Scottish COVID-19 Mental Health Tracker Study: Wave 3 Report

3. Mental Health Outcomes

This section presents the cross-sectional and longitudinal findings of Wave 3 of the Scottish COVID-19 (SCOVID) Mental Health Tracker Study which ran from 1^st October to 4^th November 2020.

The main mental health outcomes focused on are: depressive symptoms, anxiety symptoms, suicidal thoughts, psychological distress (as measured by the GHQ-12 and another single item), and mental wellbeing. The study also included other correlates of mental wellbeing - such as loneliness, defeat, entrapment, social support, resilience, current distress (as measured by a single item), life satisfaction; these findings are reported more briefly. Only statistically significant changes and subgroup differences are reported here.

3.1 Suicidal thoughts

To measure suicidal thoughts, respondents were asked: 'how often have you thought about taking your life in the last week?', and were provided with options that ranged from "Never", "One day", "Several days", "More than half the days", "Nearly every day", and "I would rather not answer". For the purposes of this report, respondents who experienced any suicidal thoughts in the week prior to the Wave 3 questionnaire (i.e., one day or more) were included in the suicidal thoughts findings.

Wave 3 findings

Just under one tenth (9.9%) of respondents experienced suicidal thoughts within the week prior to completing the survey. The subgroups which reported higher rates of suicidal thoughts compared to their subgroup counterpoints were:

• Young adults (age 18-29 years)
• Young women
• Those with a pre-existing mental health condition

There were some differences in rates of suicidal thoughts by age and sex, illustrated in Table 3.1. In the overall sample, there were no statistically significant differences between men (10.3%) and women (9.6%) in rates of suicidal thoughts in week prior to responding to the Wave 3 questionnaire.

The oldest age group (60+ years) reported the lowest rates of suicidal thoughts (2.4%). In contrast, nearly one fifth (19.3%) of young adults (18-29 years) reported suicidal thoughts, compared to one tenth of those aged 30-59 years (10.6%). Across the age and sex subgroups, young women reported the highest rates of suicidal thoughts in the past week (20.5%), higher than that of young men (18.1%). Older women reported the lowest rates of suicidal thoughts (0.8%), lower than that of older men (4.3%).

Table 3.1: Rates of suicidal thoughts in the last week, by age and sex

Sex	Aged 18 - 29 years (n=519)	Aged 30 - 59 years (n=1114)	Aged 60+ years (n=742)	Total (n=2375)
All adults	19.3%	10.6%	2.4%	9.9%
Men	18.1%	10.3%	4.3%	10.3%
Women	20.5%	10.8%	0.8%	9.6%

Respondents' backgrounds also had a bearing on the rates of suicidal thoughts reported, and some of these are displayed in Figure 3.1. Individuals from the lower SEG reported higher rates of suicidal thoughts in the last week (12.4%) compared to those from the higher SEG (8.5%). There was also a stark difference in the reporting of suicidal thoughts in those with or without a pre-existing mental health condition; those with a pre-existing condition reported higher rates of suicidal thoughts (26.8%) than those without a pre-existing mental health condition (7.8%). There were no statistically significant differences in suicidal thoughts for those with or without a pre-existing physical health condition.

Differences in financial and home life circumstances also appear to be associated with varying rates of suicidal thoughts. Respondents who had experienced a change in working status (e.g., working from home, lost job or furloughed) reported higher rates of suicidal thoughts (11.6%) compared to those respondents who had not experienced a change (7.9%). Further, people who had dependents under five years old were more likely to report suicidal thoughts (14.9%) compared to those who had no dependents under five (9.1%). There were differences reported in rates of suicidal thoughts by caring responsibilities; carers (13.6%) were more likely to report suicidal thoughts than those with no caring responsibilities (9.0%). Finally, people with no access to outdoor space in their homes (15.5%) reported higher rates of suicidal thoughts than those with access (9.5%).

Changes across the waves

For the overall sample, there was a statistically significant increase in the proportion of respondents reporting suicidal thoughts from Wave 1 (7.3%) to Wave 2 (14.9%), and then a decrease in the proportion who reported suicidal thoughts at Wave 3 (9.4%). This change over time is illustrated in Figure 3.2.

The proportion of several subgroups reporting suicidal thoughts decreased from Wave 2 to Wave 3, including:

• 30-59 year old men and women,
• 60+ year old women,
• Individuals from the lower SEG,
• Respondents with and without a physical health condition.

Looking at age and sex, there was a reduction in rates of suicidal thoughts from Wave 2 to Wave 3 for woman aged 30-59 years (Wave 2 = 13.9%; Wave 3 = 11.7%) and for women aged 60+ years (Wave 2 = 2.3%; Wave 3 = 0.8%). Similarly, there was a reduction in suicidal thoughts for men aged 30-59 years (Wave 2 = 14.0%; Wave = 9.2%) and for men aged 60+ years (Wave 2 = 5.1%; Wave = 3.9%). Due to the loss at follow-up, it is not possible to report the changes for the 18-29 year old age group over the waves.

