The relationship between leisure and mental wellbeing in

middle-aged women who care for more than 20 hours per week:

A secondary analysis using data from a national survey

Angela Clarke

Submitted for the Degree of

Doctor of Psychology

(Clinical Psychology)

School of PsychologyFaculty of Health and Medical Sciences

University of SurreyGuildford, SurreyUnited KingdomSeptember 2018

Page 1 of 197

Abstract

Background: Research has found that carers have limited leisure engagement

compared with non-carers and they have reduced mental wellbeing. Middle aged

women who are intensive carers (>20 hours a week) are at particular risk and were

therefore the focus for this study.

Objectives: The cross-sectional part of this study aimed to explore whether there

was an association between leisure time satisfaction, variety, sporting engagement

and frequency of leisure with carer wellbeing. The longitudinal part of this study

aimed to explore whether becoming an intensive carer was associated with reduced

leisure engagement and reduced wellbeing. Further, whether leisure engagement

predicts wellbeing.

Method: This study used data from a national UK study (UKLHS) that stratified

sampling across the country. Data was collected annually and waves two and five

were used for this study as they included a module about leisure and culture.

Wellbeing was assessed through the GHQ-12. Secondary analysis of this data

included general linear modelling and chi square.

Results: Generally, cross sectional hypotheses were supported although frequency of

leisure engagement was less relevant for wellbeing than variety and satisfaction (the

latter of which explained 12% of the variance). Individuals who did sport had better

wellbeing than those who did not. Individuals who became carers did not reduce

their leisure engagement more than non-carers. Change in satisfaction and variety

predicted change in wellbeing but change in frequency did not. Unexpectedly,

Page 2 of 197

individuals who were not carers at wave two, but were at wave five had poorer

wellbeing at both time points compared to the non-carers.

Conclusions: Leisure is a key contributor to emotional wellbeing, in particular,

carer’s satisfaction with the amount of leisure time they have and whether they

engage in physical activities. This has important implications for services that work

with carers at a local level, and at a policy level.

Page 3 of 197

AcknowledgementsThis has not been an easy endeavour and therefore I owe huge thanks to the many

individuals who offered help, support, and expertise throughout the completion of

this doctorate including all of my supervisors along the way.

Of particular note are my supervisors, Linda Morison and Kate Gleeson. They have

both endured my distress, supported me through the difficulties, and enthused at the

work as it came closer and closer to completion. Their wealth of experience has been

both practically, and emotionally invaluable and without either of them this project

would not have been the same. I thank them both wholeheartedly and am truly

grateful for all their time, energy, patience and enthusiasm.

I would also like to thank Sarah Warrell Phillips for all of her peer supervision and

support throughout the research project.

I would like to that my parents as their support over the years has been invaluable.

Without their unwavering practical and emotional support, I would not even have

made it onto the doctorate in the first place.

Finally, I would like to thank my partner, Michael King, for being a rock of strength.

He has been there to listen to my difficulties, bounce ideas off, and support me in all

my problem solving endeavours.

Page 4 of 197

Table of contents

Abstract......................................................................................................................................Acknowledgements....................................................................................................................Table of contents........................................................................................................................Declaration.................................................................................................................................Overview of portfolio.................................................................................................................

Empirical Paper..........................................................................................................................Statement of journal choice........................................................................................................Abstract......................................................................................................................................Introduction................................................................................................................................Hypotheses...............................................................................................................................Method.....................................................................................................................................Results: Cross sectional study..................................................................................................Results: Longitudinal study......................................................................................................Discussion................................................................................................................................References................................................................................................................................List of Appendices:..................................................................................................................

Literature review....................................................................................................................Statement of journal choice....................................................................................................Abstract..................................................................................................................................Introduction............................................................................................................................Method...................................................................................................................................Results....................................................................................................................................Discussion..............................................................................................................................Conclusion..............................................................................................................................References..............................................................................................................................

Clinical Experience................................................................................................................Table of assessments completed during training...................................................................

The relationship between leisure and mental wellbeing in middle-aged

women who care for more than 20 hours per week: A secondary analysis

using data from a national survey

By

Angela Clarke

Submitted in partial fulfilment of the degree of Doctor of Psychology (Clinical

Psychology)

School of Psychology

Faculty of Health and Medical Sciences

University of Surrey

April 2018

© Angela Clarke 2018

Page 1 of 197

Declaration

I confirm that the submitted work is my own work and that I have clearly identified and fully acknowledged all material that is entitled to be attributed to others (whether published or unpublished) using the referencing system set out in the programme handbook/other programme research guidance. I agree that the University may submit my work to means of checking this, such as the plagiarism detection service Turnitin® UK. I confirm that I understand that assessed work that has been shown to have been plagiarised will be penalised.

Signature:

Name: Angela Clarke

Date: 5/4/18

Page 2 of 197

Overview of portfolioBeing a carer is rich and rewarding, however it can also present many challenges

particularly for those providing many hours of care each week. These carers are at

risk of losing time for leisure pursuits and also of having poorer wellbeing. This

portfolio aimed to explore the relationship between leisure engagement and

wellbeing for carers who spend over 20 hours a week providing care.

The first part is an empirical paper that used secondary data analysis to answer

whether poorer leisure engagement is associated with poorer wellbeing, specifically

for women carers in their midlife. Analysis explored this relationship cross-

sectionally and longitudinally. The findings from the empirical paper suggest that

poorer leisure engagement is associated with poorer wellbeing for women. Change in

leisure participation over a three-year period predicted change in wellbeing over the

same time. Part two presents a structured literature review that aimed to critically

examine and summarise the existing literature on the extent to which leisure

influences well-being among those who spend a significant amount of time caring for

others. Poorer leisure engagement was associated with increased depression, poorer

general wellbeing, reduced positive affect, increased negative affect and fewer

positive attitudes to caregiving.

Page 3 of 197

Empirical Paper

The relationship between leisure and mental wellbeing in

middle-aged women who care for more than 20 hours per week:

A secondary analysis using data from a national survey

Word Count: 1040

Statement of journal choice

This paper will be submitted to “Social Science & Medicine” whose aim is to publish

“original research articles…to inform current research, policy and practice in all

areas of common interest to social scientists, health practitioners, and policy

makers”. It accepts articles from the field of psychology and has an interest in mental

health, as stated in the scope of the journal. This paper explores issues pertaining to

carers, who are commonly at risk of becoming mental health service users and

therefore fits within the remit of this journal. Findings are relevant to clinicians and

policy makers alike.

The impact factor of the journal is 2.32 (October 2017).

If this article is not accepted by the first choice journal, it will then be submitted to

“Health and Social Care in the Community” and “Health and Quality of Life

Outcomes”.

Page 4 of 197

Abstract

Background: Research has found that carers have limited leisure engagement

compared with non-carers and they have reduced mental wellbeing. Middle aged

women who are intensive carers (>20 hours a week) are at particular risk and were

therefore the focus for this study.

Objectives: The cross-sectional part of this study aimed to explore whether there

was an association between leisure time satisfaction, variety, sporting engagement

and frequency of leisure with carer wellbeing. The longitudinal part of this study

aimed to explore whether becoming an intensive carer was associated with reduced

leisure engagement and reduced wellbeing. Further, whether leisure engagement

predicts wellbeing.

Method: This study used data from a national UK study (UKLHS) that stratified

sampling across the country. Data was collected annually and waves two and five

were used for this study as they included a module about leisure and culture.

Wellbeing was assessed through the GHQ-12. Secondary analysis of this data

included general linear modelling and chi square.

Results: Generally, cross sectional hypotheses were supported although frequency of

leisure engagement was less relevant for wellbeing than variety and satisfaction (the

latter of which explained 12% of the variance). Individuals who did sport had better

wellbeing than those who did not. Individuals who became carers did not reduce

their leisure engagement more than non-carers. Change in satisfaction and variety

predicted change in wellbeing but change in frequency did not. Unexpectedly,

Page 5 of 197

individuals who were not carers at wave two, but were at wave five had poorer

wellbeing at both time points compared to the non-carers.

Conclusions: Leisure is a key contributor to emotional wellbeing, in particular,

carer’s satisfaction with the amount of leisure time they have and whether they

engage in physical activities. This has important implications for services that work

with carers at a local level, and at a policy level.

Page 6 of 197

Introduction

Carer Wellbeing

Providing care to a loved one is reported to be a rewarding experience that adds

positive aspects to a relationship (Szmukler et al., 1996), and improves family bonds,

love, hope and support for the person cared for (Treasure et al., 2001). The

opportunity to learn and experience reciprocity have also been identified as valuable

consequences (Stern, Doolan, Staples, Szmukler, & Eisler, 1999).

However, carers are more likely to have reduced wellbeing compared to those who

do not have a caregiving role (Cooper, Balamurali, Selwood, & Livingston, 2007;

LoGiudice et al., 1998; Mausbach, Coon, Patterson, & Grant, 2008; Schulz, O’Brien,

Bookwala, & Fleissner, 1995; Smith et al., 2014; Williamson & Schulz, 1992).

In particular, carers who spend more than 20 hours per week caring are at increased

risk of mental health difficulties when compared with people who spend less than 10

hours caring (Smith et al., 2014). Such individuals are also more likely to find that

their caring role interferes with their work and leisure. Indeed, there is a large body

of research indicating that carers often have to either reduce or cease employment

(Mosher et al., 2013; Ory, Hoffman, Yee, Tennstedt, & Schulz, 1999; Otis-Green &

Juarez, 2012), and that becoming a carer is associated with a reduction in leisure

engagement (Magliano, Fiorillo, Rosa, & Maj, 2006; Martin, 2015; Morais et al.,

2012; Rochette, Desrosiers, Bravo, Tribble, & Bourget, 2007). In one recent study as

many as 90% of caregivers had difficulties with their leisure activities as a result of

their caregiving responsibilities (Peña-Longobardo & Oliva-Moreno, 2015).

Page 7 of 197

The stress-process model provides a framework for conceptualising the relationships

between caregiving, work, leisure and wellbeing (Pearlin, 2009; Pearlin, Mullan,

Semple, & Skaff, 1990). It suggests that individuals have limited resources and when

the demands placed on them exceed these, individuals experience stress and mental

illness. Primary stressors (such as becoming a carer) exist within a background of

contextual factors (such as age, gender and socio-economic background) which can

affect one’s ability to cope. Additionally, primary stressors can have a knock-on

effect for other areas of life. For example, the time demands of caring may affect the

ability to engage in leisure activities which may have previously been an important

stress coping mechanism (secondary stressor). This model also recognises the

importance of social relationships in maintaining or exacerbating wellbeing. This

model holds face validity and has been used widely within the caregiving literature

(e.g. Papastavrou, Kalokerinou, Papacostas, Tsangari, & Sourtzi, 2007; Stansfeld et

al., 2014).

Leisure and carers

Leisure is the engagement in activities which are neither required for financial gain,

nor for day to day living (Voss, 1967), activities that are chosen and intrinsically

motivated rather than necessary (Neulinger, 1981). Judgement about whether or not

an activity is necessary is inevitably subjective, therefore some also describe leisure

as a “state of mind” (Parr & Lashua, 2004). For example, cooking might be a form of

employment for some, a daily necessity for others, and a pleasurable pastime

(leisure) for others.

The impact of leisure on carer wellbeing has been widely researched. For example,

caregivers of the elderly who were less satisfied with their leisure time were also

Page 8 of 197

more likely to be more anxious, and more depressed than caregivers who were more

satisfied (Del-Pino-Casado & Ordóñez-Urbano, 2016). Leisure satisfaction was also

related to quality of life for parents of children with learning disabilities (Hsieh,

2011). Similar findings emerged from a study with carers of individuals with spina

bifida (Grosse, Flores, Ouyang, Robbins, & Tilford, 2009), with a lack leisure days

being associated with lower wellbeing and “feeling blue”. An association between

leisure and wellbeing was also found in caregivers of individuals with mental health

difficulties (Grover & Dutt, 2011), and in a more general sample of caregivers

(White-Means & Chang, 1994). These studies were all questionnaire based. A study

using daily diary methodology found that the total number of activities was related

to positive affect (Mausbach, Coon, et al., 2008), engaging in more activities being

associated with greater positive affect.

Although there is a large body of evidence to suggest that leisure is associated with

wellbeing in carers, there is also some research with contradictory findings. For

example, Loi and colleagues (2016) did not find a relationship between physical

leisure activity and depression in older carers despite this relationship being

evidenced in this population in other studies (Del-Pino-Casado & Ordóñez-Urbano,

2016). Neither was a relationship found between leisure participation and wellbeing

in another study (Rizk, Pizur-Barnekow, & Darragh, 2011). The mix of findings

could be due to the complex nature of the constructs and measurements of leisure.

Dimensions of Leisure

Different types of leisure may have different levels of impact on carer wellbeing. For

example, exploration, domestic and nature related leisure pursuits were all associated

with fewer depressive symptoms (Thompson, Solano, & Kinoshita, 2002). Outside

Page 9 of 197

leisure activities were related to improvements in life satisfaction but not to

depression and home leisure and social engagement were related to reduced

depression and increased life satisfaction respectively (Wakui, Saito, Agree, & Kai,

2012). Interestingly, monthly engagement in home leisure had a greater impact on

carer satisfaction than more frequent participation. This might suggest that while

leisure can lead to positive outcomes, there can be burdens associated with making

time for it and arranging it.

Support for the role of sport and exercise in maintaining carer wellbeing comes in

part from intervention studies. A 6 month intervention study found that a supported

physical activity programme for carers improved their symptoms of depression (Hill,

Smith, Fearn, Rydberg, & Oliphant, 2007). A home exercise programme led to

improvement in depression scores (Vincente, Delgado, Fuertes, & Prieto, 2009). A

yoga intervention resulted in reduced depression and anxiety in caregivers (Waelde,

Thompson, & Gallagher-Thompson, 2004). However there has been less work

investigating the impact of increasing other types of leisure activities.

A very commonly used measure of leisure is satisfaction with leisure time (Bedini,

Gladwell, & Dudley, 2011; Mausbach, Harmell, Moore, & Chattillion, 2011;

Williams, 2005). Some of these studies have been mentioned in more detail above.

Leisure satisfaction has frequently been shown to be positively correlated with

wellbeing in carers.

As described above, the literature in this field has explored facets of engagement

such as satisfaction with leisure time (Bedini et al., 2011; Williams, 2005), frequency

of participation in different types of leisure activities (Ficker, 2011; Wakui et al.,

2012), whether people are engaging with physical exercise (Hill et al., 2007;

Page 10 of 197

Vincente et al., 2009) and overall engagement with leisure activities. However, most

studies do not measure engagement in a range of leisure activities, and only measure

one dimension of leisure engagement (e.g. either satisfaction with leisure time, or

frequency of participation). Therefore, further research is warranted to better

understand the roles each of these factors play in the relationship between leisure

engagement and the emotional wellbeing of carers.

Sociodemographic factors

Gender

There is good evidence that sociodemographic variables are important in affecting

the leisure engagement and wellbeing of carers. For example, women are less likely

than men to take part in physical activity and this was affected by gender-based time

negotiation and ethic of care (prioritising the needs of others over their own needs)

(Miller & Brown, 2005). This finding is consistent with another study that found that

males were more likely to be working full time and therefore to perform the role of

secondary carer (Grant & Whittell, 2000). Women rated their role to care for others

as a higher priority than their responsibility to meet their own self care needs,

including their right to leisure time (Bedim & Guinan, 1996; Miller & Brown, 2005).

In one study women rated the barriers to leisure more highly than men in the

following areas: “difficult to find others [to participate with], too busy with family,

no physical ability, don't know where to participate, lack of transportation, don't

know where to learn, not at ease in social situations, and physically unable to

participate” (Jackson & Henderson, 1995, p40). Differences in preferred leisure

activities have also been found between men and women, and across different

Page 11 of 197

perceived social classes, however the quality of these differences (i.e. how and in

what ways they were different) was not explored (Iso-Ahola, Jackson, & Dunn,

1994).

Finally, there is evidence that women carers experience reduced wellbeing compared

with men. One meta-analysis found that caregivers were more impaired than non-

caregivers in terms of depression and subjective wellbeing when the studies had a

higher percentage of female participants (Pinquart & Sörensen, 2003). Another study

showed that carers who were women had higher psychiatric morbidity (Raj,

Manigandan, & Jacob, 2006).

Therefore, there are many factors differentiating male and female leisure

engagement. Women are more likely to be primary caregivers, report more barriers

to leisure than men, have reduced wellbeing, and have difficulty in prioritising their

own self-care needs over the care needs of others. Given these factors, and the

evidence that leisure can affect wellbeing, it seems important to better understand the

relationship between leisure engagement and wellbeing for female caregivers.

Age

There is evidence that both leisure habits and wellbeing change across the life-span.

Iso-Ahola and colleagues (1994) found that people are more likely to start new

activities earlier in adult life and that, for women, there is a steady decrease in variety

of leisure activities over the life course. Another study found that perception of a lack

of skills increased as people got older, and family and work commitments peaked in

mid-life (Jackson & Henderson, 1995). These were barriers to engaging in leisure

activities.

Page 12 of 197

Defining distinct age stages is a challenge within the literature which has not been

fully resolved, however “midlife” can be considered as occurring from the

approximate range of 40-60 (Staudinger & Bluck, 2001) These individuals often fall

within the so-called ‘sandwich generation’, named for the position they hold caring

for those in both the generation above (often parents or in-laws), and the generation

below themselves (Chassin, Macy, Seo, Presson, & Sherman, 2010; Hamill &

Goldberg, 1997). Individuals within this group are less likely to engage in healthy

behaviours such as physical leisure activities (Chassin et al., 2010).

Other relevant variables

According to the stress process model other variables may be relevant to the

relationship between carers’ leisure engagement and their wellbeing. Evidence from

the literature supports the idea that socioeconomic status is a key contextual factor or

carer characteristic that might impact on wellbeing (Lee & Bhargava, 2004).

Primary stressors can include whether the individual lives with the cared-for person

and how many hours per week they spend caregiving (Pearlin et al., 1990).

Secondary stressors include other demands on a caregivers’ time which may be

affected by the caregiving role including employment status and childcare

responsibilities (Lee & Bhargava, 2004; Pearlin et al., 1990). Finally, social support

can be a protective factor for carers (Gallo, 1990; Goode, Haley, Roth, & Ford,

1998). Therefore, any research exploring the relationship between leisure and

wellbeing would need to take these other factors into account.

Page 13 of 197

Summary

Female carers in midlife are at risk of having decreased wellbeing due to the

competing demands on their time which may exceed their resources (Staudinger &

Bluck, 2001). In the UK, state pension can be claimed from the age of 65 which

indicates that work as a competing demand is likely to continue until at least that age.

The stress process model provides a framework for understanding how these

competing demands on carer time, leisure engagement and other relevant variables

impact on carer wellbeing (Pearlin, 2009; Pearlin et al., 1990).

Engaging in leisure activities is often used as a coping mechanism to manage the

stress of competing demands and research shows that carers who engage in leisure

activities are likely to have a better wellbeing than those who don’t (Azman, Jamir

Singh, & Sulaiman, 2017; Orgeta & Miranda-Castillo, 2014). Although there is some

recent research which conflicts with this notion (Loi et al., 2016), and research

looking specifically at women who care for more than 20 hours per week is limited.

Throughout the literature, many different aspects of leisure have been measured and

it is not clear which facets are most strongly related to wellbeing. There has been

some indication that satisfaction with leisure time, overall leisure engagement,

frequency of leisure engagement, and whether people do sport, may each be related

to wellbeing. No studies were found that explored the relative effects of all of these

factors.

Additionally, the literature regarding carers and leisure activities is often limited in

terms of participant sample sizes, frequently only explore a limited number of leisure

activities and rarely explore relationships longitudinally (Clarke, 2018; Loi et al.,

Page 14 of 197

2014). Therefore, further research is needed to better understand how the wellbeing

of females in midlife is affected by their engagement in leisure activities.

Understanding Society

In 2009 a national longitudinal project in the UK called Understanding Society was

launched with its first full wave of data collection. It aimed to be representative of

the UK population taking a stratified sample of 40,000 households. Questionnaires

were administered annually to each of the residents within those households (See

Knies [2015] for more details). The study includes a variety of topics ranging from

leisure engagement to financial circumstances, and includes questions relating to key

demographic characteristics, including whether the individual cares for anyone

within or outside of their home and factors described in the stress process model.

Although restricted to the measures that were determined by the Understanding

Society team, the survey provides a good opportunity to explore the relationship

between leisure and wellbeing. Measures being repeated at multiple time points

allowed for both cross sectional and longitudinal exploration of relationships.

Additionally, as with any longitudinal study, attrition rates may bias the sample in

later waves of data collection. Fortunately, with such a large starting sample, and

with new participants regularly being incorporated into the project, attrition rates are

likely to have a reduced impact compared with smaller projects of a similar nature.

Therefore, the Understanding Society project provides a good opportunity to

examine this area of interest with a large participant sample which is representative

of the UK population. The study reported here is a secondary analysis of this dataset.

It aimed to examine leisure activities as a predictor of well-being and the impact of

Page 15 of 197

becoming a 20+ hours carer on wellbeing and leisure activities for female carers in

mid-life.

Hypotheses

1. At a cross sectional level, lower leisure engagement will predict poorer wellbeing

for women aged between 40 and 65 who care for 20 hours or more each week.

a. Lower frequency, variety, and satisfaction of leisure activities, will predict

lower levels of wellbeing.

b. Those not involved in moderate to high intensity sporting activities will have

poorer wellbeing than those who are involved in sporting activities.

2. Becoming a carer who cares for 20 hours or more each week will affect leisure

engagement and wellbeing for women aged between 40 and 65.

a. Becoming a carer who spends 20 or more hours per week caring will be

associated with reduced frequency, variety, and satisfaction with leisure

activities. These relationships will be moderated by changes in the number of

competing demands (employment and childcare), such that the decrease in

frequency, variety and satisfaction will be stronger in those with an increase

in competing demands, and weaker for those who have had a reduction in

competing demands.

b. Becoming a carer who spends 20 or more hours caring a week will be

associated with reduced wellbeing when compared with wellbeing prior to

becoming a carer.

c. Change in leisure will predict change in wellbeing.

Changes over time for carers will be explored in relation to non-carers to

control for general temporal changes.

Page 16 of 197

Method

Participants

Participants were selected from a larger sample of participants who were part of the

UK Household Longitudinal Study (UKHLS) also known as Understanding Society

(University of Essex, 2017). Original members were selected for the study based on a

random sample of households which was stratified by location, and totalled

approximately 40,000 in number at its first wave of data collection. UKHLS aimed to

interview all members of the household. Sample stratification took into account the

population density, ethnic minority density and proportion of households with non-

manual workers. Although the population sample is largely stable (Lynn & Knies,

2016), temporary and permanent members have been recruited depending on new

members (e.g. children, and partners) joining or leaving households. The survey

aimed to keep members who were in the original sample even if they moved house.

Data for participants who were female, between the ages of 40 and 65 and who

reported being a carer were used. A “carer” was defined as someone who provides

special help and support to individuals who are sick, disabled or elderly living within

or outside of the household. Parents of children without additional needs were not

classed as carers. This definition is in keeping with the wording used within

Understanding Society (see Appendix B for exact wording of the question).

Design

Data from the UKHLS were used and details of the study are widely available

(Knies, 2015). To summarise here, it is an annual cross-sectional survey of the same

Page 17 of 197

people. The data is collected in face to face interviews with trained interviewers

using Computer Aided Personal Interview (CAPI).

Core modules are asked at every wave and rotating modules are asked at one off time

points, or at regular intervals greater than one year. The rotating module that was of

interest to this study was the Leisure, Culture and Sport module which was repeated

at waves two (W2) and five (W5), and therefore data from these time points were

used to explore the research questions. Data were also taken from core modules to

identify participants who met the criteria for this study (see above) and to explore the

impact of relevant variables from the stress process model. See “Measures” section

for further details.

This study had a cross sectional component which looked at the relationship between

levels of leisure and wellbeing using data from W2. It also had a longitudinal aspect

which looked at the effects of becoming a carer using W2 and W5 which were 3

years apart. In order to control for general temporal changes, non-carers were used as

a comparison group in the longitudinal analysis.

Ethical Issues

The Understanding Society study received ethical approval from the University of

Essex Ethics Committee. All data has been anonymised (names, contact information,

and dates of birth were removed) and is stored electronically with the UK Data

Archive based at the University of Essex. Full participant consent was obtained at

each wave of data collection and participants were provided with a £10 Love2Shop

High Street voucher as a token of appreciation for taking part. Participants had the

opportunity to specify the most appropriate times to receive contact from the

Page 18 of 197

researchers. Data is freely available for social researchers to access however is not

available to commercial companies. Further discussion about ethical issues

associated with UKLHS and how these have been addressed can be found in the

Understanding Society Quality Profile (Lynn & Knies, 2016).

For the purpose of this study only data from relevant waves were accessed and used.

Data were stored on a password protected computer. An online self-assessment form

was completed through the University of Surrey to ensure it was not necessary to

gain further ethics approval for this secondary analysis study (see Appendix A).

Measures

Outcome measure: Wellbeing

In order to measure wellbeing this study used the 12 item version of the General

Health Questionnaire (GHQ-12). The GHQ-12 is a screening tool for minor

psychiatric conditions within the general population and is based on the original 60

item measure (Goldberg, 1972). It has good reliability and convergent validity

(Hardy, Shapiro, Haynes, & Rick, 1999), with the alpha coefficient being .88 and a

test re-test correlation of .73. Hardy and colleagues also found a good correlation

between the GHQ-12 and a range of other mental health measures (e.g. Clinical

Interview Schedule – Revised). Cronbach’s alpha for cross sectional analysis for this

study was .93, and for the longitudinal analysis was .93.

Although GHQ-12 is sometimes used to report on caseness, it was not in this study

due to the researcher’s ethical stance not to propagate narratives that mental

wellbeing is a binary construct. It was decided to report only on findings from likert

Page 19 of 197

data as this was felt to more accurately represent real world experiences of mental

wellbeing lying on a continuum.

For the longitudinal analysis, change in wellbeing was calculated by subtracting

GHQ-12 at W2 from GHQ-12 at W5. Negative scores represented an improvement

in wellbeing from W2 to W5.

Leisure Variables

Satisfaction with leisure time

This was taken from the response to one item asking participants to indicate on a

scale of 1-7 (with 1 being “not at all satisfied” and 7 being “highly satisfied”) how

they feel about the amount of leisure time they have. For the longitudinal analysis,

change in satisfaction was calculated by subtracting satisfaction at W2 from

satisfaction at W5. Positive values represented an increase in the amount of

satisfaction with leisure time from W2 to W5.

