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Quality of Life Technologies Lab
University of Geneva (CH) & University of Copenhagen (DK)
qualityoflifetechnologies.org
coQoL Approach
coCalibrating Physical and Psychological Outcomes
& Consumer Wearable Activity Outcomes
Prof. Katarzyna Wac & QoL Team
ISOQOL Conference, October 2020
PLENARY SESSION: “Video killed the radio star”: How technology is changing the way we collect, analyze and interpret patient-relevant data
Sources & Types of Outcomes
Mayo, N. E., Figueiredo, S., Ahmed, S., & Bartlett, S. J. (2017). Montreal Accord on Patient-Reported Outcomes (PROs) use series–Paper 2: Terminology proposed to measure what matters in health. Journal of clinical epidemiology, 89, 119-124.
TechROs
PROs
Currently...
3~6 months
The Big
Picture
Dey, A. K., Wac, K., Ferreira, D., Tassini, K., Hong, J. H., & Ramos, J. (2011). Getting closer: An Empirical Investigation Of The Proximity Of User To Their Smart Phones. In Proceedings of the ACM UBICOMP.
Smartphone 88%
of the time
next to us
Wac, K. (2018). From Quantified Self to Quality of Life, Chapter in: Digital Health: Scaling Healthcare to the World, Series: Health Informatics, Springer Nature, Dordrecht, the Netherlands.
Annotated wearables dataset https://doi.org/10.6084/m9.figshare.9702122
Smartphone
& Wearables
438 wearables (2018)
Future...
Bending the Curve
Wac, K., Fiordelli, M., Gustarini, M., & Rivas, H. (2015). Quality of life technologies: Experiences from the field and key challenges.
IEEE Internet Computing, 19(4), 28-35.
Fries, J. F. (2002). Aging, natural death, and the compression of morbidity. Bulletin of the World Health Organization, 80, 245-250.
QoL Domains QoL Facets (13/24)
Physical
health
Activities of daily living ✓
Dependence on medicinal substances and medical aids
Energy and fatigue ✓
Mobility ✓
Pain and discomfort ✓
Sleep and rest ✓
Work capacity
Psychological
health
Bodily image and appearance
Negative feelings ✓
Positive feelings ✓
Self-esteem
Spirituality / Religion / Personal beliefs ✓
Thinking, learning, memory, and concentration
Social
relationships
Personal relationships ✓
Social support ✓
Sexual activity
Environment
Financial resources
Freedom, physical safety, and security ✓
Health and social care: accessibility, and quality
Home environment
Opportunities for acquiring new information and skills
Participation in and opportunities for recreation / leisure activities
Physical environment (pollution / noise / traffic / climate) ✓
Transport ✓
{
{
{
{
Computational
Models
Self-management &
Behaviour Change
Facilitation
World Health Organization | www.who.int
“The World Health Organization Quality of Life Assessment (WHOQOL): development and general
psychometric properties.,” Soc. Sci. Med., vol. 46, no. 12, pp. 1569–85, Jun. 1998.
TechROs
PROs
The Momentary Co-calibration (ML-based)
Gustarini, M., Scipioni, M., Fanourakis, M., Wac, K. (2016). Differences in Smartphone Usage: Validating, Evaluating, and Predicting Mobile User Intimacy, Pervasive and Mobile Computing (PMC), Elsevier.
Ciman, M., Wac, K., (2018). Individuals’ Stress Assessment Through Human-Smartphone Interaction Analysis, IEEE Transactions on Affective Computing (IEEE TAC), 9(1): 51-65.
Ciman, M., Wac, K. (2019). Smartphones as Sleep Duration Sensors: Validation of the iSenseSleep Algorithm, JMIR mhealth and uhealth, Vol 7, No 5.
