App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie?
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App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? Prof. Dr. Tobias Kowatsch Assistant Professor for Digital Health, University of St.Gallen, Switzerland Scientific Director, Centre for Digital Health Interventions, ETH Zurich & University of St.Gallen, Switzerland Lead Principal Investigator, Mobile Health Interventions, Singapore-ETH Centre, Singapore Partner, Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, USA Member, Competence Centre for Rehabilitation Engineering and Science, ETH Zurich, Switzerland Psychiatrische Universitätsklinik Zürich | 12. März 2021 | 11:00 – 12:30 Uhr
Who we are Center Leadership Assist. Prof. Dr. Tobias Kowatsch Advisory Board Olivia Clare Keller, MSc Matthias Heuberger, MA Prof. Dr. Elgar Fleisch Prof. Lisa A. Marsch, PhD Postdoctoral Researcher Prof. Dr. Urte Scholz Prof. Dr. Florian v. Wangenheim Dr. Filipe Barata, Head of AI & Digital Biomarker Research Dr. med. Thomas Züger, Diabetes Technology Jacqueline Mair, PhD, Behavioral and Exercise Sciences Alicia Salamanca, PhD, Clinical Psychology Doctoral Students Alina Aishah Caterina George David Christoph Robert Roman Vera Yanick Marcia Joseph Dominik Theresa Gisbert Jiali Asisof Alattas Bérubé Boateng Cleres Gross Jakob Keller Lehmann Lukic Nißen Ollier Rüegger Schachner Teepe Yao MobileCoach Team Student Research Assistants, Master & Bachelor Students and many more… P. Santhanam F. Schneider S. Harperink S. Ultsch Aliena Mutter Z. Kovac T. Tarantini M. Rauch B. Frese T. Stauffer S. Jokić Software Engineer Software Engineer St.Res.Assist. MA Student MA Student MA Student MA Student MA Student MA Student MA Student BA Student Folie 2 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
What we do SNF Digital Future Health CSS Health / PEACH Technologies Personality Health Lab Project Singapore Development Respiratory & Cardiavascular CAS in Prevention of Diseases & Mental Digital Health Depression & Health for Executives Type-2 Diabetes (coming in 2022) Open-Source Education Software MobileCoach NIH The Sweetgoals Research Digital Pill USA Book Type-1 Diabetes Open Research Startups Data Resmonics Respiratory InnoSuisse SNF SNF Conditions CAir HEADWIND DyMand Pathmate COPD Type-1 Type-2 Altoida Chronic Diabetes Alzheimer Disease Diabetes Coach … and much more Folie 3 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Our research partners Folie 4 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Funding Folie 5 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Was sind digitale Pillen? Digital Pillen sind digitale Gesundheitsanwendungen, Web- oder App-basiert, welche entweder verschreibungspflichtig sind („das ist ganz neu“) oder frei bzw. käuflich erhältlich sind („das kennt jeder“).
Braucht es denn evidenzbasierte digitale Pillen aus Ihrer Sicht? Den Umfrage-Link finden Sie im Zoom-Chat oder hier:
App on Prescription in the U.S. December 2018 Prescription Digital Therapeutics, or PDTs, are software-based disease treatments. PDTs are designed to directly treat disease, tested for safety and efficacy in randomized clinical trials, evaluated by the FDA, and prescribed by healthcare providers. https://peartherapeutics.com Folie 9 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
App on Prescription in Germany diga.bfarm.de/de Folie 10 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
App on Prescription in Germany diga.bfarm.de/de Folie 11 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
App on Prescription in Germany diga.bfarm.de/de Folie 12 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
App on Prescription in Germany diga.bfarm.de/de Folie 13 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
App on Prescription in Germany diga.bfarm.de/de Folie 14 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Example: deprexis https://diga.bfarm.de/de/verzeichnis/450 Folie 15 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Ein Schritt zurück: Vom fertigen Produkt in die Forschung. Was könnte denn eine digitale Wunsch-Pille leisten?
