Public perceptions of organised crime in Scotland: report

1. Introduction

Background to the research

In 2015 the Scottish Government published Scotland's Serious Organised Crime Strategy. The overarching aim of the strategy is to reduce the harm caused by serious organised crime through the pursuit of four core objectives:

• DIVERT: To divert people from becoming involved in serious organised crime and using its products
• DETER: To deter serious organised crime groups by supporting private, public and third sector organisations to protect themselves and each other
• DETECT: To identify, detect and prosecute those involved in serious organised crime
• DISRUPT: To disrupt serious organised crime groups

Raising public awareness of serious organised crime and the harm it can cause is a key focus of the strategy. Accordingly, in spring 2013, the Scottish Government commissioned a module of questions on the Ipsos MORI Scotland Public Opinion Monitor; a quarterly survey carried out among a representative sample of c1,000 adults (aged 18+) in Scotland. The module measured the public's awareness and experience of organised crime, thus proving a source of baseline evidence against which progress towards the aim and objectives of the strategy could be measured.

In autumn 2017 the Scottish Government commissioned a repeat of the question module on the Ipsos MORI Scotland Public Opinion Monitor (Questionnaire, Appendix A). This report presents the findings of the research.

Methodology

The Scottish Public Option Monitor is a multi-client survey carried out by telephone among a random sample of adults across Scotland every quarter. Respondents are selected using random digit dialing ( RDD) and sample quotas are set on age, sex, working status and region, to ensure the achieved sample is broadly representative of the Scottish adult population (aged 16+). All interviews are conducted using Computer Assisted Telephone Interviewing ( CATI).

For this wave of the survey, a total of 1,088 respondents across Scotland were interviewed between 27 November and 5 December 2017.

The data are weighted to match the known profile of the Scottish population by age, sex, and working status using census data; tenure using Scottish Household Survey data; and employment sector data using the Scottish Government Quarterly public sector employment series data.

Table 1.1 shows both the weighted and unweighted sample profile by age, sex and working status.

Table 1.1: Sample profile – age, sex and working status

Sample variable	Unweighted profile %	Weighted profile %
Age
16-24	11	14
25-34	12	15
35-54	34	34
55+	42	35
Sex
Male	43	48
Female	57	52
Working status
Working full time	41	41
Working part time	13	9
Not working	44	48

We conducted 90% of interviews using a RDD sample and 10% using a mobile number sample. This ensured comparability with the 2013 methodology (which used an entirely RDD sample) while also including a proportion of mobile numbers to improve the representativeness of the sample, given that 17% of Scottish households are mobile-only.

Interpreting the findings

Where percentages do not sum to 100%, this may be due to computer rounding, the exclusion of 'don't know' categories or multiple answers. Throughout the report, an asterisk (*) denotes any value of less than half of one per cent but more than zero.

The respondents to a survey are only a sample of a total "population", so we can never be certain that the figures obtained are exactly those that would have been if everybody had completed the survey questionnaire (the "true" values). However, the variation between the sample results and the "true" values can be predicted from knowing the size of the samples on which the results are based and the number of times that a particular answer is given.

This extent of uncertainty is represented as a "Confidence Interval" ( CI), and it represents the level of confidence for a prediction of a "true", underlying result ( e.g. percentage satisfied) from a sample result. The confidence with which we can make predictions is usually chosen to be 95%, and it means that there is a 95% chance that the "true" value will fall within a specified range.

The table below illustrates the required ranges for different percentage results within the overall sample at the "95% confidence interval"

Table 1.2: Approximate sampling tolerances applicable to percentages at or near these levels for overall sample

	Sample size (n)	10% or 90% +	30% or 70% +	50% +
Overall sample	1,088	1.88	2.7	3.0

For example, if 50% of all respondents were to give a particular answer, the chances are 95 in 100 that the "true value" will fall within the range of plus or minus 3.0 percentage points, in other words between 47% and 53%.

When results are compared between two different samples, in this case, 2017 and 2013 results, the difference between the two sample results must be greater than the values given in the table below.

Table 1.3: Approximate sampling tolerances applicable to percentages at or near these levels for comparing 2017 and 2013 results

	Sample size (n)	10% or 90% +	30% or 70% +	50% +
2013 vs. 2017	1,001 vs. 1,088	2.6	4.4	4.0

Similarly, when results are compared between separate groups within a sample, the differences between results may be "real", or it may occur by chance. To test if the difference is a real one, in other words, if it is statistically significant, we take into account the size of the population, the size of the samples, the percentages giving a certain answer and the degree of confidence chosen.

If we again assume a 95% confidence interval, the difference between the two results must be greater than the values given in the table below:

Table 9.1 – Approximate sampling tolerances applicable to percentages at or near these levels for comparing sub-group findings

	Sample size (n)	10% or 90% +	30% or 70% +	50% +
Men	470	3.6	5.5	6.0
Women	618
Most deprived areas	169	6.3	9.6	10.5
Least deprived areas	180
Aged16-24 Aged 55+	121	6.0	9.2	10.1
Aged 55+	453

For example, if 50% of men give a particular answer, there needs to be a difference of 6.0 percentage points between this result and the comparable result for women in order for the difference between the sexes to be statistically significant.

Throughout the report, inter-year and sub-group differences are highlighted only where these are statistically significant at the 95% confidence interval.