Looking more closely at the subgroups based on background and health, some differences in suicidal thoughts emerged (Figure 3.3). The rate of those with a pre-existing mental health condition reporting suicidal thoughts in the week prior decreased from 42.9% in Wave 2 to 38.3% in Wave 3, although this was still an overall increase from Wave 1 (20.5%). The proportion of respondents in the lower SEG reporting suicidal thoughts decreased from Wave 2 (21.8%) to Wave 3 (12.5%). Those with a pre-existing physical health condition reported lower rates of suicidal thoughts at Wave 3 (9.6%) compared to Wave 2 (15.2%), although those without a physical health condition also reported a decrease in rates of suicidal thoughts from Wave 2 (14.8%) to Wave 3 (9.3%).

Findings also suggest that other employment and household factors were associated with changes in rates of suicidal thoughts. Specifically, rates of suicidal thoughts decreased for respondents with no dependents under 16 years old from Wave 2 (15.6%) to Wave 3 (8.8%), while they stayed similar for those with dependents under 16 years (Wave 2 = 12.0%; Wave 3 = 11.5%).

3.2. Depressive symptoms

This study's findings on moderate to severe depressive symptoms are based on participants' responses to questions on the mental health measure called the Patient Health Questionnaire (PHQ-9; Kroenke et al., 2001), which assesses frequency of depressive symptoms over the previous two weeks.^[15]

Wave 3 findings

Just over one fifth (21.4%) of the overall sample met the cut-off for moderate to severe depressive symptoms.

The following groups reported higher rates of moderate to severe depressive symptoms than their subgroup counterparts:

• Young adults (age 18-29 years old)
• Women, in particular those aged 18 to 29 years old
• Those with a pre-existing mental health condition
• Those with a pre-existing physical health condition

There were clear differences in moderate to severe depressive symptoms according to age and sex, illustrated in Table 3.2. For example, women were more likely to report depressive symptoms (24.9%) than men (17.8%). In addition, just over a third (37.7%) of young adults (18-29 year olds) reported depressive symptoms, compared to a fifth (20.6%) of those in the middle age group (30-59 years) and a tenth (10.7%) of the oldest age group (60+ years). Furthermore, young women between 18-29 years old reported higher rates of depressive symptoms at 44.1%, compared to 31.3% of men in the same age group.

Table 3.2: Rates of moderate to severe depressive symptoms[16] by age and sex

Sex	Aged 18- 29 years (n=565)	Aged 30- 59 years (n=1165)	Aged 60+ years (n=765)	Total (n=2495)
All adults	37.7%	20.6%	10.7%	21.4%
Men	31.3%	16.2%	9.6%	17.8%
Women	44.1%	24.6%	11.8%	24.9%

Beyond age and sex, respondents' backgrounds also had a bearing on the likelihood of reporting moderate to severe depressive symptoms, illustrated in Figure 3.4. Respondents in the lower SEG reported higher rates of depressive symptoms (25.8%) compared to those in the higher SEG (18.9%).

This wave of the study also offers insight into how an individual's health may be associated with depressive symptoms. Around two thirds of respondents with a pre-existing mental health condition reported depressive symptoms (62.5%), compared to just under one sixth of those without a pre-existing condition (15.2%). Respondents with a pre-existing physical health condition reported higher rates of depressive symptoms (27.6%) than those with no pre-existing physical health condition (20.0%).

Differences in financial and home life circumstances also appear to be associated with varying rates of depressive symptoms, and indicate that those living with greater financial uncertainty or added responsibilities at home may be a greater risk for depressive symptoms. For example, respondents who reported a change to their working status (e.g., furloughed, lost job or reduction in pay) experienced higher rates of depressive symptoms (24.9%) than those that had experienced no change in their working status (18.7%). Those with dependents under five years old (28.6%) reported higher rates of depressive symptoms compared to those with no dependents under five (20.9%). Respondents that had any unpaid caring responsibilities (30.1%) reported higher rates of depressive symptoms than those with no additional caring responsibilities (19.3%). Finally, people with no access to outdoor space in their homes (36.6%) reported higher rates of moderate to severe depressive symptoms than those with access (20.1%).

Changes across the waves

Looking at respondents who had completed every wave, the change in rates of moderate to severe depressive symptoms was not statistically significant from Wave 2 (22.0%) to Wave 3 (21.4%), although rates for Wave 2 and Wave 3 were higher than for Wave 1 (18.6%), see Figure 3.5.

A number of subgroups saw changes to rates of moderate to severe depressive symptoms from Wave 2 to Wave 3, including:

• Men aged 30-59 and 60+ years both reported a decrease in rates of depressive symptoms
• Respondents with a physical health condition reported a decrease in their rates of depressive symptoms

Some differences by age and sex from Wave 2 to Wave 3 were evident. There were no statistically significant changes in rates of depressive symptoms for women aged 30-59 years (Wave 2 = 25.1%; Wave 3 = 25.5%), while for women aged 60+ years rates increased (Wave 2 = 10.5%; Wave 3 = 12.1%). Rates of depressive symptoms for 30-59 year old men decreased from Wave 2 (18.5%) to Wave 3 (15.0%), and for the 60+ year old men (Wave 2 = 12.9%; Wave 3 = 9.2%). Due to the loss at follow-up, it is not possible to report the changes for the 18-29 year old age group over the waves.

Looking more closely at changes in moderate to severe depressive symptoms by health and background factors, some differences emerged (see Figure 3.6). Those with a pre-existing mental health condition reported higher rates of depressive symptoms at Wave 2 (62.7%) and Wave 3 (66.6%) compared to Wave 1 (53.0%). Similarly, a higher proportion of the low SEG group reported depressive symptoms at Wave 2 (26.8%) and Wave 3 (25.7%) compared to Wave 1 (20.2%). Additionally, respondents with a physical health condition reported a decrease in their rates of depressive symptoms from Wave 2 (34.4%) to Wave 3 (29.3%).

