Publication - Research publication

Attitudes to Mental Health in Scotland: Scottish Social Attitudes Survey 2013

Published: 10 Nov 2014
Part of:
Research
ISBN:
9781784128869

Report on public attitudes to mental health, based on data collected in the 2013 Scottish Social Attitudes Survey, and comparison with data collected through four previous surveys between 2002 and 2008.

154 page PDF

2.3 MB

154 page PDF

2.3 MB

Contents
Attitudes to Mental Health in Scotland: Scottish Social Attitudes Survey 2013
Annex B - Technical Details of the Survey

154 page PDF

2.3 MB

Annex B - Technical Details of the Survey

The Scottish Social Attitudes series

1. The Scottish Social Attitudes (SSA) survey was launched by the Scottish Centre for Social Research (ScotCen) in 1999, following the advent of devolution. Based on annual rounds of interviews of between 1,200 to 1,500 people drawn using probability sampling (based on a stratified, clustered sample)[59], it aims to facilitate the study of public opinion and inform the development of public policy in Scotland. In this it has similar objectives to the British Social Attitudes (BSA) survey, which was launched by ScotCen's parent organisation, the National Centre for Social Research (NatCen) in 1983. While BSA interviews people in Scotland, these are usually too few in any one year to permit separate analysis of public opinion in Scotland (see Park, et al, 2013 for more details of the BSA survey).

2. The SSA survey has been conducted annually each year since 1999, with the exception of 2008. The survey has a modular structure. In any one year it typically contains three to five modules, each containing 40 questions. Funding for its first two years came from the Economic and Social Research Council, while from 2001 onwards different bodies have funded individual modules each year. These bodies have included the Economic and Social Research Council, the Scottish Government and various charitable and grant awarding bodies, such as the Nuffield Foundation and Leverhulme Trust. 2013 funders were the Scottish Government, Economic and Social Research Council, NHS Health Scotland, University of Edinburgh and the Scottish Institute for Policing Research.

The 2013 survey

3. The 2013 survey contained modules of questions on:

  • Attitudes to government, the economy, health and social care services and social capital - funded by the Scottish Government
  • Attitudes to mental health and recovery - funded by the Scottish Government
  • Attitudes to alcohol - funded by NHS Health Scotland
  • Constitutional change - funded by the ESRC and University of Edinburgh
  • Attitudes to policing - funded by the Scottish Institute for Policing Research and ScotCen.

4. Findings from the modules funded by the Scottish Government will be available in reports published on their website (www.scotland.gov.uk). Separate programmes of dissemination are planned for each of the other modules. This technical annex covers the methodological details of the survey as well as further discussion of the analysis techniques used in this report.

Sample design

5. The survey is designed to yield a representative sample of adults aged 18 or over, living in Scotland. The sample frame is the Postcode Address File (PAF), a list of postal delivery points compiled by the Post Office. The detailed procedure for selecting the 2013 sample was as follows:

i. 110 postcode sectors were selected from a list of all postal sectors in Scotland, with probability proportional to the number of addresses in each sector for addresses in urban areas and a probability of twice the address count for sectors in rural areas (i.e. the last 3 categories in the Scottish Government's 6 fold urban-rural classification). Prior to selection the sectors were stratified by Scottish Government urban-rural classification[60], region and percentage of household heads recorded as being in non-manual occupations (SEG 1-6 and 13, taken from the 2001 Census).

ii. 28 addresses were selected at random from each of these 110 postcode sectors

iii. Interviewers called at each selected address and identified its eligibility for the survey. Where more than one dwelling unit was present at an address, all dwelling units were listed systematically and one was selected at random using a computer generated random selection table. In all eligible dwelling units with more than one adult aged 18 or over, interviewers had to carry out a random selection of one adult using a similar procedure.

Response rates

6. The Scottish Social Attitudes survey involves a face-to-face interview with respondents and a self-completion section (completed using Computer Assisted Personal Interviewing). The numbers completing each stage in 2013 are shown in Table 1. See Bromley, Curtice and Given (2005) for technical details of the 1999-2004 surveys, Given and Ormston (2006) for details of the 2005 survey, Cleghorn, Ormston and Sharp (2007) for the 2006 survey, Ormston (2008) for the 2007 survey, Ormston (2010) for the 2009 survey and Ormston and Reid (2011 & 2012) for the 2010 and 2011 surveys.