Anatomie einer digitalen Pille Example Distal Quality of Life Outcome Evidence- based knowledge Proximal Stress Physical activity Diet Behavior Outcomes management Digital Pill 1. Vulnerability 2. Receptivity 3. Support Folie 17 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Sensing & Support for People with Depression https://www.c4dhi.org/projects/kti-moss/
Mobile Sensing and Support for People With Depression: A Pilot Trial in the Wild Wahle F, Kowatsch T, Fleisch E, Rufer M,Weidt S (2016) Mobile Sensing and Support for People With Depression: A Pilot Trial in the Wild JMIR Mhealth Uhealth 2016;4(3):e111 doi: 10.2196/mhealt h.5960 Note: cognitive behavioral therapy (CBT) Folie 19 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Sensing Stress at the Workplace with the help of a PC mouse Objective Development of an early warning system that is able to detect (chronic) stress, burnout or even depression
Visual Results of the lab experiment (N=18) Subject was relaxed (Square Task 1) Subject was stressed (Square Task 2) Kowatsch, T., Wahle, F., Filler, A., Design and Lab Experiment of a Stress Detection Service based on Mouse Movements, The 11th Mediterranean Conference on Information Systems (MCIS), Genoa, Italy ***Best Paper Award*** https://www.c4dhi.org/projects/jsiss/ Banholzer, N., Feuerriegel, S., Fleisch, E., Bauer, G., Kowatsch, T. (in press) Computer mouse movements as a scalable detector of work stress: A longitudinal observational field study, Journal of Medical Internet Research. Folie 21 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Health literacy intervention for children with asthma www.c4dhi.org/projects/health-literacy-children-asthma/
Interaction with MAX Smartphone Family Member SMS SMS, phone call face-to-face or face-to-face MAX Digital Health Assistant eMail Chat with MAX Asthma Expert App chat with expert Patient Web-based cockpit or face-to-face Mobile App Folie 23 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Inhalation Assessment of Norah, 12 Informed consent was received from patient and parent to use video, name and age for presentation purposes 1. Video recording by family member 2. Expert rating 3. Feedback to Norah 1 + Automated feedback generation based on inhalation guidelines Folie 24 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Main results of the pilot study 1. The average adherence rate of 49 subjects was 80.4%. 2. The result of a pre-post test shows that asthma knowledge was improved significantly with a large effect size (d=0.9). 3. On average, 1 inhalation mistake was identified in each video clip; 3 serious inhalation mistakes could be directly addressed and eliminated by the experts’ feedback in this trial. Kowatsch, T., Schachner, T., Harperink, S., Barata, F., Dittler, U., Xiao, G., Stanger, C., Oswald, H., Fleisch, E., von Wangenheim, F., Möller, A. (2021) Conversational Agents as Mediating Social Actors in Chronic Disease Management Involving Health Care Professionals, Patients, and Family Members: Multisite Single-Arm Feasibility Study, Journal of Medical Internet Research (JMIR) 23(2):e25060 10.2196/25060. Folie 25 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
One asthma expert received a lovely “Thank You” post card from a young patient after the intervention Folie 26 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
One asthma expert received a lovely “Thank You” post card from a young patient after the intervention Folie 27 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Den Umfrage-Link finden Sie im Zoom-Chat oder hier:
Design of a prognostic digital biomarker for asthma control https://www.c4dhi.org/projects/css-mobile-asthma-companion/
