Using Time Diaries to Locate Hidden Carers of the Elderly and People with Disabilities

1. Using Time Diaries to Locate Hidden Carers of the Elderly and People with Disabilities Michael Bittman, Kimberly Fisher, Trish Hill, and Cathy Thomson Social Policy Research Centre

2. Overview of the presentation • The problem of unidentified care activity and non-identified carers • Methodology for identifying the time signatures of carers and care activity • Profile of non-identified carers • Estimates of care time

3. Partners in the project • Carers New South Wales • NSW Department of Ageing, Disability and Home Care • NSW Department of Community Services • NSW Department for Health • NSW Department for Women • Social Policy Research Centre • With partial funding from an Australian Research Council linkage grant

4. This presentation solely represents the views of the authors from the SPRC and does not necessarily represent the views of the project partners or the Minister or NSW government

5. Why some carers do not recognised care activity as care • Some carers cope by denying the level of care an impairment requires • People do not perceive subtle changes in their behaviour over time as a consequence of care – especially as some care activities are very similar to routine domestic activities

6. Why some carers do not recognised care activity as care • No well developed public discourse about care and care activity • Criteria to receive public benefits tend to have narrow definitions of the carer role – people told they do not qualify as a carer may believe that they are not carers in a broader sense

7. Policy implications of unrecognised care • Policies ineffectively target the population of carers and may miss out some carers in great need • Need relatively accurate estimates of the time range needed for care to design policies to help people who do not have access to sufficient informal care help

8. Implications of unrecognised care for carers • Non-identified carers miss out on information and services that may save them time, energy and money while reducing their risk of injury or burnout

9. 2 Aims of time use element of project • profile non-identified carers • estimate the daily time cost of providing care to people with disabilities and the frail elderly in Australia

10. Why seek time signatures • Qualitative interviews with identified carers reveal that these carers perceive multiple dimensions in which their daily activities differ from non-carers • To look for people with similar distinctive time signatures we need random national sample data that include daily activities – an ideal use for time diary data

11. 1997 ABS National Time Use Survey • Random national sample of households • All members aged 15+ asked to keep 2 24 hour time diaries on 2 consecutive days • Diaries collected in fours waves, once in each season • 84.5% response rate

12. 1997 ABS National Time Use Survey • Diaries started at 00:00 and end at 24:00 • Own words activity reporting • Diaries also covered • secondary activity • location and how travelled • who else was present • for whom activities performed

13. How time diaries can profile non-identified carers • People recorded care activities in their diaries who do not report being a carer on the individual questionnaire items • People who have a carer time signature

14. Numbers of carers • 889 self-identified carers • 262 identify as primary carers • 627 identify as providing other assistance • 240 people record adult/child disability care who did not identify themselves as carers

16. BUT - of diarists recording adult care in their diaries • 35.1% are self-identified carers • the other 64.9% of diarists recording adult care are not identified carers • of self-identified carers, only 14.6% recorded a care activity in their diary

17. This means two things • many carers are not identifying some care activities as care • the population of non-identified carers is likely to be much bigger than identified so far

18. Identifying care time signatures • comparison of median and Z scores • 1-way Anova and comparison of means • OLS regression models accounting for sex, urban/rural residence, income bands, child aged <5 in household, age, marital status, migration, education, employment status, season, normal/unusual day, weekend/week day, whether care recorded in diary

19. Identifying care time signatures • grouped primary activities • grouped secondary activities • number of episodes • location • for whom • with people with disabilities and alone • concepts of interrupted sleep and leisure

20. Identifying care time signatures • of 73 items tested, carers have distinct patterns on 58 items, 52 of these items measure distinct concepts • 24 items used to create an ordinal scale • when carers do more of an activity, scores at or above the carer 60 percentile coded as 1 • when carers do less of an activity, scores at or below the carer 40 percentile coded as 1

21. People • living with a child aged <5 • living with children aged 5 to 14 • looking after a child from another household • living with a person with a temporary illness or injury in the household separated into other categories – 1263 diarists remain as possible carers

22. Hierarchical cluster (simple matching) analysis of whether people scored like a carer on the 52 distinct concepts and whether people fall into each of the 4 carer categories or other households reveals that the possible carers cluster with other carers

23. C A S E 0 5 10 15 20 Label Num +---------+---------+---------+---------+ B23 47 òø temporary injuryòú B20 44 òú A19 19 òú lives with child 5-14òôòø B10 34 ò÷ó B8 32 òòòú non-identified carer òòòú identified primary carer òòòôòø A9 9 òòò÷ó B6 30 òòòòòú has child aged <5 òòòòòú non-residential child careòòòòòôòø A5 5 òûòòò÷ó A14 14 ò÷ùòø B13 37 òòòòòòòúùòòòø B14 38 òòòòòòò÷óùòø other identified carer òòòòòòòòò÷óó B25 49 òòòòòòòòòòòòò÷ùòø possible careròòòòòòòòòòòòòòòúó B3 27 òòòòòòòòòòòòòòò÷ùòø not a careròòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòòò÷

25. Comparing carer groups • all carer groups are more likely to work part-time or not be in the labour market and to feel time pressured • performed more care activities on unusual than ordinary days

26. Comparing carer groups • identified carers are less likely to be aged 75+ while non-identified and possible carers are more likely to be aged 75+

27. Comparing carer groups • identified and possible carers are more likely to have a disability themselves • identified primary carers and possible carers are more likely to live in households that receive housework services and also more likely to receive income support

28. Comparing carer groups • identified primary carers, non-identified carers and possible carers are more likely to be women • possible carers and identified non-primary carers are less likely to live in a capital city

29. main activity is adult care main activity not care but secondary activity is adult care neither main or second activity is adult care but activity done for person with a disability - but these combined estimates are low 80 percentile for self-identified and non-identified carers is 23 minutes per day estimates of care time

30. main activity is adult care main activity not care but secondary activity is adult care neither main or second activity is adult care but activity done for person with a disability plus 75% of the sum of time spent in activities associated with carers above the 60 percentile for time spent in each of these activities by age and sex group minus the median score of non-carers estimates of care time

31. self-identified primary carers 20 percentile 15 min 80 percentile 3 hrs 46 min self-identified other carers 20 percentile 4 min 80 percentile 3 hrs 40 min non-identified carers recorded care in diaries 20 percentile 50 min 80 percentile 5 hrs 1 min possible carers 20 percentile 30 min 80 percentile 4 hrs 4 min estimates of care time

32. Policy implications • non-identified carers spend more time on care • some non-identified carers • may not provide care with maximum efficiency because they lack information on best practice or available services • may experience less balance in their lives

33. Conclusions • time use data have some limitations to the study of care • most studies have no information on the degree of impairment experienced by care recipients • difficult to accurately estimate error terms for activities associated with care - need to be conservative with estimates

34. Conclusions • but time use data do • illuminate how caring roles impact daily life • help identify the size of the population providing care • allow limited estimation of the time devoted to care