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CHAPTER FIVE: MENTAL HEALTH AND WELLBEING

5.1 This chapter examines findings from the GHQ12 component of the survey, which was used to gauge levels of possible psychiatric morbidity among the population; and from the Warwick-Edinburgh Mental Well-being Scale ( WEMWBS), designed to assess positive mental health. It also looks at the factors respondents feel have a positive or negative effect on their mental health.

The dual dimensional model of mental health

5.2 In Europe, there is a shared principle of enhancing positive mental health rather than focusing exclusively on mental ill-health (Jane-Llopis & Anderson, 2006) and Scotland is at the forefront of driving this principle forward. Indeed mental health policy in Scotland integrates this two dimensional model of mental health which brings together mental health improvement (i.e., health promotion and prevention) and care, treatment and support. Positive mental health is defined as "a state of wellbeing in which the individual realizes his or her own abilities, can cope with the normal stresses of life, can work productively and fruitfully, and is able to make a contribution to his or her community" (Jane-Llopis & Anderson 2006).

5.3 Consistent with this focus on the dual dimensional model of mental health, the survey included both the General Health Questionnaire ( GHQ12) - a well established screening instrument designed to detect possible psychiatric morbidity in the general population - and the new Warwick-Edinburgh Mental Well-being Scale ( WEMWBS), designed to measure positive mental wellbeing.

The GHQ12

5.4 The GHQ12 was included in the survey for the first time in 2004. Each item in the GHQ12 consists of a question asking whether the respondent has recently experienced a symptom or feeling (eg happiness, depression, anxiety, self-confidence, and stress) on a scale ranging from 'less than usual' to 'more than usual'. The GHQ12 is traditionally administered using a paper and pen self-completion approach. However, because the present survey is conducted using CAPI, respondents were instead invited to enter their responses directly into the interviewer's computer. Interviewers provided assistance to those for whom computer literacy was an issue.

5.5 Although 973 respondents agreed to complete the self-completion module, only 460 respondents were presented with the full GHQ12 section with the remainder completing only the first two questions. This was due to an administrative error in the scripting of the survey (full details on this omission are included in Annex H). Nonetheless, the sample of 460 was judged to be adequate for basic analyses of the findings. The rationale underpinning this judgement was three-fold. Firstly, a preliminary analysis of profile and attitudinal data for the sample of 460 found that it did not differ significantly from the wider sample and thus could be said to be broadly representative and free from any systematic bias. Secondly, the distribution of responses to the GHQ12 was in line with that recorded in the 2004 survey which further reinforced confidence in the data. Thirdly, and in terms of statistical reliability, the decrease in the achieved number of responses resulted in only a 1% increase in sampling tolerances, vis a vis the full sample.

5.6 The completed GHQ12 sections were scored according to the bimodal scoring method outlined in A Users Guide to the General Health Questionnaire (Goldberg and Williams, 1991). A score of 1 was allocated to an item if the respondent had been experiencing the symptom or behaviour described more than usual, and a score of 0 was given if the respondent had not done so.

5.7 These scores were summed to give a total GHQ12 score for each respondent, which ranged from zero to 12. The scores were then recoded into a binary variable; scores of 0-3 were recoded as 'low mental ill-health scores' (no or few signs of possible mental health problems) and scores of 4+ were recoded as 'high mental ill-health scores' (possible mental health problems). Table 5.1 (below) presents the results of the analysis together with comparable data from the 2004 survey (The GHQ12 was not included in the 2002 survey). Throughout this report, the GHQ12 binary variable is used as a key analysis variable.

5.8 There are no significant differences between the results for the 2004 and 2006 surveys, with around four in five respondents in each case classified as having a 'low mental ill-health score' and around one in five a 'high mental ill-health score'. The results are also consistent with findings from the 2003 Scottish Health Survey, in which 15% were classified as having a low score and 85% a high score (Scottish Executive 2005).

Table 5.1: Frequency of sample scoring GHQ12 scores

Source: Ipsos MORI

WEMWBS

5.9 In addition to the GHQ12, the 2006 survey also included the Warwick-Edinburgh Mental Well-being Scale ( WEMWBS), designed to measure positive mental wellbeing. WEMWBS was recently developed by researchers at Warwick and Edinburgh Universities as a user-friendly and psychometrically sound tool for measuring positive mental wellbeing at a population level in Scotland. It is intended to complement standard scales which measure ill-health and mental health problems (see Tennant et al, 2006). Currently, WEMWBS is undergoing validation for use in Scotland and the UK. To date, it has been validated in studies among students and in the autumn 2006 wave of the Health Education Population Survey. The 2006 'Well? What do you think?' survey was felt to present another suitable validation opportunity.

