1. Yang Fang1 , Anson K. C. Chau2, Anna Wong1,
Information and communicative technology use enhances psychological well-being of older adults: The when and the how
Yang Fang1 , Anson K. C. Chau2, Anna Wong1,
Helene H. Fung2, & Jean Woo1
1 CUHK Jockey Club Institute of Ageing, 2 Department of Psychology
The Chinese University of Hong Kong

2. ICT Use among Older Adults
ICT : Information and Communicative Technologies General ICT: use of computing devices capable of providing internet access, such as computers, smartphones, and tablets. Generally positive outcomes: Negatively associated with loneliness (Sum, Mathews, Hughes, & Campbell, 2008) Buffers against depressive symptoms and negative well-being (Elliot, Mooney, Douthit, & Lynch, 2014; Francis, Kadylak, Cotten, & Rikard, 2016)
(Khosravi, Rezvani, & Wiewiora, 2016; Leist, 2013)

3. Socioemotional Selectivity Theory (Carstensen, Isaacowitz, & Charles, 1999; Carstensen, Fung, & Charles, 2003)
Older age perceive more limited future time Motivates older people to prioritize present-oriented goals such as (e.g. maintaining meaningful social relationships) over future-oriented goals (e.g., seeking new acquaintances) Does ICT use benefit older people by helping them maintain close social connections?

4. Selective Optimization & Compensation (Baltes & Baltes, 1990; Baltes, 1997; Freund & Baltes, 1998)
Adaptation to losses in physiological, cognitive, social and motivational reserves in late adulthood
Interaction of three inter-related processes
Selection (restricting the number of domains of functioning)
Optimization (adopting behaviors and strategies to enrich and maximize their engagement)
Compensation (making up for reduced capacities necessary for adequate functioning)

5. Moderators of ICT benefits?
Age group
young-olds vs. old-olds
Physical frailty (Clegg, Young, Iliffe, Rikkert, & Rockwood, 2013; Fried et la., 2001)
cumulative decline in physiological systems over the lifespan
increased vulnerability to adverse outcomes, such as comorbidity, disability, and mortality

6. Research Questions
What are the effects of ICT use between the middle-aged, young-olds and old-olds?
Can this be explained by frequency of contact with close social partners?
Are the effects of ICT use on frail and nonfrail older adults the same?
Population: Hong Kong—urban, densely populated, highly wired, and rapidly ageing.

7. Survey Methodology
Telephone interviews were conducted in mid-2016 with 1201 participants aged 50 and above. Numbers were randomly drawn from the household telephone directory. Additional numbers were created by replacing the last two digits of selected telephone numbers with randomly generated numbers. The interviews were introduced as a study on older people’s quality of life, and had a total response rate of 49.4%.

8. Measures
Psychological well-being: life satisfaction, positive affect, meaning in life (0-10) ICT use: how often they ‘go online’ & ‘use smart devices, such as smartphones and iPads’ [1 (never) to 4 (often)] FRAIL Scale: 5 items (Morley, Malmstrom, & Miller, 2012; Woo et al., 2015) Robust: 0 points; Prefrail: 1-2 points; Frail: 3-5 points Social Contact: how often they were ‘together with’ & ‘talked to’ 1) Family, 2) Friends, 3) Neighbours [1 (never) to 4 (often)] Self-rated health: 1(very poor) to 5 (very good) Subjective financial sufficiency: 1 (very insufficient) to 5 (very sufficient)
(OECD, 2013)

9. Sample CharacteristicsN
1201
Age range
50—80+
50-54 (17.6%), (18.1%), (17.4%), (16.5%), (13.2%), (7.7%), and >= 80 (7.7%)
Gender
55.7% female
Education Level
≤Preschool or less: 7.2%; Primary school: 25.3%
Middle school: 21.8%; High school: 25.5%
Tertiary: 20.2%
Employment Status
32.9% currently employed
Frailty Status
Robust: 38.7%; pre-frail: 51.2%; frail: 10.1%
Participant reported their age in ascending brackets:.
The sample characteristics were highly similar to the population characteristics of Hong Kong during the same time period
The prevalence of pre-frailty and frailty in our sample were 52.7% and 15.9% respectively among participants 65 years and older, which is very close to the respective prevalence rates of 52.4% and 12.5% previously reported in the Hong Kong population (Woo et al., 2015).

