Multimodal Machine Learning for Quality of Life Assessment: Throwing Data at a Problem?
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The document discusses multimodal machine learning applications for assessing quality of life, highlighting the integration of self-reported data and wearable technology in healthcare. It emphasizes the importance of understanding behavioral patterns and patient-reported outcomes in improving chronic health management. Key challenges include data privacy, reliability, and ensuring that the technology aids in meaningful health improvements.
Multimodal Machine Learning for Quality of Life Assessment: Throwing Data at a Problem?
- 1. Quality of Life Technologies Lab University of Geneva (CH) qualityoflifetechnologies.org Multimodal Machine Learning for Quality of Life Assessment Throwing Data at a Problem? Prof. Dr. Katarzyna Wac & QoL Lab ZHAW Digital Health Lab Day, September 2021
- 2. A Patient (female, 69) Type 2 Diabetes (1992) Heart attack (2014) Hip fracture & replacement (2016) Loves cooking Much (too much) food (carbs) Clinical Case
- 3. Not the Only One 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: A Systematic Analysis For The Global Burden Of Disease Study 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. Behavioural patterns Deaths Tobacco intake 18.1% Poor diet Physical inactivity 16.6% Alcohol consumption 3.5% ... {
- 4. ‘Behaviour marker’, ‘Behaviome’, If you can’t measure it, you can’t improve it. William Thomson, 1st Baron Kelvin, 1824-1907
- 5. At the Doctor’s Office 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
- 6. Sleep “During the past month, How many hours of actual sleep did you get at night”? Buysse, D. J., Reynolds III, C. F., Monk, T. H., Berman, S. R., & Kupfer, D. J. (1989). The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Research, 28(2), 193-213.
- 9. 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
- 10. 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)
- 11. *-Reported Outcomes: A New Paradigm
- 12. Assessing Quality of Life: Instruments Gill, T. M., and A. R. Feinstein. "A critical appraisal of the quality of quality-of-life measurements." Jama 272.8 (1994): 619-626. Linton M, Dieppe P, Medina-Lara, A Review of 99 self-report measures for assessing well-being in adults: exploring dimensions of well-being and developments over time, BMJ Open 2016;6:e010641 (159 instruments)
- 13. Bending the Curve Fries, J. F. (2002). Aging, natural death, and the compression of morbidity. Bulletin of the World Health Organization, 80, 245-250. Berrocal, A., Manea, V., De Masi, A., Wac, K. mQoL-Lab: Step-by-Step Creation of a Flexible Platform to Conduct Studies Using Interactive, Mobile, Wearable and Ubiquitous Devices, MobiSPC 2020 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 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 ✓ { { { { mQoL-Lab Computational Modelling Self-management & Behaviour Change Facilitation 1000+ Participants (mQoL Living Lab) mqol.unige.ch 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. www.qol.unige.ch TechROs PROs
- 14. mQoL-Lab: Multimodal Machine Learning Modalities Baltrušaitis, T., Ahuja, C., & Morency, L. P. (2018). Multimodal machine learning: A survey and taxonomy. IEEE transactions on pattern analysis and machine intelligence, 41(2), 423-443. Wilson, I. B., & Cleary, P. D. (1995). Linking clinical variables with health-related quality of life: a conceptual model of patient outcomes. JAMA, 273(1), 59-65. TechROs PROs Body/Face Voice Content (or ClinRo PerfRO TechRO)
- 15. The Bigger Picture qualitative summary Open Access Book supported by
- 16. mQoL-Lab: Multimodal Machine Learning Modalities Wilson, I. B., & Cleary, P. D. (1995). Linking clinical variables with health-related quality of life: a conceptual model of patient outcomes. JAMA, 273(1), 59-65. Baltrušaitis, T., Ahuja, C., & Morency, L. P. (2018). Multimodal machine learning: A survey and taxonomy. IEEE transactions on pattern analysis and machine intelligence, 41(2), 423-443. TechROs
- 17. 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. Wulfovich, S., Buur, J., Wac, K. (2021). Unfolding The Quantification Of Quality Of Life, Chapter in: Quantifying Quality of Life, Series: Health Informatics, Springer Nature, Cham, Switzerland. Wac, K. (2018). From Quantified Self to Quality of Life, Chapter in: Digital Health: Health Informatics, Springer Nature, Dordrecht, the Netherlands. mQoL-Lab: Multimodal Machine Learning Modalities
- 18. mQoL-Lab: Multimodal Machine Learning Modalities 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. Wulfovich, S., Buur, J., Wac, K. (2021). Unfolding The Quantification Of Quality Of Life, Chapter in: Quantifying Quality of Life, Series: Health Informatics, Springer Nature, Cham, Switzerland. Wac, K. (2018). From Quantified Self to Quality of Life, Chapter in: Digital Health: Health Informatics, Springer Nature, Dordrecht, the Netherlands.
- 19. mQoL-Lab: Multimodal Machine Learning Modalities 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. Wulfovich, S., Buur, J., Wac, K. (2021). Unfolding The Quantification Of Quality Of Life, Chapter in: Quantifying Quality of Life, Series: Health Informatics, Springer Nature, Cham, Switzerland. Wac, K. (2018). From Quantified Self to Quality of Life, Chapter in: Digital Health: Health Informatics, Springer Nature, Dordrecht, the Netherlands.
- 20. Timescale of Targets Wac, K. (2021). The Future Of Quantifying Behaviors, Health And Quality Of Life, Chapter in: Quantifying Quality of Life, Series: Health Informatics, Springer Nature, Cham, Switzerland.
- 22. 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. Current State of the Research Can it Work? Maybe.
- 24. ↗ Opportunities ▪ Approach ▫ Passive (vs. active reporting) ▫ Individual (vs. population-based) ▫ Holistic (vs. fragmented) ▫ In-situ/in-context (vs. in the lab) ▫ Long-term (short-term) ▫ Collaborative (vs. CS-only) ▪ Meaningful, actionable, high resolution (if needed) knowledge ▪ Future: better (self-) care → long-term QoL How Can Our Research Help Others? ↘ Challenges ▪ Human factors ▫ “I just want my life back” (S111) ▫ What matters for the patient? ▫ vs. sensitivity of feedback ▪ Data privacy, security ▫ Trust in service providers ▫ Data ownership ▫ → EPR integration ▪ Data quality, accuracy, reliability ▫ Meaningful data analysis ▫ Safety & Quality of care ▪ Where is the evidence Wac., K. (2020). Quality of Life Technologies. In: Gellman M.D., Turner J.R. (eds) Encyclopedia of Behavioral Medicine. Springer, New York, NY. Rivas, H. and Wac, K. (Eds.) (2018). Digital Health, Series: Health Informatics, Springer Nature, Dordrecht, the Netherlands. Wac, K. Wulfovich, S. (Eds.) (2021). Quantifying Quality of Life - Incorporating Daily Life into Medicine, Series: Health Informatics, Springer Nature, Dordrecht, the Netherlands.
- 25. Quality of Life Technologies Lab University of Geneva & University of Copenhagen qol.unige.ch welcoming collaborations Prof. Dr. Katarzyna Wac & The QoL Team Quality of Life, Center for Informatics, University of Geneva, Switzerland 2021