Overview of the asthma study with Clara https://vimeo.com/258412196 Folie 30 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Results of the study Response rate to daily self-reported asthma control tests of 93 participants: 97.3% (2487 / 2557 self-reports) Paper N subjects N coughs Vizel et al. 2010 12 n/a McGuiness et al. 2012 10 n/a Casaseca-de-La-Higuera et al. 2015 9 n/a Monge-Alvarez et al. 2018 13 n/a Swarnkar et al. 2013 3 342 Amoh et al. 2016 14 627 Birring et al. 2008 15 1.836 Barry et al. 2006 15 2.000 Amrulloh et al. 2015 24 2.090 Drugman et al. 2011 22 2.304 Liu et al. 2014 20 2.549 Larson et al. 2011 17 2.558 Coyle et al. 2005 8 3.645 Klco et al. 2018 18 5.200 Kadambi et al 2018 9 5.670 Our Clara study > 77 23.488 Folie 31 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Cough Detection with Smartphones is Feasible “This research represents a step towards enabling passive https://www.jmir.org/2020/7/e18082/ and scalable cough monitoring for adults with asthma.” see also… Tinschert, P., Rassouli, F., Barata, F., Steurer-Stey, C., Fleisch, E., Puhan, M., Kowatsch, T., Brutsche, M. (2020) Nocturnal cough and sleep quality to assess asthma control and predict attacks, Journal of Asthma and Allergy 13, 669-678 10.2147/JAA.S278155. Rassouli, F., Tinschert, P., Barata, F., Steurer-Stey, C., Fleisch, E., Puhan, M., Baty, F., Kowatsch, T., Brutsche, M. (2020) Characteristics of Asthma- related Nocturnal Cough: A Potential New Digital Biomarker, Journal of Asthma and Allergy 13, 649—657 10.2147/JAA.S278119 . Folie 32 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Using Car Sensor Data to Predict Hypoglycemia The “healing” car Hey Mercedes, make it cooler and play my music! Hey Joe, I recommend you to take in some glucose! Source: youtu.be/sgF4jj2FGlw Sinergia Mercedes text was developed with a type-1 diabetes patient. https://voicebot.ai/2019/02/04/mercedes-focuses-entire-super-bowl-ad-around-hey-mercedes-voice-assistant/ Folie 33 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Increasing adherence to home exercises in chronic Alex back pain patients https://www.c4dhi.org/projects/digital-physiotherapy-coaching-with-alex/
Overview of the blended treatment with Alex Kowatsch, T., Lohse, K.M., Erb, V., Schittenhelm, L., Galliker, H., Lehner, R., Huang, E.M. (2021) Hybrid Ubiquitous Coaching With a Novel Combination of Mobile and Holographic Conversational Agents Targeting Adherence to Home Exercises: 4 Design and Evaluation Studies, Journal of Medical Internet Research, 23(2):e23612, 10.2196/23612 Folie 35 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Participant performing the squat exercise while wearing the augmented reality hardware. Kowatsch, T., Lohse, K.M., Erb, V., Schittenhelm, L., Galliker, H., Lehner, R., Huang, E.M. (2021) Hybrid Ubiquitous Coaching With a Novel Combination of Mobile and Holographic Conversational Agents Targeting Adherence to Home Exercises: 4 Design and Evaluation Studies, Journal of Medical Internet Research, 23(2):e23612, 10.2196/23612 Folie 36 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Results from a lab experiment (N=15) & 4-week intervention in the field (N=1) 3 modes of instructions Alex (Augmented Reality) Video Paper 1. What is your preferred 2. Session Alliance Inventory 3. Four-week intervention study (N=1) mode of instruction? Completely 7 Goal: 3 sessions per week for 4 weeks 8 6 Number of answers 6 5 Adherence: 92% (11 of 12 sessions) 4 Feedback: Intention to continue working 3 with Alex 1 2 Not at all 1 naR dn2 knaR ts1 Alex Kowatsch, T., Lohse, K.M., Erb, V., Schittenhelm, L., Galliker, H., Lehner, R., Huang, E.M. (2021) Hybrid Ubiquitous Coaching With a Novel Error bar indicates 95% confidence interval Combination of Mobile and Holographic Conversational Agents Targeting Adherence to Home Exercises: 4 Design and Evaluation Studies, Journal of Medical Internet Research, 23(2):e23612, 10.2196/23612 Folie 37 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Results from the 4-week intervention in the field (N=1) Box plot of the exercise execution errors during the 4 weeks. The number of errors was aggregated for each week. Kowatsch, T., Lohse, K.M., Erb, V., Schittenhelm, L., Galliker, H., Lehner, R., Huang, E.M. (2021) Hybrid Ubiquitous Coaching With a Novel Combination of Mobile and Holographic Conversational Agents Targeting Adherence to Home Exercises: 4 Design and Evaluation Studies, Journal of Medical Internet Research, 23(2):e23612, 10.2196/23612 Folie 38 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Ally The Assistant to Lift Your Level of Activity https://www.c4dhi.org/projects/ally-a-digital-assistant-to-lift-your-level-of-activity/