There were changes between Wave 2 and Wave 3 in rates of moderate to severe depressive symptoms by household factors. For example, for respondents with dependents under 16 years old, rates of depressive symptoms increased from Wave 2 (18.8%) to Wave 3 (24.8%), compared to those with no dependents, whose rates decreased from Wave 2 (22.8%) to Wave 3 (20.5%). Individuals with caring responsibilities reported a decrease in their depressive symptoms from Wave 2 (28.4%) to Wave 3 (24.9%), compared to those with no caring responsibilities whose rates of depressive symptom remained the same at Wave 2 and Wave 3 (21.0%).

3.3. Anxiety symptoms

Anxiety symptoms were assessed using the mental health measure called the Generalised Anxiety Disorder (GAD-7; Spitzer et al., 2006) scale, which asks about frequency of anxiety symptoms in the last 2 weeks. For the purposes of this report, the clinical cut-off for moderate to severe anxiety (score ≤ 10) was reported, indicating anxiety symptoms that may require further treatment.

Wave 3 findings

The Wave 3 cross-sectional data, including the additional booster sample, indicated that just over one sixth (16.2%) of respondents reported moderate to severe anxiety symptoms.

A number of subgroups reported higher rates of moderate to severe anxiety symptoms compared to their subgroup counterpoints, specifically:

• Young adults (18-29 years old)
• Women
• Those with a pre-existing mental health condition
• Those from the lower SEG

Looking more closely at the findings there were differences in anxiety symptoms according to sex and age, displayed in Table 3.3. For example, when comparing sex only, women reported higher rates of anxiety symptoms (19.2%) than men (12.9%). There were also differences by age group, with 28.0% of young adults (18-29 year olds) reporting anxiety symptoms, compared to 15.5% of 30-59 year olds and 8.4% of 60+ year olds.

When looking at groups by both age and sex, further differences in the likelihood for experiencing moderate to severe anxiety arise. For example, young women (18-29 years) reported higher rates of anxiety symptoms (35.4%) than young men (20.8%). Older women (60+ years) reported the lowest rates of anxiety symptoms (7.0%) of the age and sex subgroups, followed by the rate of older men (9.8%).

Table 3.3: Rates of moderate to severe anxiety symptoms by age and sex

Sex	Aged 18- 29 years (n=564)	Aged 30- 59 years (n=1166)	Aged 60+ years (n=765)	Total (n=2495)
All adults	28.0%	15.5%	8.4%	16.2%
Men	20.8%	10.9%	9.8%	12.9%
Women	35.4%	19.7%	7.0%	19.2%

Beyond age and sex, respondents' health and financial circumstances also had a bearing on the likelihood of reported rates of moderate to severe anxiety, illustrated in Figure 3.7. A higher proportion of respondents in the lower SEG (19.7%) experienced anxiety symptoms than those in the higher SEG (14.0%). Additionally, over half of those with a mental health condition (52.4%) met the cut-off for moderate to severe anxiety, compared to only 10.6% of those with no mental health condition. Additionally, respondents with a physical health condition experienced higher rates of anxiety symptoms (20.6%) than those with no physical health condition (15.1%).

Differences in working life, home life, and carer circumstances appeared to be associated with rates of moderate to severe anxiety symptoms. For example, respondents whose working situation had changed during the pandemic (e.g., furloughed, lost job) reported higher anxiety rates (19.7%) than those with no change (13.4%). Shifting focus to home-life circumstances, respondents living in households with dependents under five years old reported higher rates of anxiety (23.4%) compared to those who had no dependents under five years (15.8%). Additionally, respondents who had caring responsibilities had a higher likelihood of experiencing anxiety symptoms (22.5%) than those who did not have any caring responsibilities (14.5%). Finally, people with no access to outdoor space in their homes (26.3%) reported higher rates of moderate to severe anxiety symptoms than those with access (15.2%).

Changes across the waves

Looking at the sample as a whole, there were no statistically significant changes in rates of moderate to severe anxiety symptoms from Wave 2 (14.9%) to Wave 3 (14.7%), although both were higher than Wave 1 (13.0%), see Figure 3.8.

Between Waves 2 and 3 there was an increase in the proportion of the following subgroups reporting moderate to severe anxiety symptoms:

• Respondents with a pre-existing mental health condition

Looking at age and sex, women aged 30-59 years reported similar rates of anxiety at Wave 2 (20.2%) and Wave 3 (20.1%), as did men aged 30-59 years at Wave 2 (10.8%) and Wave 3 (9.5%). For the 60+ age group, there was an increase in anxiety symptoms for women from Wave 2 (6.2%) to Wave 3 (7.2%), as well as for older men from Wave 2 (8.4%) to Wave 3 (9.5%). Due to the loss at follow-up, it is not possible to report the changes for the 18-29 year old age group over the waves.

