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Quality of Life Technologies Lab
Universities of Geneva and Copenhagen
qualityoflifetechnologies.com
Quality of Life
Vlad Manea
PhD fellow
Vlad Manea
PhD fellow
University of Copenhagen
Department of Computer Science
Quality of Life Technologies Lab
Linkedin: https://www.linkedin.com/in/vladmanea
Twitter: https://twitter.com/vladmanea
Email: manea@di.ku.dk
Quality of Life technologies lab
Quality of Life
Individuals’ perception of their
position in life in the context of the
culture and value systems in which
they live and in relation to their goals,
expectations, standards, and
concerns
Abbreviated as QoL
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.
From QoL facets...
World Health Organization | www.who.int
Activities of daily living
Dependence on medicinal substances and medical aids
Energy and fatigue
Mobility
Pain and discomfort
Sleep and rest
Work capacity
Bodily image and appearance
Negative feelings
Positive feelings
Self-esteem
Spirituality / Religion / Personal beliefs
Thinking, learning, memory, and concentration
Personal relationships
Social support
Sexual activity
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
Physical environment (pollution / noise / traffic / climate)
Transport
From QoL facets to behaviors...
World Health Organization | www.who.int
Activities of daily living
Dependence on medicinal substances and medical aids
Energy and fatigue
Mobility
Pain and discomfort
Sleep and rest
Work capacity
Bodily image and appearance
Negative feelings
Positive feelings
Self-esteem
Spirituality / Religion / Personal beliefs
Thinking, learning, memory, and concentration
Personal relationships
Social support
Sexual activity
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
Physical environment (pollution / noise / traffic / climate)
Transport
From QoL facets to behaviors to health risks
Behavioral patterns Deaths
Tobacco intake 18.1%
Poor diet
Physical inactivity
16.6%
Alcohol consumption 3.5%
...
}Naghavi, M., Abajobir, A. A., Abbafati, C., Abbas, K. M., Abd-Allah, F., Abera, S. F., ... & Ahmadi, A. (2017). Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016 [...]. The Lancet, 390 (10100), 1151-1210.
Mokdad, A. H., Marks, J. S., Stroup, D. F., & Gerberding, J. L. (2004). Actual causes of death in the United States, 2000. JAMA, 291 (10), 1238-1245.
}
From behavior modeling...
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.
Daily life
monitoring
Behavioral patterns
Tobacco intake
Poor diet
Physical inactivity
Alcohol consumption
...
{ Computational
models
Self-management
Behavior change
facilitation
Improved QoLMedical
evidence
QoL living lab
1000+ participants
6B+ data points
From behavior modeling to risk assessment
Laghouila, S., Manea, V., Estrada, V., Wac, K. (2018). Digital Health Tools for Chronic Illness and Dementia Risk Assessment in Older Adults, 39th Annual Meeting and Scientific Sessions of the Society of Behavioral Medicine (SBM 2018), USA, 2018
Research study details
Exploratory analysis of behaviors: physical activity
N = 13 participants, aged 65+, enrolled for 6+ months, located in Spain and Hungary
Recommendation: 10K steps 3 times
per week or face chronic disease risk.
Reality: less than half met this threshold;
adjusted physical activity to 3K, 5K, 7K steps.
From behavior modeling to risk assessment
Laghouila, S., Manea, V., Estrada, V., Wac, K. (2018). Digital Health Tools for Chronic Illness and Dementia Risk Assessment in Older Adults, 39th Annual Meeting and Scientific Sessions of the Society of Behavioral Medicine (SBM 2018), USA, 2018
Research study details
Exploratory analysis of behaviors: sleep
N = 13 participants, aged 65+, enrolled for 6+ months, located in Spain and Hungary
Recommendation: 7 to 8 hours of sleep
or face chronic disease risk.
Reality: only half of the participants meet the
recommendations, many sleep under 7h
If you continue like this [...]
Planned research
Future behavior model simulation by leveraging a large dataset (N = 10K
participants, 3 years of participation) and deep neural networks: gated
recurrent units (GRU) and long short-term memory (LSTM) for time series, and
variational autoencoders (VAE) and generative adversarial networks (GAN) as
frameworks for behavior generation.
