Drug policy is a contentious political issue in the UK. On the one hand, the British government remains firmly committed to the criminalisation of narcotic substances (see for example BBC, 2018), reflecting wider public attitudes that are mixed regarding decriminalisation of “soft” drugs like cannabis but largely opposed to the decriminalisation of “harder” drugs like cocaine and heroin (YouGov, 2018). On the other hand, underpinned by the argument that incarceration is ineffective for deterring illicit drug use, several police areas in England and Wales have shifted towards education and support for minor drugs possession offences rather than using legal sanctions (see for example Durham Constabulary’s Drug Arrest Referral Scheme; Durham Constabulary, 2019).
Among other things, opposition to decriminalisation of narcotic substances is underpinned by the perceived social harms that result from drug use that go beyond individual health and wellbeing. Goldstein’s (1985) seminal work, for example, argues that drugs result in violent crime owing to: (1) the effects they have on people taking them; (2) the need for money to purchase drugs; and (3) the systems which emerge around the sale and supply of drugs (e.g. criminal gangs). However, more recent scholarship has challenged Goldstein’s conclusion, pointing to the specificity of the context his model was developed in and the paucity of empirical supporting it (see for example MacCoun et al., 2003). Further, so-called “harm reductionists” argue that the social harms arising from drug use are more effectively mitigated by decriminalisation and treatment, including state-funded “substitution” therapy where drug users are provided with substitute substances without charge to help them break their addiction and offset the need to resort to crime to buy drugs (see for example Erickson et al., 1997).
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The RMA Drugs and Crime dataset on DUO contains data collected from a random survey of people arrested in England and Wales between 2003 and 2006. There are three variables:
Drug_Use: whether the respondent had taken any “hard” (heroin, cocaine, crack) or “soft” illicit drugs in the month preceding the survey
Arrest_Reason: the type of crime the respondent was arrested for
Prison_History: whether the respondent has spent time in prison and whether that time was recent (i.e. in the last 12 months)
Questions:
Using appropriate statistics, describe the distribution of the Drug_Use variable. To what extent is drug use characteristic of offenders in England and Wales?
Using appropriate statistics, analyze the association between Drug_Use and Arrest_Reason. In what ways do your results demonstrate that social harms arise out of illicit drug use?
Using appropriate statistics, analyze the association between Drug_Use and Prison_History. In what ways do your results demonstrate that the experience of going to prison deters future offending?
In view of your answers to (a), (b) and (c) above, what do you conclude about the decriminalisation of currently illicit drugs?
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Section 2 starts on the next page
Section 2 – Assessing the Russel Group (30%)
The Russel Group is a collection of British universities that have come to represent the prestigious end of UK higher education. Director General of the Russel Group, Wendy Piatt, asserts that:
“Our students work with world-class experts, use first-rate libraries and facilities, are part of a highly motivated and talented peer group and often engage with cutting-edge research.
Graduate recruiters rank ten Russell Group universities in the top 30 universities worldwide, and Russell Group graduates typically receive a 10% salary ‘top-up’ over others. Why? Because the combination of teaching and research excellence creates the ideal learning environment which produces ‘work-ready’ graduates” (cited in Sharp, 2019)
The focus of this second question is to test Piatt’s claims regarding the outstanding educational environment of Russel Group institutions.
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The RMA UK HEI dataset on DUO contains data from a sample of UK higher education institutions (HEIs):
InstitutionType: this defines whether the case is a Russel Group University, another “old” university, or a “new” university founded since 1992
CourseScore: the proportion of students at the university who agreed that they were satisfied with their degree programme overall in the 2018 National Student Survey
TeachingScore: the proportion of students at the university who agreed that they were satisfied with the quality of teaching on their degree programme in the 2018 National Student Survey
FeedbackScore: the proportion of students at the university who agreed that they were satisfied with the quality of feedback on their work in the 2018 National Student Survey
The Universities of Oxford and Cambridge – both members of the Russel Group – have been excluded from the data as they are significant outliers in terms of student intake and economic resources (see Boliver, 2015) and therefore may have an excessive influence on the results.
Questions:
Using appropriate statistics, analyse the association between InstitutionType and CourseScore. What do your results indicate about the quality of education provided by different institutional groups?
Using appropriate statistics, analyse the association between InstitutionType and TeachignScore. What do your results indicate about the quality of teaching and learning provided by different institutional groups?
Using appropriate statistics, analyse the association between InstitutionType and FeedbackScore. What do your results indicate about the quality of feedback provided to students by different institutional groups?
Considering your answers to questions (a), (b) and (c) above, can you conclude that Russel Group universities offer educational “excellence” in excess of other British higher education institutions?
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Section 3 – Exercise Referral Evaluation (40%)
The data for this final section are drawn from Hanson et al.’s (2013) study examining the efficacy of an exercise referral scheme in the North East of England. The scheme aimed to help people with weight- and fitness-related health conditions through referral by a doctor to a six-month exercise programme. Data were collected from participants at the point of referral, three months after starting the programme and finally on completion of the programme to track change over time.
Hanson et al’s study demonstrates that engagement with the exercise programme is variable: many do not start the programme and of those who do, not all will complete it. They also found that engagement was related in part to age: older participants were more likely to start and complete the programme than younger participants. However, their paper is focused on participation and not whether participation has positive health outcomes. This is the focus of the final question.
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The RMA Exercise Referral dataset on DUO contains a selection of data from the project, including:
Attendance: how many of the 48 programme sessions participants attended in total
Age: how many years old participants were at the start of the programme
Physical_Change: how much participants’ physical wellbeing improved or declined between the start and end of the programme
Psychological_Change: how much participants’ psychological wellbeing improved or declined between the start and the end of the programme
The final two variables were measured using the World Health Organisation Quality of Life (WHOQOL) assessment, where respondents are asked several questions related to health and wellbeing and the answers totalled into a single numerical value. Higher scores mean higher levels of wellbeing, so a positive value indicates an increase in wellbeing, while a negative value indicates a decrease in wellbeing across the six months of the programme. For the sake of this assessment, you should treat these two variables as scale even through this can be disputed.
Questions:
Using appropriate statistics, describe the distribution of the Physical_Change variable. What can you conclude about changes in physical wellbeing over the length of the programme?
Using appropriate statistics, describe the distribution of the Psychological _Change variable. What can you conclude about changes in psychological wellbeing over the length of the programme?
Using appropriate statistics, determine the effect of Age and Attendance on Physical_Change. From your results, what can you conclude about the effectiveness of the programme in terms of improving physical wellbeing?
Using appropriate statistics, determine the effect of Age and Attendance on Psychological_Change. From your results, what can you conclude about the effectiveness of the programme in terms of improving psychological wellbeing?
Considering your answers to (a), (b), (c) and (d) above, what can you conclude about the effectiveness of the exercise referral scheme for improving physical and psychological wellbeing?
