Policy Oriented Ageing Research
Clemens Tesch-Römer
German Centre of Gerontology, Berlin
Presentation at the First Conference of the Project
“Pro Health 65+ Health Promotion and Prevention of Risk
– Actions for Seniors”, Cracow, 21-22 September 2015
Policy Oriented Ageing Research
1. What politicians should know about science
2. Scientific policy consulting and social reporting
3. An example of policy oriented ageing research
4. How to communicate with politicians?
5. Outlook
Page 2
20 Things Politicians Need to Know About Science
1. Differences and chance cause
variation.
2. No measurement is exact
3. Bias is rife.
4. Bigger is usually better for sample
size.
5. Correlation does not imply
causation.
6. Regression to the mean can
mislead.
7. Extrapolating beyond the data is
risky.
8. Beware the base-rate fallacy.
9. Controls are important.
10. Randomisation avoids bias.
11. Seek replication, not pseudo-
replication.
12. Scientists are human.
13. Significance is significant.
14. Separate no effect from non-
significance.
15. Effect size matters.
16. Data can be dredged or cherry
picked.
17. Extreme measurements may
mislead.
18. Study relevance limits
generalisations.
19. Feelings influence risk perception.
20. Dependencies change the risks.
Page 3Milman, O. (2013). Top 20 things politicians need to know about science. The Guardian, 20 November 2013.
20 Things Politicians Need to Know About Science
1. Differences and chance cause
variation.
2. No measurement is exact
3. Bias is rife.
4. Bigger is usually better for sample
size.
5. Correlation does not imply
causation.
6. Regression to the mean can
mislead.
7. Extrapolating beyond the data is
risky.
8. Beware the base-rate fallacy.
9. Controls are important.
10. Randomisation avoids bias.
11. Seek replication, not pseudo-
replication.
12. Scientists are human.
13. Significance is significant.
14. Separate no effect from non-
significance.
15. Effect size matters.
16. Data can be dredged or cherry
picked.
17. Extreme measurements may
mislead.
18. Study relevance limits
generalisations.
19. Feelings influence risk perception.
20. Dependencies change the risks.
Page 4Milman, O. (2013). Top 20 things scientists need to know about policy-making. The Guardian, 20 November 2013.
Policy Oriented Ageing Research
1. What politicians should know about science
2. Scientific policy consulting and social reporting
3. An example of policy oriented ageing research
4. How to communicate with politicians?
5. Outlook
Page 5
Page 6
Scientific Policy Consulting
– „Aufklärung / Enlightenment“
Transfering and translating scientific knowledge into political
discourse and decision making.
– Types of scientific policy consulting
Providing information for political decisions (e.g. social reporting)
Alerting to new societal problems
Support in political goal setting (see my example later in the talk)
– Quality of scientific policy consulting
Advice is based on scientific evidence, is given independently, is
adequate and relevant, comes timely, and is easy to understand.
– …but:
Keeping distance to power, pointing out plurality of scientific
positions, giving advice publicly
Page 7
Social Reporting/Accounting/Monitoring
(that’s what we decided to do in my institute)
– Description and analysis
Using scientific methods, social reporting monitors the living
situation of (older) citizens over time:
Description of the living situation of citizens over time
Analysis of social change, analysis of individual trajectories
embedded in social change
– Normative ambition
Evaluating the living situation of (older) people according to
predefined political or ethical goals.
Providing knowledge for political decisions
Providing knowledge for societal discourse
Processes in Social Reporting
– Choice of topics
Specifying themes
Formulating questions
– Appointment of expert commission
Representing different disciplines
Nominating experts
– Producing the report
Writing (and discussing) chapters
Drawing conclusions and formulating recommendations
– Exchange with stakeholders
Discourse with senior citizens
Involving other scientists
Page 8
Policy Oriented Ageing Research
1. What politicians should know about science
2. Scientific policy consulting and social reporting
3. An example of policy oriented ageing research
4. How to communicate with politicians?
5. Outlook
Page 9
German Social Reports on Older People in Germany
Page 10
7th Reports on Older People in Germany:
Local Policies for Senior Citizens
– Assumption: In demographically changing societies the welfare state is
not able any more to fulfill all tasks necessary; hence (older) citizens
have to step in.
– Political concepts like “Big Society” (UK), “Participation Society” (NL)
and “Caring Communities” (DE), and “Active Ageing” (UNECE) are
based on that assumption.
– Policy consulting: Can scientific evidence support these political
concepts, e.g. giving advice how to activate older citizens in the local
context?