Mobile QoL Lab
bit.ly/mobileQoLlab
Manea, V., & Wac, K. (2018). mQoL: Mobile Quality of Life Lab: From Behavior Change to QoL.Mobile Human Contributions: Workshop in conjunction with ACM UBICOMP, Singapore, October 2018.
ResearchKit, Informed Consent | http://researchkit.org/docs/docs/InformedConsent/InformedConsent.html
HealthKit, Access to Health Data | https://developer.apple.com/design/human-interface-guidelines/healthkit/overview/introduction/
A mobile informed consent...
Study elements
Terms review Data privacyDigital signature
A mobile informed consent in the big picture
Freedom from harm or disadvantage
Anonymity
Right to withdrawConfidentiality
Informed consent
1. Addressing relevant question
2. Choice of control and standard of care
3. Choice of study design
4. Choice of subject population
5. Potential benefits and harms
6. Informed consent
7. Community engagement
8. Return of research results
9. Management of incidental findings
10. Post-trial access
11. Payment for participation
12. Study-related injury
{
UCD Teaching and Learning, Key Ethical Issues | http://www.ucd.ie/teaching/resources/researchintoteaching/ethicalapprovalexpemption/
MRCT Harvard, Essential Elements of Ethics | https://globalhealthtrainingcentre.tghn.org/site_media/media/medialibrary/2014/10/EssentialElementsofEthics.pdf
So, can data decide your health?
We think not
Indeed, data can show evidence of health and risks
Otherwise, we would never know
However, behaviors ultimately decide health
Over long periods of time
Quality of Life Technologies Lab
Universities of Geneva and Copenhagen
qualityoflifetechnologies.com
Thank You
Vlad Manea
manea@di.ku.dk
Research funded by the Horizon 2020 WellCo project at wellco-project.eu. Images from unsplash.com. Presentation also available at http://bit.ly/CanDataDecideYourHealthVladManeaQoLTechLab

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Can Data Decide Your Health? Quality of Life Technologies Lab

  • 1. Quality of Life Technologies Lab Universities of Geneva and Copenhagen qualityoflifetechnologies.com Quality of Life Vlad Manea PhD fellow
  • 2. Vlad Manea PhD fellow University of Copenhagen Department of Computer Science Quality of Life Technologies Lab Linkedin: https://www.linkedin.com/in/vladmanea Twitter: https://twitter.com/vladmanea Email: manea@di.ku.dk
  • 3. Quality of Life technologies lab
  • 4. Quality of Life Individuals’ perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards, and concerns Abbreviated as QoL 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.
  • 5. From QoL facets... World Health Organization | www.who.int Activities of daily living Dependence on medicinal substances and medical aids Energy and fatigue Mobility Pain and discomfort Sleep and rest Work capacity Bodily image and appearance Negative feelings Positive feelings Self-esteem Spirituality / Religion / Personal beliefs Thinking, learning, memory, and concentration Personal relationships Social support Sexual activity 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 Physical environment (pollution / noise / traffic / climate) Transport
  • 6. From QoL facets to behaviors... World Health Organization | www.who.int Activities of daily living Dependence on medicinal substances and medical aids Energy and fatigue Mobility Pain and discomfort Sleep and rest Work capacity Bodily image and appearance Negative feelings Positive feelings Self-esteem Spirituality / Religion / Personal beliefs Thinking, learning, memory, and concentration Personal relationships Social support Sexual activity 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 Physical environment (pollution / noise / traffic / climate) Transport
  • 7. From QoL facets to behaviors to health risks Behavioral patterns Deaths Tobacco intake 18.1% Poor diet Physical inactivity 16.6% Alcohol consumption 3.5% ... }Naghavi, M., Abajobir, A. A., Abbafati, C., Abbas, K. M., Abd-Allah, F., Abera, S. F., ... & Ahmadi, A. (2017). Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016 [...]. The Lancet, 390 (10100), 1151-1210. Mokdad, A. H., Marks, J. S., Stroup, D. F., & Gerberding, J. L. (2004). Actual causes of death in the United States, 2000. JAMA, 291 (10), 1238-1245. }
  • 8. From behavior modeling... 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. Daily life monitoring Behavioral patterns Tobacco intake Poor diet Physical inactivity Alcohol consumption ... { Computational models Self-management Behavior change facilitation Improved QoLMedical evidence QoL living lab 1000+ participants 6B+ data points
  • 9. From behavior modeling to risk assessment Laghouila, S., Manea, V., Estrada, V., Wac, K. (2018). Digital Health Tools for Chronic Illness and Dementia Risk Assessment in Older Adults, 39th Annual Meeting and Scientific Sessions of the Society of Behavioral Medicine (SBM 2018), USA, 2018 Research study details Exploratory analysis of behaviors: physical activity N = 13 participants, aged 65+, enrolled for 6+ months, located in Spain and Hungary Recommendation: 10K steps 3 times per week or face chronic disease risk. Reality: less than half met this threshold; adjusted physical activity to 3K, 5K, 7K steps.
