Our work, our lives and working time How the length of working hours, their fit with preferences and self-employment affect work-life outcomes in Australia Centre for Work and Life, Hawke Research Institute, University of South Australia In partnership with the Western Australian State Health Advisory Committee on Work Life Balance and SafeWork SA, Government of South Australia. Australian Research Council Linkage Project (LP ) Natalie Skinner Barbara Pocock Philippa Williams Our Work Our Lives Conference, Adelaide, South Australia, September 2007.

2 Overview Why are work-life issues important? Why are work-life issues important? Introduction to AWALI Introduction to AWALI Research questions: current study Research questions: current study AWALI measures AWALI measures Key findings Key findings Implications – policy & practice Implications – policy & practice Future studies Future studies

3 Why are work-life issues important? Health economics (Higgins et al 2004) Health economics (Higgins et al 2004) 2001, Canada, health costs 2001, Canada, health costs High work-family spillover: C$2.8 billion High work-family spillover: C$2.8 billion Mental and physical health impairments Mental and physical health impairments Organisational costs (turnover intention, performance effectiveness) Organisational costs (turnover intention, performance effectiveness) Reduced marital and life satisfaction Reduced marital and life satisfaction (Kossek & Ozeki 1999; Allen et al. 2000)

4 AWALI Methodology National survey of work–life outcomes National survey of work–life outcomes Repeated annually from March 2007 Repeated annually from March 2007 CATI interviews conducted by Newspoll CATI interviews conducted by Newspoll 1435 randomly selected working Australians 1435 randomly selected working Australians 29 Qs + 10 demographic Qs (Newspoll) 29 Qs + 10 demographic Qs (Newspoll)

5 Overview of AWALI 2007 sample characteristics (%) MenWomenAll ABS labour force survey 1 All (male) Type of employment Employee Self-employed Work status Full-time (35+ hours per week) Part-time (< 35 hours per week) Total Trade union membership Note. Data weighted by Australian Bureau of Statistics (ABS) data on age, highest level of schooling completed, sex and area. 1 ABS Cat. No November 2006 and Cat. No May ABS data for states includes 2.2% from the Northern Territory, and includes 15–24 year olds in first age group.

6 The current study What makes a difference to work-life interaction? What makes a difference to work-life interaction? Three common strategies: Three common strategies: Work part-time (esp. for women) Work part-time (esp. for women) Flexible work scheduling (org policy) Flexible work scheduling (org policy) Self-employment Self-employment Good in theory – but effective in practice? Good in theory – but effective in practice? Lack of studies directly comparing the three strategies Lack of studies directly comparing the three strategies Gender differences? Gender differences?

7 Measurement of work-life interaction 1. Work interferes with responsibilities or activities outside of work 2. Work restricts time with family or friends 3. Work interferes with connections and friendships in local community 4. Feel rushed or pressed for time 1 = never, 2 = rarely, 3 = sometimes, 4 = often, 5 = almost always 5. Satisfied with balance between work and rest of life 1 = not at all, 2 = not very, 3 = somewhat, 4 = very

8 The work-life index Average of responses across the 5 work–life questions Average of responses across the 5 work–life questions Standardised scale Standardised scale Mean set at 100 and a standard deviation of 15 Mean set at 100 and a standard deviation of 15 Similar to interpreting a standard IQ score Similar to interpreting a standard IQ score But – higher index score indicates worse work-life interaction But – higher index score indicates worse work-life interaction

9 Work schedule flexibility & work hours Flexibility: Average of 2 items: Average of 2 items: freedom to decide when do work freedom to decide when do work working times flexible to meet needs working times flexible to meet needs 4-point scale: strongly disagree – strongly agree 4-point scale: strongly disagree – strongly agree Work hours: Full-time Full-time Standard: hours Standard: hours Long: 45 + hrs Long: 45 + hrs Part-time Part-time Short: 15 hrs or less Short: 15 hrs or less Long: hrs Long: hrs

10 Key findings 1. Work hours 2. Flexible work scheduling 3. Self-employment

11 Work hours (%) MenWomenAll Full-time (35+ hrs) Part-time (< 35 hrs) Standard full-time (35-44 hrs) Long full-time (45+) Short part-time (1-15 hrs) Long part-time (16-34 hrs) **employees only**