TechROs
ON/OFF
coQoL
Approach
CoQoL
2018
S169
69yo, female, HU
disease (HTN)
mid-2018 winter
2018/2019
mid-2019
steps: 8035
active: 300 min
sleep: 7h06m
steps: 6760
active: 273 min
sleep: 8h08m
steps: 8172
active: 294 min
sleep: 7h03m
Nutrition: 7
PSQI: 15
MSPSS: 5
GADS: 68
EQ5D-health: 80
Nutrition: 5
PSQI: 15
MSPSS: 5
GADS: 51
EQ5D-health: 75
Nutrition: 7
PSQI: 14
MSPSS: 5
GADS: 47
EQ5D-health: 80
Manea, V., Wac, K. (2020). Co-calibrating Physical and Psychological Outcomes and Consumer Wearable Activity Outcomes in Older Adults: An Evaluation of the Co-QoL Method. Journal of Personalized Medicine, MDPI (under revision)
Step 1
Step 2
Step 3
Step 4
Step 5
CoQoL
Manea, V., Wac, K. (2020). Co-calibrating Physical and Psychological Outcomes and Consumer Wearable Activity Outcomes in Older Adults: An Evaluation of the Co-QoL Method. Journal of Personalized Medicine, MDPI (under revision)
coQoL:
Social
Support
(MSPSS)
Manea, V., Wac, K. (2020). Co-calibrating Physical and Psychological Outcomes and Consumer Wearable Activity Outcomes in Older Adults: An Evaluation of the Co-QoL Method. Journal of Personalized Medicine, MDPI (under revision)
N=39, 18 healthy, 26F, 70±7yo
MSPSS: moderate vs. 2 years of TechRO data
Manea, V., Wac, K. (2020). Co-calibrating Physical and Psychological Outcomes and Consumer Wearable Activity Outcomes in Older Adults: An Evaluation of the Co-QoL Method. Journal of Personalized Medicine, MDPI (under revision)
Spearman correlations rs
> 0.5
healthy participants
family and friends
diseased participants
significant other
N=39, 18 healthy, 26F, 70±7yo
MSPSS: moderate vs. 2 years of TechRO data
coQoL:
Negative
Feelings,
Anxiety
(GADS)
Manea, V., Wac, K. (2020). Co-calibrating Physical and Psychological Outcomes and Consumer Wearable Activity Outcomes in Older Adults: An Evaluation of the Co-QoL Method. Journal of Personalized Medicine, MDPI (under revision)
N=39, 18 healthy, 26F, 70±7yo
GADS: possible/mild vs. 2 years of TechRO data
Manea, V., Wac, K. (2020). Co-calibrating Physical and Psychological Outcomes and Consumer Wearable Activity Outcomes in Older Adults: An Evaluation of the Co-QoL Method. Journal of Personalized Medicine, MDPI (under revision)
Spearman correlations rs
> 0.5
healthy participants
lost interest in things
diseased participants
worrying a lot
N=39, 18 healthy, 26F, 70±7yo
GADS: possible/mild vs. 2 years of TechRO data
Human Factors:
What about
the
Individual?
Human Factors
Study details
N = 200 participants (US)
Affinity clustering of significant factors
Q: Do you use technologies (smartphone/wearable) for your own health/care?
Wac, K., Rivas, H., & Fiordelli, M. (2016). Use and misuse of mobile health information technologies for health self-management. Annals of Behavioral Medicine, 50 (Supplement 1).
Wac, K. et al., (2019). “I Try Harder”: The Design Implications for Mobile Apps and Wearables Contributing to Self-Efficacy of Patients with Chronic Conditions, Frontiers in Psychology, SI: Improving Wellbeing in Patients with Chronic Conditions.
coQoL
Can it Work?
Maybe.
Quality of Life Technologies Lab
qualityoflifetechnologies.org
...welcoming collaborations
Prof. Katarzyna Wac and the QoL Team
Quality of Life, Center for Informatics, University of Geneva, Switzerland
Human-Centered Computing, University of Copenhagen, Denmark
katarzyna.wac@unige.ch
2021

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coQoL Approach: coCalibrating Physical and Psychological Outcomes & Consumer Wearable Activity Outcomes

  • 1. Quality of Life Technologies Lab University of Geneva (CH) & University of Copenhagen (DK) qualityoflifetechnologies.org coQoL Approach coCalibrating Physical and Psychological Outcomes & Consumer Wearable Activity Outcomes Prof. Katarzyna Wac & QoL Team ISOQOL Conference, October 2020 PLENARY SESSION: “Video killed the radio star”: How technology is changing the way we collect, analyze and interpret patient-relevant data
  • 2. Sources & Types of Outcomes Mayo, N. E., Figueiredo, S., Ahmed, S., & Bartlett, S. J. (2017). Montreal Accord on Patient-Reported Outcomes (PROs) use series–Paper 2: Terminology proposed to measure what matters in health. Journal of clinical epidemiology, 89, 119-124. TechROs PROs
  • 5. Dey, A. K., Wac, K., Ferreira, D., Tassini, K., Hong, J. H., & Ramos, J. (2011). Getting closer: An Empirical Investigation Of The Proximity Of User To Their Smart Phones. In Proceedings of the ACM UBICOMP. Smartphone 88% of the time next to us
  • 6. Wac, K. (2018). From Quantified Self to Quality of Life, Chapter in: Digital Health: Scaling Healthcare to the World, Series: Health Informatics, Springer Nature, Dordrecht, the Netherlands. Annotated wearables dataset https://doi.org/10.6084/m9.figshare.9702122 Smartphone & Wearables 438 wearables (2018)