5.10 WEMWBS comprises 14 separate statements describing feelings relating to mental wellbeing. For each statement, respondents are asked to indicate how often they have felt this way over the last two weeks, using a 5 point scale (none of the time, rarely, some of the time, often, all of the time). The scale represents a score for each item from 1 to 5 respectively. The overall score for WEMWBS is calculated by totalling the scores for each item. The minimum score possible from the scale is 14 while the maximum is 70. The higher a person's score is, the better his/her level of mental wellbeing.

5.11 In the previous validation exercises cited above, WEMWBS was found to be normally distributed, to correlate highly with other measures, and to have a single underlying factor - that is, to tap one underlying concept i.e. mental wellbeing (Tennant et al 2006). These tests were re-run using the data from the current survey to determine if the same was found with general population data. In the event, WEMWBS was found to be normally distributed among the general population, to correlate strongly ¹³ with the GHQ12 and to have a single underlying factor.

5.12 Respondents' mean score on WEMWBS was 51.05 and the standard deviation was 8.54. As table 5.2 shows, there was some sub-group variation. People in the top income bracket had higher mean scores - i.e. better mental wellbeing - than those in the lowest bracket. Similarly, those who found it easy to manage on their income scored more highly than those who found it difficult to manage. There were also differences by self-assessed general health status: people who said their general health was good or very good obtained higher mean scores than those said their health was bad or very bad.

5.13 Analysis by experience of mental ill-health revealed that those who reported having no such experience (either personal or proxy) had higher scores than those who had personally experienced a problem. And, consistent with the finding that the GHQ12 and WEMWBS are highly correlated, people displaying no or few signs of psychiatric disorder had higher mean scores than those with a possible psychiatric disorder. There were no significant differences by gender or age.

5.14 As discussed in the previous section, respondents' GHQ12 scores were used to derive a binary analysis variable indicating whether or not they exhibited signs of possible psychiatric disorder. The variable was created by following a coding procedure outlined in the GHQ manual. As WEMWBS is a relatively new scale no analogous classification system exists. As a result, a categorical variable was derived for the purposes of this report by dividing the survey population into three groups as follows: (i) those with "good mental wellbeing" (a WEMWBS score of over one standard deviation above the mean), (ii) those with "average mental wellbeing" (a WEMWBS score of within one standard deviation of the mean) and those with "poor mental wellbeing" (a WEMWBS score of more than one standard deviation below the mean) ¹⁴. This resulted in 14% of people being classed as having "good mental wellbeing", 73% of people were classed as having "average mental wellbeing" and 14% of people with "poor mental wellbeing." This three-fold classification is used as a key analysis variable throughout this report.

Table 5.2: WEMWBS: Mean, Standard Deviation, Median, Range

Source: Ipsos MORI

Positive effects on mental health and wellbeing

5.15 Respondents were asked what sorts of things have a positive or good effect on their own emotions or mental health and wellbeing. Although the structure and wording of the question differed slightly from that used in previous surveys (and the results are therefore not directly comparable), findings were very similar to those recorded in 2002 and 2004. Specifically, spending time with family (30%) and leisure activities, hobbies and a social life (28%) were the factors most commonly mentioned, followed by spending time with friends (19%), weather (14%) and supportive relationships with family, partners or friends (11%).

5.16 As illustrated in table 5.3, there was significant variation by gender and age. Women were more likely than men to cite family and friends as a positive influence on mental health, while the reverse was the case with regard to leisure activities, hobbies and a social life. Younger age groups were more likely than older age groups to mention work and having enough money or a good income. On the other hand, older age groups were more likely than younger age groups to cite weather and being healthy. This latter finding is particularly pertinent given the link between old age and ill-health, highlighted in the previous chapter.

5.17 There was also some variation by key economic measures. In particular, people in the highest household income category (£36,400 or more per annum) were more likely than lower income groups to mention seeing friends and family, and working patterns as positive influences. Meanwhile, those who found it difficult to manage on their income were more likely than those who found it easy to manage to mention having enough money. These sub-group differences are broadly consistent with the findings from 2004.

Table 5.3: Positive effects on mental health and wellbeing

Source: Ipsos MORI

Negative effects on mental health and wellbeing

5.18 Asked what sorts of things have a negative or bad effect on their emotions or mental health and wellbeing, respondents most commonly mentioned weather (13%) and work or having too much work (12%). These factors were closely followed by not having a good income or enough money (10%) and physical illness (8%). Again, although these results are not directly comparable with those for 2004, the rank ordering of responses is broadly similar.

5.19 Again, there was notable variation in the 2006 data by gender and age. Women, and particularly older women, were more likely than men to mention the weather as a negative influence. People aged 75 and over were more likely than younger groups to mention physical illness, while younger respondents were more likely to mention work and not having enough money (table 5.4).