Table 1: 2013 Scottish Social Attitudes survey response

No. %
Addresses issued 3,080
Vacant, derelict and other out of scope1 339 11
Achievable or 'in scope' 2741
Unknown eligibility2 9 *
Interview achieved 1497 55
Self-completion completed 1340 49
Interview not achieved
Refused3 851 31
Non-contacted4 187 7
Other non-response5 196 7

Notes to table

1 This includes empty / derelict addresses, holiday homes, businesses and institutions, and addresses that had been demolished.

2 'Unknown eligibility' includes cases where the address could not be located, where it could not be determined if an address was residential and where it could not be determined if an address was occupied or not.

3 Refusals include: refusals prior to selection of an individual; refusals to the office; refusal by the selected person; 'proxy' refusals made by someone on behalf of the respondent; and broken appointments after which a respondent could not be re-contacted.

4 Non-contacts comprise households where no one was contacted after at least 6 calls and those where the selected person could not be contacted.

5 'Other non-response' includes people who were ill at home or in hospital during the survey period, people who were physically or mentally unable to participate and people with insufficient English to participate.

Sample size for previous years

7. The table below shows the achieved sample size for the full SSA sample (all respondents) for all previous years.

Table 2: Scottish Social Attitudes survey sample size by year

Survey year Achieved sample size
1999 1482
2000 1663
2001 1605
2002 1665
2003 1508
2004 1637
2005 1549
2006 1594
2007 1508
2009 1482
2010 1495
2011 1197
2012 1229
2013 1497

Weighting

8. All percentages cited in this report are based on weighted data. The weights applied to the SSA 2013 data are intended to correct for three potential sources of bias in the sample:

  • Differential selection probabilities
  • Deliberate over-sampling of rural areas
  • Non-response

9. Data were weighted to take account of the fact that not all households or individuals have the same probability of selection for the survey. For example, adults living in large households have a lower selection probability than adults who live alone. Weighting was also used to correct the over-sampling of rural addresses. Differences between responding and non-responding households were taken into account using information from the census about the area of the address as well as interviewer observations about participating and non-participating addresses. Finally, the weights were adjusted to ensure that the weighted data matched the age-sex profile of the Scottish population (based on 2012 mid-year estimates from the General Register Office for Scotland).

10. In addition to the usual weighting on SSA a special weight was developed specifically for any questions in the section conducted by computer assisted self-complete (CASI), to adjust for differences in the profile of those who agreed to complete the CASI and those who refused.

Fieldwork

11. Fieldwork for the 2013 survey ran between June and October 2013, with 78% of interviews completed by the end of August and 91% by the end of September. An advance postcard, followed by an advance letter were sent to all addresses and were followed up by a personal visit from a ScotCen interviewer. Interviewers were required to make a minimum of 6 calls at different times of the day (including at least one evening and one weekend call) in order to try and contact respondents. All interviewers attended a one day briefing conference prior to starting work on the study.

12. Interviews were conducted using face-to-face computer-assisted interviewing (a process which involves the use of a laptop computer, with questions appearing on screen and interviewers directly entering respondents' answers into the computer). All respondents were asked to fill in a self-completion questionnaire using the interviewer's laptop. If the respondent preferred, the questions could be read out by the interviewer. Table 1 (above) summarises the response rate and the numbers completing the self-completion section in 2013.

Analysis variables

13. Most of the analysis variables are taken directly from the questionnaire and are self-explanatory. These include age, sex, household income, and highest educational qualification obtained.

National Statistics Socio-Economic Classification (NS-SEC)

14. The most commonly used classification of socio-economic status used on government surveys is the National Statistics Socio-Economic Classification (NS-SEC). SSA respondents were classified according to their own occupation, rather than that of the 'head of household'. Each respondent was asked about their current or last job, so that all respondents, with the exception of those who had never worked, were classified. The seven NS-SEC categories are:

  • Employers in large organisations, higher managerial and professional
  • Lower professional and managerial; higher technical and supervisory
  • Intermediate occupations
  • Small employers and own account workers
  • Lower supervisory and technical occupations
  • Semi-routine occupations
  • Routine occupations.

The remaining respondents were grouped as 'never had a job' or 'not classifiable'.