Some changes in rates of moderate to severe anxiety were found looking at background factors and health of respondents, illustrated in Figure 3.9. For example, the lower SEG reported an increase in rates of anxiety from Wave 1 (14.5%) to Wave 3 (20.1%), although there were no statistically significant changes from Wave 2 (21.3%) to Wave 3 (20.1%). In contrast, rates of anxiety for the higher SEG remained similar across the waves (Wave 1: 12.1%; Wave 2: 11.4%; Wave 3: 11.7%). Those with a pre-existing mental health condition reported an increase in rates of anxiety from Wave 1 (45.7%) to Wave 2 (51.1%) to Wave 3 (54.5%).

Additionally, those who were key workers reported their rates of anxiety decreased from Wave 1 (16.7%) to Wave 2 (14.9%) and Wave 3 (14.9%), bringing their rates in line with those who were not a key worker (e.g., Wave 3: 14.6%) as well as with the overall sample (Wave 3: 14.7%). There were no other statistically significant changes from Wave 1 or Wave 2 to Wave 3 for any further subgroups.

3.4. General Health Questionnaire

The General Health Questionnaire (GHQ-12) is a psychological measure that assesses psychological distress and mental ill-health in the previous two weeks, including sleep, self-esteem, stress, despair, depression, and confidence. In this report, as consistent with other mental health research studies (McLean et al., 2018), GHQ-12 scores of four or more are reported because this cut-off is deemed a high GHQ-12 score and indicates the presence of a possible psychiatric disorder.

Wave 3 findings

In the Wave 3 cross-sectional data, including the additional booster sample, nearly one third (32.0%) of the sample recorded a high GHQ-12 score. The groups that had elevated rates of high GHQ-12 scores compared to their subgroup counterpoints included:

• Young adults (18-29 years)
• Women (18-29 years)
• Those with a pre-existing mental health condition
• Those from the lower SEG

There were clear differences in rates of high GHQ-12 scores by sex and age, as presented in Table 3.5. Specifically, women were more likely to have a high GHQ-12 score (36.6%) than men (27.0%). Additionally, just under half (49.4%) of the younger age group (18-29 year olds) reported a high GHQ-12 score, compared to 31.9% of 30-59 year olds and 19.2% of 60+ year olds. Young women were also more likely to have a high GHQ-12 score (57.3%) compared to young men (41.5%). Across all the age and sex subgroups, older men reported the lowest rates of high GHQ-12 scores (18.0%), followed by older women (20.4%).

Table 3.4: Rates of high psychological distress (high GHQ-12 score) by age and sex

Sex	Aged 18- 29 years (n=565)	Aged 30- 59 years (n=1166)	Aged 60+ years (n=765)	Total (n=2495)
All adults	49.4%	31.9%	19.2%	32.0%
Men	41.5%	25.6%	18.0%	27.0%
Women	57.3%	37.6%	20.4%	36.6%

Beyond age and sex, respondents' backgrounds and health also had a bearing on the likelihood of reporting a high GHQ-12 score (Figure 3.10). Specifically, individuals in the lower SEG were more likely to report a high GHQ-12 score (36.0%) than those from the higher SEG (29.6%). Two thirds (67.4%) of those with a pre-existing mental health condition recorded a high GHQ-12 score, compared to just over a quarter (26.6%) of those with no pre-existing mental health condition. Additionally, those with a pre-existing physical health condition reported higher rates of high GHQ-12 (37.7%) than those with no pre-existing physical health condition (30.6%).

Differences in home life and carer circumstances also appear to be associated with varying rates of high GHQ-12 scores. For example, respondents whose household had dependents under five years old were more likely to have high GHQ-12 scores (43.0%) than those without dependents under five years (31.1%). In addition, 43.6% of respondents with caring responsibilities recorded a high GHQ-12 score, which was higher than those with no caring responsibilities (29.3%).

Additionally, people whose working status had changed during the pandemic (i.e., lost job, furloughed) reported higher rates of high GHQ-12 (38.9%) than those with no change (26.2%). Further, people who had no access to outdoor space reported higher rates of high GHQ-12 (44.5%) than those with access to outdoor space at home (30.9%).

Changes across the waves

Analysis suggests that the proportion of respondents who met the GHQ-12 cut-off for a possible psychiatric disorder increased from Wave 2 (24.8%) to Wave 3 (27.8%), as illustrated in Figure 3.11.

An increase in rates of high GHQ-12 from Wave 2 to Wave 3 were found for a particular subgroups:

• Respondents with a pre-existing mental health condition
• Men aged 30-50 years and men aged 60+ years

Looking more closely at changes in rates of GHQ-12 by age and sex, some differences emerge. Men aged 30-59 years reported an increase in rates of high GHQ-12 from Wave 2 (24.4%) to Wave 3 (27.0%), and men aged 60+ also had an increase in rates of high GHQ-12 from Wave 2 (15.4%) to Wave 3 (18.2%). In contrast, for women aged 30-59 years and 60+ years there were no statistically significant changes in rates of high GHQ-12 from Wave 2 to Wave 3 (30-59 years: 35.3% at Wave 2 and 35.9% at Wave 3) (60+ years: 19.0% at Wave 2 and 19.2% at Wave 3), although for both age groups, these rates were lower than at Wave 1 (30-59 years: 39.3%; 60+ years: 24.3%). Due to the loss at follow-up, it is not possible to report the changes for the 18-29 year old age group over the waves.

