User requirements for smartphone apps

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The importance of considering user requirements when designing mobile apps for mental healthcare. A presentation by Dr Mike Craven of NIHR MindTech …

The importance of considering user requirements when designing mobile apps for mental healthcare. A presentation by Dr Mike Craven of NIHR MindTech
www.mindtech.org.uk

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  • 1. Mobile Technology and Mental Health, Manchester 11/09/2013 User requirements for smartphone applications NIHR MindTech Healthcare Technology Co-operative Dr. Michael Craven – Senior Research Fellow
  • 2. University of Nottingham Innovation Park Institute of Mental Health MindTech NIHR HTC in Mental health & neurodevelopmental disorders Since January 2013. Based in Nottingham. Official launch 11th November 2013, London 2
  • 3. Clinical Landscape • Mood Disorders – Unipolar depression – Bipolar depression • Neurodevelopmental disorder – Autism spectrum disorder (ASD) – Tourette syndrome – Attention Deficit Hyperactivity Disorder (ADHD) • Dementia 3 14.0 7.0 6.9 5.4 5.0 4.9 3.4 3.0 2.0 1.3 1.2 1.0 0.9 0.7 0.4 1.0 0 2 4 6 8 10 12 14 Anxiety disorders Insomnia Unipolar depression Dementia ADHD Somatoform disorders Alcohol dependence Conduct disorder PTSD Personality dis. Psychotic disorder Cannabis dependence Eating disorder OCD opiate dependence Mental retardation Wittchen et al. 2011 European Neuropsychopharmacology Current prevalence of mental health disorders in Europe
  • 4. Research Strategy • Technology Innovation Pipeline • High quality collaborative projects • User-led design • New partnerships • National resource • Transformation of mental health care and services
  • 5. Bringing Partners Together 1: Institute of Mental Health 2: Technology Transfer Office Academics Patients & Carers Clinicians SMEs University NHS Industry HTC IMH1 Medilink TTO2 ADDISS Tourettes Action Computer Science Nottinghamshire Healthcare Trust Biomedical Engineering Business School BuddyApp Qbtech Ltd Buzz3D Ltd Red Embedded Ltd
  • 6. Text messaging app to support therapy Diary: SMS or web Analysis tool Goal reminders Appointment prompts
  • 7. QbTest: Objective Assessment of ADHD • Computerised assessment of attention and activity • Supports clinical decision making • Provides patients with objective reports on their condition 7
  • 8. ADHD measurement App 8 • QbTest via smartphone application – link with on-going work aimed at assessing capacity of QbTest to inform clinical decision making • Specification: – 1. continuous performance test delivered via a mobile phone app • provides measurement of attention and impulsivity – 2. in-built accelerometer and gyroscope to assess levels of activity • continuously • during specific portions of the day • while performing the cognitive task
  • 9. A few new mental health Apps • My Journey App – Early Intervention in Psychosis Service for 14 - 35 year olds. Surrey & Borders Partnership NHSFT Graded self-assessment, mood management tips, emergency contacts, information • Actissist – personalised CBT treatment for early stage psychosis. University of Manchester • Doc Ready – checklist for patient/GP communication. Social Spider and others. • CANTABmobile – Mobile app for memory assessment using Paired Associates Learning test. Cambridge Cognition Ltd. 9
  • 10. Earlier self-reporting App case studies 10 Craven, M. P., Selvarajah, K., Miles, R., Schnädelbach, H., Massey, A., Vedhara, K., Raine-Fenning, N., Crowe, J. User requirements for the development of Smartphone self- reporting applications in healthcare, in Kurosu, M (Ed.): Human-Computer Interaction, Part II, HCII 2013, LNCS 8005, 36-45, 2013.
  • 11. The problem of user elicitation 11 Perceptions • Limited involvement of health professional involvement during App development (Rosser et al. J. Telemed Telecare, 2011 - Pain Apps survey) • Lack of end user involvement in the App design process (McCurdie et al. AAMI Horizons 2012) • Little good quality evidence for mHealth interventions used by ‘lay people’. Text messaging services shown to increase adherence to anti-retroviral medication in low cost setting, increase smoking cessation in high cost setting (Free et al. PLOS Medicine, 2013) Demands • Regulatory (for ‘medical device’ Apps) e.g. HE75, IEC 62366:2007 - Medical devices -- Application of usability • Patient Public Involvement – imperative for NIHR research • Implementation science (Brooks et al. 2011 – ‘conducive’ & ‘impeding’ conditions for innovation in mental health services) • Ethical (Wenze & Miller 2010 - ecological momentary assessment in mood disorders research)
  • 12. Ethical issues with Apps • Security – data storage and communication. Apps vs. text messaging & email (also a regulatory issue) • Privacy - What do patients/participants expect or imagine might happen with their data e.g. a trained professional monitoring it and acting upon it. • Sensitive information - maybe better revealed face-to-face, in a group situation …? • Burden - what frequency of data collection is acceptable? • Impact on clinical care - how to respond to results of data collection: do nothing, give advice, treat as an emergency? • Impact on health – stress, being reminded could cause exacerbation, constant reminder of condition? • Social – effect on family, carers etc. 12
