the respondent profile, which inquires on five demographic profile of the students respondents – gender, age, college level, ethnicity, and course (degree); (2) perception on the decriminalization of marijuana, one item; and reasons for such perception, which consists of seven items. Responses to the second part of the questionnaire take the form of a 5-point Likert scale where the respondents share their reaction to 8 statements by indicating their level of support (for decriminalization of marijuana) or the level of importance (of the reasons for their perception). Tables 2 and 3 present the interpretation guides with statistical limits which will facilitate analysis of the responses to the second part of the research instrument. Table 2. Interpretation Scale for the Level of Support for the Legalization or Decriminalization of Marijuana Scale Questionnaire Response Statistical Limits Interpretation 5 Strongly Agree 4.50 – 5.00 Exhibits very high support for decriminalization 4 Slightly Agree 3.50 – 4.49 Exhibits moderate support for decriminalization 3 Neither Agree nor Disagree 2.50 – 3.49 Indecisive 2 Slightly Disagree 1.50 – 2.49 Exhibits moderate disapproval for decriminalization 1 Strongly Disagree 1.00 -1.49 Exhibits extreme disapproval for decriminalization Table 2. Interpretation Scale for the Level of Importance of the Reason for Support / Disapproval of Marijuana Decriminalization Scale Questionnaire Response Statistical Limits Interpretation 5 Strongly Agree 4.50 – 5.00 Argument is of extreme importance 4 Slightly Agree 3.50 – 4.49 Argument is of moderate importance 3 Neither Agree nor Disagree 2.50 – 3.49 Argument borders between important or trivial 2 Slightly Disagree 1.50 – 2.49 Argument is importance to a small extent 1 Strongly Disagree 1.00 -1.49 Argument is not importance The instrument will be subject to procedures to verify internal consistency reliability through Cronbach alpha to be computed after pilot-testing the questionnaire to at least 20 college student-respondents in a comparable state university in Southeastern US. The computed Cronbach alpha should be greater than 0.70 to be considered reliable. Face validity of the questionnaire will also be verified with the help of experts from the university. 5.0. Research Procedure The following procedure will be followed in the conduct of the study: 5.1. Permission will be requested from the concerned authorities in two universities in southeastern US for the conduct of a pilot-testing and administration of the survey questionnaires. Request for access to student names and course schedules will be included in the letter for the research local. 5.2. After permissions have been granted, pilot testing will be carried out to 20 respondents by quota sampling. Data will be inputted in a computer and reliability analysis will be performed using SPSS Statistics Version 17 to calculate for Cronbach alpha. At the same, face validity will also be determined from the opinions of two experts. If the reliability analysis and face validity results are positive, the questionnaires are ready for floating. 5.3. Respondents will be contacted and invited to the scheduled administration of the survey questionnaire. Two batches of 80 students will be accommodated in one hour using a room with at least 40 desks. Five one hour sessions will be conducted each day for one week in different time slots to accommodate students with different schedules. Room availability will be coordinated and requested with the facilities department. The 30 minutes for each batch will also cover for the briefing on informed consent and the signing of informed consent forms. The respondents will be provided with their own copy of the signed consent forms. 5.4. After retrieval of the answered questionnaires, responses will be encoded and processed in MS Excel (2003) using a coding guide for the preparation of a data matrix. The data matrix will be copy pasted in SPSS Statistics (2008) for data analysis. The coding guide is shown as Appendix 3. 5.5. The profile variables will be presented as frequency and percentage distributions in the form of a pie chart. Perceptions pertaining to the legalization of marijuana and the reasons for such perception will be shown as tabulation with mean and standard deviations. The results of items 7 to 13 will be ranked and exhibited with the most important to the least important reasons. 5.6. The association between the variable perceptions pertaining to decriminalization of marijuana which was answered in Item 6 of the research instrument, and is the dependent variable and the variable age of respondents, which is the independent or the predictor variable in the study will be verified using one way analysis of variance (ANOVA) will evaluate whether the perceptions in one or more of the 5 age groups will differ significantly. The null hypothesis that there is no significant association between age and student perceptions pertaining to the decriminalization of marijuana will be tested using a non-directional or two-tailed analysis and a 0.05 level of significance (? = 0.05). If the computed significance level (Sig. in SPSS or p-value) is greater than 0.5, the null hypothesis is accepted. Otherwise, if the computed significance level is 0.5 or less, the null hypothesis will be rejected. There is a significant difference in the perceptions when the respondents are grouped by age and that age influences college students’ perception on the decriminalization of marijuana. A post hoc analysis using either least significant difference (LSD) when variance is homogeneous, or Tamhane’s T2, when there is no homogeneity of variance, will be used depending on the results of the Levene’s test which is done automatically in ANOVA with SPSS. .  