Seite 11
The German Ageing Survey (DEAS)
Objectives
Characteristics
Provision of micro data for social and behavioural
scientific research on age and ageing
Contribution to social reporting and policy consulting
on ageing
Interdisciplinary combination of gerontological
concepts with sociological, psychological, social policy
and economic approaches
Focus on living situations and ageing as individual and
social processes in their societal contexts
Page 12
DEAS: Sample and Methods
Sampling and
age range
Methodology
Data base
Cross-sectional and longitudinal survey study based
on a disproportionally stratified register sample of
community-dwelling people >=40 years
Face-to-face interview (CAPI)
Self-administered questionnaire (PAPI)
Few objective health measures
Up to now 4 waves: 1996, 2002, 2008, 2011
A fifth wave was conducted in 2014
Page 13
Generations,
Families and
Social
Networks
Activities,
Participation,
Volunteering
Housing and
Long-Term Care
Health, Health
Behaviour,
Subjective
Well-Being
DEAS: Topics
Work and
Retirement
Images of
Ageing,
Attitudes,
Norms and
Values
Standard of
Living and
Economic
Behaviour
Page 15
DEAS: Study Design and Data Structure
40
55
70
85
100
1996 20021999 2005 2008 2011 2014
Cross-sectional, panel, and cohort sequence design
Page 15
DEAS: Study Design and Data Structure
40
55
70
85
100
1996 20021999 2005 2008 2011 2014
Individual development:
What happens when people grow older?
Page 16
Study Design and Data Structure
Social change:
How does the situation of older people change in the German society?
40
55
70
85
100
1996 20021999 2005 2008 2011 2014Page 17
7th Report: Local Policies for Senior Citizens
Facing Regional Disparities in Germany
Industrial regions with high economic potential
Urban regions with high proportion of science
and service industry
Regions with average economic potential
Rural regions with strong tourism industry
Regions with low economic potential and weak
infrastructure
Reference
Clustering counties (2008)
based on several indicators measuring
the dimensions:
Population density
Wealth and strength of infrastructure
Manufacturing trade
Innovation
Tourism
Page 17
DEAS: Regional Disparities in Various Life Domains
0
20
40
60
80
100
Pro
zent
Referenz
Durchschnitts-
kreise
Geringe
Wirtschafts-
kraft
Tourismus-
gebiete
Großstädte Industrie-
standorte
59
17
24
50
22
28
60
19
21
56
21
23
65
20
16
(Sehr) gut
Mittel
(Sehr) schlecht
Referenz
Kreisregionen mit
durchschnittlichen
Produktionspotenzialen
Peripher
gelegene
Kreisregionen
mit starken
strukturellen
Defiziten
Periphere,
gering
verdichtete
Kreisregionen
mit starken
Tourismus-
potenzialen
Struktur-
starke hoch-
verdichtete
Dienst-
leistungs-
zentren
Struktur-
starke west-
deutsche
Industrie-
standorte
Funktionale Gesundheit
(sehr) schlecht
mittel
(sehr) gut
Low economic potential & weak infra-structure
Rural regions
with strong tourism
High proportion science &
service industry
Industrial regions
high economic potential
Reference
Average economic potential
Functional health
(very) bad
medium
(very) good
0
20
40
60
80
100
Pro
zent
Referenz
Durchschnitts-
regionen
Geringe
Wirtschafts-
kraft
Tourismus-
gebiete
Großstädte Industrie-
standorte
81
12
7
76
16
8
78
13
9
80
14
6
77
18
5
Eher geringe
Depressivität
Mittlere
Depressivität
Eher hohe
Depressivität
Depressive Symptome
eher hohe
Depressivität
mittlere
Depressivität
eher geringe
Depressivität
Referenz
Kreisregionen mit
durchschnittlichen
Produktionspotenzialen
Peripher
gelegene
Kreisregionen
mit starken
strukturellen
Defiziten
Periphere,
gering
verdichtete
Kreisregionen
mit starken
Tourismus-
potenzialen
Struktur-
starke hoch-
verdichtete
Dienst-
leistungs-
zentren
Struktur-
starke west-
deutsche
Industrie-
standorte
Low economic potential & weak infra-structure
Rural regions
with strong tourism
High proportion science &
service industry
Industrial regions
high economic potential
Reference
Average economic potential
Depressive symptoms
(rather) high
medium
(rather) low
0
20
40
60
80
100
Pro
zent
Referenz
Durchschnitts-
kreise
Geringe
Wirtschafts-
kraft
Tourismus
-gebiete
Großstädte Industrie-
standorte
18
49
33
13
46
41
14
34
52
14
55
31
18
51
31
Eher großes
Netzwerk
Mittleres
Netzwerk
Eher kleines
Netzwerk
(rather) small
network
medium-sized
network
(rather) large
network
Size of Social Network
Referenz
Kreisregionen mit
durchschnittlichen
Produktionspotenzialen
Peripher
gelegene
Kreisregionen
mit starken
strukturellen
Defiziten
Periphere,
gering
verdichtete
Kreisregionen
mit starken
Tourismus-
potenzialen
Struktur-
starke hoch-
verdichtete
Dienst-
leistungs-
zentren
Struktur-
starke west-
deutsche
Industrie-
standorte
Low economic potential & weak infra-structure
Rural regions
with strong
tourism
High proportion science &
service industry
Industrial regions
high economic potential
Reference
Average economic potential
0
20
40
60
80
100
Pro
zent
Referenz
Durchschnitts-
kreise
Geringe
Wirtschafts-
kraft
Tourismus-
gebiete
Großstädte Industrie-
standorte
18
82
9
91
9
91
17
83
13
87
Ehrenamt
Kein Ehrenamt
Honorary Post
No Honorary Post
Honorary Post
Referenz
Kreisregionen mit
durchschnittlichen
Produktionspotenzialen
Peripher
gelegene
Kreisregionen
mit starken
strukturellen
Defiziten
Periphere,
gering
verdichtete
Kreisregionen
mit starken
Tourismus-
potenzialen
Struktur-
starke hoch-
verdichtete
Dienst-
leistungs-
zentren
Struktur-
starke west-
deutsche
Industrie-
standorte
Low economic potential & weak infra-structure
Rural regions
with strong
tourism
High proportion science &
service industry
Industrial regions
high economic potential
Reference
Average economic potential
Functional Health Depressive Symptoms
Network Size Volunteering
Page 19
Potential Advice to Policy Makers from
DEAS Analyses on Regional Disparities
– Regional Differences in Need for Support
Need for support and care are highest in regions with low economic potential and
weak infrastructure (as compared to regions with average economic potential).
