This document discusses a study on the potential of self-monitoring and self-tracking for health promotion. The study explored the experiences of self-trackers through an online survey and interviews. Key findings included that self-trackers engaged in tracking for self-knowledge, curiosity and health optimization. While self-tracking provided benefits like empowerment and motivation, barriers included issues with data interpretation and consistency. Overall self-tracking improved self-awareness and informed decision making for health, though future research should explore long term impacts and how to better integrate these tools into healthcare.

1. The potential of self-monitoring for Health Promotion

2. Health Promotion
 Health promotion is the process of enabling people to
increase control over, and to improve, their health.
 It moves beyond a focus on individual behaviour
towards a wide range of social and environmental
interventions

3. The Ottawa Charter for Health
Promotion (WHO)

4. Quantified Self for Health
Promotion
 Developing Personal Skills
 Self-awareness & self-optimisation
 understanding data
 Strengthening Community Action
 Asthmapolis
 Google flu trends
 Building Healthy Public Policies
 Big data to guide policy makers
 Creating Supportive Environments
 Providing resources for tracking
 Re-orientating Healthcare Services
 Prevention practises over curative measures
 Promotion of QS by Health care professionals

5. Research Aim
 To explore the experiences and impact self-monitoring
and data collection has had on the lives of self-
trackers, and the potential for their data to be used to
better understand behaviour change mechanisms for
human health and wellbeing.

6. Objectives
 Explore the driving factors and reasons behind individuals’
self-tracking and self-monitoring habits.
 Gain insight into what participants have discovered
through their self-tracking and self-monitoring habits.
 Discover the perceived benefits and barriers to self-
tracking.
 Gain insight into the experiences self-trackers have had
with their chosen habit.
 Explore participants’ views on the potential for integration
of self-tracking and self-monitoring behaviour into
mainstream daily life

7. Methodology
 Mixed methods approach
 Online questionnaire
 semi-structured interviews
 Data Collection & Analysis
 Survey Monkey
 Skype
 SPSS
 Inductive thematic analysis

8. Results
 Demographics
 25 respondents, 11male 8 female 6 undisclosed
 Age range: 18-84 (M=25-34)
 High socio-economic status

9. 0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
PercentageofUsers
Catagories of Tools
Tools Used

12. Benefits
Evidence
based
approach to
health
Improve/
optimise
health
Greater
understanding
of oneself
Mindfulness
Self-
awareness/
self-
knowledge
Preventative

13. Barriers
Consistency/
forgetfulness
Time-costs
Frequency
and effort
Poor inter-
operability
Skills
required
Lack of
privacy
Cheating

15. 0% 50% 100%
Yes
No
Confidentiality Concerns
0% 20% 40% 60%
Yes
No
Familiarity with privacy Terms
and Conditions of Devices
0% 20% 40% 60%
Yes
No
I don't know
Devices used Sharing with a
Third Party
0% 50% 100%
Yes
No
Willing to Share Data
Anonymously

16.  Overall positive experience of self tracking
 Satisfied with the available tools, process and usability
of the devices
 Self-awareness and self-knowledge to optimise health
 Desire to anonymously share data

17. Interview Results
 Demographics
 11 Interviews, 8 males, 3 females
 Experience 6 months- 40 years
 High Socio-economic Status
 22 variables of tracking
 20 tools mentioned
 Time-costs:2.5mins-1hours

18. Motivations & data Usage
 Motivations
 Cue to action
 Curiosity
 Sports
 school or work requirements
 Usage
 surgery, treatment and illness management
 self-diagnosis
 Accountability
 self-knowledge
 objective decision making
 prevention

19. Process & Impact
 Process
 quick and easy
 Consistency
 Cheating
 passive tracking
 Stressful
 obsessive
 Impact
 rational decision making
 Confidence
 Support
 self-efficacy

20. Benefits and Barriers
 Barriers
 Inter-operability
 Correlations
 passive tracking
 interpretation of data & context
 self-doubt
 Benefits
 Motivating
 objective viewpoint
 improve performance
 Lifestyle
 overall health

21. London Survey Comparisons
 Respondents:
 London: 105
 Dublin: 25
 Measuring weight:
 London: 47%
 Dublin: 70%
 Pen and paper still being used to track
 London: 28%
 Dublin: 32%
 Willingness to share data
 London:84%
 Dublin: 90%

22. Summary of Results
 Motivations
 Self-knowledge
 self-optimization
 curiosity
 Engagement
 Fitness
 Weight
 Nutrition
 sleep
 Perception of time
consumption
 Data Usage
 informed choices
 Motivate
 Empowerment
 self-awareness
 self-efficacy
 Barriers
 interpretation of data
 Correlations & Context
 Consistency
 psychological stresses

23. Self-awareness
 “It is like when you are driving a car and you see the
fuel gauge. If you couldn’t see the fuel gauge you would
just drive on but because you see it, you say ‘oh I am
running low on fuel’ so I suppose if you see your weight
going up or down, you can take action”

24. Psychological Stress
 “I staggered home with my flashlight knowing that I’d
advance to sixty-five thousand, and that there will be
no end to it until my feet snap off at the ankles. Then
it’ll just be my jagged bones stabbing into the soft
ground. Why is it some people can manage a thing like
a Fitbit, while others go off the rails and allow it to rule,
and perhaps even ruin, their lives?” (Sedaris, 2014)

25. Future Integration in Ireland
 Reputation: “nerdy”, time consuming
 Early adopters & innovators
 Role of Health Care Professionals
 Adaption of devices to better suit the needs of
individuals

26. Recommendations for Technology
 Securing continued engagement from its users
 Avoiding early drop-offs in usage
 Increasing devices passive tracking abilities
 Providing more cross-connection and correlations of
variables between devices
 Must convey the meaning behind the data
 Make more suggestions to the user as to how to
improve their results

27. Recommendations for Research
 Study the defining characteristics of self-trackers, for example,
personality types and traits
 Study the current and potential uses of self-tracking within alternative
social classes, for which the experiences, perceived benefits and
barriers may vary widely
 Research on the actual impact self-tracking has on its users published
work focused on initial integration and adoption, neglected to look at
the effects of long term adoption and sustainable behaviour change
 Evidence base required to promote more active integration of self-
monitoring in to health promotion and primary care practices