63% of push notifications are sent at the wrong time “Most push notifications are being sent and not opened, because they arrive at the wrong time, according to Leanplum’s research. It examined more than 671,500,000 push notifications sent during 2015, and found 63% were sent at a time when they were less likely to be opened.” www.businessofapps.com/63-of-push-notifications- are-sent-at-the-wrong-time https://www.accengage.com/benchmark-opt-in-and-reaction-rates-of-push-notifications-and-in-app-messages-for-mobile-apps-2018-edition/ Folie 40 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
The Ally App Kramer, J., Künzler, F., Mishra, V., Smith, S.N., Kotz, D.F., Scholz, U., Fleisch, E., Kowatsch, T. (2020) Which Components of a Smartphone Walking App Help Users to Reach Personalized Step Goals? Results from an Optimization Trial, Annals of Behavioral Medicine, 10.1093/abm/kaaa002. Folie 41 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Results from the Ally Study (274 participants, 6 weeks, random notifications) Positive effect on … a) response rate (within 10min) b) response delay Weekend: after 6pm 10am-6pm Weekday: 10am-6pm Unplugged Home Unlocked Unplugged Walking Walking Künzler, F., Mishra, V., Kramer, J., Kotz, D.F., Fleisch, E., Kowatsch, T. (2019) Exploring the State-of-Receptivity for mHealth Interventions, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) 3(4): Paper 140 10.1145/3369805. Folie 42 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Ally 2.0 USA (N=83, 3 weeks) Just-in-time response rate: Percentage of users responding to a notification within 10 minutes. Mishra, V., Künzler, F., Kramer, J., Fleisch, E., Kowatsch, T., Kotz, D.F. (2020) Detecting Receptivity for mHealth Interventions in the Natural Environment, Preprint arXiv arXiv:2011.08302. Folie 43 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Prof. Dr. Mathias Allemand Prof. Dr. Christoph Flückiger Psychologists, Zurich University https://www.c4dhi.org/projects/snf-personality-change/
PEACH – Personality Coach Stieger, M., Nißen, M.K., Rüegger, D., Kowatsch, T., Flückiger, C., Allemand, M. (2019) PEACH, a smartphone- and conversational agent-based coaching intervention for intentional personality change: study protocol of a randomized, wait-list controlled trial, BMC Psychology 6(43), pp. 1-15. [PDF] Folie 45 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
“Strongest evidence to date”: PEACH Study 10-week intervention results (self-assessments) Stieger, M., Flückiger, C., Rüegger, D., Kowatsch, T., Roberts, B.W., Allemand, M. (2021) Changing Personality Traits with the Help of a Digital Personality Change Intervention, Proceedings of the National Academy of Sciences of the United States of America (PNAS) 18(8):e2017548118 10.1073/pnas.2017548118 (Preprint: 10.31234/osf.io/sur2j) Folie 46 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Breeze: A Playful Biofeedback Breathing Training for Mental and Physical Well-being https://www.c4dhi.org/projects/breeze/
A Playful Smartphone-based Self-regulation Training for the Prevention and Treatment of Child and Adolescent Obesity Kowatsch, T., Shih, I., Lukic, Y., Keller, O., Heldt, K., Durrer, D., Stasinaki, A., Büchter, D., Brogle, B., Farpour-Lambert, N., l’Allemand, D. (in press) A Playful Smartphone-based Self-regulation Training for the Prevention and Treatment of Child and Adolescent Obesity: Technical Feasibility and Perceptions of Young Patients, 1st Workshop on Healthy Interfaces (HEALTHI), collocated with the 26th ACM Annual Conference on Intelligent User Interfaces (IUI) – Where HCI meets AI, Virtually Hosted by Texas A&M University, April 13-17, 2021 Folie 48 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Perceptions of 11 Young Children and Adolescents with Obesity Kowatsch, T., Shih, I., Lukic, Y., Keller, O., Heldt, K., Durrer, D., Stasinaki, A., Büchter, D., Brogle, B., Farpour-Lambert, N., l’Allemand, D. (in press) A Playful Smartphone-based Self-regulation Training for the Prevention and Treatment of Child and Adolescent Obesity: Technical Feasibility and Perceptions of Young Patients, 1st Workshop on Healthy Interfaces (HEALTHI), collocated with the 26th ACM Annual Conference on Intelligent User Interfaces (IUI) – Where HCI meets AI, Virtually Hosted by Texas A&M University, April 13-17, 2021 Folie 49 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Breeze Lukic, Y., Shih, I., Hernández, Á., Cotti, A., Fleisch, E., Kowatsch, T. (2021) Physiological Responses and User Feedback on a Gameful Breathing Training App: Within- Subject Experiment, JMIR Serious Games 2021;9(1):e22802 10.2196/22802. Shih, I., Tomita, N., Lukic, Y., Hernández, Á., Fleisch, E., Kowatsch, T. (2019) Breeze: Smartphone-based Acoustic Real-time Detection of Breathing Phases for a Gamified Biofeedback Breathing Training, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) 3(4): Paper 152. 