Variety of leisure activities

Participants were asked to indicate which activities they had undertaken in the last 12

months from a provided list (e.g. “event connected with books or writing” (Appendix

C)). The affirmative responses were summed to assess the variety of leisure activities

undertaken. For the longitudinal analysis, change in variety over time was calculated

by subtracting variety at W2 from variety at W5. Positive values represented an

increase in the number of different leisure activities from W2 to W5.

Page 20 of 197

Frequency of leisure engagement

The Leisure, Sport and Culture module included eight categories: arts activities, arts

events, museum, library, archives, historical sites, sporting activities, and mild

intensity sporting activities (see Appendix C). Participants were given response

options for how frequently they engaged in each category e.g. “once a week”, “once

in the last year”. The categories of sporting activities and low intensity sporting

activities had an additional response option of “3+ times per week”.

Attempts were made to make this a single continuous variable, however because the

response options were broad, differed for sporting activities, and were not at regular

intervals it was not felt to be a reliable measure of leisure frequency. Therefore, the

eight separate leisure categories were analysed separately. In the longitudinal

analysis there was not enough data to analyse “Archives” frequency (how frequently

a participant had been to an archive centre or records office) and therefore this was

removed. For the longitudinal analysis, change in frequency was calculated by

determining whether participants had increased, reduced or maintained their

frequency within that category.

In the cross-sectional analysis, participant numbers for each of the frequency ratings

was variable across the different leisure categories. When participant numbers were

too low, frequency ratings were collapsed in order to make analysis viable, e.g. for

archives frequency the three categories of “not at all”, “once last year” and “twice

last year” were used.

Page 21 of 197

Sporting activities

Two questions addressed sporting activities. As seen in Appendix C, participants

were asked about various high/moderate and low intensity sporting activities. From

this data three groups were identified for comparison: participants who had taken

part in High/Moderate intensity sporting activities, individuals who had engaged in

mild intensity sporting activities, and those who had not participated in sporting

activities.

Another indication of engagement with sporting activities was taken from the

questions asking how frequently participants had engaged in moderate intensity

sporting activities, and mild intensity sporting activities. Responses fell into 5

categories: not at all, once or twice in the last year, three or four times in the last

year, at least monthly but less than weekly, and once a week or more.

Other variables in the stress process model

Carer Characteristics

In keeping with research that has found income, employment status and age are

related to leisure engagement (Lee & Bhargava, 2004), these factors were all

adjusted for. Income was explored through one question relating to subjective

financial situation (good, just about managing, or finding things difficult). This and

highest qualification also serve as some indication of socioeconomic status (SES)

which has been found to impact on leisure engagement (Hallal, Victora, Wells, &

Lima, 2003). Although job type is often used as an indicator of SES, only around

half of the carers in this participant sample were employed and therefore this was not

felt to be a useful way of understanding the SES of participants in this group. It is

Page 22 of 197

common for high proportions of carers to not be working (e.g. Bittman, Hill, &

Thomson, 2007; Mosher et al., 2013; Thompson et al., 2002). Household income is

also commonly used however, due to the complexities of the Understanding Society

dataset, it was not possible to calculate this.

Primary Stressors

Primary stressors included the number of hours spent caring, and whether the carer

lived with the person for whom they were providing care. Information about how

many hours of care was addressed in one question which offered 9 response options

e.g. (“0-4 hours”). For the purpose of the cross-sectional study, only responses that

were greater than 20 hours per week were included and these were condensed into 3

categories: “20-49 hours”, “50 hours or more”, and “varies over 20 hours”.

Whether someone lived with the individual for whom they were providing care was

calculated from the responses to two items: whether they provided additional help to

someone within the household, and whether they cared for someone outside the

household. It was a binary variable.

Secondary Stressors (Competing Demands)

According to the stress process model it is likely that having competing time

demands would be a secondary stressor, carers often giving up leisure activities due

to the time constraints (Dunn & Strain, 2001). Women with children are also less

likely to engage with leisure than women without children (Miller & Brown, 2005).

Therefore, participant data about employment status and whether they were

responsible for children under the age of 15 were used.

Page 23 of 197

In cross sectional analysis employment status was grouped into four categories:

Working, looking after family/health/home, retired, and unemployed or doing

something else. This enabled the data to be explored in terms of the likely cultural

and personal meaning related to a particular employment status. It was also deemed

that within these categories people might have different opportunities for leisure.

However, for the longitudinal analysis employment status was a binary variable

(employed/not employed) as this was more appropriate for the statistical methods

used.

Change in competing demands was calculated by adding up how many competing

demands each participant had at W5 (i.e. work or childcare), and subtracting it from

how many competing demands they had at W2. Positive scores indicated an increase

in competing demands from W2 to W5.

Social Support

Finally, social support has been shown to be influential in carers’ wellbeing (Gallo,

1990; Goode et al., 1998). Additionally women who do not live with a partner have

lower levels of physical activity (Hallal et al., 2003). Therefore, two indicators of

social support were included: living with a partner, and relationship quality.

Relationship quality was determined through a relationship quality rating scale

relating to each of the following: their partner (Cronbach’s alpha for the cross

sectional study was .82, and for the longitudinal study was .81), best friend (.73

and .79 respectively), and closest family member (.81 and .71 respectively). Not

every participant was able to rate a person from each category and therefore the

highest rating across the three evaluated relationships was taken as an indicator of

Page 24 of 197

social support. This variable was described as “relationship quality” throughout the

analysis.

See Figure 1 for a diagrammatic representation of variables considered, and the

direction of the effects.

Page 25 of 197

Data analysis

Cross sectional study

Participants who were female, between the ages of 40 and 65 and who identified as

carers were selected from the overall dataset. Individuals with missing data for

leisure and outcome variables were excluded leaving a total of 710 participants for

this analysis. See Figure 2 for a diagram representing the participant exclusion

process.

The data were assessed to see the extent to which the assumptions for parametric

testing were met (Appendix D). Levene’s and Hartley’s Fmax (Field, 2013) were

examined to assess homogeneity of variances but the large sample sizes meant their

results were not a good indicator of whether the validity of the results was likely to

Figure 1: A diagrammatic representation of variables considered in this study. Based on Pearlin's (2009) stress process model. Within the diagram only effects and variables that were explored in this study are labelled

Secondary Stressors (competing demands)

Employment.Childcare.

Social Support

Highest quality relationship.Living with partner.

Wellbeing

GHQ-12 (MCS).

Primary Stressors

Hours per week spent caring.Living with the cared for individual.

Leisure

Frequency.Variety.Sport/No sport.Leisure time satisfaction.

Carer characteristics

Age.Socioeconomic status:

Highest qualification Subjective finances

Page 26 of 197

be affected by heterogeneity of variance (Field, 2013; Lumley, Diehr, Emerson, &

Chen, 2002). With these sample sizes anything other than exactly equal variances

(i.e. variance ratio=1) was significant using Levenes or the F test and therefore

heterogeneity of variances was assessed by inspection of the observed standard

deviations. Histograms, and Q-Q plots were used to assess normality and again the

large sample meant that only marked non-normality was likely to affect the validity

of the results (Motulsky, 2014). Some positive skew was apparent so in order to

examine robustness of the results from parametric tests, equivalent non-parametric

and robust tests were also conducted. Results from robust and non-parametric tests

were consistent with results from parametric tests (Appendix E). Results that were

statistically significant from parametric tests were also significant when using non-

parametric and robust tests.

The General Linear Modelling (GLM) in SPSS was used to examine the extent to

which each of the leisure variables predicted GHQ-12. GLM was used as it allows

for categorical predictors as well as continuous predictors. In this analysis the aim

was to focus on the relationship between leisure and well-being rather than trying to

fit the whole stress process model. Therefore, the other measured variables in the

stress process model were added separately to the above GLM to examine their

individual impact on the relationship between leisure and wellbeing. Where the

addition of the variables substantially altered the relationship between leisure and

wellbeing further analysis was conducted to examine how that variable was related to

the leisure variable and wellbeing (using GLM).

Page 27 of 197

Longitudinal study

Participants who were female and between the ages of 40 and 65 at both waves were

selected from the overall dataset. Participants who were providing 20 or more hours

of care per week at both waves, or who were carers at W2 but not at W5 were

excluded. Those who had stopped providing care were not included because they

could have been affected by issues of role loss or bereavement that could impact on

findings.

Participants were then grouped by caregiving status into: those providing less than 20

hours of care at W2 and more than 20 hours of care at W5 (increased caring), those

not providing care at W2 and providing more than 20 hours of care at W5 (new

carer), and those not providing any care at either time point (non-carer). The non-

carer group was included to control for temporal changes (i.e. changes occurring for

the whole cohort over time, not because of caring). Participants with missing leisure

and wellbeing data were excluded, leaving a total number of 109 women who had

increased their caring, 103 who were new carers, and 4224 women in the comparison

group of non-carers. See Figure 3 for a diagram representing the participant selection

process.

The data was assessed to see the extent to which the assumptions for parametric

testing were met. Histograms were used to assess normality (Appendix H). As with

the cross-sectional study, non-parametric equivalents tests were used to assess the

robustness of findings from parametric tests (Appendix I).

Repeated measures analysis was used to explore the extent to which wellbeing,

variety and satisfaction decreased over time. This allows examination of between-

Page 28 of 197

subjects effect of being a carer, main effect of time, and the interaction between time

and carer group. The latter is the effect of most interest as it tests whether changes

over time were different between carer groups. Additional models were fitted to

examine effects of competing demands and other variables from the stress process

model (Appendix J).

Chi square tests were used to explore whether changes in frequency of leisure

changed differentially over time. In general, sample sizes were large enough to meet

assumptions of this test, and where cell counts were low, frequency categories were

collapsed to mitigate this. Due to very low numbers of participants reporting using

archives, this variable was not included in the analysis process.

GLM was also used to explore the extent to which a change in leisure predicted a

change in wellbeing. GLM was used as it allows for categorical predictors as well as

continuous predictors.

Bonferroni corrections were not used in this study because evidence suggests that

they are unnecessary and may cause problems such as increasing the likelihood of

type II errors (Perneger, 1998).

Page 29 of 197

Figure 2: Flow chart depicting the participant exclusion process for the cross-sectional study.

Total sample W2

Total n = 54597

Select women

Total n = 29551

Select people who were 40-65

Total n = 12931

Select carers 20+ hours per week

Total n = 876

Exclude people where relationship to cared for

person is described as “client” (n=3)

Total n = 873

Exclude people who care for more than 3 people

(n = 8)

Total n = 865

Exclude people with “missing” data for wellbeing

(n=145)

Total n = 720

Exclude people with no data for leisure

satisfaction (n=10)

Total n = 710

Page 30 of 197

Total participants who

meet inclusion criteria

N=5490

Non-carers n = 5215

Increased caring n = 131

New carers n = 144

Select people who were not carers at either wave,

increased care from <20 hours per week (hpw) to >20

hpw, or became carers (>20 hpw).

Total n = 5492

Exclude people with “missing” data for wellbeing at

either wave (n=926)

Total n = 4564

Total sample W2 and W5

Total n = 62095

Select women

Total n = 20521

Exclude people with missing data for leisure

satisfaction (n=51)

Total n = 4513

Select people who were 40-65 at both W2 and W5

Total n = 8577

Exclude people with missing data from other relevant

variables (n=15)

4435

Exclude people with relationship to cared for

described as “client” (n=2)

Total n = 5490

Exclude people with missing data for leisure

frequency/variety (n=63)

Total n = 4450

Non-carers n = 4340

Increased caring n = 113

New carers n = 111

Non-carers n = 4296

Increased caring n = 113

New carers n = 104

Non-carers n = 4238

Increased caring n = 109

New carers n = 103

Non-carers n = 4224

Increased caring n = 109

New carers n = 103

Figure 3: Flow chart depicting participant exclusion process for longitudinal hypotheses.

Page 31 of 197

Results: Cross sectional study

Participant characteristics

A total of 710 women were included in this study through the selection process

described above. Most participants were White-British (66%), were living with the

individual they were caring for (71%), living with a partner (72%) and were not

responsible for a child under the age of 15 (73%). Only 39% of participants were

working and 34% reported they were not working for either health, caregiving or

home care reasons (Table 1).

Table 1: Participant demographic information for cross section participant sample. Total n = 710.

N %Age M= 52.4, SD=7.4

40-44 139 2045-49 134 1950-54 140 2055-59 133 1960-65 164 23

Ethnicity British, Irish or other White backgroundOther ethnic groupData not provided

46874168

661024

Subjective Finances GoodJust about managingThings are difficult

327251132

463519

Hours per week spent caring 20-49 hours50 or more hoursVaries over 20 hours

296282132

424018

Children under 15 YesNo

189521

2773

Highest qualification Degree or higherLess than degree but higher than GCSEGCSE and other school certificatesNone of the aboveInapplicable

6280180241147

911253421

Page 32 of 197

N %

Living with a partner YesNo

514196

7228

Employment status WorkingFamily/health/home careRetiredUnemployed or doing something else

27924712163

3935179

Living with the person for whom they provide care

Cares at homeCares outside homeBoth

41420690

582913

Study Measures

The range of GHQ-12 scores within this study was 0-36 which is the same as the

possible range for this measure. The mean was 13.9 with a standard deviation of 6.7.

The means and standard deviations for satisfaction with leisure time and variety of

leisure activities can be seen in Table 2. The range of possible responses for

satisfaction was 0-7 which were all represented within this sample. For variety, the

possible range was broader (0-71) and the range observed in this study was 0-43.

Some of the response options for frequency variables were collapsed to mitigate for

low cell counts in some of the categories. Frequency categories and the number and

percentage of participants indicating each response can be seen in Table 2.

Hypothesis 1a: Less satisfaction, variety, and frequency of leisure

activities, will predict lower levels of wellbeing.

General Linear Models (GLMs) were used to examine the extent to which each

leisure variable predicted GHQ-12 score. The relationship between satisfaction with

leisure time and wellbeing was statistically significant (p<.001). People who were

less satisfied with their leisure time also had poorer wellbeing than those who

reported higher levels of satisfaction. The regression coefficient showed an estimated

Page 33 of 197

decrease of 1.317 in the GHQ-12 for every point increase in satisfaction. Further,

satisfaction accounted for 12.4% of the variance in GHQ-12 scores (Table 2).

There was a significant main effect of variety on wellbeing (p=.015). The regression

coefficient showed an estimated decrease of .093 in the GHQ-12 for every additional

type of activity.

For arts events, such as the theatre and carnivals, there was a significant main effect

of frequency of on wellbeing (p=.013). Individuals who took part in these activities

monthly had the best wellbeing (M=11.875, SE=.785), and those who took part in

activities once in the past year or not at all had the poorest wellbeing (M=14.791,

SE=.718 and M=14.687, SE=.409 respectively). There was no significant main effect

of frequency of arts activities (e.g. drawing), library, archives, museum or historical

sites on wellbeing (Table 2). Frequency variables were also fitted as a trend, and

results were consistent with previous findings, that individuals who take part in arts

events more frequently had better wellbeing than those who took part less frequently.

Most of the other frequency variables showed non-significant negative relationships

with GHQ-12 scores.

Table 2: Associations between leisure variables and the GHQ-12. Total n = 710.

M (SD) b (SE) F P R2

Satisfaction 4.17 (1.79) -1.317 (.132)

100.278 <.001 .124

Variety 7.03 (6.57) -.093 (.038) 5.947 .015 .008

% (N) M (SD) b (SE) PArts Activities -.147 (.146) .314 . 546 .702 .003

Not at all 25.8% (183) 14.21 (6.78)1-2 times last year 3.1% (22) 14.91 (7.95)At least 3/4 times 7.0% (50) 14.48 (7.50)At least monthly 8.2% (58) 13.17 (6.00)Weekly 55.9% (397) 13.73 (6.70)

Page 34 of 197

% (N) M (SD) b (SE) P F P R2

Arts Events -.793 (.230) .001 3.488 .008 .019Not at all 37.3% (265) 14.69 (7.01)1-2 times last year 25.6% (181) 14.38 (6.81)At least 3/4 times 25.2% (179) 13.10 (6.02)Monthly 10.1% (72) 11.88 (6.46)Weekly 1.8% (13) 13.38 (6.33)

Library -.309 (.197) .117 1.213 .304 .007Not at all 64.9% (461) 14.16 (6.66)1-2 times last year 7.6% (54) 13.06 (6.74)At least 3/4 times 9.7% (69) 14.38 (7.22)Monthly 13.8% (98) 13.34 (6.75)Weekly 3.9% (28) 12.00 (6.70)

Archives .868 (.775) .263 .695 .499 .002Not at all 95.3% (677) 13.83 (6.64)once last year 2.5% (18) 15.22 (8.25)Twice last year 2.1% (15) 15.27 (7.76)

Museum -.447 (.316) .158 .882 .474 .005Not at all 70.4% (500) 14.12 (6.56)1-2 times last year 16.6% (118) 13.21 (6.61)At least 3/4 times 10.3% (73) 13.84 (7.33)Monthly 2.7% (19) 11.95 (7.75)Weekly 3.9% (28) 12.00 (5.72)

Historical sites -.264 (.243) .278 2.251 .062 .013Not at all 46.2% (328) 14.30 (6.82)1-2 times last year 26.4% (188) 13.97 (6.61)At least 3/4 times 18.6% (132) 12.45 (5.70)Monthly 7.0% (50) 14.26 (7.78)Weekly 1.7% (12) 16.25 (6.70)

MI = moderate intensity; LI= low intensity; F, P and R2 are reported for when frequency was included in the model as a categorical variable. B(SE) and P are reported for when the frequency variables were fitted as a trend.

Adjusting for other stress process model variables

The other variables in the stress-process model were considered as potentially

influencing leisure, or the relationship between measures of leisure and GHQ-12. To

examine this each variable was included in the model with the leisure variable to

examine whether its inclusion altered the relationship between the leisure variable

and GHQ-12 (Tables 4 and 6).

Page 35 of 197

The relationship between leisure satisfaction and wellbeing remained robust when

other variables from the stress process model were input into the regression model.

The relationship between the number of different activities and wellbeing remained

similar when most of the other variables were controlled for. Exceptions to this were

when finances were controlled for which substantially altered the regression

coefficient and the p-value (Table 3). Smaller alterations were seen when considering

whether the carer lived with the cared for and whether they were employed.

Due to the large effect of adding finances into the model this was explored further

(Table 4). People who had more money did more leisure activities (p<.001).

Comparisons of means showed that people whose financial situation was “good”

were doing significantly more (M=8.569, SE=.355) than people who were “just

about managing” (M=5.821, SE=.406) and those who were “finding things difficult”

(M=5.538, SE=.559) (Table 4). In summary, those who felt they had a good

financial situation generally had a greater variety of leisure activities which is likely

to be one route through which they experienced better well-being.

For most of the frequency variables the addition of the other stress process variables

made little difference (Table 5). The relationship between frequency of arts events

was affected by finances (p=.268) and, to a lesser degree, by childcare (p=.070).

Further, frequency of going to the library emerged as having a significant

relationship with wellbeing when hours per week of care were taken into account

(p=.023).

Page 36 of 197

Table 3: Statistics from the GLM for Variety and Satisfaction with GHQ-12.

Adjusted for Variety Satisfaction

b F P R2 b F P R2

Unadjusted -.093 5.95 .015 .008 -1.317 100.28 <.001 .124

Carer characteristicsAge -.104 7.39 .007 .020 -1.293 92.98 <.001 .125Finances -.038 1.05 .307 .099 -1.074 2401.52 <.001 .173Qualification -.099 5.67 .018 .016 -1.342 103.80 <.001 .135

Primary stressorsCares at home -.071 3.35 .068 .019 -1.292 3784.41 <.001 .133HPW caregiving

-.080 4.36 .037 .019 -1.287 94.78 <.001 .130

Competing demandsWork -.065 2.87 .091 .050 -1.300 10.59 <.001 .162Childcare -.094 5.97 .015 .008 -1.337 101.97 <.001 .126

Social supportRelationship quality

-.083 5.16 .023 .096 -1.133 75.40 <.001 .177

Relationship status

-.092 5.91 .015 .019 -1.294 4.79 <.001 .130

HPW = hours per week; Figures shown represent the values for variety/satisfaction when the additional variables were added into the model.

Table 4: Variety as DV and finances as IV in GLM with pairwise comparisons.

N M (SE) F P17.380 <.001

Good 8.57 (.355)Managing 5.82 (.406)Difficult 5.54 (.559)

Pairwise comparisons: MD (SE) PGood / Managing 2.75 (.539) p<.001Good / Difficult 3.03 (.663) p<.001Managing / Difficult .283 (.691) p=.682

MD = Mean difference.

Page 37 of 197

Table 5: Associations between frequency of leisure engagement and wellbeing adjusting for variables from the stress process model.

Arts Activities Arts Events Library Archives Museum Historical sitesF P, R2 F P, R2 F P, R2 F P, R2 F PP, R2 F P, R2

Unadjusted .546 .702, .003 3.488 .008, .014 1.213 .304, .007 .695, .499, .002 .882 .474, .005 2.251 .062, .013

Carer characteristicsAge .493 .741, .013 4.038 .003, .032 1.418 .226, .018 .713 .490, .012 .911 .457, .015 2.274 .060, .023Finances .537 .708, .106 1.919 .106, .115 1.254 .287, .116 .120 .811, .102 1.023 .395, .112 .840 .500, .109Qualification .486 .746, .032 2.569 .037, .051 .685 .603, .032 1.113 .329, .033 .707 .588, .035 1.984 .095, .061

Primary stressorsCares at home

.635 .637, .021 2.438 .046, .034 .635 .637, .027 1.561 .211, .021 .589 .671, .025 1.698 .149, .026

HPW caregiving

.550 .699, .025 2.721 .029, .037 2.848 .023, .046 .805 .522, .020 .547 .701, .022 2.110 .078, .031

Competing demandsWork .403 .807, .059 4.566 .001, .078 1.461 .212, .072 .054 .947, .053 1.127 .342, .036 .920 .452, .065Childcare .335 .855, .013 2.106 .078, .022 .873 .480, .010 1.334 .264, .006 1.114 .349, .010 1.468 .210, .020

Social supportRelationship quality

.417 .797, .091 2.688 .030, .103 1.060 .375, .095 .978 .377, .092 .782 .537, .093 1.806 .126, .099

Relationship status

.576 .680, .015 3.062 .016, .032 1.923 .105, .035 .108 .898, .015 1.232 .296, .029 1.754 .136, .029

HPW = hours per week.

Page 38 of 197

Hypothesis 1b: Those not involved in moderate to high intensity sporting

activities will have poorer wellbeing than those not involved in sporting

activities.

Firstly, the relationship between sports participation and wellbeing was explored by

comparing three groups: those engaging in moderate intensity sports in the last year,

those participating in mild intensity sport in the last year, and those who did not

participate in sport. As can be seen in Table 6, results of the GLM showed there was

a significant main effect of participation in sport on wellbeing (p=.002). Pairwise

comparisons showed that those who took part in moderate or low intensity sports had

better well-being than those who did no sport (Table 6). There was no difference

between those who did mild intensity sport and those who did moderate intensity

sport (p=.706).

Other variables from the stress process model were hypothesised to have an

influence in this relationship and therefore they were entered into the GLM one at a

time. This relationship was affected when childcare was entered into the model

(p=.210). Otherwise, the relationship was relatively unaffected by the other factors in

the stress process model (Table 7).

Secondly, the relationship between frequency of participation and wellbeing was

explored. GLMs explored the relationship between the frequency of low intensity

sport and moderate intensity sport (e.g. weekly, monthly etc.) and wellbeing. The

GLMs exploring the frequency of engagement in sporting activities showed no main

effect of frequency of moderate intensity sport (p=.078) or low intensity sport

(p=.167) on wellbeing (Table 9). However, when fitted as a trend there was a

Page 39 of 197

significant negative relationship between frequency of both types of sport and GHQ-

12 (b=-.398, p=.12 and b=-.352, p=.017 respectively) (Table 9). Carers who did

sports less regularly had higher GHQ scores (indicating poorer wellbeing). Overall,

this suggests some evidence for the relationship between frequency of participation

and wellbeing.

When the other variables from the stress process model were entered into the GLM

one at a time, both age and employment status impacted on the relationship between

frequency of moderate intensity sport and wellbeing (Table 9). Inspection of the

estimated marginal means when these variables were adjusted for (Appendix G),

broadly speaking, showed wellbeing was poorer for those who took part less

frequently. Otherwise, the relationships were relatively unaffected by the other

factors in the stress process model.

Table 6: Associations between levels of sport and GHQ-12 with pairwise comparisons.

N M (SE) F P R2

6.106 .002 .017MI sport 324 13.142 (.370)LI sport 113 13.416 (.626)No sport 273 14.996 (.403)

Pairwise comparisons:

MD (SE) P

MI sport / LI sport .274 (.727) .706MI sport / No sport 1.854 (.547) .001LI sport / No sport 1.580 (.744) .034

MI = Moderate intensity; LI = Low intensity.

Page 40 of 197

Table 7: Associations between participating in some or no sport with GHQ-12.

Adjusted for SportF P R2

Unadjusted 6.106 .002 .017

Carer characteristicsAge 8.033 <.001 .032Finances 3.605 .028 .109Qualification 7.641 .001 .040

Primary stressorsCares at home 3.003 .050 .028HPW caregiving 6.350 .002 .031

Competing demandsWork 7.470 .001 .076Childcare 1.566 .210 .019

Social SupportRelationship quality

6.371 .002 .105

Relationship status 4.946 .007 .030HPW = hours per week. Figures shown represent the values for sport participation when the additional variables were added into the model.

Table 1: Associations between frequency of sporting activities and GHQ-12.

% (N) M(SD) b (SE) P F P R2

MI sport -.398 (.154) .012 2.111 .078 .012Not at all 54.4% (386) 14.53 (7.03)1-2 times last year 6.9% (49) 13.73 (6.70)At least 3 / 4 times 8.0 %(57) 12.60 (5.18)Monthly 12.4% (88) 13.05 (6.38)Weekly 18.3% (130) 13.22 (6.35)

LI sport -.352 (.148) .017 1.623 .167 .009Not at all 54.4% (386) 14.32 (6.83)1-2 times last year 6.9% (49) 14.24 (7.03)At least 3 / 4 times 6.9% (49) 14.39 (7.24)Monthly 8.9% (63) 13.54 (6.71)Weekly 23.0% (163) 12.80 (6.04)

MI sport = Moderate intensity sport; LI sport=Low intensity sport. F, P and R2 values are reported for the model when frequency was modelled as a categorical variable, and b(SE) and p values are reported for when the frequency was fitted as a trend.

Page 41 of 197

Table 9: Associations between frequency of sports and GHQ-12, adjusted for the variables in the stress process model.