References Bates, Scott W. 2004. The Economic Implications of Marijuana Legalization in Alaska. Anchorage, AK: Boreal Economic Analysis and Research. Black, Ken. 2010. Business statistics for contemporary decision making. 6th ed. Hoboken, NJ: John Wiley & Sons. Board of Regents of the University System of Georgia. 2010. “Ten-Year Enrollment Reports: 2000-2010.” Office of Research and Policy Analysis. Retrieved April 12, 2011 (http://www.usg.edu/research/students/enroll/ 10yr/rpt00-09.pdf). Cameron, Lisa and Jenny Williams. 2001. “Cannabis, Alcohol, and Cigarettes: Substitutes or Complements?” The Economic Record. 77(236): 19-34. Cohen, Louis, Lawrence Manion, and Keith Morrison. 2007. Research methods in education. 6th ed. Oxon, GBR: Routledge. Fetherston, James and Simon Lenton. 2005. “Community Attitudes towards Cannabis Law and the Proposed Cannabis Infringement Notice Scheme in Western Australia”. Drug and Alcohol Review. 24(4): 301-309. Fox, William and Mohamed Saheed Bayat. 2007. A guide to managing research. Cape Town, ZAF: Juta. Hughes, Caitlin E. and Alex Stevens. 2010. “What Can We Learn from the Portuguese Decriminalization of Illicit Drugs?” British Journal of Criminology. 50: 999-1022. Jenkins, Richard. 2006. Cannabis and young people: reviewing the evidence. London, GBR: Jessica Kingsley Publishers. Joffe, Alain and Samuel Yancy. 2004. “Legalization of Marijuana: Potential Impact on Youth”, Pediatrics. 113(6): e632-e638. McCoun, Robert, et al. 2009. Do Citizens Accurately Perceive Marijuana Sanction Risks? A Test of a Critical Assumption in Deterrence Theory and Decriminalization Debate. Berkeley, CA: Center for the Study of Law and Society Jurisprudence and Social Policy Program, UC Berkeley. Mitchell, Mark L. and Janina M. Jolley. 2010. Research design explained. 7th ed. Belmont, CA: Wadsworth / Cengage Learning. Office of Admission. 2011. “Degree Programs.” Augusta State University. Retrieved April 12, 2011 (http://www.aug.edu/admissions/degrees.htm). Pacula, R. L., et al. 2005. “What does it mean to decriminalize marijuana? A cross-sectional empirical examination.” Pp. 347-370 in Substance Use: Individual Behavior, Social Interactions, Markets and Politics, edited by Bjorn Lindgren and Michael Gross. San Diego, CA: Elsevier Reyda, Valerie F. and Frank Farley. 2006. “Risk and Rationality in Adolescent Decision Making.” Psychological Science in the Public Interest. 7(1):1-44. Wang, Mo and Yiwei Chen. 2006. “Age Differences in Attitude Change: Influences of Cognitive Resources and Motivation on Responses to Argument Quantity.” Psychology and Aging. 21(3): 581-589. Appendix 1 RESEARCH INSTRUMENT Instruction: Kindly provide the demographic information being requested by choosing the appropriate response and checking the category or writing the data on the space provided for. Please rest assured that your anonymity will be protected and the confidentiality of the data you supplied will be safeguarded. Demographic Variable Demographic Variable Categories 1. Gender Female ? Male ? - - - 2. Age: _____ years old 19 & below ? 20 – 22 ? 23 – 25 ? 26 - 28 ? 29 & older ? 3. College Level Freshman ? Sophomore ? Junior ? Senior ? - 4. Ethnicity American ? African-American ? European/ British ? Asian ? Other: ? Please specify: ________ 5. Course Business Administration ? Education ? Nursing / Allied Health? Computer Science / IT ? Other: ? Please specify: ________ Instruction: Please provide your opinions regarding the following statements using the five-point Likert scale shown below. 5 4 3 2 1 Strongly Agree Slightly Agree Neither Agree nor Disagree Slightly Disagree Strongly Disagree STRONGLY AGREE SLIGHTLY AGREE NEITHER AGREE NOR DISAGREE SLIGHTLY DISAGREE SRONGLY DISAGREE 5 4 3 2 1 6. I support the legalization of marijuana. ? ? ? ? ? 7. Marijuana is harmless as long as it is used in moderation. ? ? ? ? ? 8. Most college students consider smoking marijuana as a right of passage. ? ? ? ? ? 9. Marijuana has positive health effects which benefit people. ? ? ? ? ? 10. State laws against marijuana violate the first, fourth, sixth, eighth, ninth and tenth amendments. ? ? ? ? ? 11. Marijuana prohibition costs billions of taxpayer’s money on enforcement, which is a costly failure. ? ? ? ? ? 12. Prohibiting marijuana is just like prohibiting smoking, alcohol and soda. ? ? ? ? ? 13. There are many industrial applications of hemp, which is a non-psychoactive sister of marijuana. ? ? ? ? ? Appendix 2. SCREENSHOT OF OUTPUT FROM WEB-BASED SAMPLE SIZE CALCULATION Appendix 1 CODING GUIDE Demographic Variable Codes for Demographic Variable Categories 1 2 3 4 5 1. Gender Female Male - - - 2. Age: _____ years old 19 & below 20 – 22 23 – 25 26 - 28 29 & older 3. College Level Freshman Sophomore Junior Senior - 4. Ethnicity American African-American European/ British Asian Other: Please specify: ________ 5. Course Business Administration Education Nursing / Allied Health Computer Science / IT Other: Please specify: ________ Use the number codes as marked in the responses. 5 4 3 2 1 Strongly Agree Slightly Agree Neither Agree nor Disagree Slightly Disagree Strongly Disagree Read More