10.1145/3369835 Folie 50 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Breeze: First results of the slow-paced breathing training (Lab study, N=3/16) Shih, I., Tomita, N., Lukic, Y., Hernández, Á., Fleisch, E., Kowatsch, T. (2019) Breeze: Smartphone-based Acoustic Real-time Detection of Breathing Phases for a Gamified Biofeedback Breathing Training, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) 3(4): Paper 152. 10.1145/3369835 Folie 51 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Elena+, Care for COVID-19 30+ Volunteers Elena+ Care for COVID-19: A pandemic lifestyle care intervention https://youtu.be/cRPKGbNcCnw Screencast https://vimeo.com/412004844 The Team’s Story https://youtu.be/ajDa9qnqnPU www.elena.plus Elena+ inspired by Elena Pagliarini Folie 52 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Und nochmals zur Erinnerung: Anatomie einer „idealen“ digitalen Pille Example Distal Quality of Life Outcome Evidence- based knowledge Proximal Stress Physical activity Diet Behavior Outcomes management Digital Pill 1. Vulnerability 2. Receptivity 3. Support Folie 53 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Vor dem Hintergrund des Gesagten: Braucht es denn evidenzbasierte digitale Pillen aus Ihrer Sicht jetzt? Den Umfrage-Link finden Sie im Zoom-Chat oder hier:
Are mobile apps for mental health effective? “Effect sizes for single trials ranged from g = −0.05 to 0.14 for PTSD and g = 0.72 to 0.84 for insomnia. Although some trials showed potential of apps targeting mental health symptoms, using smartphone apps as standalone psychological interventions cannot be recommended based on the current level of evidence.” https://doi.org/10.1038/s41746-019-0188-8 Folie 55 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
How about extremely popular mental health apps? Teepe et al. (manuscript in preparation) … Folie 56 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
How about extremely popular mental health apps? Teepe et al. (manuscript in preparation) ! Teepe et al (manuscript in preparation) Folie 57 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Try it out: BLV MySwissFoodPyramid & Sanitas Coach Folie 58 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Braucht es denn evidenzbasierte digitale Pillen in der Psychotherapie? Den Umfrage-Link finden Sie im Zoom-Chat oder hier:
Wo könnten digitale Pillen in der Psychotherapie am sinnvollsten eingesetzt werden? Den Umfrage-Link finden Sie im Zoom-Chat oder hier:
Haben Sie weitere Ideen, wie evidenzbasierte digitale Pillen am sinnvollsten in der Psychotherapie eingesetzt werden könnten? Dann schreiben Sie diese bitte jetzt gerne in einem kurzen Satz auf. Den Umfrage-Link finden Sie im Zoom-Chat oder hier:
Die Teilnehmer haben geantwortet… 1. Um z.B. bei Essstoerungen Ausloeser zu identifizieren 2. manualisierte Therapien für Patienten, die aus sprachlichen Gründen keine Psychotherapie im Wohnort machen können 3. Psychoedukative Informationen 4. Erreichen von Patienten in Regionen mit Versorgungsproblemen (z.B. auf dem Land) 5. präventive Apps für Schüler, wo Mental Gesundheit & Quality of Life erfasst und gleichzeitig Hilfen aktiviert werden .... Dies v.a. weil ein nicht unbeträchtlicher Teil der Schüler (v.a. mit interner Symptomatik) schlicht nicht wahrgenommen wird, wenn er/sie Probleme im Bereich von Mental Health hat ... ... evtl. dann mit Aktivierung auch von Schul-gebundenen Personal .... ... oder auch Apps, die Familien in Kommunikation über das Thema bringt .... wären toll 6. Sinnvoll wäre eine Evaluation der digitalen Affinität von Patienten vor einer "digitalen Pille" 7. Alkohol Intoxikation überwachen, Warnung bei gesteigerte Affektivität ==> Gewaltschutz 8. Blended approach in Ergänzung zu regulärer Psychotherapie um die zeitliche Interaktion und durchgeführte konkrete Übungen für den Patienten zu erhöhen - am besten mit natürlichem Chatbot. 9. Konsumtagegebuch, Symptomtagebuch, Erinnerungsfunktionen für Interventionen (z.B. Medikamenteneinnahme), Psychoedukation to-go 10. Suizidalität 11. Social Networking 12. Bessere Ästhetik. 13. Physiotherapeutische Motivation bei Depression 14. Vernetzung mit anderen Betroffenen