MI Sport LI SportF P R2 F P R2

Unadjusted 2.111 .078 .012 1.623 .167 .009

Carer characteristicsAge 2.981 .019 .027 1.644 .161 .019Finances 1.441 .219 .112 .792 .531 .109Qualification 1.577 .179 .038 2.216 .066 .043

Primary stressorsCares at home 1.048 .381 .026 .920 .452 .022HPW caregiving 2.351 .053 .031 1.934 .103 .034

Competing demandsWork 2.942 .020 .079 1.406 .230 .071Childcare 1.189 .314 .014 .551 .699 .016

Social supportRelationship quality

2.385 .050 .101 1.056 .377 .095

Relationship status 1.378 .240 .028 1.378 .240 .022MI sport = Moderate intensity sport; LI sport=Low intensity sport.

Results: Longitudinal study

Participant characteristics

The sample for this analysis consisted of women whose data could be linked between

waves 2 and 5 of the survey (three years apart) as described previously. Over this

time 109 women had increased their caring hours to over 20 a week (increased

caring) and 103 had become a carer for over 20 hours a week (new carers). The

comparison group consisted of 4224 women who were not carers at either time.

Table 10 shows participant characteristics by carer group.

Across the increased caring and new carer groups, many of the participants reported

having a good financial situation (56.9%, and 49.6% respectively), most did not have

Page 42 of 197

a child under 15 (87.2%, and 81.6% respectively), and most were living with a

partner (64.2%, and 68% respectively). Around half of the carers at wave 5 were

employed, whereas 70.2% of non-carers had a job. The majority of participants were

from British, Irish, or other White backgrounds (91.7%, and 85.4% respectively).

Most characteristics did not vary significantly across groups (Table 10). In general,

those who became carers for more than 20 hours a week tended to be older, have

poorer subjective finances and were less likely to be employed than those who did

not become carers. New carers were more likely to be living with the person for

whom they were providing care than those who had increased their caregiving.

Table 10: Demographic information and between group comparisons for the longitudinal participant sample.

WAVE 5 Not a carer: % (n)

Increased caring: % (n)

New carer:% (n)

F P

Total n 4224 109 103

Age M= 49.9SD=6.7

M=52.2SD=6.4

M=50.4SD=6.6

6.207 .002

40-44 11.2% (474) 4.6% (5) 14.6% (15)45-49 26% (1099) 21.1% (23) 11.7% (12)50-54 22% (928) 15.6% (17) 31.1% (32)55-59 18.3% (774) 26.6% (29) 21.4% (22)60-65 3.9% (166) 32.1% (35) 14.6% (15)

χ2 PEthnicity 3.39 .185

British, Irish, or other white background

90% (3829) 91.7% (100) 85.4% (88)

Other 9.4% (395) 8.3% (9) 14.6% (15)

Subjective Finances 22.15 <.001Good 64.7% (2735) 56.9% (62) 45.6% (47)Just about managing 23.9% (1009) 26.6% (29) 32% (33)Things are difficult 11.4% (480) 16.5% (18) 11.4% (480)

WAVE 5 Not a carer: Increased New carer: χ2 P

Page 43 of 197

% (n) caring: % (n) % (n)Hours per week spent caring *1.57 .456

20-49 hours n/a 55% (60) 46.6% (48)50 or more hours n/a 24.8% (27) 28.2% (29)Varies over 20 hours n/a 20.2% (22) 25.2% (26)

Children under 15 4.5 .106Yes 20.9% (882) 12.8% (14) 18.4% (19)No 79.1% (3342) 87.2% (95) 81.6% (84)

Highest qualification 7.77 .256Degree or higher 25.1% (1061) 17.4% (19) 18.4% (19)Less than degree but higher than GCSE

14% (592) 16.5%) (18) 14.6% (15)

GCSE and other school certificates

23.4% (987) 25.7% (28) 31.1% (32)

None of the above / Inapplicable

37.5% (1584) 40.4% (44) 35.9% (37)

Living with a partner 2.18 .337Yes 70.4% (2973) 64.2% (70) 68% (70)No 29.6% (1251) 35.8% (39) 32% (33)

Employed 35.07 <.001Yes 70.2% (2964) 50.5% (55) 51.5% (53)No 29.8% (1260) 49.5% (54) 48.5% (50)

Living with the person for whom they provide care *5.69 .017Yes n/a 46.8% (51) 63.1% (65)No n/a 53.2% (58) 36.9% (38)

M=mean; SD=standard deviation; *=non-carer group removed from chi square analysis.

Study measures

The means and standard deviations for satisfaction with leisure time and variety of

leisure activities at each wave can be seen in Table 11. The range of possible

responses for satisfaction was 0-7 which were all represented within this sample. For

variety, the possible range was 0-71 and the range observed in this study was 0-40 at

both waves.

Due to the frequency variables being ordinal and at irregular intervals, three

categories were derived in order to explore change in frequency over time: less, the

Page 44 of 197

same, and more. Numbers and percentages for each category across the frequency

variables are in Table 13.

The range of GHQ-12 scores within this study at both waves was 0-36 which is the

same as the possible range for this measure. See Table 14 for a summary of the

means and standard errors for each carer group at each wave.

Hypothesis 2a: Becoming a carer who spends 20 or more HPW caring will

be associated with reduced frequency, variety, and satisfaction with

leisure activities.

This relationship will be moderated by changes in number of competing demands

(employment and childcare).

Results from the repeated measures analysis suggested that overall, the level of

satisfaction in leisure time decreased by .03 over the three years (p=.001). Inspection

of Figure 5 appears to show the decrease in satisfaction with leisure time was slightly

more for new carers than for non-carers, however this interaction did not reach

significance (p=.096), indicating no strong evidence that carer groups were affected

differentially over time (Table 11). However, it can be noted from Figure 4 and

Table 11 that at both time points, the mean satisfaction was lower for new carers than

for non-carers (p=.009).

Results from the repeated measures analysis suggested that overall, the number of

different types of leisure activities undertaken decreased by 0.45 over the three years

(p=.027) (Table 11). The interaction between time and carer group was not

significant providing no evidence that this decrease was greater for those who

became carers for more than 20 hours a week (Table12). This is also clear from

Page 45 of 197

inspection of Figure 5. However, Table 11 and Figure 5 show that the mean variety

over both time points was significantly different between the carer groups, being

lowest among new carers and similar for those who increased their caring and the

comparison group. Results were robust when other variables from the stress process

model were adjusted for (Appendix J).

It was hypothesised that decreases in variety and satisfaction in the carer groups

would be greater where there were also increases in the competing demands of work

and childcare. The three-way interaction in Table 12 shows that the interaction

between time and carer group was not moderated by a measure of competing

demands. There is therefore no evidence that competing demands affected the

reductions in either variety of activities or satisfaction with leisure.

Table 13 shows changes in frequency of each of the different leisure activities by

carer group. The chi-square results show there were no significant differences in

patterns of change over the three groups and therefore there was no evidence that

those who became carers for 20 or more hours reduced the frequency of activities

more than the comparison group.

Page 46 of 197

W2 W53.9

4

4.1

4.2

4.3

4.4

4.5

4.6

4.7

New carer Increased caring Non-carer

Satis

facti

on

Figure 4: Graph showing the change in satisfaction with leisure over time for each of the three carer groups.

W2 W56

6.5

7

7.5

8

8.5

9

9.5

10

10.5

New carer Increased caring Non-carer

Varie

ty

Figure 5: Graph showing change in variety over time for each of the three carer groups.

Page 47 of 197

Table 21: Associations between Variety and Satisfaction over time and carer group.

ME time ME Care Status IE Time * Care status

M(SE) F P M(SE) F P M(SE) F P

Satisfaction W2: 4.509 (.076)W5: 4.205 (.079)

11.704 .001 NeC: 4.189 (.136)IC: 4.330 (.132)NoC: 4.552 (.021)

4.741 .009 W2 NeC: 4.398 (.163)IC: 4.523 (.159)NoC: 4.606 (.025)

W5 NeC: 3.981 (.168)IC: 4.138 (.164)NoC: 4.498 (.026)

2.345 .096

Variety W2: 8.899 (.314)W5: 8.450 (.8.457)

4.882 .027 NeC: 6.626 (.639)IC: 9.624 (.621)NoC: 9.785 (.100)

11.950 <.001 W2 NeC: 6.981 (.672)IC: 9.697 (.653)NoC: 10.020 (.105)

W5 NeC: 6.272 (.675)IC: 9.550 (.656)NoC: 9.549 (.105)

.458 .633

ME = Main effect; IE = Interaction effect; W2 = Wave 2; W5 = Wave 5; NeC = New carer; IC = Increased caring; NoC = Non- carer.

Page 48 of 197

Table 32:Associations between variety and satisfaction over times when change in competing demands was included in the models.

Time Care T*Care T*Change T*Ca*ChF P F P F P F P F P

Variety 4.66 .031 12.11 <.001 .46 .633 .15 .692 1.63 .164

Satisfaction 15.41 <.001 4.79 .008 2.50 .082 26.73 <.001 4.22 .231

Time = Main effect of time; Care = Main effect of care status; T*Care = Time by care status interaction effect; T*Change = Time by Change in competing demands interaction effect; T*Ca*Ch = three-way interaction effect. Where three-way interaction effects were not significant, they were removed from the model to explore other effects in more detail, and these are reported below.

Table 13: Associations between change in frequency of activities over time, with care status.

Carer StatusNew Increased Non χ2 pn (%) n (%) n (%)

Arts Less 19.4% (20) 19.3% (21) 20.4% (862) .927 .921Activities Same 56.3% (58) 58.7% (64) 58.9% (2488)

More 24.3% (25) 22.0% (24) 20.7% (874)

Arts Events Less 31.1% (32) 22% (24) 28.8% (1215) 4.646 .326Same 42.7% (44) 54.1%(59) 44.3% (1873)More 26.2% (27) 23.9% (27) 26.9% (1136)

Library Less 26.2% (27) 21.1% (23) 23.9% (1009) 1.111 .892Same 60.2% (62) 66.1% (72) 64% (2703)More 13.6% (14) 12.8% (14) 12.1% (512)

Museum Less 21.4% (22) 19.3% (21) 22.9% (967) 5.403 .283Same 65% (67) 57.8% (63) 56.1% (2370)More 13.6% (14) 22.9% (25) 21.0% (887)

MI Sport Less 26.2% (27) 25.7% (28) 28.8% (1215) .893 .926Same 47.6%(49) 48.6% (53) 47.1% (1988)More 26.2% (27) 25.7% (28) 24.2% (1021)

LI Sport Less 22.3% (23) 27.5% (30) 27.7% (1169) 3.263 .515Same 53.4% (55) 46.8% (51) 44.8% (1893)More 24.3% (25) 25.7% (28) 27.5% (1162)

Historical Less 26.2% (27) 24.8% (27) 29.2% (1232) 1.971 .741Sites Same 42.&% (44) 46.8% (51) 44% (1858)

More 31.1% (32) 28.4% (31) 26.8% (1134)MI sport = moderate intensity sport; LI sport = low intensity sport. Percentages relate to the proportion of individuals within each carer group who did less, the same, or more activities at wave 5 compared with wave 2.

Page 49 of 197

Hypothesis 2b: Becoming a carer who spends 20 or more hours caring

will be associated with reduced wellbeing when compared with prior to

becoming a carer, and to non-carers.

It was hypothesised that GHQ-12 scores in the two groups who became intensive

carers would increase, relative to little change being found for the comparison group.

Overall there was very little change in GHQ-12 scores between the two waves with

Table 14 showing a nonsignificant mean fall of .01 (p=.963). There was also no

evidence that the change in GHQ-12 scores over the three years was different

between the three carer groups (p=.747). Table 14 and Figure 6 show that the GHQ-

12 scores averaged over both time points did vary by carer group, being highest for

the new carer group and lowest for the comparison (non-carer) group. A surprising

finding is that the “new carer” group showed the worst GHQ-12 score prior to

becoming carers whereas at this point they would be expected to have similar values

to the comparison (non-carer) group. Results were relatively unaffected by other

variables from the stress process model (Appendix J).

W2 W511.5

12

12.5

13

13.5

14

14.5

15

New carer Increased caringNon-carer

Wel

lbei

ng

Figure 6: Graph showing change in wellbeing over time for each of the carer groups. Note: higher scores represent poorer wellbeing.

Page 50 of 197

Table 4: Associations between wellbeing over time and carer group.

ME time ME Care Status IE Time * Care status

M(SE) F P M(SE) F P M(SE) F P

GHQ-12 W2: 13.283 (.270)W5: 13.270 (.274)

.002 .963 NeC: 14.335 (.502)IC: 13.693 (.488)NoC: 11.802 (.078)

19.301 <.001 W2 NeC: 14.505 (.578)IC: 13.550 (.562)NoC: 11.794 (.090)

W5 NeC: 14.165 (.586)IC: 13.385 (.570)NoC: 11.811 (.092)

.292 .747

ME = Main effect; IE = Interaction effect; W2 = Wave 2; W5 = Wave 5; NeC = New carer; IC = Increased caring; NoC = Non- carer.

Page 51 of 197

Hypothesis 2c: Change in leisure will predict change in wellbeing for

individuals who become a carer who spends 20 or more hours caring.

It was hypothesised that change in satisfaction would predict change in wellbeing,

which was supported by the results from the GLM analysis (p=.013) (Table 15).

When carer status was added into the model as a main effect, there were no between

group differences (p=.699). Figure 7 shows that although the fitted line is slightly

steeper for new carers, there was no statistically significant interaction between

change in satisfaction and carer status (p=.740) (Table 16).

Results from the GLM support the hypothesis that change in variety predicts change

in wellbeing (b=-.049, p=.017) (Table 15). When carer status was included in the

model as a main effect, there were no between group differences (p=.728). Figure 8

shows that although the fitted line is steeper for increased carers, there was no

statistically significant interaction effect between change in variety and carer status

(p=.375).

The above described models, although showing some significant relationships, had

very small effect sizes and accounted for only small amounts of the overall variance

(Tables 16 and 17).

A GLM was used to examine how change in GHQ-12 scores varied by whether the

frequency of that activity was less, the same, or more over the time period. None of

the frequency variables had a significant main effect on change in wellbeing when

entered into models independently, giving little evidence of any association between

changes in frequency of specific activities and wellbeing (Table 15). Results were

largely unaffected when care status was entered into the model (Table 16).

Page 52 of 197

-6 -4 -2 0 2 4 6

-2.5

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

Non-carer Increased caring New Carer

Change in satisfaction

Chan

ge in

wel

lbei

ng

Figure 7: Associations between change in wellbeing and change in satisfaction for each carer group.

Note: Higher scores represent poorer wellbeing.

-20 -15 -10 -5 0 5 10 15 20

-6

-4

-2

0

2

4

6

New carer Non carer Increased caring

Change in variety

Chan

ge in

wel

lbei

ng

Figure 8: Associations between change in wellbeing and change in variety for each carer group.

Note: Higher scores represent poorer wellbeing.

Page 53 of 197

Table 5: Associations between change in leisure and change in wellbeing

b (SE) F P R2

Variety -.049 (.021) 5.694 .017 .001

Satisfaction -.357 (.046) 59.211 <.001 .013

n M (SD)Arts activities .322 .725 .000

Less 903 .1362 (5.942)Same 2610 .0096 (5.760)More 923 -.0878 (6.620)

Arts events .035 .966 .000Less 1271 -.017 (6.242)

Same 1976 .017 (5.975)More 1189 .046 (5.718)

Library .984 .374 .000Less 1059 .174 (5.517)

Same 2837 .010 (6.050)More 540 -.269 (6.497)

Museum 2.359 .095 .001Less 1010 .348 (5.789)

Same 2500 -.032 (6.235)More 926 -.221 (5.474)

MI sport .100 .905 .000Less 1270 -.047 (5.985)

Same 2090 .034 (5.959)More 1076 .053 (6.038)

LI sport .808 .446 .000Less 1222 .196 (5.861)

Same 1999 -.077 (6.232)More 1215 -.105 (5.686)

Historical Sites 1.845 .158 .001Less 1286 .222 (6.116)

Same 1953 .033 (5.957)More 1197 -.237 (5.882)

Page 54 of 197

Table 6: Associations between change in leisure and change in wellbeing considering care status. Main effect Care status IE R2

b (SE) F P M (SE) F P F PVariety -.050 (.021) 5.743 .017 NeC -.352 (.589) .318 .728 .981 .375 .001

IC .300 (.573)NoC .017 (.092)

Satisfaction -.357 (.046) 59.320 <.001 NeC -.445 (.586) .359 .699 .301 .740 .013IC .190 (.570)NoC .022 (.091)

n M (SE)Arts activities Less 903 .111 (.329) .320 .726 NeC -.331 (.591) .289 .749 1.675 .153 .000

Same 2610 -.016 (.286) IC .291 (.575)More 923 -.112 (.325) NoC .021 (.103)

Arts events Less 1271 -.043 (.312) .033 .968 NeC -.338 (.590) .289 .749 2.249 .061 .001Same 1976 -.013 (.292) IC .284 (.575)More 1189 -.019 (.315) NoC .017 (.094)

Library Less 1059 .150 (.319) .989 .372 NeC -.383 (.593) .297 .743 1.371 .241 .001Same 2837 -.017 (.284) IC .248 (.577)More 540 -.294 (.365) NoC -.026 (.114)

Museum Less 1010 .323 (.323) 2.381 .093 NeC -.333 (.593) .315 .730 1.486 .204 .001Same 2500 -.056 (.285) IC .317 (.575)More 926 -.250 (.329) NoC -.032 (.101)

MI sport Less 1270 -.077 (.312) .101 .904 NeC -.344 (.590) .292 .747 .563 .690 .000Same 2090 -.004 (.292) IC .280 (.574)More 1076 .024 (.317) NoC .015 (.096)

Page 55 of 197

Main effect Care status IE R2

b (SE) F P M (SE) F P F PLI sport Less 1222 .172 (.314) .792 .453 NeC -.305 (.591) .276 .759 2.392 .059 .000

Same 1999 -.098 (.291) IC .305 (.574)More 1215 -.038 (.314) NoC .036 (.094)

Historical Sites Less 1286 .199 (.318) 1.838 .159 NeC -.332 (.590) .285 .752 1.660 .156 .001Same 1953 .020 (.299) IC .288 (.574)More 1197 -.322 (.317) NoC -.007 (.094)

ME = Main effect; IE = Interaction effect; NeC = New carer; IC = Increased caring; NoC = Non- carer. Where interaction effects were not significant, main effects were explored using models without interaction effects, and these are the values reported in the table below.

Page 56 of 197

DiscussionGiven that research has found carers to experience limitations in their leisure

activities, and that they experience reduced wellbeing when compared to non-

caregivers, this research sought to further understand the relationship between leisure

and wellbeing for this group of individuals (Magliano et al., 2006; Mausbach,

Patterson, & Grant, 2008). Of interest were women who care for more than 20 hours

a week as there is evidence to suggest that they are at particular risk of having poorer

wellbeing (Bedim & Guinan, 1996; Smith et al., 2014). The cross-sectional study

explored whether leisure predicts wellbeing. The longitudinal study explored

whether carers experienced a decline in their leisure engagement and in their

wellbeing. It further asked whether change in leisure predicts change in wellbeing.

Data from the UK Longitudinal Household Study (UKLHS), also known as

Understanding Society, were used (University of Essex, 2017). Although there are

limitations to this study, it provided access to a large, nationally representative

sample. Further, it allowed for exploration of associations over time which is a lesser

researched area when compared with cross-sectional studies (Clarke, 2018).

Overall, hypotheses were mostly supported and poorer levels of leisure engagement

were associated with poorer levels of wellbeing. These findings are consistent with

results from studies with men and women, and from participant samples with broader

age ranges (Ficker, 2011; Hatzmann, Maurice-Stam, Heymans, & Grootenhuis,

2009; Mausbach, Roepke, et al., 2011; Williams, 2005). Among the participant

samples in both studies the range of wellbeing scores reported were broad, and carers

reported engaging in a wide range of leisure activities. This indicates that for women

Page 57 of 197

who provide care for over 20 hours a week it is possible to have a varied and

satisfying quality of leisure and a good wellbeing.

Although the relationship between leisure and wellbeing tended to be robust when

taking into consideration other key factors in the stress-process model, subjective

financial situation may be one variable which does affect this relationship. Findings

showed that people who had a greater variety of activities had better wellbeing, and

there was no relationship independent of perceived financial situation. Individuals

who perceived themselves to have more money took part in a wider variety of

activities than those who felt their financial situation was difficult. Similarly, the

relationship between frequency of arts events and wellbeing was not independent of

finances and employment, suggesting that frequency of arts events alone may not be

the cause of improved wellbeing.

Other research has linked leisure activities to SES, finding that women from a lower

SES undertake significantly less leisure activity than women from a higher SES

(Ford et al., 1991). Other research has found that finances allow carers to fund care

for their loved ones, enabling the carer to engage in leisure activities (Gladwell &

Bedini, 2004). This could be one mechanism through which finances affect the

relationship between leisure and wellbeing. More research would be helpful in better

understanding whether finances mediate, moderate or confound the effect of variety

of leisure on wellbeing, and this could be done using the UKLHS dataset.

In the cross-sectional study it was found that satisfaction with leisure time was more

relevant to wellbeing than the other leisure variables, explaining 12% of the variance.

This finding might suggest that how someone feels about their leisure engagement is

more important for wellbeing than how much leisure they are actually engaging in.

Page 58 of 197

Similarly, studies which use measures of restriction on leisure engagement (i.e.

wanting to do more but not being able to), have found significant relationships with

wellbeing, with medium to large effect sizes for some of their comparisons (Cramm

& Nieboer, 2011; Loucks-Atkinson, Kleiber, & Williamson, 2006; Mausbach,

Roepke, et al., 2011).

In line with projected findings, there was a reduction in variety and satisfaction with

leisure over time for women who became carers for more than 20 hours per week. A

strength of this study was the inclusion of a non-carer group to control for temporal

changes across the cohort, and this group also experienced the same decline. It is

possible to speculate as to reason for this. For example, research suggests that there

is an association between getting older and poorer wellbeing and therefore changes

could be attributable in some part to the increase in age of participants from W2 to

W5 (Hallal et al., 2003). Alternatively, there may have been broader social and

economic changes that affected the whole cohort, for example the recession.

Unexpectedly, becoming a carer was not associated with reduced wellbeing, which

remained stable for all groups between W2 and W5 and, surprisingly, those who

became carers had the highest GHQ-12 score at W2 prior to reporting doing caring

activities. These findings were unaffected when adjusting for change in competing

demands. Although (to the authors knowledge) these findings have not been found

elsewhere in the literature, another unpublished dissertation using UKLHS data has

had similar findings when looking at male caregivers (Warrell-Phillips, 2018).

Another related issue is whether the individual identifies with the label of “carer”,

and the impact of this on responses. However, a strength of the Understanding

Society study is the wording of questions exploring this. Participants were asked

Page 59 of 197

whether they “look after” or “provide special help” to a family member, friend,

relative or neighbour. This reduces the chance of people responding negatively to the

question because they do not identify with the label “carer” which has been found to

describe the role poorly (Hughes, Locock, & Ziebland, 2013; Molyneaux, Butchard,

Simpson, & Murray, 2011). More qualitative studies exploring the process of

becoming a carer may also be helpful in better understanding when becoming a carer

starts to impact on wellbeing.

Change in satisfaction and change in variety of leisure activities predicted change in

wellbeing. In a recent review of the literature (Clarke, 2018), Loucks-Atkinson et al.

(2006) were the only researchers to explore the relationship between leisure

engagement and wellbeing longitudinally in carers who spend a lot of time providing

care. They found that restriction with activities at time one was associated with more

symptoms of depression one and two years later. Given the limited range of

longitudinal studies in this population, further longer-term studies would be helpful

in developing understanding about the impact of leisure engagement over time, and

whether this relationship is causal.

As expected, engagement in sports was related to wellbeing as those who took part in

sports had better wellbeing than those who didn’t. Additionally, change in mild

intensity sports frequency over time was associated with change in wellbeing in the

expected direction. This is consistent with a recent literature review that found that

physical activity is associated with better wellbeing (Lambert et al., 2016). However,

causality can’t be inferred and feeling better might mean people have more energy

and are more motivated to do some sport.

Page 60 of 197

In general, there was limited evidence from the cross-sectional study of an

association between frequency of leisure and wellbeing, and surprisingly, frequency

of leisure activities remained stable over time for all groups. However, a limitation of

this study is that it was not possible to consider the magnitude of change in

frequency. This might have been more relevant to predicting the change in

wellbeing. For example, an individual who reduced their frequency of going to the

library from once a week to once a month would be in the category of “reduced

frequency” with an individual who had stopped going weekly and only went once in

the last year. Clearly the reduction in frequency was much greater for the latter

participant, however it was not possible to capture this in the analysis for this study.

Therefore, it may be of interest to explore this in greater detail.

Another limitation of this study is that some potentially relevant variables were not

able to be considered due to the quality of information gathered by the UKLHS. For

example, for female carers, there is a strong link between having to manage difficult

behaviours expressed by their husbands and activity restriction, and a link between

the behaviour and depressive symptoms (Bookwala & Schulz, 2000). It would have

benefited this study to have been able to adjust for behaviours that carers find

challenging.

There is also some evidence that feelings of guilt play a role in the relationship

between leisure and wellbeing. Romero-Moreno et al. (2012) found that (caregiving)

daughters who do not engage in leisure activities may be especially vulnerable to low

mood if they also have high feelings of guilt. This could be linked to cultural

narratives such as ethic of care (for example expectations around whose

responsibility it is to provide care) (Miller & Brown, 2005), which were not explored

Page 61 of 197

in this study. Self-esteem and self-efficacy have also been shown to be mediators and

moderators in one Asian literature review (Isa et al., 2016). Therefore, further models

that include guilt, self-esteem and self-efficacy would be helpful alongside

exploratory studies around issues around ethic of care and the impact this may have

on leisure engagement.

There is also some evidence to suggest there are qualitative differences within the

caregiving experience depending on the difficulty experienced by the cared for

individual. For example, one study found that dementia caregivers experience greater

levels of employment difficulties, mental and physical health problems, and

disruption to leisure activities than other caregivers (Ory et al., 1999). These effects

remained after intensity of caregiving demands was taken into account. Another

study compared caregivers of people with cancer, dementia, diabetes or frail elderly

(Kim & Schulz, 2008). They found higher levels of physical burden and

psychological distress for the cancer and dementia groups, even when

sociodemographic factors and caregiving involvement were controlled for.

Therefore, being able to explore the impact of this variable on the relationship

between leisure and wellbeing would be an interesting extension to this study.

Further useful extensions to this study would include the use of additional outcome

measures such as those that focus specifically on symptoms of low mood, anxiety or

stress. This would allow for a stronger understanding of the robustness of findings

from this study and help to identify whether there are differences between the

relationship between leisure engagement and specific constructs of mental wellbeing

for female carers in this group.