Additionally, there were some changes in rates of high GHQ-12 scores by health factors, as displayed in Figure 3.12. The proportion of respondents with a pre-existing mental health condition reporting high GHQ-12 scores increased from Wave 2 (50.2%) to Wave 3 (65.6%). In addition, the proportion of those with no caring responsibilities reporting high GHQ-12 scores increased from Wave 2 (22.4%) to Wave 3 (26.2%), whereas the proportion of those with caring responsibilities decreased from Wave 2 (39.6%) to Wave 3 (37.5%).

3.5. Mental wellbeing

Mental wellbeing is an important indicator of mental health and can indicate how protected an individual may be from mental health problems such as depression and anxiety. The SCOVID study measured a respondent's mental wellbeing using the Short Warwick-Edinburgh Mental Well-being Scale (SWEMWBS)^[17]. This scale measures the frequency of thoughts and feelings of mental wellbeing over the past two weeks; it includes items such as feelings of optimism, feelings of being useful, and feeling that one is thinking clearly.

For the SWEMWBS, a score is created for each individual by adding together their responses to each question. The scores range from 7 (indicating very low wellbeing) to 35 (indicating very high wellbeing), therefore a higher score suggests better mental wellbeing. The scale was not designed to identify individuals with exceptionally high or low levels of mental wellbeing so cut off points have not been developed. Therefore, throughout this section average mean scores are reported for each of the subgroups to compare levels of mental wellbeing between groups.

Wave 3 findings

The Wave 3 cross-sectional data, including the additional booster sample, indicated that the average mean score for mental wellbeing was 21.50 out of 35.

In looking more closely at the data, some differences on mental wellbeing by age and sex emerge (see Table 3.5). The data suggests that respondents in the older age group (60+ years old) reported a higher mental wellbeing mean (23.34) than those aged 30-59 years (21.19), and compared to the younger age group (18-29 years), who scored the lowest (19.67). Further, mean mental wellbeing scores among men were higher (21.77) than among women (21.26).

Table 3.5: Mean mental wellbeing scores by age and sex

Sex	Aged 18- 29 years (n=565)	Aged 30- 59 years (n=1166)	Aged 60+ years (n=765)	Total (n=2495)
All adults	19.67	21.19	23.34	21.50
Men	20.05	21.70	23.20	21.77
Women	19.29	20.72	23.46	21.26

Beyond age and sex, differences in respondents' backgrounds were associated with different mean SWEMWBS scores, as illustrated in Figure 3.13. For example, respondents with a pre-existing mental health condition (17.14) scored the lowest of all the subgroups, including lower than those who indicated having no pre-existing mental health condition (22.16). Additionally, those with no pre-existing physical health conditions recorded higher mental wellbeing scores (21.63) than those with a pre-existing physical health condition (20.96). Finally, respondents in the higher SEG scored higher (21.96) on the mental wellbeing scale than those in the lower SEG (20.70).

Differences in financial and home life circumstances also appear to be associated with mental wellbeing scores and indicate that those who have fewer responsibilities and more financial security have higher mental wellbeing. For example, people with no unpaid caring responsibilities had higher mean mental wellbeing scores (21.77) than those who are carers (20.32). Furthermore, those who did not experience any change in their working status reported higher mental wellbeing (21.86) than those who experienced a change in their working status, such as being furloughed or losing one's job (21.06). Finally, those with access to outdoor space at home reported higher mental wellbeing (21.65) than those with no access to outdoor space (19.71).

Changes across the waves

Analysis suggests that there were no statistically significant changes in average mental wellbeing for the overall sample over the waves (see Figure 3.14); at Wave 3 the average mental wellbeing score was 21.94, similar to Wave 1: 21.96 and Wave 2: 21.94.

A change in levels of mental wellbeing from Wave 2 to Wave 3 was found for a number of subgroups, specifically:

• For men and women aged 60+ levels of mental wellbeing decreased
• For respondents with caring responsibilities mental wellbeing decreased
• For key workers levels of mental wellbeing increased

There were some differences over the waves in mental wellbeing by age and sex. Men aged 30-59 years old reported no change in their levels of mental wellbeing from Wave 2 (21.76) to Wave 3 (21.74), whereas there was a decrease in mental wellbeing for older men (60+ years) from Wave 1 (23.88) to Wave 2 (23.28). Additionally, although there was also a decrease in levels of mental wellbeing for women aged 30-59 years from Wave 2 (20.93) to Wave 3 (20.60), and for women aged 60+ (Wave 2: 23.91; Wave 3: 23.52), these changes were not statistically significant. Due to the loss at follow-up, it is not possible to report the changes for the 18-29 year old age group over the waves.

There were some changes in levels of mental wellbeing over the waves by background and health factors (Figure 3.15). Respondents from the lower SEG had an increase in mental wellbeing from Wave 1 (20.38) to Wave 3 (20.81), although there was no statistically significant change for this subgroup from Wave 2 (20.79). In contrast, the high SEG group reported a decrease in their levels of mental wellbeing from Wave 1 (22.76) to Wave 3 (22.45), although this remained similar to Wave 2 levels (22.42). Levels of mental wellbeing also increased for those with a pre-existing mental health condition from Wave 1 (15.91) to Wave 3 (16.91), although their level of mental wellbeing did not change significantly from Wave 2 (16.85). Levels of mental wellbeing remained relatively similar (albeit with a decrease) for those with no pre-existing mental health condition across the waves (Wave 1: 22.86; Wave 2: 22.62; Wave 3: 22.64).