Scottish Index of Multiple Deprivation (SIMD)

15. The Scottish Index of Multiple Deprivation (SIMD)[61] 2009 measures the level of deprivation across Scotland - from the least deprived to the most deprived areas. It is based on 38 indicators in seven domains of: income, employment, health, education skills and training, housing, geographic access and crime. SIMD 2009 is presented at data zone level, enabling small pockets of deprivation to be identified. The data zones are ranked from most deprived (1) to least deprived (6,505) on the overall SIMD 2009 and on each of the individual domains. The result is a comprehensive picture of relative area deprivation across Scotland.

16. The analysis in this report used a variable created from SIMD data indicating the level of deprivation of the data zone in which the respondent lived in quintiles, from most to least deprived.[62]

Analysis techniques

Significance testing

17. Where this report discusses differences between two percentages (either across time, or between two different groups of people within a single year), this difference is significant at the 95% level or above, unless otherwise stated. Differences between two years were tested using standard z-tests, taking account of complex standard errors arising from the sample design. Differences between groups within a given year were tested using logistic regression analysis, which shows the factors and categories that are significantly (and independently) related to the dependent variable (see below for further detail). This analysis was done in PASW 18, using the CS logistic function to take account of the sample design in calculations.

Regression analysis

18. Regression analysis aims to summarise the relationship between a 'dependent' variable and one or more 'independent' explanatory variables. It shows how well we can estimate a respondent's score on the dependent variable from knowledge of their scores on the independent variables. This technique takes into account relationships between the different independent variables (for example, between education and income, or social class and housing tenure). Regression is often undertaken to support a claim that the phenomena measured by the independent variables cause the phenomenon measured by the dependent variable. However, the causal ordering, if any, between the variables cannot be verified or falsified by the technique. Causality can only be inferred through special experimental designs or through assumptions made by the analyst.

19. All regression analysis assumes that the relationship between the dependent and each of the independent variables takes a particular form. This report was informed by logistic regression analysis - a method that summarises the relationship between a binary 'dependent' variable (one that takes the values '0' or '1') and one or more 'independent' explanatory variables. The tables in this annex show how the odds ratios for each category in significant explanatory variables compares to the odds ratio for the reference category (always taken to be 1.00).

20. Taking Model 2 (below), the dependent variable is agreeing that 'The majority of people with mental health problems recover'. If the respondent either agreed or strongly agreed that 'The majority of people with mental health problems recover' the dependent variable takes a value of 1. If not, it takes a value of 0. An odds ratio of above 1 means that, compared with respondents in the reference category, respondents in that category have higher odds of agreeing that 'The majority of people with mental health problems recover'. Conversely, an odds ratio of below 1 means they have lower odds of saying this than respondents in the reference category. The 95% confidence intervals for these odds ratios are also important. Where the confidence interval does not include 1, this category is significantly different from the reference category. If we look at age in Model 2, we can see that those aged 55-64 years old had an odds ratio of 2.27, indicating that they have higher odds compared with those aged 18 to 24 years old (who were the reference category). The 95% confidence interval (1.29-3.99) does not include 1, indicating this difference is significant.

21. The significance of each independent variable is indicated by 'P'. A p-value of 0.05 or less indicates that there is less than a 5% chance we would have found these differences between the categories just by chance if in fact no such difference exists, while a p-value of 0.01 or less indicates that there is a less than 1% chance. P-values of 0.05 or less are generally considered to indicate that the difference is highly statistically significant, while a p-value of 0.06 to 0.10 may be considered marginally significant.

22. The models below show the final model for each variable, which was produced using the Complex Survey command (CS Logistic) in PASW 18. CS Logistic models can account for complex sample designs (in particular, the effects of clustering and associated weighting) when calculating odds ratios and determining significance. The models shown below include only those variables found to be significant after the regression models were run using CS logistic.

Regression models

Table 1: Factors associated with disagreeing that 'Anyone can suffer from mental health problems.' (2013)

Dependent variable encoding
1 = Disagreeing 'Anyone can suffer from mental health problems'

0 = All other respondents
Odds ratio 95% confidence interval
Knowing someone with a mental health problem (p=0.029)
No (reference) 1.00
Yes 0.43 0.17-1.10

Nagelkerke R2 = 23.6%

Other factors included in model but which were not significant after other factors were accounted for were: sex, age, socio-economic grouping, income, level of education, urban-rural, whether experienced a mental health problem, whether feel that most people can be trusted.