Psychiatry in the Digital Age Aref-Adib, G., McCloud, T., Ross, J., O'Hanlon, P., Appleton, V., Rowe, S., . . . Lobban, F. (2019). Factors affecting implementation of digital health interventions for people with psychosis or bipolar disorder, and their family and friends: a systematic review. The Lancet Psychiatry, 6(3), 257-266. doi:10.1016/S2215-0366(18)30302-X Graham, A. K., Lattie, E. G., & Mohr, D. C. (2019). Experimental Therapeutics for Digital Mental Health. JAMA Psychiatry, 76(12), 1223–1224. doi:10.1001/jamapsychiatry.2019.2075 Grover, S., Nguyen, J. A., Viswanathan, V., & Reinhart, R. M. G. (2021). High-frequency neuromodulation improves obsessive–compulsive behavior. Nature Medicine, 27(2), 232-238. doi:10.1038/s41591-020-01173-w Hariman, K., Ventriglio, A., & Bhugra, D. (2019). The Future of Digital Psychiatry. Curr Psychiatry Rep, 21(9), 88. doi:10.1007/s11920-019-1074-4 Marshall, J. M., Dunstan, D. A., & Bartik, W. (2020). Smartphone psychology: New approaches towards safe and efficacious mobile mental health apps. Professional Psychology: Research and Practice, 51(3), 214-222. doi:10.1037/pro0000278 Wasil, A. R., Venturo-Conerly, K. E., Shingleton, R. M., & Weisz, J. R. (2019). A review of popular smartphone apps for depression and anxiety: Assessing the inclusion of evidence-based content. Behav Res Ther, 123, 103498. doi:10.1016/j.brat.2019.103498 Wasil, A. R., Gillespie, S., Patel, R., Petre, A., Venturo-Conerly, K. E., Shingleton, R. M., . . . DeRubeis, R. J. (2020). Reassessing evidence-based content in popular smartphone apps for depression and anxiety: Developing and applying user-adjusted analyses. J Consult Clin Psychol, 88(11), 983-993. doi:10.1037/ccp0000604 Weisel, K. K., Fuhrmann, L. M., Berking, M., Baumeister, H., Cuijpers, P., & Ebert, D. D. (2019). Standalone smartphone apps for mental health—a systematic review and meta-analysis. npj Digital Medicine, 2(1), 118. doi:10.1038/s41746- 019-0188-8 Wilhelm, S., Weingarden, H., Ladis, I., Braddick, V., Shin, J., & Jacobson, N. C. (2020). Cognitive-Behavioral Therapy in the Digital Age: Presidential Address. Behavior Therapy, 51(1), 1-14. doi:https://doi.org/10.1016/j.beth.2019.08.001 Wright, J. H., Mishkind, M., Eells, T. D., & Chan, S. R. (2019). Computer-Assisted Cognitive-Behavior Therapy and Mobile Apps for Depression and Anxiety. Curr Psychiatry Rep, 21(7), 62. doi:10.1007/s11920-019-1031-2 Folie 63 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Prof. Dr. Tobias Kowatsch Assistant Professor for Digital Health, University of St.Gallen, Switzerland Scientific Director, Centre for Digital Health Interventions, ETH Zurich & University of St.Gallen, Switzerland Lead Principal Investigator, Mobile Health Interventions, Singapore-ETH Centre, Singapore Partner, Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, USA Member, Competence Centre for Rehabilitation Engineering and Science, ETH Zurich, Switzerland www.c4dhi.org | www.mobile-coach.eu | tobias.Kowatsch@unisg.ch Folie 64 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Further references Alpaydin, E. (2017). Machine Learning: The New AI. Cambridge, MA: MIT Press. Bauer, U. E., Briss, P. A., Goodman, R. A., & Bowman, B. A. (2014). Prevention of chronic disease in the 21st century: elimination of the leading preventable causes of premature death and disability in the USA. The Lancet, 384(9937), 45-52. Brennan, P., Perola, M., van Ommen, G.-J., & Riboli, E. (2017). Chronic disease research in Europe and the need for integrated population cohorts. Europen Journal of Epidemiology, 32(9), 741-749. Géron, A. (2017). Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques for Building Intelligent Systems. Boston, MA: O'Reilly. Gerteis, J., Izrael, D., Deitz, D., LeRoy, L., Ricciardi, R., Miller, T., & Basu, J. (2014). Multiple Chronic Conditions Chartbook. AHRQ Publications No, Q14-0038. Rockville, MD: Agency for Healthcare Research and Quality. Hauser-Ulrich, S., Künzli, H., Meier-Peterhans, D., Kowatsch, T. (in press) A Smartphone-based Healthcare Chatbot to Promote Self-Management of Chronic Pain (SELMA): A Pilot Randomized Control Trial, JMIR Mhealth Uhealth. Katz, D. L., Frates, E. P., Bonnet, J. P., Gupta, S. K., Vartiainen, E., & Carmona, R. H. (2017). Lifestyle as Medicine: The Case for a True Health Initiative. American Journal of Health Promotion, First Published May 19, 2017. Kramer, J., Künzler, F., Mishra, V., Smith, S.N., Kotz, D.F., Scholz, U., Fleisch, E., Kowatsch, T. (in press) Which Components of a Smartphone Walking App Help Users to Reach Personalized Step Goals? Results from an Optimization Trial, Annals of Behavioral Medicine. Künzler, F., Kramer, J., & Kowatsch, T. (2017). Efficacy of Mobile Context-aware Notification Management Systems: A Systematic Literature Review and Meta-Analysis. Paper presented at the IEEE 13th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Rome, Italy. Künzler, F., Mishra, V., Kramer, J., Kotz, D.F., Fleisch, E., Kowatsch, T. (2019) Exploring the State-of-Receptivity for mHealth Interventions, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) 3(4): Paper 140. Kowatsch, T., Fischer-Taeschler, D., Putzing, F., Bürki, P., Stettler, C., Chiesa-Tanner, G., & Fleisch, E. (2019). Die digitale Pille für chronische Krankheiten. In M. Pfannstiel, P. Da-Cruz, & H. Mehlich (Eds.), Digitale Transformation von Dienstleistungen im Gesundheitswesen. Heidelberg, Germany: Springer, 205-231. Kowatsch, T., Otto, L., Harperink, S., Cotti, A., Schlieter, H. (2019) A Design and Evaluation Framework for Digital Health Interventions, it – Information Technology 2019; 61(5-6): 253-263. Kowatsch, T., Harperink, S., Dittler, U., Xiao, G., Stanger, C., Oswald, H., Möller, A. (2019) A digital assistant for healthcare providers targeting 10 to 15-year-old patients with asthma and their family: results from a pilot study, Abstract published by the Center for Digital Health Interventions, ETH Zurich & University of St.Gallen. Kvedar, J. C., Fogel, A. L., Elenko, E., & Zohar, D. (2016). Digital medicine’s march on chronic disease. Nature Biotechnology, 34(3), 239-246. Khan, W. Z., Xiang, Y., Aalsalem, M. Y., & Arshad, Q. (2013). Mobile Phone Sensing Systems: A Survey. IEEE Communications Surveys & Tutorials, 15(1), 402-427. Lane, N. D., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., & Campbell, A. T. (2010). A Survey of Mobile Phone Sensing. IEEE Communications Magazine, 48(9), 140-150. Nahum-Shani, I., Hekler, E. B., & Spruijt-Metz, D. (2015). Building Health Behavior Models to Guide the Development of Just-in-Time Adaptive Interventions: A Pragmatic Framework. Health Psychology, 34(Supplement), 1209-1219. Nahum-Shani, I., Smith, S. N., Spring, B. J., Collins, L. M., Witkiewitz, K., Tewari, A., & Murphy, S. A. (2018). Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support. Annals of Behavioral Medicine, 52(6), 446-462. Rhyner, D., Loher, H., Dehais, J., Anthimopoulos, M., Shevchik, S., Botwey, R. H., . . . Mougiakakou, S. (2016). Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study. Journal of medical Internet research, 18(5), e101. Ryder, B., Gahr, B., Egolf, P., Dahlinger, A., & Wortmann, F. (2017). Preventing traffic accidents with in-vehicle decision support systems - The impact of accident hotspot warnings on driver behaviour. Decision Support Systems, 99, 64-74. Schembre, S. M., Liao, Y., Robertson, M. C., Dunton, G. F., Kerr, J., Haffey, M. E., . . . Hicklen, R. S. (2018). Just-in-Time Feedback in Diet and Physical Activity Interventions: Systematic Review and Practical Design Framework. Journal of medical Internet research, 20(3), e106. Shih, I., Tomita, N., Lukic, Y., Hernández, Á., Fleisch, E., Kowatsch, T. (2019) Breeze: Smartphone-based Acoustic Real-time Detection of Breathing Phases for a Gamified Biofeedback Breathing Training, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) 3(4): Paper 152. Sim, I. (2019). Mobile Devices and Health. The New England Journal of Medicine, 381(10), 956-968. Stone, A. A., & Shiffman, S. (1994). Ecological momentary assessment (EMA) in behavioral medicine. Annals of Behavioral Medicine, 16(3), 199-202. Triantafyllidis, A. K., Velardo, C., Salvi, D., Shah, S. A., Koutkias, V. G., & Tarassenko, L. (2017). A Survey of Mobile Phone Sensing, Self-Reporting, and Social Sharing for Pervasive Healthcare. IEEE Journal of Biomedical and Health Informatics, 21(1), 218-227. Wahle, F., Kowatsch, T., Fleisch, E., Rufer, M., & Weidt, S. (2016). Mobile Sensing and Support for People with Depression: A Pilot Trial in the Wild. JMIR mHealth uHealth, 4(3), e111. Wang, R., Chen, F., Chen, Z., Li, T., Harari, G., Tignor, S., . . . Campbell, A. T. (2014). StudentLife: assessing mental health, academic performance and behavioral trends of college students using smartphones. Paper presented at the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp '14), Seattle, Washington. Folie 65 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