10. Bivariate Correlations
1. Age 2.
Sex
3. Education
4. Employment status 5.
Self-rated health
6. Financial sufficiency 7.
ICT use
8. Psychological well-being 9.
Contact with family
10. Contact with friends
11. Visiting neighbors M
3.51 -
3.26
3.48
3.47
2.74
6.9
3.57
2.01 SD
1.88
1.24
1.05
1.17
1.77
0.62
0.73
0.98 2
-.03 3
-.40**
.18** 4
-.55**
.16**
.32** 5
-.21**
.13**
.22** 6
-.19**
.06*
.29**
.36** 7
-.45**
.11**
.51**
.31**
.26**
.28** 8
-.08*
-.05
.15**
.01
.41**
.45** 9
-.28**
.00
.24**
.27**
.30** 10
-.11**
-.12**
.04
.25** 11
-.01
-.04
.03
.07*
.12**

11. Does the association between ICT use and psychological well-being depend on age?
Step 1
Step 2
Step 3
Predictors β
t (p)
Education
Self-rated health
Finance
Age
ICT use
Age x ICT use
∆R2 ∆F
-.01
.30**
.33**
.271**
(p<.01)
(.839)
10.61 (<.01)
11.58 (<.01)
.00
.05
.02
.002
1.36 (p=.257)
.05 (.961)
10.59 (<.01)
11.53 (<.01)
1.64 (.102)
.64 (.520)
.34**
.06♮
.01
.07**
.005**
7.17 (p<.01)
0.20 (.839)
10.65 (<.01)
11.60 (<.01)
1.85 (.065)
0.41 (.684)
2.68 (<.01)
Note. ♮p < .10, *p ≤ .05, **p ≤ .01.

12. Association between ICT use and psychological well-being in each age group
Predictors
50 – 59 (N=406)
(N=507)
75 & above (N=161) β
t (p)
Education
Self-rated health
Finance
ICT use
∆R2 ∆F
-.02
.30**
-.09♮
.232
30.22** (p<.01)
-0.36 (.721)
6.50 (<.01)
6.26 (<.01)
-1.80 (.073)
.07♮
.29**
.34**
.03
.316
57.89** (p<.01)
1.68 (.093)
7.27 (<.01)
8.32 (<.01)
0.68 (.497)
-.09
.28**
.35**
.14*
.292
16.08** (p<.01)
-1.28 (.202)
3.92 (<.01)
4.92 (<.01)
2.00 (.048)
Note ♮p < .10, *p ≤ .05, **p ≤ .01.

13. Mediated Moderation Age Contact with family Psychological ICT use
Well-being
Age
Contact with friends
Visiting Neighbours

14. Association between ICT use and contact with family in each age group
Predictors
50 – 59
60 -74
75 and above β
t (p) Β
Education
Self-rated health
Finance
Employment Status
ICT use
∆R2 ∆F
.01
.06
.18**
-.02
.043
3.65
(<.01)
.16 (.875)
1.09 (.276)
3.45 (<.01)
-.41 (.679)
-.34 (.737)
.05
.20**
.23**
-.05
.08♮
.166
20.64
1.01 (.312)
4.59 (<.01)
5.02 (<.01)
-1.18 (.239)
1.68 (.094)
.08
.16*
.07
.28**
.153
6.22
1.02 (.311)
2.17 (.031)
.90 (.367)
.64 (.520)
3.79 (<.01)
Note. ♮p < .10, *p ≤ .05, **p ≤ .01.

15. Moderating effect of age and frailty status on the ICT use-psychological well-being association
Reference group: robust

16. Summary of Findings
More frequent ICT use is related to better psychological well- being only among older adults aged 75 and above. This moderation was explained by more frequent contact with family members. The results above were qualified by frailty status: the age- related increase in ICT use-related well-being was observed only among those identified as frail.

17. Theoretical Contributions
Demonstrated SST dynamics and mechanisms underlying the beneficial effects of ICT use among older adults
ICT benefited PWB by facilitating contact with family members
Explained ICT benefits of older adults in terms of compensation processes in the SOC model
The old-olds and the frail are particularly likely to benefit

18. Practical Implications
Older adults are not necessarily “left behind” by macrosocial trend of technology adoption. Their well-being can be potentially enhanced by improving ICT accessibility and literacy. Limitations: cross-sectional in nature.

19. Questions & Comments Thank you for your attention!
Contact:
This work was supported by The Hong Kong Jockey Club Charities Trust.
Fang, Y., Chau, A. K. C., Wong, A., Fung, H. H., & Woo, J. (2017). Information and communicative technology use enhances psychological well-being of older adults: the roles of age, social connectedness, and frailty status. Aging & Mental Health, 1–9.