M-HEALTH APPS AND SELF-QUANTIFICATION TECHNOLOGIES ON THE RISE. OPPORTUNITIES AND RISKS FOR USE IN PRACTICE

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M-HEALTH APPS AND SELF-QUANTIFICATION TECHNOLOGIES ON THE RISE. OPPORTUNITIES AND RISKS FOR USE IN PRACTICE Presentation at the WFOT Congress May 23 rd 2018 Ursula Meidert & Heidrun Becker Institute of Occupational Therapy Mandy Scheermesser Institute of Physical Therapy Zurich Universities of Applied Sciences and Arts 1

Research Questions What is the current state and what are future trends in self-quantification technologies? What are opportunities and risks for practice? What recommendations can be made? 2

Methods Extensive Literature review 19 expert interviews from the fields of health care, economy, society, technology, law and ethics 3 focus groups with healthy and chronically ill users and health professionals Online survey with >1000 participants Workshop to assess risks and opportunities 3

Results: Self-Quantification with Wearables 4

and Apps 5

How Self-Quantification Applications Work Mobile Apps Bit Data Quantified Self Visuali sation Sensors Gami fication 6

What is Measured? Consumption Body functions Activities Symptoms Mobility Psychological parameters Physiological parameters Source: spektrum.de 7

Future Trends Increasing dissemination of products Improved quality of content and data Development of ancillary equipment (home lab) Certification of products for the health sector Improved data protection Facilitated integration of client data in e-records Increased use in research and practice 8

Opportunities (1/2) Diagnostics and therapy: Continuous measurement and automatic alerting systems Improved disease- and health-management Interventions and evaluation Body awareness: Reflection of own behaviour and support of behaviour change Administration and documentation: Data can be transferred into electronic patient files 9

Opportunities (2/2) Prevention: Health literacy and information about health & healthy lifestyle Early detection of problematic behaviour or measures Motivation: Easy-to-understand visualisation of own data Active participation of patient in diagnostics and therapy Support of self-efficacy Gamification elements are motivating and support compliance Zurich Universities of Applied Sciences and Arts 10

Risks Data protection: Data is often not protected (cloud-storage, unencrypted transfer), used for other purposes or sold to third parties Quality: Apps often have poor content quality Tracker and apps often provide unreliable data Discrimination tendencies: Risk of discrimination through increased transparency (health- or life-insurances, employers) Loss of skills and perception: De-skilling : loss of skills through use of technology Perception of the body can change 11

Recommendation for Practice Data can be used in practice for educational purposes, evaluation and motivation Person-technology-match is important Seek out recommendations from consumer-, patient- or professional organisations Read terms and conditions, check data protection policy If possible use apps from reliable sources (health care sector) or which are approved as medical devices 12

Produkte für ET und PT AOTA Database of Apps for Practice Source: https://www.aota.org/ 13

Project Team ZHAW School of Health Professions Prof. Dr. Heidrun Becker Ursula Meidert Mandy Scheermesser ZHAW School of Management and Law Stefan Hegyi Yvonne Prieur ZHAW School of Engineering Prof. Dr. Kurt Stockinger Gabriel Eyyi IZT-Institute for Futures Studies and Technology Assessment Michaela Evers-Wölk Mattis Jacobs Britta Oertel 14

Thank you for your attention! Contact: ursula.meidert@zhaw.ch Project website: www.zhaw.ch/gesundheit/quantified-self 15