  • 8. Bending the Curve Wac, K., Fiordelli, M., Gustarini, M., & Rivas, H. (2015). Quality of life technologies: Experiences from the field and key challenges. IEEE Internet Computing, 19(4), 28-35. Fries, J. F. (2002). Aging, natural death, and the compression of morbidity. Bulletin of the World Health Organization, 80, 245-250. QoL Domains QoL Facets (13/24) Physical health Activities of daily living ✓ Dependence on medicinal substances and medical aids Energy and fatigue ✓ Mobility ✓ Pain and discomfort ✓ Sleep and rest ✓ Work capacity Psychological health Bodily image and appearance Negative feelings ✓ Positive feelings ✓ Self-esteem Spirituality / Religion / Personal beliefs ✓ Thinking, learning, memory, and concentration Social relationships Personal relationships ✓ Social support ✓ Sexual activity Environment Financial resources Freedom, physical safety, and security ✓ Health and social care: accessibility, and quality Home environment Opportunities for acquiring new information and skills Participation in and opportunities for recreation / leisure activities Physical environment (pollution / noise / traffic / climate) ✓ Transport ✓ { { { { Computational Models Self-management & Behaviour Change Facilitation World Health Organization | www.who.int “The World Health Organization Quality of Life Assessment (WHOQOL): development and general psychometric properties.,” Soc. Sci. Med., vol. 46, no. 12, pp. 1569–85, Jun. 1998. TechROs PROs
  • 9. The Momentary Co-calibration (ML-based) Gustarini, M., Scipioni, M., Fanourakis, M., Wac, K. (2016). Differences in Smartphone Usage: Validating, Evaluating, and Predicting Mobile User Intimacy, Pervasive and Mobile Computing (PMC), Elsevier. Ciman, M., Wac, K., (2018). Individuals’ Stress Assessment Through Human-Smartphone Interaction Analysis, IEEE Transactions on Affective Computing (IEEE TAC), 9(1): 51-65. Ciman, M., Wac, K. (2019). Smartphones as Sleep Duration Sensors: Validation of the iSenseSleep Algorithm, JMIR mhealth and uhealth, Vol 7, No 5. TechROs ON/OFF
  • 11. CoQoL
  • 12. 2018 S169 69yo, female, HU disease (HTN) mid-2018 winter 2018/2019 mid-2019 steps: 8035 active: 300 min sleep: 7h06m steps: 6760 active: 273 min sleep: 8h08m steps: 8172 active: 294 min sleep: 7h03m Nutrition: 7 PSQI: 15 MSPSS: 5 GADS: 68 EQ5D-health: 80 Nutrition: 5 PSQI: 15 MSPSS: 5 GADS: 51 EQ5D-health: 75 Nutrition: 7 PSQI: 14 MSPSS: 5 GADS: 47 EQ5D-health: 80 Manea, V., Wac, K. (2020). Co-calibrating Physical and Psychological Outcomes and Consumer Wearable Activity Outcomes in Older Adults: An Evaluation of the Co-QoL Method. Journal of Personalized Medicine, MDPI (under revision)
  • 13. Step 1 Step 2 Step 3 Step 4 Step 5 CoQoL Manea, V., Wac, K. (2020). Co-calibrating Physical and Psychological Outcomes and Consumer Wearable Activity Outcomes in Older Adults: An Evaluation of the Co-QoL Method. Journal of Personalized Medicine, MDPI (under revision)
  • 15. Manea, V., Wac, K. (2020). Co-calibrating Physical and Psychological Outcomes and Consumer Wearable Activity Outcomes in Older Adults: An Evaluation of the Co-QoL Method. Journal of Personalized Medicine, MDPI (under revision) N=39, 18 healthy, 26F, 70±7yo MSPSS: moderate vs. 2 years of TechRO data
  • 16. Manea, V., Wac, K. (2020). Co-calibrating Physical and Psychological Outcomes and Consumer Wearable Activity Outcomes in Older Adults: An Evaluation of the Co-QoL Method. Journal of Personalized Medicine, MDPI (under revision) Spearman correlations rs > 0.5 healthy participants family and friends diseased participants significant other N=39, 18 healthy, 26F, 70±7yo MSPSS: moderate vs. 2 years of TechRO data
  • 18. Manea, V., Wac, K. (2020). Co-calibrating Physical and Psychological Outcomes and Consumer Wearable Activity Outcomes in Older Adults: An Evaluation of the Co-QoL Method. Journal of Personalized Medicine, MDPI (under revision) N=39, 18 healthy, 26F, 70±7yo GADS: possible/mild vs. 2 years of TechRO data
  • 19. Manea, V., Wac, K. (2020). Co-calibrating Physical and Psychological Outcomes and Consumer Wearable Activity Outcomes in Older Adults: An Evaluation of the Co-QoL Method. Journal of Personalized Medicine, MDPI (under revision) Spearman correlations rs > 0.5 healthy participants lost interest in things diseased participants worrying a lot N=39, 18 healthy, 26F, 70±7yo GADS: possible/mild vs. 2 years of TechRO data
  • 21. Human Factors Study details N = 200 participants (US) Affinity clustering of significant factors Q: Do you use technologies (smartphone/wearable) for your own health/care? Wac, K., Rivas, H., & Fiordelli, M. (2016). Use and misuse of mobile health information technologies for health self-management. Annals of Behavioral Medicine, 50 (Supplement 1). Wac, K. et al., (2019). “I Try Harder”: The Design Implications for Mobile Apps and Wearables Contributing to Self-Efficacy of Patients with Chronic Conditions, Frontiers in Psychology, SI: Improving Wellbeing in Patients with Chronic Conditions.
  • 23. Quality of Life Technologies Lab qualityoflifetechnologies.org ...welcoming collaborations Prof. Katarzyna Wac and the QoL Team Quality of Life, Center for Informatics, University of Geneva, Switzerland Human-Centered Computing, University of Copenhagen, Denmark katarzyna.wac@unige.ch 2021