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How do wearable technology users interpret

automatically generated health visualisations?

A study submitted in partial fulfilment

of the requirements for the degree of

MSC Data Science

at

THE UNIVERSITY OF SHEFFIELD

by

CHARLOTTE VICTORIA NICKELS

September 2016

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Acknowledgments

I want to thank my two tutors, Skye and Peter, for their amazing and continual support throughout

this whole process.

I would also like to thank my parents and sister for their love, wishes and endless tissues when

things are going wrong as well as champagne and kisses when thing start looking up again.

Thank you.

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Abstract

Background

This research looks at the recent development of wearable technologies and their health

visualisations, most notably Fitbit devices. Lots of research has been conducted into the uptake and

use of Fitbit technologies for leading a healthier lifestyle, however, there is no research on whether

or not users can understand the information these devices produce. This dissertation looks to fill this

gap in the knowledge.

Aims

To discover if users understand the visualisations produced, look at whether the length of ownership

of the devices or how regularly users access this information has an effect on these results.

This esea h ai s to p o ide a odel to displa ho use s go a out de idi g o a good o ot as good health g aph o isualisatio .

Methods

Using qualitative inductive research this research project involves detailed interviews with 15 regular

Fitbit users. The development of an interview guide sheet is used to make this research unique as

well as aiming to help increase the quality of data collected during the research stages.

Tasks de ised the esea he usi g Fit it g aphs allo fo a i sight i to the use s ps holog he atte pti g o de i g the g aphs f o est to o st usi g thei o ethods ith thei o

views.

Results

This research found the participants in this study had little knowledge of resting heart rates and

what made them dangerous but knew lots about daily step guidelines. This research found

participants were taking knowledge from other experiences in order to attempt to answer questions

on resting heart rate tasks.

Notably, this research found that it is possible that although participants suggested they were using

their Fitbit to help them monitor health information or keep fit, it was actually more likely they were

usi g it to e pa t of the lu . This ool fa to as so ethi g ot oted du i g the de elop e t of the methodology section.

Conclusion

This research project provides a sound methodology for developing an understanding in users

experience and unde sta di g of Fit it te h ologies. This esea h s fi di gs suggest use s eed more support from Fitbit in order to understand their devices and the visualisations provided

effectively, especially if they are using their device to live or improve on a healthy active lifestyle.

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Contents Abstract ................................................................................................................................................... 2

Background ......................................................................................................................................... 2

Aims .................................................................................................................................................... 2

Methods .............................................................................................................................................. 2

Results ................................................................................................................................................. 2

Conclusion ........................................................................................................................................... 2

Introduction ............................................................................................................................................ 6

P o oti g a d li i g the health lifest le ........................................................................................ 6

Why is this research important? ......................................................................................................... 6

Research Aims and Objectives ............................................................................................................ 7

Literature Review .................................................................................................................................... 8

Motivations for using Fitbit ................................................................................................................. 8

Illiteracy and the inability to read graphs ........................................................................................... 8

Historic use of graphs to display information ..................................................................................... 9

Designing a good visualization .......................................................................................................... 10

Data privacy and wearable technologies .......................................................................................... 10

Literature relating to the methodology ............................................................................................ 10

Methodology ......................................................................................................................................... 12

Qualitative research, sampling and participant recruitment ........................................................... 12

Qualitative research ...................................................................................................................... 12

Sampling and participant recruitment .......................................................................................... 12

Interview Process .............................................................................................................................. 13

Interview design ............................................................................................................................ 14

The graph tasks ................................................................................................................................. 16

Ethical considerations ....................................................................................................................... 19

Results of the research project ............................................................................................................. 22

Th ee pa ti ipa t s sto ies ................................................................................................................ 22

Ja e s sto .................................................................................................................................... 22

Da s sto .................................................................................................................................... 22

Matt s sto ................................................................................................................................... 23

Results from the graph tasks ............................................................................................................ 24

Resting heart rate graphs task results (line graph) ....................................................................... 24