Page 62 of 197

Although many of the research hypotheses were supported, it is important to consider

that use of large sample sizes can result in small differences achieving statistical

significance. Further, effect sizes were small and small amounts of variance were

explained, suggesting that other factors also play a role in wellbeing for carers.

Structural equation modelling and path analysis of the variables considered in this

study may help to develop a better understanding of the range of contributing factors

to carer wellbeing and model complex pathways between variables. Other studies

have begun to develop more comprehensive models. For example, Hsieh (2011)

found that leisure time satisfaction did not moderate the relationship between

caregiving demands and quality of life. However, satisfaction and participation in

leisure buffered the effects of stress on quality of life. Also, Ficker (2011) used path

analysis and found that work disruption affected financial strain, which affected

leisure, which in turn affected depression (accounting for 12.3% of the variance in

depression).

Implications of findings

For individuals concerned with developing policy and guidelines for carers, this

study lends support for consideration of leisure as a key contributor to emotional

wellbeing for female carers in midlife who spend a significant amount of time caring.

In particular, the satisfaction that this group of carers have with the amount of leisure

time they have and whether they do physical activities. There is some research into

the barriers people face when attempting to engage in leisure activities (e.g. Gladwell

& Bedini, 2004; Innes, Page, & Cutler, 2016), however, a more nuanced

understanding for this population may be helpful for informing interventions.

Page 63 of 197

At a local level, clinicians should be aware that sport and leisure is linked with better

wellbeing for female carers in midlife who care for 20 hours a week or more. This

would enable them to develop their assessment, formulation and interventions. For

example, they might pass this knowledge on to this group of carers, and support them

to problem solve barriers to sport and leisure engagement.

Conclusions

Leisure is a key contributor to emotional wellbeing for female carers in midlife who

spend 20 or more hours a week providing care. In particular, the satisfaction that they

have with the amount of leisure time they have and whether they do physical

activities is associated with better wellbeing. This has important implications for

working with this group of carers at a local level, and at a policy level.

Page 64 of 197

ReferencesAzman, A., Jamir Singh, P. S., & Sulaiman, J. (2017). Caregiver coping with the

mentally ill: a qualitative study. Journal of Mental Health, 26(2), 98–103. https://doi.org/10.3109/09638237.2015.1124395

Bedim, L. A., & Guinan, D. M. (1996). “If I could just be selfish …”: Caregivers’ perceptions of their entitlement to leisure. Leisure Sciences, 18(3), 227–239. https://doi.org/10.1080/01490409609513284

Bedini, L., Gladwell, N., & Dudley, W. (2011). Mediation analysis of leisure, perceived stress, and quality of life in informal caregivers. Journal of Leisure, 43(2), 153–175. https://doi.org/10.1080/00222216.2011.11950231

Bittman, M., Hill, T., & Thomson, C. (2007). The Impact of Caring on Informal Carers’ Employment, Income and Earnings: a Longitudinal Approach. Australian Journal of Social Issues, 42(2), 255–272. https://doi.org/10.1002/j.1839-4655.2007.tb00053.x

Bookwala, J., & Schulz, R. (2000). A comparison of primary stressors, secondary stressors, and depressive symptoms between elderly caregiving husbands and wives: The caregiver health effects study. Psychology and Aging, 15(4), 607–616. https://doi.org/10.1037/0882-7974.15.4.607

Chassin, L., Macy, J. T., Seo, D.-C., Presson, C. C., & Sherman, S. J. (2010). The association between membership in the sandwich generation and health behaviors: A longitudinal study. Journal of Applied Developmental Psychology, 31(1), 38–46. https://doi.org/10.1016/J.APPDEV.2009.06.001

Clarke, A. (2018). Leisure influences on wellbeing among those who spend a significant amount of time caring for others: A systematic review. (Unpublished doctoral dissertation). University of Surrey, Guildford.

Cooper, C., Balamurali, T. B. S., Selwood, A., & Livingston, G. (2007). A systematic review of intervention studies about anxiety in caregivers of people with dementia. International Journal of Geriatric Psychiatry, 22(3), 181–188. https://doi.org/10.1002/gps.1656

Cramm, J. M., & Nieboer, A. P. (2011). Psychological well-being of caregivers of children with intellectual disabilities: Using parental stress as a mediating factor. Journal of Intellectual Disabilities, 15(2), 101–113. https://doi.org/10.1177/1744629511410922

Del-Pino-Casado, R., & Ordóñez-Urbano, C. (2016). Effects of satisfaction with leisure time in family carers of elderly dependents. Atencion Primaria / Sociedad Española De Medicina De Familia Y Comunitaria, 48(5), 295–300. https://doi.org/10.1016/j.aprim.2015.06.005

Dunn, N., & Strain, M. A. (2001). Caregivers at risk?: Changes in leisure

Page 65 of 197

participation. Caregivers at Risk?: Changes in Leisure Participation, 33(1), 32–55. Retrieved from https://search.proquest.com/docview/201221814?OpenUrlRefId=info:xri/sid:primo&accountid=17256

Ficker, L. J. (2011). The role of employment status, work disruption, leisure, and resources in the mental health of dementia caregiving daughters. Dissertation Abstracts International: Section B: The Sciences and Engineering. Retrieved from http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3433474%5Cnhttp://ovidsp.ovid.com/ovidweb.cgi?T=JS&PAGE=reference&D=psyc7&NEWS=N&AN=2011-99160-365

Field, A. P. (2013). Discovering statistics using IBM SPSS statistics: and sex and drugs and rock “n” roll (4th ed.). London: Sage.

Ford, E. S., Merritt, R. K., Heath, G. W., Powell, K. E., Washburn, R. A., Kriska, A., & Haile, G. (1991). Physical Activity Behaviors in Lower and Higher Socioeconomic Status Populations. American Journal of Epidemiology, 133(12), 1246–1256. https://doi.org/10.1093/oxfordjournals.aje.a115836

Gallo, J. J. (1990). The effect of social support on depression in caregivers of to the elderly. Journal of Family Practice, 30(4), 430–437. Retrieved from http://go.galegroup.com/ps/anonymous?id=GALE%7CA9023155&sid=googleScholar&v=2.1&it=r&linkaccess=fulltext&issn=00943509&p=AONE&sw=w&authCount=1&isAnonymousEntry=true

Gladwell, N. J., & Bedini, L. A. (2004). In search of lost leisure: the impact of caregiving on leisure travel. Tourism Management, 25(6), 685–693. https://doi.org/10.1016/J.TOURMAN.2003.09.003

Goode, K. T., Haley, W. E., Roth, D. L., & Ford, G. R. (1998). Predicting longitudinal changes in caregiver physical and mental health: A stress process model. Health Psychology, 17(2), 190–198. https://doi.org/10.1037/0278-6133.17.2.190

Grant, G., & Whittell, B. (2000). Differentiated Coping Strategies in Families with Children or Adults with Intellectual Disabilities: the Relevance of Gender, Family Composition and the Life Span. Journal of Applied Research in Intellectual Disabilities, 13(4), 256–275. https://doi.org/10.1046/j.1468-3148.2000.00035.x

Grosse, S. D., Flores, A. L., Ouyang, L., Robbins, J. M., & Tilford, J. M. (2009). Impact of Spina Bifida on Parental Caregivers: Findings from a Survey of Arkansas Families. Journal of Child and Family Studies, 18(5), 574–581. https://doi.org/10.1007/s10826-009-9260-3

Grover, S., & Dutt, A. (2011). Perceived burden and quality of life of caregivers in obsessive-compulsive disorder. Psychiatry and Clinical Neurosciences, 65(5), 416–422. https://doi.org/10.1111/j.1440-1819.2011.02240.x

Page 66 of 197

Hallal, P. C., Victora, C. G., Wells, J. C. K., & Lima, R. C. (2003). Physical inactivity: prevalence and associated variables in Brazilian adults. Medicine and Science in Sports and Exercise, 35(11), 1894–900. https://doi.org/10.1249/01.MSS.0000093615.33774.0E

Hamill, S. B., & Goldberg, W. A. (1997). Between adolescents and aging grandparents: Midlife concerns of adults in the “Sandwich generation.” Journal of Adult Development, 4(3), 135–147. https://doi.org/10.1007/BF02510593

Hardy, G. E., Shapiro, D. A., Haynes, C. E., & Rick, J. E. (1999). Validation of the General Health Questionnaire-12: Using a sample of employees from England’s health care services. Psychological Assessment, 11(2), 159–165. https://doi.org/10.1037/1040-3590.11.2.159

Hatzmann, J., Maurice-Stam, H., Heymans, H. S. A., & Grootenhuis, M. A. (2009). A predictive model of Health Related Quality of life of parents of chronically ill children: the importance of care-dependency of their child and their support system. Health and Quality of Life Outcomes, 7(72). https://doi.org/10.1186/1477-7525-3-34

Hill, K., Smith, R., Fearn, M., Rydberg, M., & Oliphant, R. (2007). Physical and Psychological Outcomes of a Supported Physical Activity Program for Older Carers. Journal of Aging and Physical Activity, 15(3), 257–271. https://doi.org/10.1123/japa.15.3.257

Hsieh, P.-C. (2011). Contributions of leisure participation in predicting stress coping and quality of life among parental caregivers of children with developmental disabilities. Indiana University.

Hughes, N., Locock, L., & Ziebland, S. (2013). Personal identity and the role of “carer” among relatives and friends of people with multiple sclerosis. Social Science & Medicine, 96, 78–85. https://doi.org/10.1016/j.socscimed.2013.07.023

Innes, A., Page, S. J., & Cutler, C. (2016). Barriers to leisure participation for people with dementia and their carers: An exploratory analysis of carer and people with dementia’s experiences. Dementia, 15(6), 1643–1665. https://doi.org/10.1177/1471301215570346

Isa, S. N. I., Ishak, I., Ab Rahman, A., Mohd Saat, N. Z., Che Din, N., Lubis, S. H., & Mohd Ismail, M. F. (2016). Health and quality of life among the caregivers of children with disabilities: A review of literature. Asian Journal of Psychiatry, 23, 71–77. https://doi.org/10.1016/j.ajp.2016.07.007

Iso-Ahola, S. E., Jackson, E., & Dunn, E. (1994). Starting, ceasing, and replacing leisure activities over the life-span. Journal of Leisure Reseach, 26(3), 227–249. Retrieved from https://search.proquest.com/docview/201177494/58068194B8CC4410PQ/1?accountid=17256

Jackson, E. L., & Henderson, K. A. (1995). Gender‐based analysis of leisure

Page 67 of 197

constraints. Leisure Sciences, 17(1), 31–51. https://doi.org/10.1080/01490409509513241

Kim, Y., & Schulz, R. (2008). Family Caregivers’ Strains. Journal of Aging and Health, 20(5), 483–503. https://doi.org/10.1177/0898264308317533

Knies, G. (2015). Understanding Society - UK Household Longitudinal Study: Wave 1-5, 2009-2014, User Manual. Colchester: University of Essex.

Lambert, S. D., Duncan, L. R., Kapellas, S., Bruson, A.-M., Myrand, M., Santa Mina, D., … Lambrou, A. (2016). A Descriptive Systematic Review of Physical Activity Interventions for Caregivers: Effects on Caregivers’ and Care Recipients’ Psychosocial Outcomes, Physical Activity Levels, and Physical Health. Annals of Behavioral Medicine, 50(6), 907–919. https://doi.org/10.1007/s12160-016-9819-3

Lee, Y., & Bhargava, V. (2004). Leisure time: Do married and single individuals spend it differently? Family and Consumer Sciences, 32(3), 254–274. https://doi.org/10.1177/1077727X03261631

LoGiudice, D., Kerse, N., Brown, K., Gibson, S. J., Burrows, C., Ames, D., … Flicker, L. (1998). The Psychosocial Health Status of Carers of Persons with Dementia: A Comparison with the Chronically Ill. Quality of Life Research, 7(4), 345–351. https://doi.org/10.1023/A:1024990131445

Loi, S. M., Dow, B., Ames, D., Moore, K., Hill, K., Russell, M., & Lautenschlager, N. (2014). Physical activity in caregivers: What are the psychological benefits? Archives of Gerontology and Geriatrics, 59(2), 204–210. https://doi.org/10.1016/j.archger.2014.04.001

Loi, S. M., Dow, B., Moore, K., Hill, K., Russell, M., Cyarto, E., … Lautenschlager, N. (2016). Factors associated with depression in older carers. International Journal of Geriatric Psychiatry, 31(3), 294–301. https://doi.org/10.1002/gps.4323

Loucks-Atkinson, A., Kleiber, D. a., & Williamson, G. M. (2006). Activity restriction and well‐being in middle‐aged and older caregivers. Topics in Geriatric Rehabilitation, 22(4), 269–282.

Lumley, T., Diehr, P., Emerson, S., & Chen, L. (2002). The Importance of the Normality Assumption in Large Public Health Data Sets. Annual Review of Public Health, 23(1), 151–169. https://doi.org/10.1146/annurev.publhealth.23.100901.140546

Lynn, P., & Knies, G. (2016). Understanding Society: The UK Household Longitudinal Study, waves 1-5, quality profile. Colchester: University of Essex.

Magliano, L., Fiorillo, A., Rosa, C., & Maj, M. (2006). Family burden and social network in schizophrenia vs. physical diseases: preliminary results from an Italian national study. Acta Psychiatrica Scandinavica, 113(s429), 60–63. https://doi.org/10.1111/j.1600-0447.2005.00719.x

Page 68 of 197

Martin, S. C. (2015). Psychosocial Challenges Experienced by Partners of People With Parkinson Disease. Journal of Neuroscience Nursing, 47(4), 211–222. https://doi.org/10.1097/JNN.0000000000000141

Mausbach, B. T., Coon, D. W., Patterson, T. L., & Grant, I. (2008). Engagement in Activities Is Associated With Affective Arousal in Alzheimer’s Caregivers: A Preliminary Examination of the Temporal Relations Between Activity and Affect. Behavior Therapy, 39(4), 366–374. https://doi.org/10.1016/J.BETH.2007.10.002

Mausbach, B. T., Harmell, A. L., Moore, R. C., & Chattillion, E. A. (2011). Influence of caregiver burden on the association between daily fluctuations in pleasant activities and mood: A daily diary analysis. Behaviour Research and Therapy, 49(1), 74–79. https://doi.org/10.1016/j.brat.2010.11.004

Mausbach, B. T., Patterson, T. L., & Grant, I. (2008). Is depression in Alzheimer’s caregivers really due to activity restriction? A preliminary mediational test of the Activity Restriction Model. Journal of Behavior Therapy and Experimental Psychiatry, 39(4), 459–466. https://doi.org/10.1016/J.JBTEP.2007.12.001

Mausbach, B. T., Roepke, S. S. K., Depp, C. A. C., Moore, R., Patterson, T. L., & Grant, I. (2011). Integration of the Pleasant Events and Activity Restriction Models: Development and Validation of a “PEAR” Model of Negative Outcomes in Alzheimer’s Caregivers. Behavior Therapy, 42(1), 78–88. https://doi.org/10.1016/j.beth.2009.11.006

Miller, Y. D., & Brown, W. J. (2005). Determinants of Active Leisure for Women with Young Children—an “Ethic of Care” Prevails. Leisure Sciences, 27(5), 405–420. https://doi.org/10.1080/01490400500227308

Molyneaux, V., Butchard, S., Simpson, J., & Murray, C. (2011). Reconsidering the term “carer”: a critique of the universal adoption of the term “carer.” Ageing & Society, 31(3), 422–437. https://doi.org/10.1017/S0144686X10001066

Morais, H. C. C., Soares, A. M. de G., Oliveira, A. R. de S., Carvalho, C. M. de L., Silva, M. J. da, & Araujo, T. L. de. (2012). Burden and modifications in life from the perspective of caregivers for patients after stroke. Revista Latino-Americana de Enfermagem, 20(5), 944–953.

Mosher, C. E., Champion, V. L., Azzoli, C. G., Hanna, N., Jalal, S. I., Fakiris, A. J., … Ostroff, J. S. (2013). Economic and social changes among distressed family caregivers of lung cancer patients. Supportive Care in Cancer, 21(3), 819–826. https://doi.org/10.1007/s00520-012-1585-6

Motulsky, H. (2014). Intuitive biostatistics: a nonmathematical guide to statistical thinking (3rd ed.). USA: Oxford University Press.

Neulinger, J. (1981). The Psychology of Leisure (2nd ed.). Springfield, Ill.: C. C. Thomas.

Orgeta, V., & Miranda-Castillo, C. (2014). Does physical activity reduce burden in

Page 69 of 197

carers of people with dementia? A literature review. International Journal of Geriatric Psychiatry, 29(8), 771–783. https://doi.org/10.1002/gps.4060

Ory, M. G., Hoffman, R. R., Yee, J. L., Tennstedt, S., & Schulz, R. (1999). Prevalence and Impact of Caregiving: A Detailed Comparison Between Dementia and Nondementia Caregivers. The Gerontologist, 39(2), 177–186. https://doi.org/10.1093/geront/39.2.177

Otis-Green, S., & Juarez, G. (2012). Enhancing the Social Well-Being of Family Caregivers. Seminars in Oncology Nursing, 28(4), 246–255. https://doi.org/10.1016/J.SONCN.2012.09.007

Papastavrou, E., Kalokerinou, A., Papacostas, S. S., Tsangari, H., & Sourtzi, P. (2007). Caring for a relative with dementia: family caregiver burden. Journal of Advanced Nursing, 58(5), 446–457. https://doi.org/10.1111/j.1365-2648.2007.04250.x

Parr, M. G., & Lashua, B. D. (2004). What is Leisure? The Perceptions of Recreation Practitioners and Others: EBSCOhost. Leisure Sciences, 26(1), 1–17. Retrieved from http://web.b.ebscohost.com/ehost/detail/detail?vid=2&sid=b510ebe7-4a78-4d63-ae09-c6be73274f13%40pdc-v-sessmgr01&bdata=JkF1dGhUeXBlPWlwLHNoaWImc2l0ZT1laG9zdC1saXZl#AN=11985262&db=s3h

Pearlin, L. I. (2009). The Life Course and the Stress Process: Some Conceptual Comparisons. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 65B(2), 207–215. https://doi.org/10.1093/geronb/gbp106

Pearlin, L. I., Mullan, J. T., Semple, S. J., & Skaff, M. M. (1990). Caregiving and the Stress Process: An Overview of Concepts and Their Measures. The Gerontologist, 30(5), 583–594. https://doi.org/10.1093/geront/30.5.583

Peña-Longobardo, L. M., & Oliva-Moreno, J. (2015). Caregiver Burden in Alzheimer’s Disease Patients in Spain. Journal of Alzheimer’s Disease, 43(4), 1293–1302. https://doi.org/10.3233/JAD-141374

Pinquart, M., & Sörensen, S. (2003). Differences between caregivers and noncaregivers in psychological health and physical health: a meta-analysis. Psychology and Aging, 18(2), 250–267. https://doi.org/10.1037/0882-7974.18.2.250

Raj, J., Manigandan, C., & Jacob, K. (2006). Leisure satisfaction and psychiatric morbidity among informal carers of people with spinal cord injury. Spinal Cord, 44(11), 676–679. https://doi.org/10.1038/sj.sc.3101899

Rizk, S., Pizur-Barnekow, K., & Darragh, A. R. (2011). Leisure and Social Participation and Health-Related Quality of Life in Caregivers of Children with Autism. OTJR: Occupation, Participation and Health, 31(4), 164–171. https://doi.org/10.3928/15394492-20110415-01

Rochette, A., Desrosiers, J., Bravo, G., Tribble, D. S.-C., & Bourget, A. (2007).

Page 70 of 197

Changes in participation level after spouse’s first stroke and relationship to burden and depressive symptoms. Cerebrovascular Diseases (Basel, Switzerland), 24(2–3), 255–60. https://doi.org/10.1159/000104487

Romero-Moreno, R., Márquez-González, M., Mausbach, B. T., & Losada, A. (2012). Variables modulating depression in dementia caregivers: a longitudinal study. International Psychogeriatrics, 24(8), 1316–1324. https://doi.org/10.1017/S1041610211002237

Schulz, R., O’Brien, A. T., Bookwala, J., & Fleissner, K. (1995). Psychiatric and Physical Morbidity Effects of Dementia Caregiving: Prevalence, Correlates, and Causes. The Gerontologist, 35(6), 771–791. https://doi.org/10.1093/geront/35.6.771

Smith, L., Onwumere, J., Craig, T., McManus, S., Bebbington, P., & Kuipers, E. (2014). Mental and physical illness in caregivers: results from an English national survey sample. The British Journal of Psychiatry, 205(3), 197–203. https://doi.org/10.1192/bjp.bp.112.125369

Stansfeld, S., Smuk, M., Onwumere, J., Clark, C., Pike, C., McManus, S., … Bebbington, P. (2014). Stressors and common mental disorder in informal carers – An analysis of the English Adult Psychiatric Morbidity Survey 2007. Social Science & Medicine, 120, 190–198. https://doi.org/10.1016/J.SOCSCIMED.2014.09.025

Staudinger, U. M., & Bluck, S. (2001). A View on Midlife Development from Life-Span Theory. In M. E. Lachman (Ed.), Handbook of Midlife Development (pp. 3–39). New York: John Wiley & Sons, Inc.

Thompson, L., Solano, N., & Kinoshita, L. (2002). Pleasurable activities and mood: Differences between Latina and Caucasian dementia family caregivers. Journal of Mental Health and Ageing, 8(3), 211–224. Retrieved from https://asu.pure.elsevier.com/en/publications/pleasurable-activities-and-mood-differences-between-latina-and-ca

University of Essex. Institute for Social and Economic Research, NatCen Social Research, K. P. (2017). Understanding Society: Waves 1-7, 2009-2016 and Harmonised BHPS: Waves 1-18, 1991-2009. [data collection]. (9th ed.). SN: 6614: UK Data Service. Retrieved from https://www.understandingsociety.ac.uk/documentation/citation

Vincente, M. M., Delgado, M. G., Fuertes, N., & Prieto, J. P. (2009). Effects of a program of physical exercise at home in carers of Alzheimer’s patients: a pilot study. Revista de Psicología Del Deporte, 18(2), 255–270. Retrieved from https://ddd.uab.cat/record/62733

Voss, J. (1967). The definition of leisure. Journal of Economic Issues, 1(1), 91–106. https://doi.org/10.1080/00213624.1967.11502742

Waelde, L. C., Thompson, L., & Gallagher-Thompson, D. (2004). A pilot study of a yoga and meditation intervention for dementia caregiver stress. Journal of

Page 71 of 197

Clinical Psychology, 60(6), 677–687. https://doi.org/10.1002/jclp.10259

Wakui, T., Saito, T., Agree, E. M., & Kai, I. (2012). Effects of home, outside leisure, social, and peer activity on psychological health among Japanese family caregivers. Aging & Mental Health, 16(4), 500–506. https://doi.org/10.1080/13607863.2011.644263

Warrell-Phillips, S. (2018). What factors affect the mental health and wellbeing of Middle Aged Male Carers? (Unpublished doctoral dissertation). University of Surrey, Guildford.

White-Means, S. I., & Chang, C. F. (1994). Informal caregivers’ leisure time and stress. Journal of Family and Economic Issues, 15(2), 117–136. https://doi.org/10.1007/BF02353636

Williams, I. C. (2005). Emotional Health of Black and White Dementia Caregivers: A Contextual Examination. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 60(6), 287–295. https://doi.org/10.1093/geronb/60.6.P287

Williamson, G. M., & Schulz, R. (1992). Pain, Activity Restriction, and Symptoms of Depression Among Community-residing Elderly Adults. Journal of Gerontology, 47(6), P367–P372. https://doi.org/10.1093/geronj/47.6.P367

Page 72 of 197

List of Appendices:

Appendix A: Ethical approval................................................................................................Appendix B: Questions from Understanding Society............................................................Appendix C: Leisure activities mentioned and their respective categories...........................Appendix D: Testing assumptions cross section....................................................................Appendix E: Non-parametric and robust tests for cross sectional hypotheses......................Appendix F: Frequency variables fitted as a trend in the GLM.............................................Appendix G: estimated marginal means for frequency of mild and moderate intensity sport when age and employment were adjusted for...............................................................Appendix H: Testing assumptions for longitudinal data........................................................Appendix I: Non-parametric and robust tests for longitudinal hypotheses............................Appendix J: Longitudinal analysis adjusting for other variables in the stress process model......................................................................................................................................

Page 73 of 197

Appendix A: Ethical approval

Page 74 of 197

Page 75 of 197

Page 76 of 197

Appendix B: Questions from Understanding Society

Carer characteristics (age, qualification, finances)Pos. = 1275 Variable = b_age_cr Variable label = age corrected

Value label information for b_age_cr

Page 77 of 197

Page 78 of 197

Primary stressors (hours per week caring, living with the cared for individual)

Page 79 of 197

Page 80 of 197

Competing demands (work, childcare)

Page 81 of 197

Social support (relationship quality, living with partner)

Page 82 of 197

Page 83 of 197

Page 84 of 197

Page 85 of 197

Page 86 of 197

Page 87 of 197

Page 88 of 197

Page 89 of 197

Page 90 of 197

Leisure (frequency, variety, sport/not sport, leisure time satisfaction)

Page 91 of 197

Page 92 of 197

Page 93 of 197

Page 94 of 197

Page 95 of 197

Page 96 of 197

Page 97 of 197

Page 98 of 197

Page 99 of 197

Page 100 of 197

Wellbeing

Questions used from the mainstage questionnaire.

Page 101 of 197

Page 102 of 197

Appendix C: Leisure activities mentioned and their respective categories

Arts activities Arts events

Museum library archive Historical sites

Dance, including ballet

Sang to an audience or rehearsed for a performance (not karaoke)

Played a musical instrument

Written musicRehearsed or performed in a play/drama, opera/operetta or musical theatre

Taken part in a carnival or street arts event (e.g. as a musician, dancer, or costume maker)

Painting, drawing, printmaking or sculpture

Photography, film or video making as an artistic activity (not family or holidays)

Used a computer to create original artworks or animation

Textile crafts, wood crafts or any other crafts such as embroidery, knitting, wood turning, furniture making, pottery or jewellery

Read for pleasure (not newspapers, magazines, or comics)

Written any stories, plays or poetry

Been a member of a book

Film at cinema or other venue

exhibition or collection of art, photography or sculpture or arts exhibition (not crafts market)

Event which included video or electronic art

Event connected with books or writing

Street arts or a public arts display or installation ~(art in everyday surroundings, or an art work such as sculpture that is outdoors or in a public place)

Carnival or culturally specific festival (for example Mela, Baisakhi, Navrati, Feis)

Play/drama, pantomime or a musical

Opera/operettaClassical musical performance

Rock, pop or jazz performance

Ballet

Contemporary dance

African people's dance or South Asian and Chinese dance

Used a public library service

Been to an archive centre or records office

Visited a museum or gallery

A city or town with historic character

A historic building open to the public (non-religious)

A historic park or garden open to the public

A place connected with industrial history (e.g. an old factory, dockyard or mine) or historic transport system (e.g. an old ship or railway)

A historic place of worship attended as a visitor (not to worship)

A monument such as a castle, fort or ruin.

