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Can Data Decide Your Health? Quality of Life Technologies Lab

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The talk details:
Vlad Manea, Can Data Decide Your Health?, Future Healthcare? Human & IT & Legal Perspectives Seminar, Copenhagen, Denmark

Reference/Citation for a latest scientific paper related to this talk:
Manea, V., Wac, K., (2018). mQoL: Mobile Quality of Life Lab: From Behavior Change to QoL, Mobile Human Contributions: Opportunities and Challenges (MHC) Workshop in conjunction with ACM UBICOMP, Singapore, October 2018.

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Can Data Decide Your Health? Quality of Life Technologies Lab

  1. 1. Quality of Life Technologies Lab Universities of Geneva and Copenhagen qualityoflifetechnologies.com Quality of Life Vlad Manea PhD fellow
  2. 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. 3. Quality of Life technologies lab
  4. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 15. So, can data decide your health?
  16. 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. 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

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