The document discusses using a life course perspective to design mobile technology for older adults. It proposes that a person's experience of aging is shaped by their unique biography, social context, and historical period. It suggests this perspective can be used in HCI to predict technology acceptance among the elderly based on factors like education, work experience, and socioeconomic status. The document outlines transitions people experience as they age and how technologies could be designed to age with users through different life stages from maintenance to coping with illness and loss of independence. It raises questions about what kind of tool could accompany people throughout their lifespan and help navigate the aging process.

1. The Value of the
Life Course Perspective
for the Design of Mobile
Technology
Foong Pin Sym, PhD Candidate
NUS Graduate School of Integrated Sciences and Engineering
NUS HCI Lab
pinsym@nus.edu.sg
Twitter: @interfaceaddict
Mobile HCI 2014 Workshop:
Re-imagining commonly used mobile interfaces for older adults

2. Introduction and Goals
• Interests: Ageing, health, technology,
persuasion, end-of-life decision making
• Goals:
▫ Feedback and discussion on Life Course
perspective as a research frame
FOONG (NUS) 9/18/2014

3. The Life Course Perspective
• Experience of Aging is shaped by ...
unique personal biographies +
location in the social system +
historical period
Stoller and Gibson (2000)
• ‘transitions’
• ‘choice points’
FOONG (NUS) 9/18/2014
Image credit: luma photography @ flickr CC

4. FOONG (NUS) 9/18/2014
Uses of the life course perspective
In Gerontology In Sociology
Image credit: osteoporosis_female @ flickr CC
Image credit: Bev Norton @ flickr CC

5. • In HCI: As predictive factors of elderly technology acceptance –
education, work-usage, cognitive ability, socio-economic status
Image credit: Barbara Krawcowlcz @ flickr CC

6. HCI & Ageing Clock
Older
Goal: COPING II
- pathological age-related conditions
- cognitive orthotics
- accessibility barrier reduction
- Occupational Therapy
- Physical Therapy
-Caregiver aids
-Telecare
Loss of independence
65 years old and above
Goal: COPING I
- normal age-related impairment
- reminder systems
- accessibility barrier reduction
- social/health maintenance
Goal: MAINTENANCE
-Work
-Physical Health
-Screening
Goal?
- Quality of life?
- pleasures?
- End-of-life care?
- CAREGIVER HELP
GENERAL POPULATION HCI ACCESS/DISABILITY HCI
Younger
ACTIVE AGEING TECHNOLOGIES
Well Unwell
FOONG (NUS) 9/18/2014

7. Older
COPING I COPING II
Transitions #2
-Characterized by loss
-Of independence
- of technology
habits?
caregivers
MAINTENANCE CARING
Well Unwell
65 years old and above
GENERAL POPULATION HCI ACCESS/DISABILITY HCI
Younger
Loss of independence
Transitions #1
-Technology ageing with
us?
-Changes in social
networking, relationships,
activity, retirement
caregivers
Transitions #3
- How can access
technologies age with us?
FOONG (NUS) 9/18/2014
HCI & Ageing Clock

8. Singapore Population Demographics & Implications for
Design Goals and Technological Acceptance
Year of birth
1910’s: Colonial
1920’s: Colonial
1930’s: Colonial
1940’s: WWII
1950’s: WWII
1960’s: Ec Boom
1970’s: Ec Boom
1980’s: ICT
1990’s: ICT
2000’s: Millenials
Older
COPING I COPING II
MAINTENANCE CARING
Well Unwell
Younger
2050: Projected population 35% > 60
Parental support ratio from 10: 1 (current) to 2: 1

9. Q: What sort of tool can accompany us through the life span?

10. Q: Can this tool help navigate the vagaries of the ageing
process, including illness, disability and death?

11. Thank You & Questions
FOONG (NUS) 9/18/2014
• Is it useful to study the transitions?
▫ Dis-continuity: the challenge of age-related
limitations and ongoing technology renewal
▫ Whose work should I be looking at?
• Nursing home studies
▫ Finding the balance between caregiver and elderly
users’ needs?
▫ ‘Toys’ for elderly with Mild Cognitive Impairment
/Dementia?

12. Extra Slides
FOONG (NUS) 9/18/2014

13. Maintenance
FOONG (NUS) 9/18/2014

14. Coping I
• Acessibility
FOONG (NUS) 9/18/2014
http://app.mot.gov.sg/page_land.aspx?p=/Land_Transport/Meeting_Divers
e_Needs/Enhancing_Accessibility.aspx

15. Coping II
FOONG (NUS) 9/18/2014
• http://www.myhappystroke.com/2011/03/modi
fied-constraint-induced-movement.html

16. Coping II
FOONG (NUS) 9/18/2014
• Making Family Care Work: Dependence, Privacy and
Remote Home Monitoring Telecare Systems John
Vines, Stephen Lindsay, Gary W. Pritchard, Mabel Lie, David
Greathead, Patrick Olivier and Katie Brittain, Culture 2 Fit
Lab, Newcastle University Lab, Swansea University

17. Issue: Change over FOONG (NUS) time
9/18/2014
Multi-Level Linear Modelling to study mobile phone usage
Variance of
intercepts 휏00
Variance of slopes 휏11
Tech ability
Freq of mob usage
Time-varying variables:
1. Dependent Variable: mob0-mob3 (frequency
of mobile phone usage, measured at time
0,1,2, and 3)
2. Independent Variables: tech0-tech3
(technological ability score, measured at
time 0,1,2 and 3)
Time-invariant variables:
1. Gender: male or female
2. Tech support (received from family/friends)
Research Question:
What are the growth patterns of mobile phone
usage over time? (intra individual
differences)
What predicts the growth patterns of mobile
phone usage? (inter-individual differences)

18. Issue: Change oveFOONrG (N USt) i9/1m8/2014 e
Multi-Level Linear Modelling to study mobile phone usage
Level-1 model:
mobij = β0j + β 1jTimeij + rij
Level-2 model:
Intercept:
β0j = γ00 + γ 01Genderj + γ 02Supportj + u0j
Slope:
β1j = γ10 + γ 11Genderj + γ 12Supportj + u1j
Variance of
intercepts 휏00
Variance of slopes 휏11
Tech ability
Freq of mob usage

19. FOONG (NUS) 9/18/2014
Speed of population ageing