Additional Glossary (Sim 2019, p. 957) Decentralized clinical trials: Trials executed through telemedicine, mobile health, or local health care providers, with the use of procedures such as virtual recruitment, investigational products shipped directly to participants, or smartphone-based outcomes assessment. Digital biomarkers: Physiological and behavioral measures collected by means of digital devices such as portables, wearables, implantables, or digestibles that characterize, influence, or predict health-related outcomes. Digital diagnostics: The application of wearable and ambient sensors, mobile apps, social media, and location-tracking technology singly or in combination to diagnose medical conditions. Digital patient experience: The sum of online interactions that a patient has with a health care organization on web- sites, mobile devices, or wearables across all touchpoints and phases of care. Digital therapeutics: Interventions that use wearable and ambient sensors, mobile apps, social media, and location- tracking technology independently or in conjunction with medications, devices, or other therapies to improve patient care and health outcomes. Ecologic momentary assessment: An approach that involves repeated sampling of persons’ current behaviors and experiences in real time, in these persons’ natural environments. Food and Drug Administration (FDA) approval: FDA approval is given to class III medical devices that pass a premarket approval process to “demonstrate that the device is safe and effective when used.” Class III medical devices are ones that pose the highest risk. They “sustain or support life, are implanted, or present potential high risk of illness or injury.” FDA clearance: Class I or II medical devices pose minimal or moderate risk of harm. Unlike class III devices, they are not required to undergo premarket approval. FDA clearance can be obtained through the premarket notification, or 510(k), process to “demonstrate that the device is substantially equivalent to a device already placed into one of the three device classifications before it is marketed.” Internet of Things: The network of everyday physical objects that are embedded with sensors and software that are inter- connected and can exchange data through the Internet. Medical device: According to the Food, Drug, and Cosmetic Act, a medical device is “an instrument ... or other similar or related article [that is] intended for use in the diagnosis of disease or other conditions, or in the cure, mitigation, treatment, or prevention of disease ... and which does not achieve any of its primary intended purposes through chemical action within or on the body ... and which is not dependent upon being metabolized for the achievement of any of its primary intended purposes.” Metadata: Data that describe and give information about other data — for example, the author of a document, the size of an image, or the device that generated a reading. Mobile health: The application of wearable and ambient sensors, mobile apps, social media, and location-tracking technology singly or in combination to obtain data pertinent to wellness and disease diagnosis, prevention, and management. Patient-generated health data: Health-related data that are created, recorded, or gathered by or from patients. Patient-reported outcome: A report of the status of a patient’s health condition that comes directly from the patient. Software as a medical device: Software that is intended to be used for medical purposes and that performs these purposes without being part of a hardware medical device. Folie 66 | App auf Rezept: Was sind digitale Pillen und braucht es sie in der Psychotherapie? © Universität St.Gallen und & ETH Zürich
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