A site of archaeological interest (e.g. roman villa, ancient burial site)

A site connected with sports heritage (e.g. Wimbledon) (not visited for the purposes of watching sport)

Page 103 of 197

club where people meet up to discuss and share books Circus (not animals)

Sporting activities Mild intensity sporting activities

Health, fitness, gym or conditioning activities (including aerobics, keep fit classes, weight-training or weight-lifting)

Gymnastics

Swimming or diving

Cycling, BMX or mountain biking (for sport or recreation)

Football (including 5 or 6-a-side)

Rugby (union or league) or American footballTrack and field athletics

Jogging, cross country, road-runningHill trekking, backpacking, climbing or mountaineering

Golf (including pitch and putt)

Boxing

Martial arts (including tai chi, taekwondo, karate, and judo)

Basketball

Netball

Volleyball

Cricket

Hockey (exclude ice, roller, or street hockey but include in "other")

Baseball, softball or rounders

Racquet sports such as table tennis, tennis, badminton or squash

Ice-skating

Skiing (on snow or an artificial surface: on slopes or grass)

Motor sports

Angling or fishing

Archery (if age > 64)

Yoga or Pilates (if age > 64)

Bowls (indoors or outdoors) (if age > 64)

Snooker, pool or billiards

Darts

Ten-pin bowling

Rambling, walking for pleasure or recreation

Shooting

Archery (if age < 65)

Yoga or Pilates (if age < 65)

Bowls (indoors or outdoors) (if age < 65)

Croquet (if age < 65)

Page 104 of 197

Water sports including yachting, dinghy sailing, canoeing, rowing, windsurfing, water-skiing etc.Horse riding

Croquet (if age > 64)

Other sporting activity such as triathlon, fencing, lacrosse, orienteering, curling, Gaelic sports, skateboarding, parachuting or scuba diving or anything else

Page 105 of 197

Appendix D: Testing assumptions cross section

Distribution

DescriptivesStatistic Std. Error

Subjective wellbeing (GHQ):

Likert

Mean 13.90 .252

Median 12.00

Variance 44.923

Std. Deviation 6.702

Minimum 0

Maximum 36

Range 36

Interquartile Range 8

Skewness 1.102 .092

Kurtosis .929 .183

Page 106 of 197

SPSS output: histograms for GHQ-12 MCS at wave 2 split across the three levels of

sporting activity, with the normal distribution curve overlayed.

No Sport:

Mean = 15Standard Deviation = 7.2N = 273

Mild intensity sport:

Mean = 13.4Standard Deviation = 6.4N = 113

Moderate intensity sport:

Mean = 13.1Standard Deviation = 6.2N = 324

Page 107 of 197

Q-Q plots

SPSS output: Q-Q plots for GHQ-12 MCS split across the three levels of sport:

Page 108 of 197

Page 109 of 197

Appendix E: Non-parametric and robust tests for cross sectional hypothesesCorrelations between Wellbeing and independent variables.

Correlationssatisfaction

with amount

of leisure time

Subjective

wellbeing

(GHQ): Likert

Spearman's

rho

satisfaction with

amount of leisure time

Correlation Coefficient 1.000 -.371**

Sig. (1-tailed) . .000

N 710 710

Subjective wellbeing

(GHQ): Likert

Correlation Coefficient -.371** 1.000

Sig. (1-tailed) .000 .

N 710 710

Subjective

wellbeing

(GHQ): Likert

Total number

of activties

Spearman's

rho

Subjective wellbeing

(GHQ): Likert

Correlation Coefficient 1.000 -.106**

Sig. (1-tailed) . .002

N 710 710

Variety of activities Correlation Coefficient -.106** 1.000

Sig. (1-tailed) .002 .

N 710 710

Kruskal-Wallis Tests exploring the relationship between frequency variables and

wellbeing:

Page 110 of 197

Page 111 of 197

Robust tests: Satisfaction and wellbeing

Variety and wellbeing

Page 112 of 197

Appendix F: Frequency variables fitted as a trend in the GLM

Arts Activities

Tests of Between-Subjects EffectsDependent Variable: Subjective wellbeing (GHQ): Likert

Source

Type III Sum of

Squares df Mean Square F Sig.

Partial Eta

Squared

Corrected Model 45.521a 1 45.521 1.013 .314 .001

Intercept 42838.399 1 42838.399 953.605 .000 .574

b_artsAct_freq 45.521 1 45.521 1.013 .314 .001

Error 31805.177 708 44.923

Total 169002.000 710

Corrected Total 31850.699 709

a. R Squared = .001 (Adjusted R Squared = .000)

Parameter EstimatesDependent Variable: Subjective wellbeing (GHQ): Likert

Parameter B

Std.

Error t Sig.

95% Confidence Interval

Partial Eta

Squared

Lower

Bound

Upper

Bound

Intercept 14.290 .463 30.881 .000 13.381 15.198 .574

b_artsAct_freq -.147 .146 -1.007 .314 -.435 .140 .001

Archives

Tests of Between-Subjects EffectsDependent Variable: Subjective wellbeing (GHQ): Likert

Source

Type III Sum

of Squares df Mean Square F Sig.

Partial Eta

Squared

Page 113 of 197

Corrected Model 56.288a 1 56.288 1.253 .263 .002

Intercept 130338.051 1 130338.051 2902.376 .000 .804

b_archive_freq 56.288 1 56.288 1.253 .263 .002

Error 31794.411 708 44.907

Total 169002.000 710

Corrected Total 31850.699 709

a. R Squared = .002 (Adjusted R Squared = .000)

Parameter EstimatesDependent Variable: Subjective wellbeing (GHQ): Likert

Parameter B Std. Error t Sig.

95% Confidence Interval

Partial Eta

Squared

Lower

Bound

Upper

Bound

Intercept 13.840 .257 53.874 .000 13.336 14.344 .804

b_archive_freq .868 .775 1.120 .263 -.654 2.389 .002

Museum

Tests of Between-Subjects EffectsDependent Variable: Subjective wellbeing (GHQ): Likert

Source

Type III Sum

of Squares df

Mean

Square F Sig.

Partial Eta

Squared

Corrected Model 152.301a 4 38.075 .847 .496 .005

Intercept 43259.347 1 43259.347 962.126 .000 .577

b_museum_freq 152.301 4 38.075 .847 .496 .005

Page 114 of 197

Error 31698.397 705 44.962

Total 169002.000 710

Corrected Total 31850.699 709

a. R Squared = .005 (Adjusted R Squared = -.001)

Parameter Estimates

Dependent Variable: Subjective wellbeing (GHQ): Likert

Parameter B

Std.

Error t Sig.

95% Confidence

Interval

Partial Eta

Squared

Lower Bound

Upper

Bound

Intercept 11.947 1.538 7.766 .000 8.927 14.968 .079

[b_museum_freq=.00] 2.175 1.567 1.388 .166 -.902 5.252 .003

[b_museum_freq=1.00] 1.018 1.772 .574 .566 -2.462 4.498 .000

[b_museum_freq=2.00] 1.686 1.765 .955 .340 -1.780 5.152 .001

[b_museum_freq=3.00] 1.888 1.727 1.093 .275 -1.502 5.279 .002

[b_museum_freq=4.00] 0a . . . . . .

a. This parameter is set to zero because it is redundant.

Arts events

Tests of Between-Subjects EffectsDependent Variable: Subjective wellbeing (GHQ): Likert

Source

Type III Sum of

Squares df Mean Square F Sig.

Partial Eta

Squared

Page 115 of 197

Corrected Model 526.218a 1 526.218 11.894 .001 .017

Intercept 74148.821 1 74148.821 1675.921 .000 .703

b_artsEve_freq 526.218 1 526.218 11.894 .001 .017

Error 31324.480 708 44.244

Total 169002.000 710

Corrected Total 31850.699 709

a. R Squared = .017 (Adjusted R Squared = .015)

Parameter Estimates

Dependent Variable: Subjective wellbeing (GHQ): Likert

Parameter B

Std.

Error t Sig.

95% Confidence

Interval

Partial

Eta

Square

d

Lower

Bound

Upper

Bound

Intercept 14.800 .362 40.938 .000 14.091 15.510 .703

b_artsEve_freq -.793 .230 -3.449 .001 -1.245 -.342 .017

Library

Tests of Between-Subjects EffectsDependent Variable: Subjective wellbeing (GHQ): Likert

Source

Type III Sum of

Squares df Mean Square F Sig.

Partial Eta

Squared

Page 116 of 197

Corrected Model 110.439a 1 110.439 2.463 .117 .003

Intercept 99149.623 1 99149.623 2211.637 .000 .758

b_lib_freq 110.439 1 110.439 2.463 .117 .003

Error 31740.259 708 44.831

Total 169002.000 710

Corrected Total 31850.699 709

a. R Squared = .003 (Adjusted R Squared = .002)

Parameter Estimates

Dependent Variable: Subjective wellbeing (GHQ): Likert

Parameter B Std. Error t Sig.

95% Confidence

Interval

Partial Eta

Squared

Lower

Bound

Upper

Bound

Intercept 14.159 .301 47.028 .000 13.568 14.750 .758

b_lib_freq -.309 .197 -1.570 .117 -.696 .078 .003

Historical Sites

Tests of Between-Subjects EffectsDependent Variable: Subjective wellbeing (GHQ): Likert

Page 117 of 197

Source

Type III Sum of

Squares df Mean Square F Sig.

Partial Eta

Squared

Corrected Model 53.000a 1 53.000 1.180 .278 .002

Intercept 79750.775 1 79750.775 1775.712 .000 .715

b_hx_freq 53.000 1 53.000 1.180 .278 .002

Error 31797.699 708 44.912

Total 169002.000 710

Corrected Total 31850.699 709

a. R Squared = .002 (Adjusted R Squared = .000)

Parameter EstimatesDependent Variable: Subjective wellbeing (GHQ): Likert

Parameter B Std. Error t Sig.

95% Confidence Interval

Partial Eta

Squared

Lower

Bound

Upper

Bound

Intercept 14.140 .336 42.139 .000 13.481 14.799 .715

b_hx_freq -.264 .243 -1.086 .278 -.740 .213 .002

Page 118 of 197

Moderate intensity sport

Tests of Between-Subjects EffectsDependent Variable: Subjective wellbeing (GHQ): Likert

Source

Type III Sum of

Squares df Mean Square F Sig.

Partial

Eta

Squared

Corrected Model 284.873a 1 284.873 6.390 .012 .009

Intercept 88379.318 1 88379.318 1982.288 .000 .737

b_MIsport_freq 284.873 1 284.873 6.390 .012 .009

Error 31565.825 708 44.584

Total 169002.000 710

Corrected Total 31850.699 709

a. R Squared = .009 (Adjusted R Squared = .008)

Parameter EstimatesDependent Variable: Subjective wellbeing (GHQ): Likert

Parameter B

Std.

Error t Sig.

95% Confidence Interval

Partial Eta

Squared

Lower Bound Upper Bound

Intercept 14.417 .324 44.523 .000 13.781 15.053 .737

b_MIsport_freq -.389 .154 -2.528 .012 -.691 -.087 .009

Mild intensity sport

Tests of Between-Subjects Effects

Page 119 of 197

Dependent Variable: Subjective wellbeing (GHQ): Likert

Source

Type III Sum of

Squares df Mean Square F Sig.

Partial Eta

Squared

Corrected Model 254.047a 1 254.047 5.693 .017 .008

Intercept 87906.483 1 87906.483 1969.759 .000 .736

b_LIsport_freq 254.047 1 254.047 5.693 .017 .008

Error 31596.651 708 44.628

Total 169002.000 710

Corrected Total 31850.699 709

a. R Squared = .008 (Adjusted R Squared = .007)

Parameter EstimatesDependent Variable: Subjective wellbeing (GHQ): Likert

Parameter B

Std.

Error t Sig.

95% Confidence Interval

Partial Eta

Squared

Lower Bound Upper Bound

Intercept 14.389 .324 44.382 .000 13.753 15.026 .736

b_LIsport_freq -.352 .148 -2.386 .017 -.642 -.062 .008

Page 120 of 197

Appendix G: estimated marginal means for frequency of mild and moderate intensity sport when age and employment were adjusted for.Moderate intensity sport and wellbeing when employment status was adjusted for:

2. b_MIsport_freqDependent Variable: Subjective wellbeing (GHQ): Likert

b_MIsport_freq Mean Std. Error

95% Confidence Interval

Lower Bound Upper Bound

Not at all 15.241 .394 14.467 16.015

Once or twice in the past

year

14.175 1.268 11.685 16.664

at least 3/4 times in the past

year

12.658 1.011 10.674 14.642

less than weekly and at least

monthly

13.507 .901 11.738 15.277

at least once per week 13.217 .658 11.925 14.508

Moderate intensity sport and wellbeing when age was adjusted for:

2. b_MIsport_freqDependent Variable: Subjective wellbeing (GHQ): Likert

b_MIsport_freq Mean Std. Error

95% Confidence Interval

Lower Bound Upper Bound

Not at all 14.677a .341 14.009 15.346

Once or twice in the past

year

13.416a .953 11.544 15.287

at least 3/4 times in the past

year

12.427a .880 10.698 14.156

less than weekly and at least

monthly

12.890a .709 11.498 14.282

at least once per week 13.096a .583 11.951 14.241

a. Covariates appearing in the model are evaluated at the following values: age corrected =

52.43.

Page 121 of 197

Appendix H: Testing assumptions for longitudinal data

Equality of variances

Levene's Test of Equality of Error Variancesa

F df1 df2 Sig.

Subjective wellbeing (GHQ):

Likert (Wave 2)

13.655 2 4433 .000

Subjective wellbeing (GHQ):

Likert (Wave 5)

7.057 2 4433 .001

Tests the null hypothesis that the error variance of the dependent variable is

equal across groups.

a. Design: Intercept + care_status

Within Subjects Design: time

Levene's Test of Equality of Error Variancesa

F df1 df2 Sig.

satisfaction with amount of

leisure time (wave 2)

.204 2 4433 .816

satisfaction with amount of

leisure time (wave 5)

.919 2 4433 .399

Tests the null hypothesis that the error variance of the dependent variable is

equal across groups.

a. Design: Intercept + care_status

Within Subjects Design: time

Levene's Test of Equality of Error Variancesa

F df1 df2 Sig.

b_variety_total

(wave 2)

5.047 2 4433 .006

e_variety_total

(wave 5)

3.772 2 4433 .023

Tests the null hypothesis that the error variance of the dependent

variable is equal across groups.

a. Design: Intercept + care_status

Within Subjects Design: time

Page 122 of 197

Distribution

Page 123 of 197

Page 124 of 197

Page 125 of 197

Page 126 of 197

Page 127 of 197

Page 128 of 197

Appendix I: Non-parametric and robust tests for longitudinal hypotheses.Results from Kruskal-Wallis tests exploring the relationship between change in

variety, satisfaction, frequency and wellbeing over time for the different carer groups

(results are consistent with results from parametric tests).

Page 129 of 197

Results from Wolcoxon Signed Rank tests to explore the relationship between variety, satisfaction and wellbeing at Wave 2 and Wave 5. Results were consistent with the results from parametric tests.

Variety

Satisfaction with leisure time

Wellbeing

Page 130 of 197

Appendix J: Longitudinal analysis adjusting for other variables in the stress process model

Results from repeated measures GLM exploring satisfaction with leisure time over time between care groups, with other factors from the stress process entered into the model one at a time.

Time Carer Status Time* Carer statusF, P F,P F, P

Unadjusted 11.704, .001 4.741, .009 2.345, .096

Carer CharacteristicsAge 10.901, .001 6.453, .002 2.366, .094Qualification 16.561, <.001 1.991, .137 3.983, .019Finances 6.779, .009 2.446, .087 1.421, .242

Competing demandsEmployment 121.062, .001 8.933, <.001 2.847, .058Childcare 5.108, .024 2.308, .100 1.060, .347

Social SupportPartner 9.532, .002 3.575, .028 2.026, .132Relationship quality 11.414, .001 4.669, .009 2.425, .089

Results from repeated measures GLM exploring variety over time between care groups, with other factors from the stress process entered into the model one at a time.

Time Carer Status Time* Carer statusF, P F,P F, P

Unadjusted 4.882, .027 11.950, <.001 .458, .633

Carer CharacteristicsAge 5.816, .016 11.546, <.001 .535, .586Qualification 5.847, .016 11.636, <.001 .563, .569Finances 3.625, .057 6.248, .002 .778, .459

Competing demandsEmployment 4.426, .035 9.096, <.001 .458, .633Childcare 4.565, .003 13.231, <.001 .194, .824

Social SupportPartner 4.896, .027 7.397, .001 .641, .527Relationship quality 4.874, .027 11.768, <.001 .459, .632

Page 131 of 197

Results from repeated measures GLM exploring GHQ over time between care groups, with other factors from the stress process entered into the model one at a time.

Time Carer Status Time* Carer statusF, P F,P F, P

Unadjusted .002, .963 19.301, <.001 .292, .747

Carer CharacteristicsAge .087, .768 19.241, <.001 .266, .767Qualification .022, .883 18.698, <.001 .306, .736Finances .002, .963 19.301, <.001 .292, .747

Social SupportPartner .275, .600 13.395, <.001 .680, .507Relationship quality

.022, .882 19.225, <.001 .208, .812

Page 132 of 197

Literature review

Leisure influences on wellbeing among those who spend a

significant amount of time caring for others: A systematic

review

Word count: 7446

Statement of journal choiceThis paper will be submitted to “Social Science & Medicine”. This journal has been

selected as its aim is to publish “original research articles…to inform current

research, policy and practice in all areas of common interest to social scientists,

health practitioners, and policy makers”. It accepts articles from the field of

psychology and has an interest in mental health and material which “is of interest to

an international readership”, as stated in the scope of the journal (Appendix A).

This portfolio fits within the remit as it explores issues pertaining to carers who are

commonly at risk of becoming mental health service users. This is a field of interest

internationally to professionals from a range of backgrounds such as health

practitioners and social scientists. Implications of findings may also be relevant for

policy makers with an interest in improving carer wellbeing nationally and wishing

to develop an understanding of the complex mechanisms underlying wellbeing

within this valued group in society.

The impact factor of the journal is 2.32 (October 2017).

Page 133 of 197

If this article is not accepted by the first choice journal, it will then be submitted to

“Health and Social Care in the Community” and “Health and Quality of Life

Outcomes”.

Page 134 of 197

AbstractBecoming a carer can result in a lack of leisure opportunities and reduction in leisure

is associated with reduced psychological wellbeing for carers. Studies in this area

often do not differentiate between those who spend only a few hours and those who

spend many hours caregiving. Therefore, this review aimed to critically examine and

summarise the existing literature on the extent to which leisure influences wellbeing

among those who spend a significant amount of time caring for others. Seven

databases were searched for terms relevant to caregiving, leisure and wellbeing and

this resulted in identification of nine papers relevant for this review. Wellbeing

measures fell into four categories: depression, positive or negative affect, general

wellbeing and positive attitudes to caregiving. Studies that explored the relationship

between depression and leisure had findings that were consistent with the idea that

lower levels of engagement with leisure activities are associated with depression.

Additionally, positive affect, general wellbeing and positive feelings relating to

caregiving were associated with higher leisure engagement and satisfaction. Number

of hours spent in leisure may be less relevant to understanding the relationship

between leisure engagement and wellbeing than other dimensions of leisure

engagement. Limitations to this review included a lack of papers exploring mediators

and moderators of the relationship, limited methodological designs (largely cross-

sectional questionnaire studies) and lack of consideration of the caregiver and cared

for individual engaging in leisure activities together. Further research in these areas

would be beneficial.

Page 135 of 197

Introduction

Informal Caregiving

There are 6.5 million unpaid carers in the UK and this figure is expected to rise to 9

million over the next 20 years (Carers UK, 2015). Carers are individuals who provide

support to another including with activities which are required in order to live

independently. The types of activities they do are varied and include practical help

(e.g. preparing meals, laundry, shopping), keeping an eye on the cared for, keeping

them company, taking them out, aspects of personal care, providing physical help,

and supporting them to deal with care services, benefits, and finances (Carers UK,

2015). Unpaid carers are also called “informal” or “volunteer” carers.

The term “carer” is not always considered truly reflective of the (often reciprocal)

relationships which are characterised by one partner supporting the other in their day

to day tasks (Hughes, Locock, & Ziebland, 2013; Molyneaux, Butchard, Simpson, &

Murray, 2011). Further, there has been some suggestion that the term “carer” carries

an assumption of burden, and it would be preferable to use relationship descriptors

that existed prior to the start of the caring role (e.g. husband, wife, daughter, son,

parent). For the purpose of narrative eloquence this review will use the terms “carer”

and “caregiver” to capture the broad range of relationships held within this group.

However, wherever possible, pre-existing relationship descriptors will be used as

synonymous alternatives.

Levels of care

Those who care for more than 20 hours per week (HPW) are more likely to provide

physical help, personal care, and support with medications than those caring less than

20 HPW (Carers UK, 2015). This suggests that people who spend more time caring

Page 136 of 197

are likely to be performing different or additional caregiving tasks compared with

those who spend less time caring.

Measuring the number of hours an individual spends caring is one way of

understanding the level of care provided. However, considering time in isolation

from the type and quality of tasks carried out provides a limited picture of the actual

demands and rewards of the caregiving experience. Carers who do not live with the

individual they are caring for may have significant travel times to get to the person

cared for to fulfil their responsibilities. Caregivers may also spend time planning for

others to assist with the caregiving responsibilities (e.g. other family members or

paid professionals). Within research it is not always clear to what extent these caring

components are considered.

Another way to understand the demands of caregiving is to examine the type and

quality of caregiving tasks. Often the kinds of activities required for independence

are categorised into Activities of Daily Living (ADLs; S. Katz, Ford, Moskowitz,

Jackson, & Jaffe, 1963) and Instrumental Activities of Daily Living (IADLs; Lawton

& Brody, 1970). ADLs include basic and essential self-care tasks such as washing,

toileting and eating. In contrast to this IADLs include tasks such as shopping,

cooking and managing finances. Counting the number of ADLs and IADLs that a

carer supports someone with and the extent to which support is provided is a

common method of understanding the level of care that a carer provides. These offer

a way of understanding one aspect of the caregiving demands although do not

provide a detailed picture of the complexities of the caregiving experience (Levine,

Reinhard, Feinberg, Albert, & Hart, 2003).

Page 137 of 197

Many carers are spouses, offspring, parents, other relatives, neighbours and friends.

Some are carers from the start of the relationship (e.g. parents of children with

special needs) and others experience caregiving as a change within the existing

relationship dynamic (Gautam & Nijhawan, 1984; López, López-Arrieta, & Crespo,

2005). Carers meet the practical needs of another, and also form an important part of

the emotional and relational world of the cared for individual, often in a reciprocal

way (Hughes et al., 2013). This means that the relationship is not only beneficial for

the individual being cared for, but also for the carer themselves (e.g. gaining

satisfaction from the role, receiving emotional support from the individual they care

for, experiencing them as fun to be with, or as having a sense of humour; Nolan,

2001). All of these things contribute to the complexities of the caregiving role,

caregiving relationship and the emotional health and wellbeing of the carer.

Emotional Health and Wellbeing of Carers

Given the value of carers and their significant contribution to society it seems

important to be able to understand and support their wellbeing. Caring can be

rewarding and add to their relationship with the cared for individual (Szmukler et al.,

1996). Individuals report improved family bonds, love, hope and support for the

individual they are caring for (Treasure et al., 2001). The opportunity to learn and the

chance for reciprocity have also been identified as valuable consequences (Stern,

Doolan, Staples, Szmukler, & Eisler, 1999). Positive psychological states can exist in

caregivers alongside stressful circumstances and feelings of distress (Folkman,

1997).

Additionally, this role can be associated with challenges. The caregiving population

is at greater risk of both physical and mental health problems than non-caregivers

Page 138 of 197

(Haley, Roth, Hovater, & Clay, 2015; Peña-Longobardo & Oliva-Moreno, 2015;

Pinquart & Sörensen, 2003). This therefore makes them at risk of not being able to

continue their caregiving role or perhaps requiring care themselves. Notably in one

study, people who spent more hours caring were at greater risk, and those who cared

more than 20 HPW had a twofold increase in psychiatric symptoms when compared

with non-caregivers (L. Smith et al., 2014). One important component that is used to

understand the caregiving experience is burden, which takes into consideration some

of the negative psychological impacts of caregiving.

Burden is sometimes divided into “subjective” vs “objective (Magliano, Fiorillo,

Rosa, & Maj, 2006) or “Practical” vs “psychological” (Magliano et al., 2002)

however the distinction between these are not always well defined. The concept of

burden is very broad and, according to measurement tools such as the Zarit Burden

Interview ((Zarit, Reever, & Bach-Peterson, 1980) a commonly used measure of

burden), includes psychological components (such as feeling stressed or angry),

practical impact of caring (such as on privacy or finances), and cognitive evaluations

of caring ability (such as “should be doing a better job”).

Burden is a widely-researched concept and has been repeatedly shown to negatively

impact on the leisure experiences of caregivers (Ausserhofer, Mantovan, Pirhofer,

Huber, & Them, 2009; Chakrabarti, Raj, Kulhara, Avasthi, & Verma, 1995; Eric

Hwang, Rivas, Fremming, Rivas, & Crane, 2009), particularly in leisure reduction.

However, because burden is a broad multi-faceted concept, which includes

information additional to psychological wellbeing it was not included in this

literature review.

Page 139 of 197

Components of psychological wellbeing may include, mood or affect, worry, stress,

anxiety, or satisfaction. These ideas may be measured from a deficit oriented model

e.g. through questionnaires exploring diagnosable conditions such as depression and

anxiety. Alternatively, it may be approached from a positive psychology framework

asking more broadly about psychological wellbeing (as in quality of life measures),

or about how good people feel about their caregiving role.

Theories such as Pearlin’s Stress Process model (Pearlin, Mullan, Semple, & Skaff,

1990) seek to explain how caregiving experiences contribute to reduced wellbeing.

