1 Active Ageing, Wellbeing and Learning in Later Life Andrew Jenkins Institute of Education, University of London, UK Presentation for Cedefop/European Commission Learning Later in Life Seminar 21 st September 2011, Brussels

2 Research Questions Does participation in learning in later life have beneficial effects on wellbeing? Are some types of learning more beneficial than others?

3 Potential Outcomes of Learning [the three capitals framework, from Schuller, 2004] Human capital »Knowledge and skills Social capital »Social and civic participation, friends, networks Identity capital »Self-esteem, locus of control, sense of purpose, critical thinking

4 English Longitudinal Study of Ageing: Overview Original sample taken from 3 sweeps of Health Survey of England (1998, 1999, 2001) ELSA is representative of the English 50+ population in private households at the baseline (2002/03) ELSA Wave 1: 2002/03; ELSA Wave 2, 2004/05; ELSA Wave 3, 2007 Sample size at Wave 1: approx 11,000 Data available from UK Data Archive

5 Information on learning in ELSA Current participation in music, arts or evening classes Current participation in gym/exercise classes Recent or current participation in formal education or training course

Learning Participation: ELSA Wave 1 Type of Course, by Gender 6

Learning Participation: ELSA Wave 1 Type of Course, by Age Band 7

8 Subjective Well-being Measures in ELSA Quality of Life: CASP-19. CASP means control, autonomy, self-realisation, pleasure GHQ-12. General Health Questionnaire Life Satisfaction. SWLS – Satisfaction With Life Scale (Diener)

CASP-19 is a theory based Quality of Life Measure developed under the UK’s Economic and Social Research Council’s Growing Older Programme ( ) See “Quality of Life and the third age: key predictors of CASP- 19”. Wiggins, Higgs, Hyde and Blane. (2004). Special Issue of Ageing and Society. Vol 24(3), pp.1-16.

Concepts and indicators…… Quality of life

Concepts and indicators…… Quality of life Control & Autonomy Self- realisation Pleasure Item 1 Item 2 Item 3 Item 4 Item 19

Examples of some of the CASP-19 items 12 CONTROL & AUTONOMY  My age prevents me from doing the things I would like to do*  I feel that what happens to me is out of my control *  I feel left out of things *  I can do the things I want to do  I feel that I can please myself what I do  Shortage of money stops me doing things I want to do * * reverse code

Examples of some of the CASP-19 items 13 SELF- REALISATION  I feel full of energy these days  I feel that life is full of opportunities  I feel that the future looks good for me

Examples of some of the CASP-19 items 14 PLEASURE  I look forward to each day  I feel that my life has meaning  I enjoy the things that I do

GHQ Twelve items e.g. Have you recently..... …been able to concentrate on whatever you’re doing?* Better than Same as Less than Much less usual usual usual than usual …lost much sleep over worry?* Not at No more Rather more Much more all than usual than usual than usual …felt constantly under strain?* Not at No more Rather more Much more all than usual than usual than usual * Reverse coded. Each coded on 4-point scale from 0 to 3, maximum score 36

Satisfaction with Life Scale 16 “In most ways my life is close to my ideal” “The conditions of my life are excellent” “I am satisfied with my life” “So far I have got the important things I want in life” “If I could live my life again, I would change almost nothing” Each coded on 7-point scale, from strongly agree to strongly disagree, and then summed to obtain score (minimum 0, maximum 30)

Subjective Wellbeing Measures in each ELSA Wave ELSA WAVEWave 1Wave 2Wave Quality of Life (CASP-19) √√√ Wellbeing (GHQ-12) √√ Life Satisfaction SWLS √√ 17

Summary statistics on the outcome variables Quality of Life CASP-19 Wellbeing GHQ-12 Life Satisfaction SWLS Mean SD Min000 Max

19 Method (1): estimation strategy Interest: statistical associations between measures of wellbeing (response) and measures of learning (explanatory) Method issue 1: other observable factors influencing wellbeing »Control for these observable factors in multiple regression model Method issue 2: unobservable (but fixed) characteristics influencing both wellbeing and participation in learning »Use change in wellbeing, rather than level of wellbeing as response variable

20 Method (2): dealing with dropout and non-response Longitudinal survey: people tend to drop out over time (attrition) »Use probability weights to allow for dropout from the survey (standard set of weights supplied with ELSA survey) Respondents don’t answer all questions: a problem for multiple regression »Use multiple imputation to overcome this. (specifically imputation by chained equations in Stata)

Multiple regression models for change in outcome control variables entered in stages 1. level of outcome variable 2. Age, gender, highest qualification 3. Marital status, work status, income, health status, in pain, mobility, support from family/friends 4. Change in partner status, work status, physical health and mobility variables 21

Summarising the multiple regression models (models with all controls included) Change in Quality of Life (CASP-19) Change in Wellbeing (GHQ-12) Change in Life Satisfaction (SWLS) Formal education/ training course [0.58] [-0.22] [0.45] Music/arts/evening class [3.49]*** [2.27]** [3.78]*** Gym/exercise class [1.56] [0.12] [0.18] No of observations 6,113 5,641 5,518 Absolute values of t-statistics in parentheses. Significant at *10%, **5%, ***1%

Magnitude of ‘effects’ of adult learning? Quality of Life: mean decline in CASP-19 score between 2 waves approx 0.5; compares to an increase of approx 0.7 associated with participation in adult learning (music/arts/evening classes) Life satisfaction: score typically declines by 1 point between 2 waves; compares to an increase of approx 0.7 associated with participation in adult learning (music/arts/evening classes) 23

Analysis of sub-groups  Analysis of impact of music/arts/evening classes on wellbeing showed few differences by sub-group (gender, age group, work status, marital status)  Evidence that those with higher education who participated in learning had larger gains in wellbeing than people with no qualifications who participated in learning 24

Summary of main results  Evidence that participation in learning linked to increased wellbeing  Participation in music/arts/evening classes remains significantly associated with wellbeing, even after allowing for many other factors  Other forms of learning, including formal education and training courses, not associated with increased wellbeing (after allowing for other factors) 25

What are the implications of these findings? Learning in later life can have an impact on individual wellbeing  A contribution to ‘successful ageing’ Only some types of learning have direct impact on wellbeing  Participation in non-vocational learning i.e. leisure classes  No evidence that formal education/training courses have an effect Key message for policy  While vocational training is important in many respects other forms of learning, including learning for pleasure/interest, should not be neglected 26

Implications (continued) The research does not rule out vocational training having an indirect impact on wellbeing For example, older people who regard themselves as unemployed have much lower wellbeing (on average) than those who are in employment So IF vocational training helps to keep older adults in employment then it would contribute to wellbeing in an indirect way 27

ADDITIONAL SLIDES 28

Change in Quality of Life: CASP-19 (ELSA waves 1 to 2) 29

Change in Quality of Life by Age Band 30

Change in Quality of Life and Level at Wave 1 31

Multiple regression model of Learning on change in Quality of Life (CASP-19) 32