Table 2: Factors associated with agreeing that 'The majority of people with mental health problems recover' (2013)

Dependent variable encoding
1 = Agreeing 'The majority of people with mental health problems recover'

0 = All other respondents
Odds ratio 95% confidence interval
Gender (p=0.001)
Female (reference) 1.00
Male 0.64 0.49-0.84
Age (p=0.083)
18-24 (reference) 1.00
25-34 1.42 0.76-2.87
35-44 1.70 0.87-3.31
45-54 1.62 0.93-2.82
55-64 2.27 1.29-3.99
65+ 1.58 0.85-2.93
Income (p=0.022)
Up to £14,300 (reference) 1.00
Over £14,300 to £26,000 0.61 0.42-0.89
Over £26,000 to £44,200 0.89 0.61-1.30
Over £44,200 0.56 0.37-0.85
Having personal experience of mental health problems (p=0.011)
No (reference) 1.00
Yes 1.77 1.23-2.55

Nagelkerke R2 = 8.6%

Other factors included in model but which were not significant after other factors were accounted for were: socio-economic grouping, level of education, area deprivation, urban-rural, knowing someone with a mental health problem, having a neighbour to keep an eye on your home, whether feel that most people can be trusted, agreeing that increased immigration would lead to Scotland losing its identity.

Table 3: Factors associated with agreeing that 'People with mental health problems are largely to blame for their own condition' (2013)

Dependent variable encoding
1 = Agreeing 'People with mental health problems are largely to blame for their own condition'

0 = All other respondents
Odds ratio 95% confidence interval
Gender (p=0.075)
Female (reference) 1.00
Male 1.89 1.07-3.34
Socio-economic grouping (p=0.044)
Employers/mgrs & professional (reference) 1.00
Intermediate occupations 1.17 0.27-5.05
Small employers/ own account workers 1.32 0.35-4.97
Lower supervisory & technical 0.92 0.25-3.38
Semi-routine & routine occupations 3.55 1.31-9.65
Never worked/ not classified 1.09 0.19-6.34
Increased immigration would lead to Scotland losing its identity (p=0.054)
Disagree/ disagree strongly (reference) 1.00
Neither agree nor disagree 0.13 0.02-0.72
Strongly agree/agree 0.93 0.45-1.91

Nagelkerke R2 = 18.8%

Other factors included in model but which were not significant after other factors were accounted for were: age, income, level of education, area deprivation, urban-rural, knowing someone with a mental health problem, whether experienced a mental health problem, whether feel that most people can be trusted, having a neighbour to keep an eye on your home.

Table 4: Factors associated with agreeing that 'People are generally caring and sympathetic to people with mental health problems' (2013)

Dependent variable encoding
1 = Agreeing 'People are generally caring and sympathetic to people with mental health problems'

0 = All other respondents
Odds ratio 95% confidence interval
Gender (p=0.075)
Female (reference) 1.00
Male 1.25 0.98-1.59
Age (p=0.014)
18-24 (reference) 1.00
25-34 0.74 0.38-1.43
35-44 0.43 0.23-0.83
45-54 0.46 0.24-0.85
55-64 0.44 0.24-0.80
65+ 0.68 0.36-1.28
Socio-economic grouping (p=0.044)
Employers/mgrs & professional (reference) 1.00
Intermediate occupations 0.98 0.66-1.48
Small employers/ own account workers 2.04 1.30-3.22
Lower supervisory & technical 1.47 0.88-2.43
Semi-routine & routine occupations 1.59 1.08-2.34
Never worked/ not classified 1.72 1.01-2.92
Education (p=0.031)
No recognised qualification 1.00
Degree/ Higher education 0.53 0.33-0.85
Highers/ A-levels 0.54 0.35-0.86
Standard grades/ GCSEs 0.82 0.58-1.17
Urban-rural (p=0.046)
Urban (reference) 1.00
Small town 0.91 0.60-1.36
Rural 1.37 0.97-1.94
Knowing someone with a mental health problem (p=0.009)
No (reference) 1.00
Yes 0.65 0.47-0.90
Having personal experience of mental health problems (p=0.011)
No (reference) 1.00
Yes 0.59 0.41-0.83
If my home was empty, I could count on one of my neighbours to keep an eye on it (p=0.061)
Strongly agree/agree (reference) 1.00
Neither agree nor disagree 0.48 0.24-0.98
Disagree/ disagree strongly 1.42 0.88-2.29
Social trust (p=0.077)
Most people can be trusted (reference) 1.00
You can't be too careful in dealing with people 0.72 0.53-0.98
Increased immigration would lead to Scotland losing its identity (p=0.054)
Disagree/ disagree strongly (reference) 1.00
Neither agree nor disagree 1.09 0.70-1.68
Strongly agree/agree 1.50 1.06-2.12