Pearlin suggests that primary stressors (e.g. becoming a carer) result in secondary

stressors (e.g. having limited time for engaging in hobbies) which then impact on an

individual’s wellbeing (e.g. reduced mood). This holds face validity and has been

supported through some of the caregiving research (Haley, LaMonde, Han, Burton,

& Schonwetter, 2004; Infurna, Gerstorf, & Zarit, 2012; Pearlin, 2009; Romero-

Moreno, Márquez-González, Mausbach, & Losada, 2012). This model suggests that

there may be different (or more accentuated) secondary stressors for individuals who

spend more of their time caring. Particularly in view of the fact that there are limited

hours in a week and a greater proportion of these are taken up for caregiving

potentially means fewer hours for other usual commitments such as self-care or

leisure. They may also have increased financial strain if they have had to reduce their

working hours to accommodate for an increase in their caring hours.

Theories and measures of leisure

Voss (1967) defines leisure in terms of time allocation. Activities are either

economically motivated (called work), non-economically motivated but integral to

the maintenance of life (e.g. childcare, cleaning etc.) or discretionary (meaning one

Page 140 of 197

has the freedom of choice). Leisure is the latter of the three. This theory is similar to

Neulinger’s (1981) theory that perceived freedom of choice is integral to the

definition and so too is the need to be intrinsically motivated to do the activity.

These broad definitions pose dilemmas within research as some activities may fall

into different categories depending on the individual and the wider context of the

situation. For example, one individual may choose to spend their free time cooking

(leisure), whereas another may complete this activity only because it is integral to the

maintenance of life (not leisure), and another may cook for the financial reward

(work). It also opens up the possibility of an enormous number of specific activities

being defined as possible leisure activities. Therefore, generating exhaustive

checklists of leisure activities may not be feasible. Some researchers have attempted

to overcome this by allowing respondents to add their own activities to their checklist

(Rizk, Pizur-Barnekow, & Darragh, 2011). However, unfortunately, the validation

study for this particular checklist remains unpublished and therefore there are

challenges for researchers interested in using this measure/approach.

An alternative solution is to divide leisure activities into categories and ask about

those, or ask broader questions about leisure engagement. For example, Lee &

Bhargava (2004) divide leisure into passive, active, and social with each of these

providing different benefits to the individual (e.g. physical health and intellectual

development). Similarly, a national American study called Resources for Enhancing

Alzheimer’s Caregiver Health (REACH; Wisniewski et al., 2003) used a 7-item

measure which asked about items such as “having quiet time to yourself”, “going out

for meals”, and “taking part in hobbies”. Participants rated their engagement on a

scale from “not at all”, to “a lot”. This allows for a broader assessment of people’s

Page 141 of 197

participation in pleasant activities than those studies which use only one question,

and are quicker to administer than those that list a broad range of activities.

Other considerations within this area might be access to facilities, and practical

barriers to leisure. One theory frames this using the terms “Place-centred” and

“person centred” components of leisure (Lloyd & Auld, 2002). Their theory suggests

that access to and use of leisure facilities (“place-centred”) as well as personal

satisfaction or reward obtained from engaging with leisure activities (“person

centred”) are important. The latter component may sometimes be measured using the

Leisure Time Satisfaction questionnaire (Stevens et al., 2004). This approach may

also include measurement of the level of engagement with leisure activities (i.e.

frequency or duration of activities). Practical barriers may also fall within the

secondary stressors part of the stress process model mentioned previously.

Barriers such as time limitations, financial strain, and access to facilities may lead to

a feeling of being unable to engage as fully with leisure interests as the individual

may like. This concept has been explored using the Activity Restriction Scale (ARS;

Williamson & Schulz, 1992). The scale asks about “sports and recreation”, “visiting

friends”, “working on hobbies” and “maintaining friendships” which were

conceptualised as being “expressive activities”. Similar to Neulinger’s definition of

leisure, expressive activities were considered to be intrinsically motivated. Another

study used two alternative measures: the Satisfaction with Time for Leisure scale and

the Satisfaction with Quality of Leisure scale (Bedini, Gladwell, & Dudley, 2011).

This illustrates the variety and quantity of measures that exist within the leisure

literature. There are few measures that are widely used and there are many ways of

approaching the topic, depending on the specific research question and wider

Page 142 of 197

context. Given that leisure is such a broad concept it is important to be able to break

it down into quantifiable concepts (e.g. frequency, restriction and satisfaction) as this

enables empirical research to better understand the relationship between leisure and

wellbeing.

Impact of leisure on the wellbeing of carers

Engaging in leisure activities could be a protective factor for carers. For example,

wives who participated in a telephone based exercise intervention had reduced stress

when compared with controls (Connell & Janevic, 2009). Studies have also found

that for some individuals’ leisure activities are used as a helpful coping mechanism

and as a way of holding onto one’s sense of self (Azman, Jamir Singh, & Sulaiman,

2017; Gahagan, Loppie, Rehman, Maclellan, & Side, 2007). Within the caregiving

literature there is evidence for a link between yoga and relaxation, and reduced

anxiety (Cooper, Balamurali, Selwood, & Livingston, 2007). Additionally, there is

some evidence that satisfaction with leisure time may be associated with reduced

biological indicators associated with stress (Chattillion et al., 2012).

There is evidence that reducing leisure leads to emotional stress and reduced life

satisfaction for carers (White-Means & Chang, 1994). Carers who are more satisfied

with their leisure time experience lower levels of anxiety and depression (Del-Pino-

Casado & Ordóñez-Urbano, 2016). However, the relationship between leisure and

wellbeing for carers is not straight forwards. One study has shown that restriction in

leisure activities results in reduced wellbeing and that this relationship is mediated by

perceived stress (Cramm & Nieboer, 2011). Another model described leisure

reduction as a secondary stressor and sought to understand pathways from primary

stressors, through secondary stressors to symptoms of low mood. They found that the

Page 143 of 197

primary stressors (behaviours that challenge and amount of help needed)

significantly predicted activity restriction, however activity restriction did not

significantly predict low mood (Bookwala & Schulz, 2000).

A further model by Bedini et al (2011) explored the effects of three different leisure

variables: leisure participation, satisfaction with leisure time, and satisfaction with

quality of leisure time which were all found to be associated with quality of life.

Additionally, for the latter two leisure variables, this relationship was found to be

mediated through perceived stress.

This illustrates the complexities in understanding the impact of leisure on

individuals, and therefore the challenges for researchers seeking to develop their

understanding of the relevant processes and mechanisms involved. A limitation of

the above described literature is that there is minimal clarity over whether these

findings are applicable to those carers who spend only a few hours a week caring,

and those who spend a significant amount of their time caregiving. Therefore, it will

be helpful to establish whether there is a clear association between wellbeing and

leisure engagement for carers who spend a significant amount of time providing care.

Caregiving around the world

It has been noted that there are significant differences in how different cultures

understand mental illness, how people seek and engage with treatment and support

(Kealey, 2005; Mojaverian, Hashimoto, & Kim, 2012), and their emotional

experiences of caregiving. There are differences in how individuals perceive the

family unit and therefore caring responsibilities within that family unit. For example,

Youn and colleagues (1999) found that family values are prioritised over the needs of

individual family members more in Korean families, than in American families.

Page 144 of 197

They also found higher levels of embarrassment and anger in offspring from Korean

families than White (American) families. Another study found that Chinese

caregivers have comparable levels of psychological wellbeing to non-caregivers, in

contrast to other cultures in which caregivers have reduced psychological wellbeing

when compared to their non-caregiving counterparts (Shaw et al., 1997). These

differences might suggest that culturally derived expectations about free time play a

role in psychological wellbeing, a component that is notably missing from common

definitions of leisure described above.

Therefore, although there is a large body of literature coming out of Asia

investigating various aspects of caregiving experiences (W.-T. Chien & Norman,

2009; W. T. Chien, Chan, Morrissey, & Thompson, 2005; Oshio & Kan, 2016) it is

unclear to what extent their findings are applicable to individuals within the UK.

This is particularly the case when methodology within these studies incorporates

structures that are underpinned by theory specific to Asian cultures. With this in

mind, studies which focus outside of Westernised cultures are considered outside of

the scope of this literature review.

Summary

It has been widely evidenced that a lack of leisure opportunities can result from

becoming a carer for individuals experiencing a range of challenges including

dementia, stroke, Parkinson’s disease, cancer, schizophrenia and mood disorders

(Chakrabarti et al., 1995; Flores, Berbis, Chinot, & Auquier, 2014; Martin, 2015;

Ory, Hoffman, Yee, Tennstedt, & Schulz, 1999; Rochette, Desrosiers, Bravo,

Tribble, & Bourget, 2007). It has also been shown that reduction in leisure is

associated with reduced psychological wellbeing for carers of a range of ailments

Page 145 of 197

such as individuals who have experienced spinal cord injury, dementia, cancer, liver

and lung transplant (Flores et al., 2014; Mausbach, Coon, Patterson, & Grant, 2008;

Meltzer & Rodrigue, 2001; Raj, Manigandan, & Jacob, 2006). However, it is often

the case that studies do not differentiate between those who spend only a few hours a

week caring and those who spend many hours each day caregiving. These two

groups are likely to have significant differences in their caregiving experiences

(Carers UK, 2015). Therefore, this review aimed to critically examine and

summarise the existing literature on the extent to which leisure influences well-being

among those who spend a significant amount of time caring for others.

MethodPreliminary searches were carried out using search terms identified by the researcher

with use of a thesaurus. A collection of terms were identified to represent the

concepts of “carer”, “wellbeing”, and “leisure”. This general searching of relevant

fields yielded additional terms which are commonly used throughout the literature.

The final search terms are shown below in Table 1.

Table 1: Search terms used

Database (date of search)

Caregiving search terms

Wellbeing search terms

Leisure search terms

Hits Other specifiers

Web of science (18/12/2016)

caregivers or carers or caring or caregiver or carer or caregiving or spouse or sibling(IN TOPIC)

“Wellbeing” or “well being” or “health” or “mental health” or depression or anxiety or stress or burden or “quality of life”(IN TOPIC)

“social activit*” or “leisure activit*” or "leisure time" or “recreation” or “activity theory” or leisure(IN TOPIC)

2,597 1970+, English

Web of science (18/12/2016)

1,236 As above AND("behavior sciences" OR "Geriatrics & Gerontology" OR

Page 146 of 197

Database (date of search)

Caregiving search terms

Wellbeing search terms

Leisure search terms

Hits Other specifiers

"Health Care Sciences & Services" OR "nursing" OR Psychiatry OR "Public, Environmental & Occupational Health" OR "Arts & Humanities" Or "social sciences") (in SUBJECT) 

Psychology cross search:PsycINFO, PsycARTICLES, Psychology and Behavioral Sciences Collection, PsycBOOKS, MEDLINE (18/12/2016)

caregivers or carers or caring or caregiver or carer or caregiving or spouse or sibling 

“Wellbeing” or “well being” or “health” or “mental health” or depression or anxiety or stress or burden or “quality of life”

“social activit*” or “leisure activit*” or "leisure time" or “recreation” or “activity theory” or leisure

1,148 In title or abstract

Data Sources

PsycINFO, PsycARTICLES, Psychology and Behavioral Sciences Collection,

PsycBOOKS, MEDLINE and Web of Science were searched using the terms

identified in table 1 on 18th December 2016. This generated a list of 1851 titles (after

duplicates had been excluded), of which 1715 were assessed as not relevant based on

the title. The abstracts of the remaining 136 papers were assessed to determine

whether they met the inclusion criteria. In the case of 61 of these papers it was not

clear from the abstract whether the inclusion criteria had been met and therefore the

full paper was searched. Nine additional papers were identified through hand

searching reference lists from relevant studies that were identified in the searches and

undertaking citation searches for relevant studies. Details of how many papers were

Page 147 of 197

excluded at each stage and on what basis they were excluded are represented in

Figure 1.

Figure 1: PRISMA 2009 flow diagram showing the selection process.

Inclusion/Exclusion criteria

Papers were included in this review if the participant sample was comprised of

individuals providing a moderate to high level of care (20 HPW or more, or the cared

Full-text articles excluded,

Records excluded as the title was not relevant

(n = 1715)

Records excluded as abstract was not relevant

(n = 96)

Abstracts screened

(n = 136)

Records after duplicates removed (all titles screened; n=1851)

(n = 1851)

Additional records identified through other sources

(n = 0)

Identification

Screening

Records identified through database searching

(n = 2384)

Page 148 of 197

for individual required support with at least one ADL or two IADLs), if the cared for

individual was living at their home (rather than a residential or nursing facility), and

if it explored the relationship between leisure and psychological wellbeing.

Papers were selected if the participant sample was drawn from “Western” cultures,

and if the paper was accessible in English. Articles were all peer reviewed and were

considered to contribute new knowledge to the existing literature base. Where papers

included caregivers providing a range of levels of care, only those which

disaggregated the results by time spent caring were included.

Where levels of care were not specified, they were assumed to be high if the carer

required respite, or if they were a parent caring for a child with additional needs.

Many studies reported mean hours of care above the 20 HPW cut off for this review.

However, a significant proportion of these also reported a range which indicated at

least one participant in the study was caring for less than 20 HPW. Therefore, it was

felt that the mean hours of care across participants was not a good enough indication

of the studies meeting eligibility criteria for this review, and studies were only

included if they also reported a range above 20 HPW.

Papers were also excluded if they were not available in English and if the carers were

paid staff members. Papers which explored a leisure intervention combined with

another intervention (such as psychoeducation) as a key component were not

included in this review. This is because it was not possible to separate out the effects

of leisure and the additional intervention.

Finally, wellbeing outcome measures were considered carefully. If they included

measures of physical health, the environment, or other components that were not

Full-text articles excluded,

Page 149 of 197

separated in the analysis from psychological wellbeing, they were not considered

relevant for this review.

The first author completed the screening process independently and consulted with

two other researchers on a selection of 9 papers to check for inter-rater agreement.

Where there was disagreement the paper was discussed between the researchers until

all parties reached a consensus.

Data Extraction

Initial data extraction consisted of general study characteristics as presented in tables

2 and 3. This was followed by more detailed extraction of results from each of the

studies.

Data Analysis

All papers were evaluated for quality using Qual Syst (Kmet, Lee, & Cook, 2004), to

ensure a consistent approach to the review process. This tool was selected as it is

widely used within caregiving literature (e.g. Greenwood, Habibi, Smith, &

Manthorpe, 2015; Greenwood & Smith, 2015; Kuo, Sun, & Tang, 2017; R. Smith &

Greenwood, 2014), and it can be used with a range of different study designs.

However, the guidelines were at times vague. NICE guidelines which were designed

for use with intervention studies and so largely not applicable, did have some more

specific advice about how to consider reliability and validity (NICE, 2012).

Therefore, this was used in conjunction with the Qual Syst checklist.

Ratings from the QualSyst were not used as inclusion or exclusion criteria for this

review. Rather, the tool was used as a starting point to guide qualitative evaluation

and make relative comparisons across the included studies.

Page 150 of 197

For analysis, papers were divided based on which psychological wellbeing

component was investigated. Tables including extracted data from the studies were

critically reviewed and summarised to provide a clear synthesis of results.

ResultsA total of 9 papers met the inclusion criteria, most were from the USA (7 papers),

and 2 papers came from Europe. A total of 2,605 participants took part across all of

the studies with the smallest participant sample being 25, and the largest being 720.

Each of the studies’ participant samples were over 70% female, and two included

women only. When ethnicity was reported, all studies had a greater proportion of

Caucasian participants than from any other ethnic group. One study compared

Caucasian experiences with that of Latinas and one compared experiences of

“White” people and “Black” people. Two studies did not report on the ethnicities of

their participants.

Where reported, the ages of participants ranged from 19 to 95. The mean ages for

each study ranged from 39 to 74. In most of the studies carers were caring for

individuals with probable Alzheimer’s Disease and Related Disorders (ADRD) and

these carers tended to be spouses or off-spring. Three studies deviated from this

pattern as their participants were parents of children who had chronic illness,

disabilities, and autism. Further details relating to the studies are in tables 2-4.

Page 151 of 197

Table 2: Summary of participant characteristics

Authors (year) n

Females n (%)

Reason care is required

Relationship to cared for n (%)

Ethnicityn (%)

Educationn (%)

Employment status n

(%)

Level of caregiving need

Age range; mean; standard deviation

Cramm & Nieboer (2011)

123 98 (79.7) Children with a disability

Father = 25 (20.3)Mother = 90 (73.2)other family = 4 (3.3)Foster mother = 3 (2.4)Other = 1 (0.8)

- - - carers required additional support

27-49; M=38.6; -

Ficker (2011)

486 486 (100) ADRD, or cognitive impairment.

Daughter = 444 (91.4), Daughter-in-law = 27 (5.5),Granddaughters = 15 (3.1)

White non-hispanic = 44.9%, African American = 29.8%, Latino = 24.3%

M 13.1 years of education, SD 2.5

Full-time = 118 (40.8)Part-time = 25 (8.7)Homemaker = 59 (20.4)Retired = 49 (17.0)Unemployed = 37 (12.8)

4 or more hours per day, including help with at least 2 IADLs or 1 ADL

19-79; M=51.8; SD=10.09

Hatzmann et al. (2009)

543 452 (83) Chronically ill children

parent = 452 (100) - Primary education, Lower and Middle General Secondary education: 140 (26%)Middle Vocational education,Higher Secondary education, Pre-university education: 220 (41%)Higher Vocational Education, University = 175 (33%)

- out of 8 specified tasks required support with M=3.2, SD=2.5

M=42; SD=6.5

Page 152 of 197

Authors (year) n

Females n (%)

Reason care is required

Relationship to cared for n (%)

Ethnicityn (%)

Educationn (%)

Employment status n

(%)

Level of caregiving need

Age range; mean; standard deviation

Loucks-Atkinson et al. (2006)

t1=310, T2=214, T3=159

T1 – (77.1) aged 60 or over, 41% had ADRD

Spouse = (45.8); Children = 38.7)

79% Caucasian university/ college 60.3%

- At least 1 ADL or 2 IADLs.Mean number of ADLs = 10.44, SD=4.45

M=62.8; SD=14.23

Mausbach, Harmell et al. (2011)

25 24 (96) AD Spouses = 17 (68)Non-Spouses = 8 (32)

Caucasians = 21 (84%)Latina/Hispanic = 4 (16%)

- - at least 8 hours per day and at least 1 ADL or 2 IADLs.Mean hours of care per week = 56.7, SD 51.4

M=63.2; SD=11.4

Mausbach, Roepke et al. (2011)

108 77 (71.3) probable AD

Spouses = 108 (100) - University/ college graduates = 50 (46.3%), <High school = 2 (1.9%), High school equivalent = 19 (17.6), some college = 37 (34.3%)

- Total ADLs/IADLs requiring support with M=9.29, SD = 3.64

M=73.88; SD=8.02

Rizk et al. (2011)

33 33 (100) Child with autism

Mother = 33 (100) - - Employed = 21 (67.7)Unemployed = 10 (32.3)

Parent of child with additional needs

27-49; M=38.6;

Thompson et al. (2002)

257 257 (100) ADRD, or cognitive impairment.

Wife = 100 (38.9), Daughter = 157 (61.1)

Caucasians = 147Latinas = 110

White: less than HS = 6 (4%), HS Graduate = 141 (96%); Hispanic: less than High school = 48 (44%), High School graduate = 62 (56%)

Employed = 53 (36)unemployed = 94 (64%)

4 or more hours per day, including help with at least 2 IADLs or 1 ADL

Caucasian: M=61.45; SD=13.03Latina: M=51.76; SD=12.89

Page 153 of 197

Authors (year) n

Females n (%)

Reason care is required

Relationship to cared for n (%)

Ethnicityn (%)

Educationn (%)

Employment status n

(%)

Level of caregiving need

Age range; mean; standard deviation

Williams (2005)

720 Black (82) White (73)

ADRD, or cognitive impairment.

Black: Spouse = (26) Child = (55)Other relative = (16)Other = (3); White: Spouse = (61), Child = (35), Other relative = (3), Other = (1)

Black = 295 (41), White = 425 (59),

Black: >= High School = (77), <High School = (23); White: >=High School = (85), <High School = (15)

Black: Employed = (36), Homemaker = (12), unemployed = (52)White: Employed = (26), Homemaker = (21), Unemployed = (52)

4 or more hours per day, including help with at least 2 IADLs or 1

range: 23-95Black: M=58.1, SE = 0.75White: M=65, SE = 0.62

Table 3: Summary of study characteristics, quality ratings and limitations.

Authors (year)

Location Study design & sampling method

Study aims relevant to this review

Leisure measure (Reported reliability of measure)

Wellbeing measure (reported reliability of

measure)

Quality rating and key limitations

Cramm & Nieboer (2011)

Netherlands

Cross section, questionnaires

Identify which factors affect the psychological wellbeing of caregivers of children with learning disabilities

6-point rating scale for the number of times in the last 4 weeks that social activities had been hindered by caregiving tasks

HADS (Cronbach’s alpha = .86)

95%No consideration of the education level and ethnicity of participants which affects the generalisability of findings.

Ficker (2011)

USA Cross section To understand the extent to which restrictions in leisure activities mediate the

7 item scale devised by REACH to measure leisure/pleasant events

CES-D (Cronbach’s alpha = .86)PAC (Cronbach’s alpha = .88)

86% Cronbach’s alphas were not reported for all measures, there was limited consideration of

Page 154 of 197

Authors (year)

Location Study design & sampling method

Study aims relevant to this review

Leisure measure (Reported reliability of measure)

Wellbeing measure (reported reliability of

measure)

Quality rating and key limitations

relationship between work reduction and mental health in daughter caregivers.

variance, and exact p values were not reported.

Hatzmann et al. (2009)

Netherlands

Cross section To explore leisure time and holidays as mediators of health related quality of life of parents of chronically ill children.

HPW spent doing leisure activitiesNumber of holiday days in the past year

TAAQOL (not reported)MCS (not reported – reference supplied)

86%Ethnicity of participants not reported, no Cronbach’s alpha for outcome measures in this study, diagram of paths and variance not included.

Loucks-Atkinson et al. (2006)

USA Cross section andLongitudinal/ prospective cohortquestionnaires

To assess the ability of activity restriction to predict the wellbeing of carers.

ARS (Cronbach’s alpha= .89),

CES-D (Cronbach’s alpha=.91)

100%

Mausbach Harmell et al. (2011)

USA Cross section, activity diary self-report over a week and questionnaires

To explore the relationship between affect and activity in caregivers.

PES-AD (Cronbach’s alpha=.83)

PANAS (PA Cronbach’s alpha >.86, and NA Cronbach’s alpha >.84)

91%Level of education of participants not reported, not all confounding variables controlled for.

Mausbach, Roepke, et

USA Cross section To test an integrated “pleasant events” and

ARS (Cronbach’s alpha = .76),

CES-D 10 (coefficient alpha = .76)

95%Ethnicity not reported.

Page 155 of 197

Authors (year)

Location Study design & sampling method

Study aims relevant to this review

Leisure measure (Reported reliability of measure)

Wellbeing measure (reported reliability of

measure)

Quality rating and key limitations

al. (2011) “activity restriction” (PEAR) model.

PES-AD (Cronbach’s alpha = .75)

PANAS (PA Cronbach’s alpha = .88; NA Cronbach’s alpha = .82)

Rizk et al. (2011)

USA Cross section To examine the association between leisure and social participation and health related quality of life of mothers of children with ASC.

LICL (weighted kappa coefficients = .76)

MCS (reliability coefficient = 0.86)

77%Limited reliability and validity data for the main outcome measure.The methodology for calculating leisure participation may lack validity.Ethnicity and education not reported.

Thompson et al. (2006)

USA Cross section To compare the impact of pleasant activities on levels of depression across ethnicities.

OPPES-A (alphas for the subscales ranged from .60 to .82)

CES-D (not reported) 100%

Williams (2005)

USA Cross section To determine what contextual factors predict emotional health.

LTS (Cronbach’s alpha = .80)

CES-D (Cronbach’s alpha = .72)PAC (Cronbach’s alpha = .90)

95%p values/ranges for correlations were not reported.

CES-D: Centre for Epidemiologic Studies - Depression Scale; PANAS: Positive and Negative Affect Scale; PAC: Positive aspects of caregiving; MCS: Mental Component Score from the SF12; LICL: Lin Interest Checklist; OPPES-A: Older Persons Pleasant Events Scale; ARS: Activity Restriction Scale; PES-AD: Pleasant Events Schedule- Alzheimer’s Disease; HADS: Hospital Anxiety and Depression Scale; LTS: Leisure Time Satisfaction; TAAQOL: TNO-AZL Questionnaire for Adult's Health Related Quality of Life; HPW: Hours per week.

Page 156 of 197

Table 4: Summary of study results, organised by dependent variable

Authors (year)

Independent variable Dependent variable

Mediator/ moderator

Statistical test Result and effect size P value

Depression:Ficker (2011)

Frequency of leisure Frequency of leisure (low vs high)Frequency of leisure (low vs high) for people with no work disruptionFrequency of leisure (low vs high) for people whose work was disrupted by caregiving demands.