5.20 Higher income groups (i.e. those earning £15,600 or more per annum) were more likely than lower income groups to mention work and work patterns. This was reflected in the SIMD analysis, with those in the least deprived areas being more than three times as likely to mention work and work patterns as those in the most deprived areas. Of course, in part this may be a function of the fact that people in the most deprived areas are less likely to be working. People who found it difficult to manage on their income were more likely than those who find it easy to mention not having enough money as a negative influence on their mental health and wellbeing. The fact that people in higher income groups were more likely than lower income groups to mention work and/or work patterns as a positive and a negative factor is interesting and worthy of further investigation.

Table 5.4: Negative effects on mental health and wellbeing

Source: Ipsos- MORI

5.21 Previous research has shown that the absence of positive influences on mental wellbeing, rather than the presence of negative influences, is crucial in predicting suicidal behaviour ¹⁵. Accordingly, analysis was undertaken to explore whether there was a relationship between the number of positive and negative influences mentioned by respondents and their mental health as measured by their responses to the GHQ12 and WEMWBS. In the event, no such relationship was found to exist. The absence of any relationship may have been because the questions on positive and negative influences allowed open responses rather than forced, closed responses. A fuller discussion of the analysis is provide in Annex I.

Self assessed control over factors affecting mental health

5.22 Respondents were asked how much control they felt they had over things which affect their mental health and wellbeing. Around two thirds (65%) felt they had a good deal or complete control, compared with 8% who felt they had little or no control. Although there has been some variation over time in the level of control people feel they have over factors that affect their mental health (see figure 5.1), a comparison of the mean scores across the three waves of the surveys uncovers no significant differences.

Figure 5.1: Levels of control over mental health. Trend since 2002

Table 5.5: Perceived levels of control over factors affecting mental health

Source: Ipsos MORI

5.23 There were no differences between men and women in terms of the level of control they feel they have. And although it was mainly among women that the sense of being in control decreased between 2002 and 2004 (from 70% in 2002 to 62% in 2004), this figure has remained static in the present survey. A comparison of the mean scores for men and women across the three waves confirms this pattern.

5.24 There was significant variation by age group in the 2006 survey however; respondents aged 16-24 were more likely to feel in control than most other age groups, and especially those aged 45-55 and 65+. The 16-24 age group in 2004 also reported higher levels of control than the other age groups. It may be that the factors which young people most commonly mention are having an effect on their mental health and wellbeing - namely, work and having enough money - are easier to control or, at least tolerate, than the factors mentioned by older people, that is, illness and weather.

5.25 People with a household income of over £36,400 were more likely to feel in control of factors affecting their mental health than those with an income of less than £5,200. Similarly, those who found it easy to manage on their income were more likely to feel in control than those who found it difficult. If we relate these findings back to the factors that respondents with higher and lower incomes identified as having an influence on their mental health and wellbeing, it may be the case that contact with friends and family and work pattern are easier to control than not having enough money. On the other hand, it could be the case that people who are better off are likely to feel more in control because they have fewer concerns about how to support basic day-to-day living (e.g. food and utilities bills) and can afford access to services that promote a more relaxed lifestyle, for example, holidays and alternative therapies.

5.26 People who rated their general health as bad or very bad tended to feel less in control than those who rated it as good or very good. Similarly, those who said that they had experienced a mental health problem themselves, or who had a high mental ill-health score, were more likely to feel they lacked control than other respondents. Finally, those with poor or average mental wellbeing were less likely to feel in control than those with good mental wellbeing (table 5.7).

5.27 Mediation analysis was undertaken to explore whether and to what extent, the relationship between socio-economic status and mental health, highlighted elsewhere in this report, is mediated by perceptions of control (over factors that influence mental well being). Mediational analysis is helpful in this context, as it allows us to examine what factors, if any, link socio-economic status to mental health. With respect to perceptions of control, it may be that if you are from a lower socio-economic background that this is associated with lower perceptions of control which, in turn, are associated with poor mental health. The analysis drew on four individual measures of socio-economic status ( SES), namely:

• area deprivation (as measured by SIMD and derived from postcode - 5 categories);
• annual income (5 bands: up to £5,200; £5,200- £15,600; £15,600-£26,000; £26,000-£36,000; and over £36,000);
• employment status (working or not working);
• highest professional qualification (4 bands: SLC, O Grade/ Standard Grade or equivalent; GSVQ/ SVQ/ SCOTVEC or equivalent; SEC Highers, A-levels, or equivalent); and first degree, higher degree, professional qualifications or equivalent).

5.28 A composite SES measure, comprising all 4 variables was also added to the analysis. The mental health indicators used in the analysis were the GHQ12 and WEMWBS.

5.29 Looking at the results of the analysis, perceptions of control were found to have a substantial mediating effect on the relationship between employment status and mental health - although this effect was only significant in respect to the WEMWBS measure of mental health, not the GHQ12 measure. In this case, people in paid employment reported higher perceptions of control (over factors that influence mental well being) which were in turn associated with more positive mental wellbeing. No other mediating effects were uncovered.

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