Nagelkerke R2 = 14.4%

Other factors included in model but which were not significant after other factors were accounted for were: income, area deprivation.

Table 5: Factors associated with agreeing that 'If I was suffering from mental health problems, I wouldn't want people knowing about it'

Dependent variable encoding
1 = Agreeing 'If I was suffering from mental health problems, I wouldn't want people knowing about it'

0 = All other respondents
Odds ratio 95% confidence interval
If my home was empty, I could count on one of my neighbours to keep an eye on it (p = 0.000)
Strongly agree/agree (reference) 1.00
Neither agree nor disagree 0.97 0.44-2.12
Disagree/ disagree strongly 2.82 1.94-4.10

Nagelkerke R2 = 5.8%

Other factors included in model but which were not significant after other factors were accounted for were: sex, age, socio-economic grouping, income, level of education, area deprivation, urban-rural, knowing someone with a mental health problem, whether experienced a mental health problem, whether feel that most people can be trusted, agreeing that increased immigration would lead to Scotland losing its identity.

Table 6: Factors associated with agreeing that 'I would find it hard to talk to someone with mental health problems' (2013)

Dependent variable encoding
1 = Agreeing 'I would find it hard to talk to someone with mental health problems'

0 = All other respondents
Odds ratio 95% confidence interval
Gender (p=0.000)
Female (reference) 1.00
Male 2.41 1.75-3.33
Age (p=0.033)
18-24 (reference) 1.00
25-34 1.56 0.64-3.80
35-44 1.66 0.81-3.38
45-54 0.83 0.40-1.74
55-64 1.25 0.56-2.79
65+ 2.11 0.96-4.61
Socio-economic grouping (p=0.049)
Employers/mgrs & professional (reference) 1.00
Intermediate occupations 2.03 1.22-3.39
Small employers/ own account workers 1.37 0.71-2.66
Lower supervisory & technical 1.01 0.53-1.92
Semi-routine & routine occupations 1.59 0.94-2.68
Never worked/ not classified 2.09 0.98-4.45
Knowing someone with a mental health problem (p=0.000)
No (reference) 1.00
Yes 0.43 0.29-0.63
If my home was empty, I could count on one of my neighbours to keep an eye on it (p = 0.015)
Strongly agree/agree (reference) 1.00
Neither agree nor disagree 0.31 0.11-0.89
Disagree/ disagree strongly 1.70 1.01-2.86

Nagelkerke R2 = 19.6%

Other factors included in model but which were not significant after other factors were accounted for were: income, level of education, area deprivation, urban-rural, whether experienced a mental health problem, whether feel that most people can be trusted, agreeing that increased immigration would lead to Scotland losing its identity.

Table 7: Factors associated with agreeing that 'People with mental health problems are often dangerous' (2013)

Dependent variable encoding
1 = Agreeing 'People with mental health problems are often dangerous'

0 = All other respondents
Odds ratio 95% confidence interval
Gender (p=0.068)
Female (reference) 1.00
Male 1.43 0.97-2.09
Area deprivation (p=0.084)
Least deprived (5th) (reference) 1.00
Most deprived (1st) 0.45 0.22-0.91
2nd 0.52 0.27-0.99
3rd 0.44 0.26-0.77
4th 0.54 0.28-1.07
Knowing someone with a mental health problem (p=0.005)
No (reference) 1.00
Yes 0.62 0.45-0.87
Having personal experience of mental health problems (p=0.088)
No (reference) 1.00
Yes 0.68 0.43-1.07
If my home was empty, I could count on one of my neighbours to keep an eye on it (p=0.028)
Strongly agree/agree (reference) 1.00
Neither agree nor disagree 0.81 0.29-2.24
Disagree/ disagree strongly 2.34 1.24-4.35
Social trust (p=0.072)
Most people can be trusted (reference) 1.00
You can't be too careful in dealing with people 1.28 0.91-1.80
Increased immigration would lead to Scotland losing its identity (p=0.000)
Disagree/ disagree strongly (reference) 1.00
Neither agree nor disagree 0.67 0.37-1.22
Strongly agree/agree 1.78 1.16-2.71

Nagelkerke R2 = 17.3%

Other factors included in model but which were not significant after other factors were accounted for were: age, socio-economic grouping, income, level of education, urban-rural, whether experienced a mental health problem.