DepressionDepressionDepression

Depression

- CorrelationT-testT-test

T-test

r=-.35 t=-5.35t=5.09

t=5.35

p<.001p≤.001p<.001

p≤.001

Mausbach, Roepke et al. (2011)

Pleasant events / activity restriction Depression - ANOVA FM (SD) [95% CI]

Cohen’s d

F=10.89HPLR: 5.61 (5.65) [3.65-7.56]HPHR/LPLR: 8.07 (4.61) [6.49-9.65]LPHR: 11.58 (5.52) [9.88-13.28]LPHR vs HPLR = 1.07LPHR vs HPHR/LPLR = 0.7

-

Loucks-Atkinson

T1: Expressive activity restrictionT1: Expressive activity restrictionT1: Instrumental activity restrictionT1: Expressive activity restrictionT1: Expressive activity restriction

T1: depressionT1: depressionDepressionT2: depressionT3: depression

- CorrelationRegressionRegressionRegressionRegression

0.39β=.34, ΔR2 =.08β=.39, ΔR2 =.15β=.34, ΔR2 =.08β=.26, ΔR2 =.0.05

p<.001p=.001p=.001p=.001p=.005

Thompson (2002)

Leisure exploration

Leisure domestic

Nature

Depression

Depression

Depression

- Regression

Regression

Regression

Caucasians: r=-.326Latinas: r=-.165Z=-1.353Pooled: r=-.259Caucasians: r=.300Latinas: r=-.123z=1.464Pooled: r=-.226Caucasians: r=-.199Latinas: r=-.189Z=-.082Pooled: r=-.195

p<.01n.s.

p<.01p<.01n.s.

p<.01p<.05p<.05

p<.01

Page 157 of 197

Authors (year)

Independent variable Dependent variable

Mediator/ moderator

Statistical test Result and effect size P value

Williams (2005)

Social activities

Social activities

Social activities

Depression

Depression

Depression

Model 1 - w/o race interaction termsModel 2 - w race interaction terms

Correlation

Regression

Regression

r=-0.34

β=-.15 (SE=.12)F=17.38 (for the model)r2=.36

β=-.14 (SE=.17)F=9.76 (for the model)r2=0.36

n.s.

p<.001

p<.01

Positive and negative affect:Mausbach Harmell et al. (2011)

Leisure satisfactionLeisure satisfaction

Leisure satisfactionLeisure satisfaction

Positive affectPositive affect

Negative affectPositive affect

-Burden (moderator)-Burden (moderator)

RegressionRegression

RegressionRegression

β=.420 (SE=.041), t=10.30β=.016 (SE=.007), t=2.44

β=-.102 (SE=.025), t=-4.08β=-.008 (SE=.004), t=-2.07

p<.001p=.026

p<.001p=.047

Mausbach, Roepke et al. (2011)

Leisure restriction / Pleasant events

Leisure restriction / Pleasant events

Positive affect

Negative affect

- ANOVA FM (SD) [95 % CI]

Cohen’s d

ANOVA FM (SD) [95 % CI]

Cohen’s d

F=3.48HPLR: 33.64 (8.35) [30.88-36.41]HPHR/LPLR: 32.33 (6.47) [30.10-34.55]LPHR: 29.05 (7.59) [26.65-31.46]LPHR vs HPLR=-0.58LPHR vs HPHR/LPLR=-0.47F=10.12HPLR: 15.18 (4.58) [13.21-17.14]HPHR/LPLR: 16.98 (4.37) [15.39-18.56]LPHR: 20.81 (6.50) [19.10-22.52]LPHR vs HPLR=0.99LPHR vs HPHR/LPLR=0.72

-

-

General WellbeingCramm (2011) Activity restriction General wellbeing Correlation r=0.286 p=.002

Hatzmann et al. (2009)

Leisure time/weekHolidays

General wellbeingGeneral wellbeing

RegressionRegression

β=.07β=.21

p>.05p<.05

Page 158 of 197

Authors (year)

Independent variable Dependent variable

Mediator/ moderator

Statistical test Result and effect size P value

Rizk et al. (2011)

Overall activity participationsports/physical activities/ naturehobbiescraftsgamessociocultural/entertainmentcommunity/education

General wellbeingGeneral wellbeingGeneral wellbeingGeneral wellbeingGeneral wellbeingGeneral wellbeingGeneral wellbeing

- CorrelationCorrelationCorrelationCorrelationCorrelationCorrelationCorrelation

r=-.066r=-.060r=.032r=-.226r=.294r=-.130r=.251

p=.714p=.758p=.858p=.458p=.184p=.485p=.189

Positive feelings towards caregiving:Ficker (2011)

LeisureLeisure (Low vs High)Frequency of leisure (low vs high) for people with no work disruptionFrequency of leisure (low vs high) for people whose work was disrupted by caregiving demands.

Positive affectPositive affectPositive affect

Positive affect

- CorrelationT-testT-test

T-test

r=0.17t=-2.01t=-1.75

t=-2.01

p<.001p<0.05*n.s.

p<.05

Williams (2005)

Social activities Positive affect - Correlation r=.22 -

*to control for type 1 errors, this was not considered to reach statistical significance.

Note:HPLR=high pleasant events and low activity restriction; HPHR/LPLR=high pleasant events and high restriction or low pleasant events and low restriction; LPHR=low pleasant events and high restriction; w/o=without; w=with.

Page 159 of 197

To aid synthesis of the findings, the results are presented according to the type of

psychological wellbeing measure that was used as the dependent variable. The

wellbeing measures fell into four categories (some papers included more than one of

these measures): Five measured depression, two measured positive and negative

affect, three measured general wellbeing, and two measured feelings towards

caregiving. Measures used are summarised in Table 5.

Table 5: Summary of leisure and wellbeing questionnaires

Name Items Response scaleLeisure measures:Activity Restriction Scale (ARS)

How restricted people felt in the last month in each of nine listed activities such as “having quiet time to yourself”, “going out for meals”, “doing fun things with other people”, and “taking part in hobbies”.

5 response options from “Never or seldom did this” to “greatly restricted”

REACH scale to measure leisure/pleasant events

Frequency of participation in 7 pleasant activities e.g. “going out for meals”

3 response options from “not at all” to “a lot”.

Cramm’s Activity Restriction Scale

1 item:“How many times during the past 4 weeks did the caregiving task for your child hinder your social activities, such as visiting friends or family?”

6 response options from “all of the time” to “never”.

Lin Interest Checklist (LICL)

123 activities (e.g. boxing, ceramics, reading) from 6 categories: sports/physical activities/nature, crafts, hobbies, games, sociocultural/entertainment, community/education.Participants could add their own items.Each item rated for level of interest, frequency of engagement, and history.

Interest: 3 response options from “like a little” to “like very much”.Frequency: 3 response options from “occasionally” to “frequently”.History: 3 response options: “past”, “present”, “future” (in the coming month).

Leisure Time Satisfaction (LTS)

Satisfaction with amount of time spent on 6 specified leisure activities over the last month.

3 response options from “not at all” to “a lot”.

Older Persons Pleasant Events Scale (OPPES-A)

Frequency and perceived pleasure from each activity (whether or not they had done the activity) over the past month.Divided into 7 subscales: social recognition, nature, social intimacy, leisure domestic, reflection, spirituality, leisure exploration.Examples of leisure exploration: “getting out of the city” and “planning

Frequency: 3 response options from “not at all (this has not happened in the past 30 days)” to “often (seven or more times)”.Pleasure: 3 response options from “somewhat pleasant” to “very pleasant”.

Page 160 of 197

Name Items Response scaletrips or vacations”.Examples of leisure domestic: “baking because I feel creative” and “creative crafts”.Examples of nature: “listening to the sounds of nature” and “seeing beautiful scenery”.

Pleasant Events Schedule- Alzheimer’s Disease (PES-AD)

Over the last 4 hours.Rating frequency of engaging in each of 20 common leisure activities e.g. “listening to music”.

3 response options from “not at all” to “2 or more times”.

Wellbeing measures:Centre for Epidemiological Studies Depression (CES-D & CESD-10)

CES-D – experience over the last week of 20 items relating to symptoms of depression.CESD-10 – 10 items from the original scale.

4 response options from “rarely or none of the time (<1 day)” to “most or almost all the time (5-7 days)”.

Positive and Negative Affect Scale (PANAS)

Ratings based on either “the present moment” or “over the past week”.10 single word items relating to energy levels, excitement and enthusiasm to reflect positive affect (e.g. “interested”, “strong”, “excited”.And 10 single word items relating to distress to reflect negative affect e.g. “distressed”, “upset”, “guilty”.

5 response options from “very slightly or not at all” to “Extremely”.

Hospital Anxiety and Depression Scale (HADS)

Experience over the last week. Frequency of 7 items relating to symptoms of depression and 7 items relating to symptoms of anxiety.

4 different response options relating to frequency of experience depending on each question e.g. from “not at all” to “most of the time”.

Mental Component Score (MCS) from the Short Form 12 (SF12)

Over the last 4 weeks.6 items relating to mental wellbeing such as energy levels, feeling peaceful, and feeling “down-hearted”.

Response options vary from binary “yes”/”no” to a 6 point scale from “all of the time” to “none of the time”.

Mental Component Score (MCS) of TNO-AZL Questionnaire for Adult's Health Related Quality of Life (TAAQoL)

Items have two parts: prevalence of problem, emotional impact of problem.The scales vitality, positive emotions, and aggressiveness pertain to experiences over the last month.

4 response options.

Positive Aspects of Caregiving (PAC)

11 items relating to positive impact of caregiving on emotional wellbeing e.g. “providing help to [care recipient] has made me feel good about myself”.

5 response options from “agree” to “disagree”.

Page 161 of 197

Depression

Of the five papers which used depression as an outcome variable, all were cross-

sectional studies using correlational analysis, and one (Loucks-Atkinson, Kleiber, &

Williamson, 2006) included a longitudinal component (Ficker, 2011; Loucks-

Atkinson, Kleiber, & Williamson, 2006; Mausbach, Roepke, et al., 2011; Thompson,

Solano, & Kinoshita, 2002; Williams, 2005). Three of the papers used baseline

measures from the same national intervention study in the USA, although improved

homogeneity for their analysis by selecting subsamples, e.g. by gender and location.

Two of the studies only used female participants (Ficker, 2011; Thompson et al.,

2002), and two of the studies made comparisons across ethnicities (Thompson et al.,

2002; Williams, 2005). All of the studies pertained to caregivers of individuals with

ADRD.

The results of the formal quality assessment showed that the studies were of a similar

quality. Three of them achieved the highest rating of one, and two achieved a rating

of 0.95 because the level of detail in reporting results was not quite as good, with

categorised rather than exact p values provided.

The five articles tended to report thoroughly on the demographic characteristics of

the participants and needs of the individual in receipt of care. This is important in

understanding the extent to which findings can be generalised outside of the study.

Given that the majority of participants were female and had at least some experience

of college and university, results are most likely to be generalisable to individuals

with these characteristics. The studies were also able to use this information to

control for potentially confounding variables during the analysis process.

Page 162 of 197

One study found significant differences in demographic factors between different

Latinas and Caucasians (Thompson et al., 2002) which suggests that for those studies

whose participant pool were predominantly Caucasian, caution should be taken when

attempting to apply findings to other ethnicities. It is also important to consider that

despite these demographic differences, Thompson and colleagues did not find

between group differences in their overall outcomes.

They used an abbreviated version of the Older Persons Pleasant Events Schedule

(OPPES-ABV). Of particular relevance to this review, were the three subscales

“leisure exploration”, “leisure domestic” and “nature”. Participants rated both

frequency of activity and level of enjoyment. They found significant correlations

between depression and both leisure exploration, domestic leisure, and nature

activities in the expected directions.

Loucks-Atkinson (2006) measured leisure as a predictor using the ARS. Participants

rated whether they felt their caregiving role impacted on their ability to engage in 9

activities such as “sports and recreation”. These were conceptualised as being in the

category of “expressive activities”, which are intrinsically motivated. In contrast to

this, Ficker (2011) used a 7 item REACH scale which asked people to rate their

frequency of engagement with pleasant events.

These two studies assessed the relationship between reduction or restriction in leisure

activities and depression using a cross section design although one of them also had a

longitudinal component (Loucks-Atkinson et al., 2006). Both studies found

significant correlations between activity restriction and depression (p<.001),

indicating that increased restriction was associated with increased depression scores.

Loucks-Atkinson also found that restriction in leisure activities at time one

Page 163 of 197

significantly correlated with increased depression scores one and two years later

(p<.005).

Ficker also explored whether this relationship existed for individuals who had

experienced work disruption (i.e. reduction or cessation of employment hours)

because of caregiving, and those who had maintained their employment. They found

that there was a significant relationship between restriction in leisure activities and

depression for both groups, which were examined separately and not compared.

Another study by Williams (2005) used a 6-item Leisure Time Satisfaction scale

(LTS). The correlation coefficient for the relationship between leisure satisfaction

and depression was r=-.34 and the p value or range was not reported. The primary

aims of this paper included a comparison between Black and White caregivers. They

devised a model to explore a range of factors to learn whether they were different

between the two groups, and whether they were associated with low mood. They

used two models: the first did not include race interaction terms and the second did.

Model 1 found satisfaction with social activities to be a predictor of depression

(β=-.15, p<.001) with higher satisfaction being associated with lower levels of

depression. This relationship was unaffected by the addition of race interaction

terms.

The final study divided participants into three groups depending on their reported

levels of pleasant events and activity restriction (Mausbach, Roepke, et al., 2011).

The groups were: high pleasant events and low activity restriction (HPLR), high

pleasant events and high activity restriction or low pleasant events and low activity

restriction (HPHR/LPLR), and low pleasant events and high restriction (LPHR).

Engagement with pleasant events was measured through the Pleasant Events

Page 164 of 197

Schedule – Alzheimer’s Disease (PES-AD) which lists 20 activities and asks people

to rate how much they have engaged in that activity over the last month on a three-

point scale. Activity restriction was measured using the ARS. They found a

significant main effect of group on depression. Individuals with more pleasant events

and less restriction had lower depression scores than individuals with low pleasant

events and high activity restriction.

Participants were asked to rate their activities over the last month and therefore some

bias could have been introduced through inaccurate memory and reporting.

Additionally, their measure for pleasant events was a modified version of a validated

measure. However, this study reported Cronbach’s alpha values for its measures

which indicated they had good internal reliability.

Positive and Negative Affect

Two studies explored the impact of leisure using the Positive and Negative Affect

scale (PANAS; Mausbach, Roepke, et al., 2011; Mausbach, Harmell, Moore, &

Chattillion, 2011). There was some variability in methodology between these studies,

where one administered retrospective questionnaires at one time point (Mausbach,

Roepke, et al., 2011), and the other used live recording over several time points in a

week (Mausbach, Harmell, et al., 2011).

Both of the studies were of a similar quality and suffered from the limitation that

they did not record as much information about participant characteristics as some of

the other papers included in this review. One paper also did not control for all

confounding variables (Mausbach, Harmell, et al., 2011). In general, it was found

that the papers were clear in their aims and methodologies, had conclusions that

Page 165 of 197

followed from the results, used validated measures, and Cronbach’s alphas were

reported.

One study asked people to complete an activity diary and questionnaires at regular

times throughout the day for a week (Mausbach, Harmell, et al., 2011). The

questionnaires included the PANAS which lists 20 mood adjectives, half of which

are associated with positive affect (e.g. interested, excited), and half with negative

affect (e.g. distressed, scared). Participants rated the degree to which they felt that

way over the last 4 hours. They also completed measures of leisure satisfaction

where 20 common activities were listed (e.g. listening to music, exercising) and

participants rated the number of times they had engaged with each activity over the

last 4 hours, and the level of enjoyment they got from each one. They found that

individuals with greater leisure satisfaction over the week had higher levels of

positive affect. They also noted a negative relationship between leisure satisfaction

and negative affect. These relationships were moderated by burden. When burden

was low, negative affect was not associated with leisure satisfaction, however when

burden was high there was a significant association. The relationship between

positive affect and leisure satisfaction was also stronger when burden was high.

The previously mentioned study which divided participants into three groups (HPLR,

HPHR/LPLR, and LPHR) also measured positive and negative affect (Mausbach,

Roepke, et al., 2011). They found that people with more pleasant events and less

restriction experienced more positive affect and less negative affect. The reverse was

true for individuals with low pleasant events and high restriction.

Page 166 of 197

General Wellbeing

Three studies explored general “mental” wellbeing using cross sectional

questionnaires in order to test out hypothesised models (Cramm & Nieboer, 2011;

Hatzmann, Maurice-Stam, Heymans, & Grootenhuis, 2009; Rizk et al., 2011).

Outcome measures used in these studies included the Health Related Quality of Life

(HRQoL) and the Hospital Anxiety and Depression Scale (HADS). These studies

included participants other than carers of people with probable ADRD: one included

parents of children with a disability (Cramm & Nieboer, 2011), one focused on

carers of children with Autism Spectrum Conditions (ASC; Rizk et al., 2011), and

the other included parents of chronically ill children (Hatzmann et al., 2009). One of

these studies was carried out in the USA and the other two in the Netherlands.

In general, these three studies did not provide as much information about the sample

characteristics as some of the other studies in this review. Additional details about

the sample characteristics may help others to contextualise their findings, however

this does not affect the validity of their statistical outcomes. Hatzmann et al (2009)

could have provided a more detailed presentation of their model as this would have

allowed for improved interpretation of results. Additionally, there were some

methodological issues with one paper (Rizk et al., 2011) which may have impacted

on their findings. These are discussed in more detail below.

Hatzmann et al. (2009) used a model in which leisure was hypothesised to be a

mediator between background variables (demographic and disease related factors)

and wellbeing. Leisure was measured by self-report of number of hours spent in

leisure per week, and holiday was measured through number of days the family spent

on holiday over the last year. General wellbeing was measured through the MCS

Page 167 of 197

component of the TNO-AZL Questionnaire for Adult's Health Related Quality of

life' (TAAQOL).

Structural Equation Modelling (SEM) was used to refine the originally suggested

model based on the findings from the dataset. They found that holidays and

emotional support both played mediating roles such that parents who had more days

on holiday had better wellbeing. No effect of leisure was found (r=.07, p value not

provided). Inclusion of a diagram of the model with variance values and error

measurements would have been helpful in further understanding this mediation.

Another study was from the USA and had a participant sample comprised of mothers

of children with ASC (Rizk et al., 2011). They measured leisure using the Lin

Interest Checklist (LICL) which categorises 123 activities into six areas:

Sports/Physical Activities/Nature, Crafts, Hobbies, Games,

Sociocultural/Entertainment, and Community/Education. Individuals rated their level

of interest, and frequency and history of participation. They were given the

opportunity to add activities onto the list if they were not already mentioned. The

authors cited an unpublished thesis for the LICL and did not report exact reliability

and validity measures. Unfortunately, due to the thesis being unpublished, it was not

possible to access details relating to the reliability and validity of this measure and

this poses a challenge when interpreting findings from this measure. Wellbeing was

measured through the mental component summary (MCS) of the SF-12.

Rizk and colleagues divided the number of activities of interest in which mothers

participated frequently with the total number of activities of interest. They suggest

that higher scores indicated greater participation. They used The Pearson Product

Moment Correlation to explore the 6 areas of leisure and their relationship to MCS,

Page 168 of 197

and found no significant associations. The relationships between MCS and leisure

categories of Games (r=.294, p=.184) and Community/Education (r=.251, p=.189)

came the closest to achieving significance. They also combined all subscales to

achieve an “overall activity participation” score which also did not have a significant

relationship with MCS (r=-.066, p=.714).

The validity of their participation calculation was not made clear within the paper as

there was no clear justification as to why they calculated it in this manner.

Theoretically, two individuals engaging in the same number of activities and for the

same amount of time could achieve different participation scores if one of them had a

greater variety of interests which they were not currently participating in. Therefore,

it is questionable to what extent their participation measure was reflective of actual

level of engagement with leisure activities. This could account for the null findings.

Further information about power calculations could also help in assessing whether a

small sample size could have contributed to the null findings.

In the Netherlands, Cramm and Nieboer (2011) ascertained restriction in leisure

activities by asking their participants “how many times during the past 4 weeks did

the caregiving task for your child hinder your social activities, such as visiting

friends or family?”. They responded on a 6-point scale from “all the time” to

“never”. They used the HADS to measure psychological wellbeing. They found a

significant positive correlation between restriction in social activities and

psychological wellbeing (r=0.286, p=0.002). This shows that increased restriction is

associated with reduced wellbeing. They also evidenced that this relationship was

mediated through parental stress.

Page 169 of 197

Positive feelings relating to caregiving

Two studies (Ficker, 2011; Williams, 2005) conceptualised their outcomes as

positive affect, and their measurement tool for this was the Positive Aspects of

Caregiving questionnaire (PAC). This has been considered in a separate section from

“positive affect” in this literature review as it was considered to be focused on a

specific area whereas the other studies measured general affect. During the quality

assessment, Ficker’s study had the limitations that Cronbach’s alpha was not

reported for all measures, there was limited consideration of variance, and exact p

values were not reported. However, this is more likely to affect nuanced

interpretations of their results than it is to have affected the main substance of their

findings.

This study used data from REACH and aimed to understand the impact of finances

and work disruption on leisure, and the overall impact this had on feelings about

being a carer. Questionnaires were completed at one time point and this included the

PAC and the 7 questions about leisure restriction as discussed previously. Findings

were that there was a trend (which did not reach statistical significance) for

caregivers with fewer leisure activities to experience less positive feelings about

being a carer.

The other study by Williams (2005), discussed previously, correlated social activities

with PAC and found an association between the two (r=.22). Unfortunately, the p

values or ranges were not provided in this paper and this raises a challenge for

readers attempting to understand the statistical significance of this finding.

Page 170 of 197

DiscussionStudies that explored the relationship between depression and leisure had findings

that were consistent with the idea that lower levels of engagement and satisfaction

with leisure activities are associated with depression in caregivers who provide a

moderate to high level of care. This is consistent with findings from other studies

exploring this issue with non-caregiving participant groups (Katz & Yelin, 2001;

Paffenbarger, Lee, & Leung, 1994). Further, two studies (Thompson et al., 2002;

Williams, 2005) found that this relationship was not affected by race, and another

(Ficker, 2011) found that the relationship was observable for those whose working

hours had been affected and those whose working hours had not been affected.

However, due to the nature of these studies being largely cross-sectional it is not

possible to infer causality. Only one study looked at the association longitudinally

which might suggest more work needs to be done using longitudinal designs,

however it does support the possibility that the data represents a causal relationship.

The studies exploring positive and negative affect (Mausbach, Roepke, et al., 2011;

Mausbach, Harmell, et al., 2011), taken together, were of comparable quality and

showed similar patterns of results. They indicate that frequency of leisure

experiences is associated with increased positive affect and that satisfaction with

leisure is also related to positive affect. The use of live recording in one of the studies

reduces bias introduced by methods that rely on accurate recall of past events, and

therefore the mixture of methodologies is helpful in understanding how reliable the

findings are. However, as there are only two studies in this category it would be

helpful for additional studies to support these findings. It would be helpful if

experimental or longitudinal studies could be designed to attempt to establish

Page 171 of 197

causality. For example, a comparison could be made before and after becoming a

caregiver.

In the category of general wellbeing, the collection of studies reported mixed

findings. Cramm (2011) found that a restriction of leisure activities was associated

with reduced anxiety and depression. Hatzmann (2009) found that individuals who

had more holiday days tended to have better general wellbeing (mental component

score). However, Hatzmann did not find a relationship between the number of hours

of leisure and wellbeing. In keeping with previous studies with non-caregivers, this

might suggest that hours of leisure may be less useful than, for example, satisfaction

with leisure time in understanding the relationship between leisure and wellbeing

(Kuykendall, Tay, & Ng, 2015). Kuykendall, Tay and Ng suggested that leisure is

effective at improving wellbeing through meeting a variety of needs. In this theory,

leisure is more likely to be beneficial if one is spending 20 hours a week on a variety

of leisure activities (therefore meeting a variety of needs), than if an individual is

spending 20 hours on the same leisure activity (therefore only meeting a limited

number of needs). Findings from their meta-analysis supported this theory as time

was found to be less associated with subjective wellbeing than other leisure

measures.

Rizk (2011) did not find a relationship between leisure participation and wellbeing.

This could be due to methodological issues in relation to the calculation of “leisure

participation”. The limited explanation about the validity of their rationale for the

calculation makes it a challenge for readers to understand, given the lack of face

validity.

Page 172 of 197

The final two studies in this review noted a pattern in the expected direction when

comparing leisure engagement with feelings about caregiving but the results were not

statistically significant in one, and the statistical significance of the other was not

reported. A limitation of this review is that there were only two papers investigating

the impact of leisure on feelings about caregiving. Given literature that caregiving

can be rewarding, and that this can occur through having fun with the cared for

individual, it may be pertinent for research to explore this further (Nolan, 2001). In

fact, none of the literature considered in this review assessed whether leisure

activities were being completed with the individual for whom they provide support.

There is some evidence that joint leisure activities may support carer wellbeing

(Searson, Hendry, Ramachandran, Burns, & Purandare, 2008), and therefore the field

may benefit from researching this further.

In general, most of the papers in this review included caregivers of individuals with

ADRD, with the exception of three which used general wellbeing measures and

focused on parents of children with chronic illness and disabilities (Cramm &

Nieboer, 2011; Hatzmann et al, 2009, Rizk et al 2011). Some research indicates there

are qualitative differences in the caregiving experience depending on the difficulties

experienced by the cared for (Ory et al., 1999). Therefore, findings from this review

are most likely to be generalisable to the groups of individuals included in this

review. Further research would be helpful in determining if the findings are

applicable to other types of carers.

ConclusionThese studies investigated a wide range of aspects of the leisure experience such as

number of hours, satisfaction, frequency, and restriction. Based on these findings it is

Page 173 of 197

possible that each of these components plays its own role in the relationship of

leisure and wellbeing, though this may be less the case for number of hours spent in

leisure. In order to better understand these findings, it would be helpful for additional

studies to compare the impact of leisure participation, leisure satisfaction, and

number of hours of leisure. More robust studies are required in this area including a

range of methodologies and with clear reporting of variance, effect sizes, and

statistical power. It is also important for studies to use published validated measures.

Research into carers who spend a significant amount of time in their caregiving role

and the relationship between leisure and wellbeing is less well developed than the

research within the non-caregiving population. Perhaps one of the most

comprehensive examples of this is a meta-analysis by Kuykendall, Tay and Ng

(2015) who reviewed 69 studies, and concluded that leisure engagement and

subjective wellbeing in non-caregivers are moderately associated with leisure

satisfaction. They also found a mediation effect of leisure satisfaction on the

relationship between leisure engagement and subjective wellbeing. Other mediators

and moderators of the relationships between leisure engagement and wellbeing have

begun to be explored within the wider caregiving literature including two of the

papers in this review (Bedini et al., 2011; Bookwala & Schulz, 2000; Cramm &

Nieboer, 2011; Thompson et al., 2002). For example, Thompson et al used path

analysis and found that work disruption affected financial strain, which affected

leisure, which in turn affected depression (accounting for 12.3% of the variance in

depression).

Page 174 of 197

Therefore, another limitation of this review is that the broader complexities of these

relationships have not been clarified and further research (in particular, with those

who spend a significant amount of their time caregiving) would be beneficial.

