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The Effectiveness Of Enhanced Overservice Law Enforcement Programs In Preventing Excessive Drinking Research Proposal Essay

¶ … Enhanced Overservice Law-Enforcement Programs in Preventing Excessive Drinking The Effectiveness of Enhanced Overservice Law-Enforcement Programs in Preventing Excessive Drinking: Research Proposal

Excessive drinking has, in recent years, grown to become one of the leading social concerns for policymakers in the United States. It is estimated that the American economy loses over $200 billion dollars every year in harms related to excessive consumption of alcohol. This text presents a proposal for a research study seeking to assess the effectiveness of overservice law-enforcement programs in preventing excessive drinking.

The Effectiveness of Enhanced Overservice Law-Enforcement Programs in Preventing Excessive Drinking

Introduction

Excessive consumption of alcohol is increasingly becoming a serious concern for policymakers and administrators in the U.S. The National Institute of Alcohol Abuse and Alcoholism (NIH) defines excessive drinking as the consumption of more than two drinks per day in the case of men, and one drink per day for women. Currently, excessive drinking stands as the third-leading cause of preventable death in the country, accounting for approximately 88,000 deaths annually (NIAAA, 2015). It is estimated that approximately 24.6% of the adult American population engages in excessive alcohol consumption every month (NIAAA, 2015). These high rates are manifested in an increased number of alcohol-impaired driving fatalities, alcohol-related health conditions and familial abuse. In 2013 alone, 10,076 driving fatalities were related to alcohol consumption and 5.1% of the burden of injury and disease was attributable to excessive drinking (NIAAA, 2015). The overall cost to the economy resulting from these figures is massive -- in 2006, for instance, the American economy lost $223.5 billion as a direct result of alcohol misuse problems (NIAAA, 2015). This comes even as the government continues to put in place stringent regulations and policies to curb excessive drinking in on-premises alcohol retail outlets. One of the most prominent initiatives that have been implemented so far is the overservice law-enforcement program. The program works by prohibiting the service of drinks to intoxicated persons in on-premises outlets. This text is geared at determining how effective the overservice law-enforcement program is in preventing excessive alcohol consumption.

The research question guiding the study is:

"Are there any observable differences in the overall rates of excessive alcohol consumption before and after the implementation of overservice programs?"

The corresponding null and alternative hypotheses are:

H0: µ1= µ2= µ3

There are no significant differences in the rates of excessive alcohol consumption before and after implementation of overservice programs

HA: µ1 ? µ2? µ3

There are significant differences in the rates of excessive alcohol consumption before and after the implementation of overservice programs

The repeated measures ANOVA test will be used to test the hypotheses. This test is appropriate for the proposed study because there are three groups to be measured. The repeated measures ANOVA is appropriate when there are three or more related groups being measured on the same dependent variable. The three groups in our case are i) the excessive drinking rates (as manifested in the number of alcohol-related harms) in the town 'before' the implementation of the overservice program (t1), the rates 1 month after implementation (t2), and the rates three months after implementation (t3).

Methods

The study will be conducted in the town of Mason in the State of Ohio, the researcher's hometown. Ohio is one of the states that have fully implemented the overservice law-enforcement initiative; however, most retail outlets are yet to begin implementing the same in their...

20 popular drinking outlets will be selected to participate in the study. The twenty will be selected through random sampling, which basically means that all the 29 eligible outlets stand equal chances of getting selected to participate. Random sampling will be used to increase objectivity and minimize the risk of bias. The average rates of reported harms directly related to excessive drinking in the town as reported by the NIAAA over the last three months will be calculated and recorded prior to the commencement of the program. Consent letters will then be sent out to the owners of all the 29 outlets requesting them to take part in the study (consent and authorization to conduct the study will already have been sought from the relevant authorities in the town). The letters will among other things provide orientation to outlet owners on the importance of the study and the benefits that could accrue from their participation in the same. Owing to time and cost constraints, only the first 20 owners to respond will be allowed take part in the study. The data collection team will then (in the presence) of the outlet owner, train staff in the 20 outlets on how to carry out the overservice program, which will basically entail looking out for bloodshot eyes, flushed face, slurred speech and balance and coordination in customers and then denying them additional drinks. The program will run for a period of three months, and the rates of reported harms related to excessive drinking 1 month after the implementation of the program and upon its completion will be obtained and recorded.
Procedures

It is evident, from the research question that excessive consumption of alcohol is our dependent variable whereas enhanced overservice programs is the independent variable. We will define excessive consumption of alcohol in terms of the number of alcohol-related harms reported in the town over a specified period. This will involve identifying the total numbers of i) alcohol-use disorders, ii) alcohol-related deaths, iii) alcohol-related driving fatalities, and iv) assaults committed by drunk persons in the town as reported by the NIAAA. For the t1 level (before the commencement of the overservice program), we will sum up the reported number in each of these cases in the three months immediately preceding the conduction of the study, and then divide the total by three to obtain the average, which will then be recorded as the t1 value. This would make this a continuous, ratio variable as a score of zero in any period would essentially mean that no alcohol-related harms were reported in that period. The independent variable, on the other hand, would be measured as a categorical, ordinal variable -- it would be composed of three categories: t1 (before the implementation of the overservice program), t2 (1 month after the implementation of the overservice program) and t3 (three months after the implementation of the program). This is an ordinal variable because in as much as the categories have no quantitative significance, they are arranged in a pre-determined order that has to be obeyed in order for the scale to make sense (Sukal, 2013). Table 1 below presents the template that will be used for the recordings.

Table 1

DV / IV

T1 (average of the numbers reported in the three months immediately preceding overservice implementation)

T2

T3

Number of alcohol-use disorders

Number of alcohol-related deaths

Number of alcohol-related driving fatalities

Number of assaults perpetrated by drunk persons

Results

As I mentioned earlier on in this text, the repeated measures ANOVA will be used to test the null hypothesis presented in the preceding section. The number of alcohol-related harms before the program will be recorded and compared to the number reported after 1 month of implementation and in the third and final month of implementation. A significance level of .05 (p

Sources used in this document:
References

NIAAA. (2015). Alcohol Facts and Statistics. The National Institute of Alcohol Abuse and Alcoholism (NIAAA). Accessed October 16, 2015 http://www.niaaa.nih.gov/alcohol-health/overview-alcohol-consumption/alcohol-facts-and-statistics

Sukal, M. (2013). Research Methods: Applying Statistics in Research. San Diego, CA: Bridgepoint Education Inc.
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