  • 10. From behavior modeling to risk assessment Laghouila, S., Manea, V., Estrada, V., Wac, K. (2018). Digital Health Tools for Chronic Illness and Dementia Risk Assessment in Older Adults, 39th Annual Meeting and Scientific Sessions of the Society of Behavioral Medicine (SBM 2018), USA, 2018 Research study details Exploratory analysis of behaviors: sleep N = 13 participants, aged 65+, enrolled for 6+ months, located in Spain and Hungary Recommendation: 7 to 8 hours of sleep or face chronic disease risk. Reality: only half of the participants meet the recommendations, many sleep under 7h
  • 11. If you continue like this [...] Planned research Future behavior model simulation by leveraging a large dataset (N = 10K participants, 3 years of participation) and deep neural networks: gated recurrent units (GRU) and long short-term memory (LSTM) for time series, and variational autoencoders (VAE) and generative adversarial networks (GAN) as frameworks for behavior generation.
  • 12. Mobile QoL Lab bit.ly/mobileQoLlab Manea, V., & Wac, K. (2018). mQoL: Mobile Quality of Life Lab: From Behavior Change to QoL.Mobile Human Contributions: Workshop in conjunction with ACM UBICOMP, Singapore, October 2018.
  • 13. ResearchKit, Informed Consent | http://researchkit.org/docs/docs/InformedConsent/InformedConsent.html HealthKit, Access to Health Data | https://developer.apple.com/design/human-interface-guidelines/healthkit/overview/introduction/ A mobile informed consent... Study elements Terms review Data privacyDigital signature
  • 14. A mobile informed consent in the big picture Freedom from harm or disadvantage Anonymity Right to withdrawConfidentiality Informed consent 1. Addressing relevant question 2. Choice of control and standard of care 3. Choice of study design 4. Choice of subject population 5. Potential benefits and harms 6. Informed consent 7. Community engagement 8. Return of research results 9. Management of incidental findings 10. Post-trial access 11. Payment for participation 12. Study-related injury { UCD Teaching and Learning, Key Ethical Issues | http://www.ucd.ie/teaching/resources/researchintoteaching/ethicalapprovalexpemption/ MRCT Harvard, Essential Elements of Ethics | https://globalhealthtrainingcentre.tghn.org/site_media/media/medialibrary/2014/10/EssentialElementsofEthics.pdf
  • 15. So, can data decide your health?
  • 16. We think not Indeed, data can show evidence of health and risks Otherwise, we would never know However, behaviors ultimately decide health Over long periods of time
  • 17. Quality of Life Technologies Lab Universities of Geneva and Copenhagen qualityoflifetechnologies.com Thank You Vlad Manea manea@di.ku.dk Research funded by the Horizon 2020 WellCo project at wellco-project.eu. Images from unsplash.com. Presentation also available at http://bit.ly/CanDataDecideYourHealthVladManeaQoLTechLab