Professor James Stubbs from the University of Leeds talks through the NoHoW porject, that’s helping to trackweight loss programmes in digital, pulling data from sources like Fitbit and using Qualtrics to collect and analyse it as part f his research.

1. #QualtricsConverge
Development and evaluation
of digital solutions for weight
loss maintenance
James Stubbs, Professor of Psychology, University of Leeds
On Behalf of The NoHoW Consortium
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement
No 643309. For more information see: nohow.eu; @nohowH2020

2. #QualtricsConverge
Lack of knowledge
Physiological compensation
Obesogenic
environment
Stress, life events
Popular rather than evidence-based
practices
>45% of adults made ≥1 weight loss attempt in the last
year
CDC. 2008. Morbidity and Mortality Weekly Report http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5742a4.htm
2

3. Obesity: a chronic relapsing condition.
Franz et al. J Am Diet Assoc. 2007;107:1755-1767.

4. #QualtricsConverge
NoHoW
• 5 year European Commission-funded Research and Innovation Action (€5 million).
• Personalising Health and Care - self management of health and disease: citizen
engagement and mHealth.
• Evidence-based digital technologies and tools for weight loss maintenance.
4

5. #QualtricsConverge
Weight loss
programmes
Obesogenic
environment
Initial weight
loss
Hostile environment,
frustration, sporadic
adherence to
behaviours/ high risk
situations
Behavioural
lapses
Discontinued
behaviours
Relapse and
weight regain
Decreased
motivation,
physical and
emotional well-
being
Weight loss
programmes
Obesogenic
environment
Initial weight
loss
Supportive
environment,
personalised
navigation tools
Individual
feedback, stress
management,
coping
Adaptive behaviour
change
Relapse
prevention
Well-being and
weight
maintenance
The cycle of weight loss

6. #QualtricsConverge
The evidence
Supporting self-regulation (self-monitoring, goal setting, action planning) using tracking
technologies.
Promoting self-efficacy and intrinsic motivation.
Improved stress management and emotion regulation for relapse prevention.
Personalising solutions to meet individual needs and engage users.
Maximising scale and minimising cost through digital technologies.

7. #QualtricsConverge
Weight loss
programmes
Obesogenic
environment
Initial weight
loss
Hostile environment,
frustration, sporadic
adherence to
behaviours/ high risk
situations
Behavioural
lapses
Discontinued
behaviours
Relapse and
weight regain
Decreased
motivation,
physical and
emotional well-
being
Weight loss
programmes
Obesogenic
environment
Initial weight
loss
Supportive
environment,
personalised
navigation tools
Individual
feedback, stress
management,
coping
Adaptive behaviour
change
Relapse
prevention
Well-being and
weight
maintenance
Using digital solutions to navigate to a
healthier weight
Self
regulation
Self efficacy,
motivation
Stress
emotion skills
Tracking
technologies

8. #QualtricsConverge
Data Hub
Personalised
tools
Scientific
evaluation
Business model and developing ecosystem
Evidence-based
Personalised
validated
quantified
commercialised
Co-designed
Digital toolkit for weight maintenance
Self
regulation
Self efficacy,
motivation
Stress
emotion skills
Tracking
technologies

9. #QualtricsConverge
NoHoW protocol
9
Screening Active intervention Follow-up
CID 1 CID 2 CID 3 CID 4
0 months 6 months 12 months 18 months
Baseline Primary outcomes
CID = Clinical investigation day
3 European countries (UK, DK, Pt)
1002 participants: BMI >25 and lost ≥5% in last 12 months
Self
regulation
Self efficacy,
motivation
Stress
emotion skills
Tracking
technologies

10. #QualtricsConverge
Data Hub
Trial
management
software
Trial
Administration
portal
Biomarkers,
Body
composition
Activity
monitors
Scales
Psychological
Questionnaires (Qualtrics)
Digital diet
records
Eligibility Screening
(Qualtrics)
API calls
to Fitbit
Self
regulation
Self efficacy,
motivation
Stress
emotion skills
Tracking
technologies
Toolkit
Digital architecture
API calls
to
Qualtrics
Quatrics
solutions

11. #QualtricsConverge
Challenges
• Recruitment and screening.
• Personalised comunications with
participants.
Solutions
• Automated recruitment and screening
website.
• Filtering potential trial participants into
contacts lists for efficient follow-up.
• baseline characterisation of participants.
• rapid overview of their status within the
trial.
• Detailed contacts list and personalised
communications with each individual
participant throughout the trial.
11
Challenges and solutions

12. #QualtricsConverge
Challenges
• Toolkit content-presentation and
engagement.
• Toolkit responses in real time data.
Solutions
• Delivery of quizzes and interactive
content as part of the toolkit behaviour
change modules.
• Export of responses to the data hub.
12
Challenges and solutions

13. #QualtricsConverge
Challenges
• Trail outcome measures.
• Multi-lingual capability.
Solutions
• Collection of all questionnaire responses
• summary, overview and status for rapid
follow-up to ensure completeness and
accuracy of data collection across 3
European trial centres.
• Delivery of the same validated
questionnaires in 3 different languages at
3 trial centres.
13
Challenges and solutions

14. #QualtricsConverge
Challenges
• Large-scale data transfer.
Solutions
• Automated data export to the NoHoW
trail administration portal and centralised
data hub through the Qualtrics API.
14
Challenges and solutions

15. Automation of resource-
intensive tasks.
Participant tracking &
data monitoring
Automated data
export through the
Qualtrics API
Date/time stamped
data in 3 languages.
Seamless integration
Improving
engagement,
data collection
and trial delivery
on an
international
scale
Personalised
communications
participants in 3
languages
For more information see: nohow.eu; @nohowH2020

16. #QualtricsConverge