Table 8: Factors associated with agreeing that 'The public should be better protected from people with mental health problems' (2013)

Dependent variable encoding
1 = Agreeing 'The public should be better protected from people with mental health problems'

0 = All other respondents
Odds ratio 95% confidence interval
Gender (p=0.018 )
Female (reference) 1.00
Male 1.51 1.08-2.13
Age (p=0.091)
18-24 (reference) 1.00
25-34 1.44 0.63-3.30
35-44 0.91 0.45-1.87
45-54 1.47 0.67-3.19
55-64 1.28 0.63-2.58
65+ 1.91 0.94-3.88
Education (p=0.013)
No recognised qualification 1.00
Degree/ Higher education 0.83 0.55-1.26
Highers/ A-levels 0.41 0.24-0.72
Standard grades/ GCSEs 0.94 0.60-1.48
Knowing someone with a mental health problem (p=0.029)
No (reference) 1.00
Yes 0.70 0.51-0.96
If my home was empty, I could count on one of my neighbours to keep an eye on it (p = 0.006)
Strongly agree/agree (reference) 1.00
Neither agree nor disagree 0.51 0.23-1.14
Disagree/ disagree strongly 2.02 1.23-3.31
Increased immigration would lead to Scotland losing its identity (p=0.000)
Disagree/ disagree strongly (reference) 1.00
Neither agree nor disagree 1.42 0.82-2.46
Strongly agree/agree 2.45 1.61-3.74

Nagelkerke R2 = 14.4%

Other factors included in model but which were not significant after other factors were accounted for were: socio-economic grouping, income, area deprivation, urban-rural, whether experienced a mental health problem, whether feel that most people can be trusted.

Table 9: Factors associated with agreeing that 'People with mental health problems should have the same rights as anyone else' (2013)

Dependent variable encoding
1 = Agreeing 'People with mental health problems should have the same rights as anyone else'

0 = All other respondents
Odds ratio 95% confidence interval
Having personal experience of mental health problems (p=0.023)
No (reference) 1.00
Yes 0.37 0.18-0.75
If my home was empty, I could count on one of my neighbours to keep an eye on it (p=0.031)
Strongly agree/agree (reference) 1.00
Neither agree nor disagree 0.60 0.15-2.38
Disagree/ disagree strongly 2.48 1.19-5.17
Social trust (p=0.041)
Most people can be trusted (reference) 1.00
You can't be too careful in dealing with people 1.79 1.06-3.02
Increased immigration would lead to Scotland losing its identity (p=0.006)
Disagree/ disagree strongly (reference) 1.00
Neither agree nor disagree 0.78 0.30-2.04
Strongly agree/agree 2.13 1.05-4.32

Nagelkerke R2 = 13.9%

Other factors included in model but which were not significant after other factors were accounted for were: sex, age, socio-economic grouping, income, level of education, area deprivation, urban-rural, knowing someone with a mental health problem.

Table 10: Factors associated with someone with schizophrenia harming others (2013)

Dependent variable encoding
1 = Thinking it likely that someone with schizophrenia would harm others

0 = All other respondents
Odds ratio 95% confidence interval
Knowing someone with schizophrenia (p=0.014)
No (reference) 1.00
Yes 1.92 1.15-3.22
Increased immigration would lead to Scotland losing its identity (p=0.002)
Disagree/ disagree strongly (reference) 1.00
Neither agree nor disagree 0.71 0.46-1.11
Strongly agree/agree 1.50 1.08-2.11

Nagelkerke R2 = 7.1%

Other factors included in model but which were not significant after other factors were accounted for were: sex, age, socio-economic grouping, education, income, area deprivation, urban-rural, having a neighbour to keep an eye on your home, whether feel that most people can be trusted, having personal experience of mental health problems, knowing someone with a mental health problem, knowing the diagnosis was schizophrenia.