There were some further changes in mental wellbeing looking at caring and employment subgroups. For example, those with caring responsibilities reported a decrease in their mental wellbeing from Wave 2 (21.72) to Wave 3 (21.20), compared to those with no caring responsibilities (Wave 2: 21.85; Wave 3: 22.00). Additionally, respondents who reported being a key worker had an increase in their mental wellbeing from Wave 2 (21.17) to Wave 3 (22.33), and those who were not a key worker found their mental wellbeing decreased (Wave 2: 22.02; Wave 3: 21.74).

3.6. Other mental wellbeing outcomes

Wave 3 of the SCOVID study assessed a range of other indicators and correlates of mental health and wellbeing. These included feelings of defeat, entrapment, loneliness, life satisfaction, and current distress (as measured by a single item). This section provides a brief overview of these measures. Findings suggest that the subgroups most at risk of poor mental health and wellbeing (compared to their subgroup counterpoints) at Wave 3 are:

• Young adults (18-29 years)
• Women
• Those with a pre-existing mental health condition
• Those in the lower SEG

3.6.1 Loneliness

In Wave 3 of the SCOVID study, we measured loneliness using the UCLA Loneliness Scale (Hughes et al., 2014), which assesses three aspects of loneliness: lacking companionship, feeling left out, and feeling isolated from others. We asked people how often they felt each of these aspects of loneliness in the week prior to responding to the Wave 3 questionnaire. A total loneliness score was created by adding the responses to each question together, creating a score between 3, indicating no loneliness, and 9, indicating high levels of loneliness. As there is no cut-off score demarcating high and low levels of loneliness, mean scores are used to compare the different subgroups in terms of perceived levels of loneliness.

Wave 3 findings

The Wave 3 cross-sectional data, including the additional booster sample, found the mean score for loneliness for the whole sample was 5.18 out of a maximum of 9. There were a number of clear differences in terms of levels of loneliness by age and sex. For example, young adults (18-29 years) had the highest levels of loneliness (5.50), compared to 30-59 year olds (4.92) and 60+ year olds (4.40). Additionally, women reported higher levels of loneliness (5.06) than men (4.70).

Subgroup analyses indicated that respondents' background and health may also be associated with higher levels of loneliness (see Figure 3.16). Specifically, respondents in the lower SEG had higher loneliness scores (5.18) than those in the higher SEG (4.73). Individuals with a pre-existing mental health condition also reported higher levels loneliness during Wave 3 (6.09) compared to those with no pre-existing mental health conditions (4.71). Additionally, people with a pre-existing physical health condition reported experiencing higher levels of loneliness (5.22) than those with no pre-existing physical health condition (4.82).

Changes across the waves

For the whole sample, feelings of loneliness increased from Wave 2 (4.59) to Wave 3 (4.73), although levels of loneliness remained lower at Wave 3 than at Wave 1 (4.86).

Some subgroups reported an increase in loneliness from Wave 2 to Wave 3, including:

• People with a pre-existing mental health condition
• Respondents living alone
• Women aged 60+

Looking at age and sex, women aged 60+ had the largest increase in levels of loneliness from Wave 2 (4.32) to Wave 3 (4.61). Men aged 60+ reported an increase as well, although not as large as their female counterparts (Wave 2: 4.12; Wave 3: 4.21). Levels of loneliness among women aged 30-59 years also increased from Wave 2 (4.93) to Wave 3 (5.10) whereas men aged 30-59 years reported no statistically significant change in loneliness from Wave 2 (4.73) to Wave 3 (4.76). Due to the loss at follow-up, it is not possible to report the changes for the 18-29 year old age group over the waves.

Those who had a pre-existing mental health condition reported that their loneliness increased from Wave 2 (5.66) to Wave 3 (6.19), compared to those with no pre-existing mental health condition, whose levels of loneliness remained stable (Wave 2: 4.42; Wave 3: 4.50). Additionally, people who lived alone reported that their loneliness had increased from Wave 2 (4.98) to Wave 3 (5.34).

3.6.2 Defeat and entrapment

Feelings of defeat and entrapment are important indicators of mental health, and have been associated with depression, anxiety, and suicidal thoughts. Defeat is a feeling of powerlessness in life and entrapment is a feeling of being trapped by circumstances or your own thoughts. In the Wave 3 SCOVID study, we assessed defeat using the short form of the Defeat Scale (Gilbert & Allan, 1998; Griffiths et al., 2015) and entrapment using the short form of the Entrapment Scale (Gilbert & Allan, 1998; De Beurs et al., 2020). All respondents are given a score for each measure by adding together each question response, with 0 indicating no feelings of defeat or entrapment and 16 indicating a very high level of feelings of defeat and entrapment.

There are no cut-off scores for defeat and entrapment measures to demarcate high or low levels of defeat and entrapment, therefore an average mean score is used to compare differences between the subgroups.

Wave 3 findings

In the Wave 3 cross-sectional data, including the additional booster sample, the overall mean score was 3.76 for defeat and 3.42 for entrapment.