– Regional Differences in Resources for Self-Help
Especially in regions with low economic potential and weak infrastructure there
are few resources for self-help.
– Responsibility of Citizens and Responsibility of the State
Implications for concepts like “Big Society”, “Participation Society” and “Caring
Communities”: These concepts are probably least suited where most needed.
Page 20
Policy Oriented Ageing Research
1. What politicians should know about science
2. Policy consulting and social reporting
3. Scientific policy oriented ageing research
4. How to communicate with politicians?
5. Outlook
Page 21
Change of perspective…
What can scientists learn from policy makers?
How to improve communication between science and policy makers?
Page 22
20 Things Scientists Should Know about Policy-Making
1. Making policy is really difficult.
2. No policy will ever be perfect.
3. Policy makers can be experts, too.
4. Policy makers are not a homogenous
group.
5. Policy makers are people too.
6. Policy decisions are subject to
extensive scrutiny.
7. Starting policies from scratch is very
rarely an option.
8. There is more to policy than scientific
evidence.
9. Economics and law are top dogs in
policy advice.
10. Public opinion matters.
11. Policy makers do understand uncertainty.
12. Parliament and government are different.
13. Policy and politics are not the same thing.
14. The UK has a brilliant science advisory
system.
15. Policy and science operate on different
timescales.
16. There is no such thing as a policy cycle.
17. The art of making policy is a developing
science.
18. 'Science policy' isn't a thing.
19. Policy makers aren't interested in science
per se.
20. 'We need more research' is the wrong
answer.
Page 23Tyler, C. (2013). Top 20 things scientists need to know about policy-making. The Guardian, 2 December 2013.
20 Things Scientists Should Know about Policy-Making
1. Making policy is really difficult.
2. No policy will ever be perfect.
3. Policy makers can be experts, too.
4. Policy makers are not a homogenous
group.
5. Policy makers are people too.
6. Policy decisions are subject to
extensive scrutiny.
7. Starting policies from scratch is
very rarely an option.
8. There is more to policy than scientific
evidence.
9. Economics and law are top dogs
in policy advice.
10. Public opinion matters.
11. Policy makers do understand uncertainty.
12. Parliament and government are different.
13. Policy and politics are not the same thing.
14. The UK has a brilliant science advisory
system.
15. Policy and science operate on different
timescales.
16. There is no such thing as a policy cycle.
17. The art of making policy is a developing
science.
18. 'Science policy' isn't a thing.
19. Policy makers aren't interested in science
per se.
20. 'We need more research” is the wrong
answer.
Page 24Tyler, C. (2013). Top 20 things scientists need to know about policy-making. The Guardian, 2 December 2013.
Policy Oriented Ageing Research
1. What politicians should know about science
2. Policy consulting and social reporting
3. Scientific policy oriented ageing research
4. What did I learn from Dorly Deeg?
5. Outlook
Page 25
If I was king… I would ask you at least 5 questions:
Whom are you talking to?
To me? To the European commission? To a national government? To the regions
within a country? To municipalities? To welfare organizations? To senior citizens?
Who is paying – and is it worthwhile?
See above. Show me that it w o r k s. And tell me short-term (and long-term)
consequences (and the side effects).
Who profits?
Are my constituents profiting from your intervention? Does everybody profit from you
intervention or do you increase (health) inequalities?
How complicated is this stuff?
One size fits all – or do we have to tailor the interventions: for the young old and the
old old, for women and men, for the better and for the less educated?
Will you prevent Alzeimer’s? Or Frailty?
If not, what other (costly) diseases will decrease in prevalence? Are you sure that you
will make “compression of morbidity” happen in the end?
Seite 26
All the Best for the Project “Pro Health 65+”!
Policy Oriented Ageing Research
Clemens Tesch-Römer
German Centre of Gerontology, Berlin
www.dza.de
The German Centre of Gerontology is funded
by the German Federal Ministry of Family Affairs,
Senior Citizens, Women, and Youth
Seite 27