Table 11: Factors associated with someone with schizophrenia harming themself (2013)

Dependent variable encoding
1 = Thinking it likely that someone with schizophrenia would harm themselves

0 = All other respondents
Odds ratio 95% confidence interval
Gender (p=0.033)
Female (reference) 1.00
Male 0.74 0.56-0.98
Income (p=0.010)
Up to £14,300 (reference) 1.00
Over £14,300 to £26,000 1.77 1.03-3.07
Over £26,000 to £44,200 1.57 0.93-2.63
Over £44,200 0.90 0.54-1.50
Urban-rural (p=0.020)
Urban (reference) 1.00
Small town 1.08 0.77-1.51
Rural 0.66 0.47-0.91
Social trust (p=0.003)
Most people can be trusted (reference) 1.00
You can't be too careful in dealing with people 1.72 1.26-2.34
Increased immigration would lead to Scotland losing its identity (p=0.008)
Disagree/ disagree strongly (reference) 1.00
Neither agree nor disagree 1.23 0.75-2.02
Strongly agree/agree 1.72 1.22-2.44

Nagelkerke R2 = 12.7%

Other factors included in model but which were not significant after other factors were accounted for were: age, socio-economic grouping, education, area deprivation, having personal experience of mental health problems, knowing someone with a mental health problem, knowing someone with schizophrenia, knowing the diagnosis was schizophrenia.

Table 12: Factors associated with someone with depression harming others (2013)

Dependent variable encoding
1 = Thinking it likely that someone with depression would harm others

0 = All other respondents
Odds ratio 95% confidence interval
Social trust (p=0.031)
Most people can be trusted (reference) 1.00
You can't be too careful in dealing with people 1.68 1.06-2.65
Knowing someone with depression (p=0.005)
No (reference) 1.00
Yes 0.44 0.25-0.78
Having personal experience of depression (p=0.079)
No (reference) 1.00
Yes 0.46 0.22-0.96

Nagelkerke R2 = 14.2%

Other factors included in model but which were not significant after other factors were accounted for were: sex, age, socio-economic grouping, education, income, area deprivation, urban-rural, having a neighbour to keep an eye on your home, agreeing that increased immigration would lead to Scotland losing its identity, having personal experience of mental health problems, knowing the diagnosis was depression.

Table 13: Factors associated with someone with depression harming themself (2013)

Dependent variable encoding
1 = Thinking it likely that someone with depression would harm themselves
0 = All other respondents
Odds ratio 95% confidence interval
Age (p=0.000)
18-24 (reference) 1.00
25-34 0.40 0.22-0.72
35-44 0.21 0.23-0.12
45-54 0.32 0.16-0.63
55-64 0.31 0.17-0.58
65+ 0.24 0.13-0.44
Social trust (p=0.024)
Most people can be trusted (reference) 1.00
You can't be too careful in dealing with people 1.26 0.96-1.66

Nagelkerke R2 = 9.5%

Other factors included in model but which were not significant after other factors were accounted for were: sex, socio-economic grouping, education, income, area deprivation, urban-rural, having personal experience of mental health problems, knowing someone with a mental health problem, knowing someone with depression, having personal experience of depression, agreeing that increased immigration would lead to Scotland losing its identity, knowing the diagnosis was depression.

References in technical annex

Bromley, C., Curtice, J., and Given, L. (2005) Public Attitudes to Devolution: the First Four Years, London: The National Centre for Social Research.

Given, L and Ormston (2006) Scottish Social Attitudes survey 2005: Scottish Executive Core module - technical report, Scottish Executive Social Research.

Cleghorn, N, Ormston, R & Sharp, C (2007) Scottish Social Attitudes survey 2006: Core module technical report, Scottish Executive Social Research.

Ormston, R (2008) Scottish Social Attitudes survey 2007 Core module: Report 1 - Attitudes to government in Scotland, Scottish Government Social Research.

Ormston, R (2010) Scottish Social Attitude survey 2009: Core Module - Attitudes to government, the economy and public services, Scottish Government Social Research.

Park, A, Clery, E, Curtice, J, Phillips, M and Utting, D (2012) British Social Attitudes 28, London: Sage


Contact

Email: Fiona MacDonald