  • 13. Case study 1 – IVF Stress App - design brief 13 Ref: Quirin, M., Kazan, M., Kuhl, S.: When nonsense sounds happy or helpless: The implicit positive and negative affect test (IPANAT). Journal of Personality and Social Psychology 3, 500–516 (2009)
  • 14. Case study 1 – phone audit for IVF Stress App 14 • 10 questions (76 users): – What type/model of mobile phone do you have? – Is your mobile phone a smart phone? – Which air time provider are you with? – Is the phone on pay as you go or on contract? – Do you use email or internet access on your phone? – Is internet coverage included in your contract? – Do you use an alarm clock function? – Are you familiar with the use of ‘Apps’ on your phone? – How regularly do you use an ‘App’ on your phone? – If you were to be asked to report your distress levels throughout your treatment which of the following methods would you prefer?
  • 15. Example 1 – phone audit 15 IVF stress self-reporting App study: Craven MP et al. (2013) User requirements for the development of Smartphone self-reporting applications in healthcare, in Kurosu, M (Ed.): Human-Computer Interaction, Part II, HCII 2013, LNCS 8005, 36-45 Phones & functions Yes % Frequency of App use % Communication preference % Is your mobile phone a smart phone? 75 Every day 53 App 58 Do you use email or internet access on your phone? 80 Weekly 17 Text message 30 Is internet coverage included in your contract? 82 Monthly 4 Telephone conversation 8 Do you use an alarm clock function? 92 Not at all 26 (Paper) Questionnaire 1 Are you familiar with the use of ‘Apps’ on your phone? 80 Other (including email) 3
  • 16. Case study 2 – mild asthma study 16 • Week 1 – diary only • Week 2 – diary + physiological measures Each weekday evening: •complete diary entry on smartphone (questionnaire modified from Juniper et al. 1992) Each weekday morning & evening: •Take 3 PEF measurements and enter data •Record 5 mins of pulse oximeter data Each weekday evening: complete diary entry
  • 17. Case study 2 – mild asthma – diary adherence Participant Days with diary entries, week 1 (of 5) Days with diary entries, week 2 (of 5) Days with diary entries, total (of 10) Days with full diary data (of 10) 1 5 3 8 6 2 3 0 3 3 3 1 1 2 2 4 2 2 4 3 5 4 5 9 8 6 1 5 6 4 7 4 1 5 4 8 2 0 2 2 9 3 3 6 4 10 4 4 8 4 11 2 1 3 3 Average (%) 56 45 51 39 17
  • 18. Case study 2 – mild asthma – physiological data adherence Participant Mornings with oximeter data (of 5) Afternoons with oximeter data (of 5) Days with some phys. data entry, total (of 10) Days with full phys. data (of 10) 1 4 4 5 1 2 0 0 0 0 3 2 2 5 2 4 3 4 4 1 5 4 5 5 4 6 3 4 5 3 7 4 3 5 0 8 2 2 2 0 9 3 3 4 1 10 1 1 5 0 11 3 3 4 1 Average (%) 53 56 80 24 18
  • 19. Case study 2 – mild asthma - user experience (results) Mild asthma self-reporting App study (with BlueTooth pulse oximeter device) • 5/11 participants - technology ‘nice’ or ‘easy to use’. – 2 ‘interesting’ – 6 minor technical problem (internet/Wi-Fi, Bluetooth, battery) – 1 not confident data upload succeeded – 1 ‘sometimes a bit of a hassle … overkill for mild asthma’ • 5/11 participants - no effect on lifestyle or ‘got used to it’ – 1 more cautious about remembering inhaler – 1 needed to plan when going out – 1 interference with daily activities – 2 difficulty or annoyance scheduling the recordings correctly – 1 inconvenience of sitting down to take measurements • 11/11 - no effect of technology on condition – 1 reported exacerbation during the study. • 7/11 - more aware of condition whilst taking part. – 2 ‘a good thing’. – 1 ‘thinking about a cough exacerbates it’. 19 Mild asthma self-reporting App study: Craven MP et al. (2013) User requirements for the development of Smartphone self- reporting applications in healthcare, in Kurosu, M (Ed.): Human-Computer Interaction, Part II, HCII 2013, LNCS 8005, 36-45
  • 20. Towards a protocol • Conduct a phone audit before commencing a research study – Discover range of prior experiences & preferences for phone functions amongst participants (e.g. alarm clock) – Detect potential for conflict between normal daily use & research study use of phone (since functions may mix or conflict) • Investigate design tolerance to real-world phone use amongst user group – Not keeping devices turned on or charged up – Effect of missing or ignoring prompts • Ensure secure collection and storage of data – Pre-empt ethical approval issues • Determine patient burden and adherence – Frequency of self-monitoring prompts – Pilot studies aimed at measuring adherence – Could more passive monitoring be preferable? Early stage user involvement and/or a participatory design process helps reveal needs which may not initially be apparent 20
  • 21. MindTech contacts: Principal Investigator Prof Chris Hollis chris.hollis@nottingham.ac.uk Technology Theme Lead: Prof John Crowe john.crowe@nottingham.ac.uk Senior Research Fellow (Technology) Dr Michael Craven michael.craven@nottingham.ac.uk 21 NIHR MindTech Healthcare Technology Co-operative Thank you for listening!