There were some differences in relation to age and sex on feelings of defeat and entrapment; young adults and women were at higher risk for feeling defeated and entrapped. More specifically, young adults' (18-29 years) mean scores on defeat (4.79) were higher than those aged 30-59 years (4.06) and those aged 60+ (2.55). Similarly, young adults (18-29 years) scored higher on entrapment (4.73) than those aged 30-59 years (3.63), and those aged 60+ years (2.06). Women reported higher mean scores on defeat (4.22) than men (3.26), as well as higher levels of feeling entrapped (3.82) than men (2.98).

Other background and health factors appear to be associated with differences in feelings of defeat and entrapment; those in the lower SEG and those who had a pre-existing mental health condition were at higher risk for feeling defeated and entrapped. More specifically, respondents in the lower SEG felt more defeated (4.20) than those in the higher SEG (3.50) and scored higher on entrapment (3.83) than those in the higher SEG (3.18). Moreover, respondents who indicated having a mental health condition scored higher on defeat (8.08) than those with no pre-existing mental health condition (3.11), as well as reporting a higher mean entrapment score (8.15) than of those with no pre-existing mental health diagnosis (2.70).

Changes across the waves

For the whole sample, average defeat scores increased from Wave 2 (3.55) to Wave 3 (3.71), and average entrapment scores also increased from Wave 2 (3.16) to Wave 3 (3.41). Several groups reported that their average defeat and entrapment scores had increased from Wave 2 to Wave 3:

• Women aged 30-59 years
• Those in the higher SEG
• Those with a pre-existing mental health condition
• Those with no physical health condition (just entrapment scores)

Looking more closely at subgroup changes in defeat and entrapment, for women aged 30-59 years defeat scores increased from Wave 2 (4.61) to Wave 3 (4.83), and their entrapment scores also increased from Wave 2 (3.96) to Wave 3 (4.46), with Wave 3 being similar to Wave 1 (defeat: 4.82; entrapment: 4.46). For men aged 60+, levels of defeat increased from Wave 2 (2.10) to Wave 3 (2.37).

People with a pre-existing mental health condition reported that their feelings of defeat had increased from Wave 2 (7.77) to Wave 3 (8.74), and their entrapment scores also increased from Wave 2 (7.32) to Wave 3 (8.18), which was higher than at Wave 1 (defeat: 8.04; entrapment: 7.84). This was in contrast to those with no pre-existing mental health condition, who reported no statistically significant changes to defeat and entrapment over the waves.

From Wave 2 to Wave 3, respondents from the higher SEG reported an increase in levels of defeat (Wave 2: 3.16; Wave 3: 3.46) and entrapment (Wave 2: 2.86; Wave 3: 3.43). This was in contrast to respondents from the lower SEG, whose levels of entrapment decreased (Wave 2: 3.70; Wave 3: 3.38).

Additionally, respondents with no pre-existing physical health condition reported that their levels of entrapment, but not defeat, increased from Wave 2 (4.57) to Wave 3 (4.79).

3.6.3 Resilience

How resilient a person is can be important for understanding their capacity to cope with difficulties and recover from hardship and stress. Being resilient can be protective for mental health problems, including depression, anxiety, and suicidal thoughts. In Wave 3 of the SCOVID study, resilience was assessed using 4 questions from the Brief Resilience Scale (BRS; Smith et al., 2008).

Respondents received a total score by summing the responses to each question; scores range from 4, indicating very low resilience, to 20, indicating very high resilience. As there are no cut-off scores to demarcate levels of high and low resilience, mean scores were used to compare the different subgroups on resilience average. Respondents were asked to rate their perceptions of their resilience in the 7 days prior to responding to the Wave 3 questionnaire.

Wave 3 findings

In the Wave 3 cross-sectional data, including the additional booster sample, the mean resilience score was 11.12 (out of a possible 20) for the whole sample.

The subgroup analyses reveal some differences in mean resilience scores by age and sex. Both women and men felt their resilience had decreased during lockdown, although women reported lower mean resilience than men overall. Specifically, mean resilience scores were higher for men (11.50) compared to women (10.71). Levels of resilience varied by age group, with the older age group (60+ years) reporting the highest levels of resilience (12.05), followed by 30-59 year olds (10.57), and young adults reported the lowest levels of resilience (9.11).

Respondents' perceptions of their resilience and ability to cope with stress varied by background and health status. For example, levels of resilience were higher for those in a higher SEG (11.30), compared to the lower SEG (10.74). Individuals with a pre-existing mental health condition also reported lower resilience (7.12) compared to those with no mental health condition (11.62).

Changes across Waves

Across the whole sample, levels of resilience did not change from Wave 2 (10.74) to Wave 3 (10.74). Analysis suggests that levels of resilience decreased for women aged 60+ years from Wave 2 (12.49) to Wave 3 (12.25), as well as for men aged 60+ years from Wave 2 (12.24) to Wave 3 (11.94). For men age 30-59 years, resilience increased (Wave 2: 10.43; Wave 3: 10.79), whereas for women of this age group it remained similar (Wave 2: 10.08; Wave 3: 10.06). For those with a pre-existing mental health condition, levels of resilience increased across the waves (Wave 1: 5.73; Wave 2: 6.76; Wave 3: 7.28), whereas for those with no pre-existing mental health condition, levels of resilience remained similar (Wave 1: 11.36; Wave 2: 11.36; Wave 3: 11.29).