12 AllMenWomenSignificance Work status Full-time101.88(15.00)101.34(15.00)103.01(14.97) Main effects work status (p <.001) and gender (p <.05) Main effects work status (p <.001) and gender (p <.05) Part-time94.72(13.96)92.99(14.13)95.35(13.81) Work hours Short part-time (15 hrs or less) 91.39(12.86) b (14.15)91.01(12.34) Main effects work hours (p <.001) and gender (p <.05) Main effects work hours (p <.001) and gender (p <.05) Long part-time (16-34 hrs) a (14.08) b (14.03) c (13.99) Standard full-time (35-44 hrs) a (14.09) b (14.21) c (13.92) Long full-time (45+) (15.14)104.41(15.14)109.24(14.91) Index scores - work hours

13 Flexible work scheduling AllMenWomenSignificance Flexibility97.43(14.19)96.31(13.87)98.55(14.56) Main effects flexibility (p <.001) and gender (p <.01) No flexibility (15.33)101.39(15.90)104.10(14.61) No interaction effect with work status (part-time/full-time) Flexible work scheduling beneficial regardless of long/short full time/part time

14 Self employment No significant difference in index scores employees vs self-employed No significant difference in index scores employees vs self-employed Similar patterns as with employees: Similar patterns as with employees: Higher scores for full-time compared to part-time workers Higher scores for full-time compared to part-time workers Women higher scores than men (controlling hours) Women higher scores than men (controlling hours)

15 Multivariate analysis Binomial logistic regression Binomial logistic regression Poor work-life interaction defined as the highest 33% of scores Poor work-life interaction defined as the highest 33% of scores Separate analyses for men and women Separate analyses for men and women Collapsed work hours categories into part-time and full-time Collapsed work hours categories into part-time and full-time Excludes self-employed Excludes self-employed Controlled for: age, income, education (university education or not) and parental status Controlled for: age, income, education (university education or not) and parental status

16 MenWomen ß Odds ratio 95% CI ß Odds ratio 95% CI Work hours Part-time Long full-time (Base: standard full- time).52** ** Work flexibility (Base: flexibility available).63** – *** Log Likelihood Constant-1.76***-1.82***

17 Key findings: Importance of capacity and opportunities to negotiate flexibility Importance of capacity and opportunities to negotiate flexibility Across part-time and full-time work Across part-time and full-time work Part-time work is not the “silver bullet” of negative work-life spillover Part-time work is not the “silver bullet” of negative work-life spillover Nor is self-employment Nor is self-employment Long hours have a significant impact – especially for women Long hours have a significant impact – especially for women Policy/practice implications: UK: parents’ right to request flexible working practices (Employment Act 2002) UK: parents’ right to request flexible working practices (Employment Act 2002) EU: 1993 Directive on working time – max working hours 48 hours weekly (on average) EU: 1993 Directive on working time – max working hours 48 hours weekly (on average) Policy and practice

18 Study limitations Small sample sizes some groups: Small sample sizes some groups: Women working long full-time hours Women working long full-time hours Men working part-time hours (esp short part-time) Men working part-time hours (esp short part-time) Absence of questions on unsocial working times Absence of questions on unsocial working times Reliance on single & dual-item questions on job characteristics (ie flexibility) Reliance on single & dual-item questions on job characteristics (ie flexibility) CATI costs CATI costs

19 Future plans Annual data collection Annual data collection Next 3 years funded through ARC Linkage Project ‘Work/Life Balance, Well-Being and Health: Theory, Practice and Policy’ Next 3 years funded through ARC Linkage Project ‘Work/Life Balance, Well-Being and Health: Theory, Practice and Policy’ Modification to items Modification to items Add item(s): eg unsociable work hours, positive spillover Add item(s): eg unsociable work hours, positive spillover Survey of WA health workforce (ARC Linkage Project) Survey of WA health workforce (ARC Linkage Project)

20 Further information Pocock B, Williams, P & Skinner N 2007, ‘The Australian Work and Life Index (AWALI): Concepts, Methodology & Rationale’, Centre for Work + Life Discussion Paper 1/07, May Pocock B, Williams, P & Skinner N 2007, ‘The Australian Work and Life Index (AWALI): Concepts, Methodology & Rationale’, Centre for Work + Life Discussion Paper 1/07, May 2007.The Australian Work and Life Index (AWALI): Concepts, Methodology & RationaleThe Australian Work and Life Index (AWALI): Concepts, Methodology & Rationale Pocock B, Williams, P & Skinner N 2007, ‘Work Life and Time: The Australian Work and Life Index 2007’, Centre for Work + Life Discussion Paper 1/07, May Pocock B, Williams, P & Skinner N 2007, ‘Work Life and Time: The Australian Work and Life Index 2007’, Centre for Work + Life Discussion Paper 1/07, May 2007.Work Life and Time: The Australian Work and Life Index 2007Work Life and Time: The Australian Work and Life Index