 

Page 175 of 197

ReferencesAusserhofer, D., Mantovan, F., Pirhofer, R., Huber, M., & Them, C. (2009). [The

burden of parents caring for their children and adolescents with severe disabilities in South Tyrol]. Pflege, 22(3), 184–192. https://doi.org/10.1024/1012-5302.22.3.184

Azman, A., Jamir Singh, P. S., & Sulaiman, J. (2017). Caregiver coping with the mentally ill: a qualitative study. Journal of Mental Health, 26(2), 98–103. https://doi.org/10.3109/09638237.2015.1124395

Bedini, L., Gladwell, N., & Dudley, W. (2011). Mediation analysis of leisure, perceived stress, and quality of life in informal caregivers. Journal of Leisure, 43(2), 153–175. https://doi.org/10.1080/00222216.2011.11950231

Bookwala, J., & Schulz, R. (2000). A comparison of primary stressors, secondary stressors, and depressive symptoms between elderly caregiving husbands and wives: The caregiver health effects study. Psychology and Aging, 15(4), 607–616. https://doi.org/10.1037/0882-7974.15.4.607

Carers UK. (2015). Facts about carers 2015. Retrieved from https://www.carersuk.org/for-professionals/policy/policy-library/facts-about-carers-2015

Chakrabarti, S., Raj, L., Kulhara, P., Avasthi, A., & Verma, S. K. (1995). Comparison of the extent and pattern of family burden in affective disorders and schizophrenia. Indian Journal of Psychiatry, 37(3), 105–112. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21743729

Chattillion, E. A., Mausbach, B. T., Roepke, S. K., von Känel, R., Mills, P. J., Dimsdale, J. E., … Grant, I. (2012). Leisure activities, caregiving demands and catecholamine levels in dementia caregivers. Psychology & Health, 27(10), 1134–1149. https://doi.org/10.1080/08870446.2011.637559

Chien, W.-T., & Norman, I. (2009). The effectiveness and active ingredients of mutual support groups for family caregivers of people with psychotic disorders: A literature review. International Journal of Nursing Studies, 46(12), 1604–1623. https://doi.org/10.1016/J.IJNURSTU.2009.04.003

Chien, W. T., Chan, S., Morrissey, J., & Thompson, D. (2005). Effectiveness of a mutual support group for families of patients with schizophrenia. Journal of Advanced Nursing, 51(6), 595–608. https://doi.org/10.1111/j.1365-2648.2005.03545.x

Connell, C. M., & Janevic, M. R. (2009). Effects of a Telephone-Based Exercise Intervention for Dementia Caregiving Wives. Journal of Applied Gerontology, 28(2), 171–194. https://doi.org/10.1177/0733464808326951

Page 176 of 197

Cooper, C., Balamurali, T. B. S., Selwood, A., & Livingston, G. (2007). A systematic review of intervention studies about anxiety in caregivers of people with dementia. International Journal of Geriatric Psychiatry, 22(3), 181–188. https://doi.org/10.1002/gps.1656

Cramm, J. M., & Nieboer, A. P. (2011). Psychological well-being of caregivers of children with intellectual disabilities: Using parental stress as a mediating factor. Journal of Intellectual Disabilities, 15(2), 101–113. https://doi.org/10.1177/1744629511410922

Del-Pino-Casado, R., & Ordóñez-Urbano, C. (2016). Effects of satisfaction with leisure time in family carers of elderly dependents. Atencion Primaria / Sociedad Española De Medicina De Familia Y Comunitaria, 48(5), 295–300. https://doi.org/10.1016/j.aprim.2015.06.005

Eric Hwang, J.-L., Rivas, J. G., Fremming, R., Rivas, M. M., & Crane, K. R. (2009). Relationship Between Perceived Burden of Caring for a Family Member with Alzheimer’s Disease and Decreased Participation in Meaningful Activities. Occupational Therapy In Health Care, 23(4), 249–266. https://doi.org/10.3109/07380570903214788

Ficker, L. J. (2011). The role of employment status, work disruption, leisure, and resources in the mental health of dementia caregiving daughters. Dissertation Abstracts International: Section B: The Sciences and Engineering. Retrieved from http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3433474%5Cnhttp://ovidsp.ovid.com/ovidweb.cgi?T=JS&PAGE=reference&D=psyc7&NEWS=N&AN=2011-99160-365

Flores, P. M., Berbis, J., Chinot, O., & Auquier, P. (2014). Assessing the quality of life among caregivers of patients with gliomas. Neuro-Oncology Practice, 1(4), 191–197. https://doi.org/10.1093/nop/npu027

Folkman, S. (1997). Positive psychological states and coping with severe stress. Social Science & Medicine, 45(8), 1207–1221. https://doi.org/10.1016/S0277-9536(97)00040-3

Gahagan, J., Loppie, C., Rehman, L., Maclellan, M., & Side, K. (2007). “Far as I Get Is the Clothesline”: The Impact of Leisure on Women’s Health and Unpaid Caregiving Experiences in Nova Scotia, Canada. Health Care for Women International, 28(1), 47–68. https://doi.org/10.1080/07399330601003408

Gautam, S., & Nijhawan, M. (1984). Burden on families of schizophernic and chronic lung disease patients. Indian Journal of Psychiatry, 26(2), 156–9. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21965975

Greenwood, N., Habibi, R., Smith, R., & Manthorpe, J. (2015). Barriers to access and minority ethnic carers’ satisfaction with social care services in the community: a systematic review of qualitative and quantitative literature.

Page 177 of 197

Health & Social Care in the Community, 23(1), 64–78. https://doi.org/10.1111/hsc.12116

Greenwood, N., & Smith, R. (2015). Barriers and facilitators for male carers in accessing formal and informal support: A systematic review. Maturitas, 82(2), 162–169. https://doi.org/10.1016/j.maturitas.2015.07.013

Haley, W. E., LaMonde, L. A., Han, B., Burton, A. M., & Schonwetter, R. (2004). Predictors of Depression and Life Satisfaction Among Spousal Caregivers in Hospice: Application of a Stress Process Model. Journal of Palliative Medicine, 6(2), 215–224. https://doi.org/10.1089/109662103764978461

Haley, W. E., Roth, D. L., Hovater, M., & Clay, O. J. (2015). Long-term impact of stroke on family caregiver well-being: a population-based case-control study. Neurology, 84(13), 1323–9. https://doi.org/10.1212/WNL.0000000000001418

Hatzmann, J., Maurice-Stam, H., Heymans, H. S. A., & Grootenhuis, M. A. (2009). A predictive model of Health Related Quality of life of parents of chronically ill children: the importance of care-dependency of their child and their support system. Health and Quality of Life Outcomes, 7(72). https://doi.org/10.1186/1477-7525-3-34

Hughes, N., Locock, L., & Ziebland, S. (2013). Personal identity and the role of “carer” among relatives and friends of people with multiple sclerosis. Social Science & Medicine, 96, 78–85. https://doi.org/10.1016/j.socscimed.2013.07.023

Infurna, F. J., Gerstorf, D., & Zarit, S. H. (2012). Substantial Changes in Mastery Perceptions of Dementia Caregivers With the Placement of a Care Recipient. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 68(2), 202–214. https://doi.org/10.1093/geronb/gbs063

Katz, P. P., & Yelin, E. H. (2001). Activity loss and the onset of depressive symptoms: Do some activities matter more than others? Arthritis & Rheumatology, 44(5), 1194–1202. https://doi.org/10.1002/1529-0131(200105)44:5<1194::AID-ANR203>3.0.CO;2-6

Katz, S., Ford, A. B., Moskowitz, R. W., Jackson, B. A., & Jaffe, M. W. (1963). Studies of illness in the aged: the index of ADL: a standardized measure of biological and psychosocial function. Jama, 185(12), 914–919. https://doi.org/10.1001/jama.1963.03060120024016

Kmet, L. M., Lee, R. C., & Cook, L. S. (2004). Standard quality assessment criteria for evaluating primary research papers from a variety of fields. Alberta Heritage Foundation for Medical Research Edmonton. Retrieved from https://www.ihe.ca/publications/standard-quality-assessment-criteria-for-evaluating-primary-research-papers-from-a-variety-of-fields

Kuo, S. C., Sun, J. L., & Tang, S. T. (2017). Trajectories of depressive symptoms for bereaved family members of chronically ill patients: a systematic review. Journal of Clinical Nursing. https://doi.org/10.1111/jocn.13720

Page 178 of 197

Kuykendall, L., Tay, L., & Ng, V. (2015). Leisure engagement and subjective well-being: A meta-analysis. Psychological Bulletin, 141(2), 364–403. https://doi.org/10.1037/a0038508

Lawton, M. P., & Brody, E. M. (1970). Assessment of older people: self-maintaining and instrumental activities of daily living. Nursing Research, 19(3), 179-186. Retrieved from http://www.eurohex.eu/bibliography/pdf/Lawton_Gerontol_1969-1502121986/Lawton_Gerontol_1969.pdf

Lee, Y., & Bhargava, V. (2004). Leisure time: Do married and single individuals spend it differently? Family and Consumer Sciences.32(3), 254-274. https://doi.org/10.1177/1077727X03261631

Levine, C., Reinhard, S., Feinberg, L. F., Albert, S., & Hart, A. (2003). Family caregivers on the job: Moving beyond ADLs and IADLs. Generations, 27(4), 17–23. Retrieved from http://web.b.ebscohost.com/ehost/detail/detail?vid=2&sid=f971ede8-b347-43f5-87ff-fa3fe2b93bf7%40sessionmgr120&bdata=JkF1dGhUeXBlPWlwLHNoaWImc2l0ZT1laG9zdC1saXZl#AN=106758911&db=c8h

Lloyd, K. M., & Auld, C. J. (2002). The role of leisure in determining quality of life: Issues of content and measurement. Social Indicators Research, 57(1), 43–71. https://doi.org/10.1023/A:1013879518210

López, J., López-Arrieta, J., & Crespo, M. (2005). Factors associated with the positive impact of caring for elderly and dependent relatives. Archives of Gerontology and Geriatrics, 41(1), 81–94. https://doi.org/10.1016/j.archger.2004.12.001

Loucks-Atkinson, A., Kleiber, D. a., & Williamson, G. M. (2006). Activity restriction and well‐being in middle‐aged and older caregivers. Topics in Geriatric Rehabilitation, 22(4), 269–282.

Magliano, L., Fiorillo, A., Rosa, C., & Maj, M. (2006). Family burden and social network in schizophrenia vs. physical diseases: preliminary results from an Italian national study. Acta Psychiatrica Scandinavica, 113(s429), 60–63. https://doi.org/10.1111/j.1600-0447.2005.00719.x

Magliano, L., Marasco, C., Fiorillo, A., Malangone, C., Guarneri, M., & Maj, M. (2002). The impact of professional and social network support on the burden of families of patients with schizophrenia in Italy. Acta Psychiatrica Scandinavica, 106(4), 291–298. https://doi.org/10.1034/j.1600-0447.2002.02223.x

Martin, S. C. (2015). Psychosocial Challenges Experienced by Partners of People With Parkinson Disease. Journal of Neuroscience Nursing, 47(4), 211–222. https://doi.org/10.1097/JNN.0000000000000141

Mausbach, B. T., Coon, D. W., Patterson, T. L., & Grant, I. (2008). Engagement in Activities Is Associated With Affective Arousal in Alzheimer’s Caregivers: A

Page 179 of 197

Preliminary Examination of the Temporal Relations Between Activity and Affect. Behavior Therapy, 39(4), 366–374. https://doi.org/10.1016/J.BETH.2007.10.002

Mausbach, B. T., Harmell, A. L., Moore, R. C., & Chattillion, E. A. (2011). Influence of caregiver burden on the association between daily fluctuations in pleasant activities and mood: A daily diary analysis. Behaviour Research and Therapy, 49(1), 74–79. https://doi.org/10.1016/j.brat.2010.11.004

Mausbach, B. T., Roepke, S. S. K., Depp, C. A. C., Moore, R., Patterson, T. L., & Grant, I. (2011). Integration of the Pleasant Events and Activity Restriction Models: Development and Validation of a “PEAR” Model of Negative Outcomes in Alzheimer’s Caregivers. Behavior Therapy, 42(1), 78–88. https://doi.org/10.1016/j.beth.2009.11.006

Meltzer, L. J., & Rodrigue, J. R. (2001). Psychological Distress in Caregivers of Liver and Lung Transplant Candidates. Journal of Clinical Psychology in Medical Settings, 8(3), 173–180. https://doi.org/10.1023/A:1011317603415

Molyneaux, V., Butchard, S., Simpson, J., & Murray, C. (2011). Reconsidering the term “carer”: a critique of the universal adoption of the term “carer.” Ageing & Society, 31(3), 422–437. https://doi.org/10.1017/S0144686X10001066

Neulinger, J. (1981). The Psychology of Leisure (2nd ed.). Springfield, Ill.: C. C. Thomas.

NICE. (2012). Quality appraisal checklist - quantitative intervention studies. In Methods for the development of NICE public health guidance (3rd ed.). National Institute for Health and Care Excellence. Retrieved from https://www.nice.org.uk/process/pmg4/chapter/appendix-f-quality-appraisal-checklist-quantitative-intervention-studies

Nolan, M. (2001). Positive aspects of Caring. In S. Payne & C. Ellis-Hill (Eds.), Chronic and terminal illness: New perspectives on caring and carers (pp. 22–43). Oxford: Oxford University Press.

Ory, M. G., Hoffman, R. R., Yee, J. L., Tennstedt, S., & Schulz, R. (1999). Prevalence and Impact of Caregiving: A Detailed Comparison Between Dementia and Nondementia Caregivers. The Gerontologist, 39(2), 177–186. https://doi.org/10.1093/geront/39.2.177

Oshio, T., & Kan, M. (2016). How do social activities mitigate informal caregivers’ psychological distress? Evidence from a nine-year panel survey in Japan. Health and Quality of Life Outcomes, 14(117). https://doi.org/10.1186/s12955-016-0521-8

Paffenbarger, R. S., Lee, I. ‐M., & Leung, R. (1994). Physical activity and personal characteristics associated with depression and suicide in American college men. Acta Psychiatrica Scandinavica, 89(s377), 16–22. https://doi.org/10.1111/J.1600-0447.1994.TB05796.X

Page 180 of 197

Pearlin, L. I. (2009). The Life Course and the Stress Process: Some Conceptual Comparisons. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 65B(2), 207–215. https://doi.org/10.1093/geronb/gbp106

Pearlin, L. I., Mullan, J. T., Semple, S. J., & Skaff, M. M. (1990). Caregiving and the Stress Process: An Overview of Concepts and Their Measures. The Gerontologist, 30(5), 583–594. https://doi.org/10.1093/geront/30.5.583

Peña-Longobardo, L. M., & Oliva-Moreno, J. (2015). Caregiver Burden in Alzheimer’s Disease Patients in Spain. Journal of Alzheimer’s Disease, 43(4), 1293–1302. https://doi.org/10.3233/JAD-141374

Pinquart, M., & Sörensen, S. (2003). Differences between caregivers and noncaregivers in psychological health and physical health: a meta-analysis. Psychology and Aging, 18(2), 250–267. https://doi.org/10.1037/0882-7974.18.2.250

Raj, J., Manigandan, C., & Jacob, K. (2006). Leisure satisfaction and psychiatric morbidity among informal carers of people with spinal cord injury. Spinal Cord, 44(11), 676–679. https://doi.org/10.1038/sj.sc.3101899

Rizk, S., Pizur-Barnekow, K., & Darragh, A. R. (2011). Leisure and Social Participation and Health-Related Quality of Life in Caregivers of Children with Autism. OTJR: Occupation, Participation and Health, 31(4), 164–171. https://doi.org/10.3928/15394492-20110415-01

Rochette, A., Desrosiers, J., Bravo, G., Tribble, D. S.-C., & Bourget, A. (2007). Changes in participation level after spouse’s first stroke and relationship to burden and depressive symptoms. Cerebrovascular Diseases (Basel, Switzerland), 24(2–3), 255–60. https://doi.org/10.1159/000104487

Romero-Moreno, R., Márquez-González, M., Mausbach, B. T., & Losada, A. (2012). Variables modulating depression in dementia caregivers: a longitudinal study. International Psychogeriatrics, 24(8), 1316–1324. https://doi.org/10.1017/S1041610211002237

Searson, R., Hendry, A. M., Ramachandran, R., Burns, A., & Purandare, N. (2008). Activities enjoyed by patients with dementia together with their spouses and psychological morbidity in carers. Aging & Mental Health, 12(2), 276–282. https://doi.org/10.1080/13607860801956977

Shaw, W. S., Patterson, T. L., Semple, S. J., Grant, I., Yu, E. S. H., Zhang, M. Y., … Wu, W. Y. (1997). A Cross-Cultural Validation of Coping Strategies and Their Associations With Caregiving Distress. The Gerontologist, 37(4), 490–504. https://doi.org/10.1093/geront/37.4.490

Smith, L., Onwumere, J., Craig, T., McManus, S., Bebbington, P., & Kuipers, E. (2014). Mental and physical illness in caregivers: results from an English national survey sample. The British Journal of Psychiatry, 205(3), 197–203. https://doi.org/10.1192/bjp.bp.112.125369

Page 181 of 197

Smith, R., & Greenwood, N. (2014). The impact of volunteer mentoring schemes on carers of people with dementia and volunteer mentors: a systematic review. American Journal of Alzheimer’s Disease & Other Dementias®, 29(1), 8–17. https://doi.org/10.1177/1533317513505135

Stern, S., Doolan, M., Staples, E., Szmukler, G. L., & Eisler, I. (1999). Disruption and Reconstruction: Narrative Insights into the Experience of Family Members Caring for a Relative Diagnosed with Serious Mental Illness. Family Process, 38(3), 353–369. https://doi.org/10.1111/j.1545-5300.1999.00353.x

Stevens, A. B., Coon, D., Wisniewski, S., Vance, D., Arguelles, S., Belle, S., … Haley, W. (2004). Measurement of leisure time satisfaction in family caregivers. Aging & Mental Health, 8(5), 450–459. https://doi.org/10.1080/13607860410001709737

Szmukler, G. I., Burgess, P., Herrman, H., Bloch, S., Benson, A., & Colusa, S. (1996). Caring for relatives with serious mental illness: the development of the Experience of Caregiving Inventory. Social Psychiatry and Psychiatric Epidemiology, 31(3–4), 137–148. https://doi.org/10.1007/BF00785760

Thompson, L., Solano, N., & Kinoshita, L. (2002). Pleasurable activities and mood: Differences between Latina and Caucasian dementia family caregivers. Journal of Mental Health and Ageing, 8(3), 211–224. Retrieved from https://asu.pure.elsevier.com/en/publications/pleasurable-activities-and-mood-differences-between-latina-and-ca

Treasure, J., Murphy, T., Szmukler, T., Todd, G., Gavan, K., & Joyce, J. (2001). The experience of caregiving for severe mental illness: a comparison between anorexia nervosa and psychosis. Social Psychiatry and Psychiatric Epidemiology, 36(7), 343–347. https://doi.org/10.1007/s001270170039

Voss, J. (1967). The definition of leisure. Journal of Economic Issues, 1(1), 91–106. https://doi.org/10.1080/00213624.1967.11502742

White-Means, S. I., & Chang, C. F. (1994). Informal caregivers’ leisure time and stress. Journal of Family and Economic Issues, 15(2), 117–136. https://doi.org/10.1007/BF02353636

Williams, I. C. (2005). Emotional Health of Black and White Dementia Caregivers: A Contextual Examination. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 60(6), 287–295. https://doi.org/10.1093/geronb/60.6.P287

Williamson, G. M., & Schulz, R. (1992). Pain, Activity Restriction, and Symptoms of Depression Among Community-residing Elderly Adults. Journal of Gerontology, 47(6), P367–P372. https://doi.org/10.1093/geronj/47.6.P367

Wisniewski, S. R., Belle, S. H., Coon, D. W., Marcus, S. M., Ory, M. G., Burgio, L. D., … Schulz, R. (2003). The Resources for Enhancing Alzheimer’s Caregiver Health (REACH): Project design and baseline characteristics. Psychology and Aging, 18(3), 375–384. https://doi.org/10.1037/0882-7974.18.3.375

Page 182 of 197

Youn, G., Knight, B. G., Jeong, H.-S., & Benton, D. (1999). Differences in familism values and caregiving outcomes among Korean, Korean American, and White American dementia caregivers. Psychology and Aging, 14(3), 355–364. https://doi.org/10.1037/0882-7974.14.3.355

Zarit, S. H., Reever, K. E., & Bach-Peterson, J. (1980). Relatives of the Impaired Elderly: Correlates of Feelings of Burden. The Gerontologist, 20(6), 649–655. https://doi.org/10.1093/geront/20.6.649

Page 183 of 197

Appendix A: Aims and Scope of Social Sciences & MedicineFrom: https://www.journals.elsevier.com/social-science-and-medicine, retrieved on

14/01/18.

“Social Science & Medicine provides an international and interdisciplinary forum for the dissemination of social science research on health. We publish original research articles (both empirical and theoretical), reviews, position papers and commentaries on health issues, to inform current research, policy and practice in all areas of common interest to social scientists, health practitioners, and policy makers. The journal publishes material relevant to any aspect of health from a wide range of social science disciplines (anthropology, economics, epidemiology, geography, policy, psychology, and sociology), and material relevant to the social sciences from any of the professions concerned with physical and mental health, health care, clinical practice, and health policy and organization. We encourage material which is of general interest to an international readership.

The journal publishes the following types of contribution:

1) Peer-reviewed original research articles and critical or analytical reviews in any area of social science research relevant to health. These papers may be up to 8,000 words including abstract, tables, and references as well as the main text. Papers below this limit are preferred.

2) Peer-reviewed short reports of research findings on topical issues or published articles of between 2000 and 4000 words.

3) Submitted or invited commentaries and responses debating, and published alongside, selected articles.

4) Special Issues bringing together collections of papers on a particular theme, and usually guest edited.”

Page 184 of 197

Clinical ExperienceYear 1 – Working Age Adults

I spent a year in a community mental health service for working age adults with

severe and enduring mental health difficulties. I worked with individuals who were

challenged by problems such as psychosis, health anxiety, OCD, and depression. I

did this in the form of consultation, one to one therapy, and group facilitation. I

offered training to staff within the team (how to use CBT worksheets) and to carers

(using ACT to support self-care). I also completed some neuropsychological

assessments including the use of psychometric testing. Whilst on placement I worked

with a range of other health and social care professionals, met clients and carers

outside of my clinical work, visited other local services and became involved in

some reflective team meetings which used a systemic framework. Main therapeutic

models used on this placement were ACT, CBT, systemic, neuropsychological, and I

had the opportunity to have some psychodynamic conversations with the art

therapist.

Year 2 – Learning Disabilities

I spent 6 months in a Learning Disabilities (LD) service for adults. During this time I

offered 1:1 therapy, family work, consultation and cognitive assessment. I worked

with individuals who were affected by a LD with difficulties such as being

vulnerable to sexual assault, distress that was difficult for their care team to manage

(challenging behaviour), memory difficulties, partner’s decline of dementia, and

satisfaction with relationships. I worked with families, carers, and individuals

affected by LD in the clinic, and in residential settings. I also worked with a range of

different health conditions (such as visual impairment, Downs syndrome and

Page 185 of 197

encephalopathy) and across the spectrum of ability within this client group (including

work with a non-verbal individual). I completed cognitive assessments including

assessment of LD in the context of autism and dementia assessment in the context of

a LD. I also offered training to local social services staff about mental health

difficulties in Learning disabilities, and dementia training to staff at a residential

home. The main therapeutic models used during this placement were Behaviour

analysis, neuropsychological and systemic.

Year 2 – Child and Adolescent Mental Health

I spent 6 months in a Child and Adolescent Mental Health Service (CAMHS)

working with children from the age of 5 to the age of 18 and their families. I worked

with a range of presenting difficulties including anxiety over exams, OCD,

depression, tics and hearing voices. Main therapeutic approaches included CBT,

habit reversal training, neuropsychological and systemic. I offered training to staff

regarding the use of outcome measures and also contributed to service development

with regards to implementation of outcome measures. I also completed some

neuropsychological assessment with children regarding possible learning disability,

and developing understanding of behaviours at school. I spent time in local services,

meeting children and young people outside of the context of clinical work. I was also

involved in a reflecting team in a systemic intervention for a family affected by

PTSD, ADHD, and anger.

Year 3 – Neurorehabilitation in-patient (specialist placement)

I spent 6 months in a neurorehabilitation ward working with individuals with head

injury, stroke, MS and other neurological difficulties. I worked with individuals to

Page 186 of 197

understand their cognitive difficulties and support them to maximise on their

cognitive strengths to aid recovery. I also worked with individuals to understand and

talk through their experiences and support and monitor their emotional wellbeing.

Predominantly I used neuropsychological models for this placement however

behavioural models, ACT, systemic working and a biopsychosocial approach were

also utilised. I contributed to a business proposal to start up a singing group on the

ward by putting together a literature review on the influence of music and singing on

emotional wellbeing. I worked with a range of professionals to ensure a shared

understanding of patient’s experiences. I provided training to stroke survivors, their

carers and professionals on cognitive impairments following stroke.

Year 3 – Older Adult Community Mental Health Service

I spent 6 months in an older adult community mental health service. This involved

memory assessments, support with mental health difficulties, and behavioural work

within a care home. Interventions were 1:1, with families, in services, and within the

multidisciplinary team. I provided training to professionals within the rehabilitation

service about psychological approaches to fear of falling. I took part in reflecting

teams for systemic interventions with families affected by bipolar disorder and

psychosis. I was involved in reinstating dementia information packs for individuals

who were newly diagnosed and planned an audit on the use of the ACE III. I

attended local services to meet older adults outside of the clinical context. I worked

with people experiencing difficulties with anxiety, memory, mood, perfectionism,

hoarding, relationship stress, and bipolar disorder.

Page 187 of 197

PSYCHD CLINICAL PROGRAMME

Table of assessments completed during trainingYear I Assessments

Assessment Title

WAIS WAIS interpretation (online assessment)

Practice report of clinical activity A Cognitive Behavioural Therapy (CBT) assessment and formulation with a female in her 40s who had a diagnosis of Obsessive Compulsive Disorder.

Audio recording of clinical activity with critical appraisal

A critical appraisal of a Cognitive Behavioural Therapy (CBT) intervention session with a British woman in her 40s with a diagnosis of Obsessive Compulsive Disorder (OCD).

Report of clinical activity N=1 A CBT assessment, formulation and intervention with a female in her 50s who was facing challenges relating to anxiety and depression.

Major research project literature survey A literature survey to examine what makes peer support effective for carers of “adult experiencers of serious mental illness” in the UK

Major research project proposal An investigation into the role of leisure activities in the wellbeing of female carers who spend 20 or more hours a week caring

Service-Related Project Evaluation of the use of goals for admission, crisis plans, and duration of admission with people with personality disorders who have been admitted to adult acute psychiatric inpatient wards.

Page 188 of 197

Year II Assessments

Assessment Title

Report of clinical activity – Formal assessment

A dementia assessment with a white-British female in

her mid-thirties with diagnoses of Learning Disability and Downs Syndrome.

PPLD Process Account Reflections from a Trainee Clinical Psychologist on

the use and impact of a Personal and Professional Development Group on personal and professional development

Presentation of clinical activity Team Resistance building a weapon against the OCD bully: Working with a ten year old boy and his family using a narrative and CBT approach

Year III Assessments

Assessment Title

Major research project literature review Leisure influences on wellbeing among those who spend a significant amount of time caring for others: A systematic review

Major research project empirical paper The relationship between leisure and mental wellbeing in middle-aged women who care for more than 20 hours per week: A secondary analysis using data from a national survey

Final reflective account A reflective account of my personal and professional development during training as I approach qualification.

Report of clinical activity A cognitive neurorehabilitation intervention with a White British male in his mid-50s following an anterior communicating artery aneurysm rupture.

Page 1 of 197