3.6.4 Social support

Questions in the Wave 3 SCOVID study assessed sources of emotional and physical support and feelings of connection to those around the respondents. Good support networks are important to protect against poor mental health, including against depression, anxiety, and suicidal thoughts. Social support was measured using four questions from the ENRICHD Social Support Instrument (ESSI; Mitchel et al., 2003), which assesses how often an individual feels they currently have emotional and physical support.

Responses are summed into a total score, with a potential range from 4, indicating low social support, to 20, indicating very high social support. Therefore, higher scores represent higher levels of social support.

Wave 3 findings

In the Wave 3 cross-sectional data, including the additional booster sample, the mean score for levels of social support was 14.49 for the whole sample. There were some differences in perceptions of social support by age and sex. Interestingly, at Wave 3 young adults (18-29 years) reported the highest levels of social support (16.18), higher than 30-59 year olds (13.97) and individuals aged 60+ years (14.86). There were no statistically significant differences in social support between men (14.59) and women (14.38).

Respondents' background and health status were also associated with different levels of social support, with those most at risk of negative outcomes such as depression and anxiety reporting lower social support. Specifically, individuals in the higher SEG reported more social support (15.01) than those in the lower SEG (13.37). Additionally, individuals with no pre-existing mental health condition reported higher levels of social support (11.62) compared to those with a pre-existing mental health condition (7.12). This suggests that those with a pre-existing mental health condition, in particular, have fewer sources of social support, a key protective factor for poor mental health.

Changes across Waves

For the whole sample, social support average scores increased from Wave 2 (14.40) to Wave 3 (14.69). Analysis suggests that levels of social support decreased for women aged 60+ years from Wave 2 (15.25) to Wave 3 (14.87), as well as for men aged 60+ years from Wave 2 (15.38) to Wave 3 (14.86).

Respondents with a pre-existing physical health condition reported that their social support decreased from Wave 2 (13.96) to Wave 3 (13.74), and those without a physical health conditions reported an increase in social support from Wave 2 (14.51) to Wave 3 (14.93).

3.6.5 Distress

Distress is a feeling of acute anxiety and pain, and it is a correlate of current and future mental wellbeing. To measure levels of current distress, we asked respondents to indicate on a 10-point scale how distressed they had felt the week prior to answering the Wave 3 questionnaire, with 0 indicating feeling no distress, to 10 indicating feeling extreme distress. As there is no cut-off for high and low distress, the subgroups are compared on their average mean scores.

Wave 3 findings

For the Wave 3 cross-sectional data, including the additional booster sample, average level of distress for the overall sample was 2.71. Different levels of distress were found for age and sex. Specifically, women (3.15) reported higher levels of distress than men (2.24). Additionally, levels of distress varied across the different age groups, with young adults (18-29 year olds) reporting the highest levels of distress (3.86), followed by 30-59 year olds (2.78), and then the 60+ group (1.76), who reported the lowest.

Levels of distress varied according to respondents' mental health. Of all the subgroups, the highest levels of distress were seen in those with a pre-existing mental health condition (4.80). In contrast the mean level of distress in those with no previous mental health diagnosis was 2.40.

Changes across Waves

For the whole sample, the average level of distress increased from Wave 2 (2.54) to Wave 3 (2.76).

Looking closer at changes in distress, some subgroup changes emerge. For example, for women aged 30-59 years, levels of distress increased from Wave 2 (2.90) to Wave 3 (3.24), whereas men aged 30-59 years remained similar from Wave 2 (2.18) to Wave 3 (2.28). For older women (60+ years) levels of distress increased from Wave 2 (1.71) to Wave 3 (1.92). For respondents with a pre-existing mental health condition, distress increased from Wave 2 (4.52) to Wave 3 (4.92).

3.6.6 Life satisfaction

Respondents were also asked about their current life satisfaction with the question 'All things considered, how satisfied are you with your life as a whole nowadays?' They were asked to rate their life satisfaction on a scale from 0, indicating extremely dissatisfied to 10, indicating extremely satisfied. As there is no cut-off for high and low life satisfaction, the subgroups are compared on their average mean scores.

Wave 3 findings

In the Wave 3 cross-sectional data, including the additional booster sample, the average mean life satisfaction for the sample was 6.21.

Looking at life satisfaction by age and sex, men reported higher life satisfaction (6.32) than women (6.12). Young adults (18-29 year old) and 30-59 year olds reported the same life satisfaction scores (5.95), which was lower than the 60+ year old group (6.80).

Subgroup analyses indicated that respondents' background and health may also be associated with higher levels of life satisfaction, as illustrated in Figure 3.17. Specifically, respondents in the higher SEG reported higher mean life satisfaction scores (6.41) than those in the lower SEG (5.86). Additionally, people without a pre-existing physical health condition reported experiencing higher life satisfaction (6.33) than those with a pre-existing physical health condition (5.69). Individuals with no pre-existing mental health condition reported higher life satisfaction during Wave 3 (6.51) compared to those with a pre-existing mental health condition (4.24).

Changes across Waves

For the overall sample, levels of life satisfaction decreased from Wave 2 (6.14) to Wave 3 (5.98). Looking at changes in life satisfaction by subgroups, women aged 30-59 years reported a decrease in life satisfaction from Wave 2 (6.15) to Wave 3 (5.87), and women aged 60+ years also reported a decrease in life satisfaction from Wave 2 (7.04) to Wave 3 (6.86). For older men (60+ year old) there was also a decrease from Wave 2 (6.96) to Wave 3 (6.72).