Step graphs task results (bar chart) .............................................................................................. 25

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How Jane, Dan and Matt responded to the tasks ............................................................................. 26

Ja e s tasks .................................................................................................................................... 26

Da s tasks .................................................................................................................................... 27

Matt s tasks ................................................................................................................................... 27

Other notable findings ...................................................................................................................... 27

Participants health data knowledge ............................................................................................. 28

Discussion of the results ....................................................................................................................... 30

Discussion of the importance of the three participants ................................................................... 30

The importance of Jane ................................................................................................................ 30

The importance of Dan ................................................................................................................. 31

The importance of Matt ................................................................................................................ 31

Findings from the heart rate graph tasks...................................................................................... 31

Findings from the step graph tasks ............................................................................................... 32

Other notable findings discussed .................................................................................................. 33

Conclusion ............................................................................................................................................. 35

Conclusion of the findings ................................................................................................................. 35

Suggested model of how participants gather information from the visualizations ......................... 36

How this research met its aims and objectives ................................................................................ 36

Further research opportunities......................................................................................................... 37

References ............................................................................................................................................ 38

Appendices ............................................................................................................................................ 40

Letter of ethical approval .................................................................................................................. 40

Copy of a completed interview guide sheet ..................................................................................... 41

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Introduction This dissertation will focus on if wearable technology users are able to effectively read and

disseminate the information about their fitness levels and general health and wellbeing, which are

automatically generated into graphs and visualizations by wearable technology businesses.

These businesses clearly invest heavily in the developments of their visualizations their apps and

computer interfaces produce. In 2004 it was suggested that development in good online

visualizations for websites was becoming the key investment for online businesses to make Plaisant

C (2004, May) and, more recently, with the development of smartphones having user centrically

designed apps is even more important for a business to succeed in today s saturated market.

The primary focus of these apps is to develop good quality, clear visualizations for users based on

the ea e s a ti it le els, numbers of steps as well as constant heart rate monitoring. If manually

inputted by the user, the app can also develop visualizations on water and calorie consumption

throughout the day, month or year. The visualizations all work towards the user reaching the

recommended amount of daily steps, minutes of exercise, water and calorie consumption.

Promoting and living the healthy lifestyle Du i g the ou se of the shift to a ds the st o g ot ski health o e e t has ee exponential. PETA UK (People for Ethical Treatment of Animals) - the leading animal rights charity in

the UK - noted 2016 as the year of the vegan movement, accounting this shift in lifestyle partly due

to the glamorization of the vegan lifestyle by a number of food bloggers such as Deliciously Ella PETA

(2016).

Follo i g the lau h of the Fit it Cha ge H‘, the ost ai st ea of Fit it s t a ki g de i es, i January 2015. 2016 has seen the UK population become more of a health conscious nation. A

number of traditionally out of shape popular reality television stars (such as Charlotte Crosby and

Holly Hagan) began their own weight loss missions inspiring the younger end of the general public to

do so as well. Leaving behind their traditionally boozy and kebab-heavy diets in favour of gym

workouts and selling DVDs, they too play a part in the shift of the UK public towards a healthier

more active lifestyle; a Fitbit can track and inform the user about progress every step of the way.

Why is this research important?

This research is important because of the fact it is unique. The UK is facing an obesity crisis with one

in four adults in the UK being affected according to the National Health Service d.u. (NHS). Although

this research will not involve obese participants, and participants health ill ot e dis ussed. This

research hopes to begin to uncover an understanding of whether or not members of the general

public are able to understand and disseminate the information produced by wearable technologies.

Without this understanding, the obesity crisis in the UK is unlikely to be stemmed as those accessing

these technologies to help them understand their activity levels may not understand the results

produced.

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This also applies to the numbers of the UK population who are partaking i the st o g ot ski movement, as well as the other members of the healthy living fad that is sweeping the nation as

mentioned in the previous section.

This research will conclude with a model of how participants in this research project approached the

g aphs p odu ed a d ho the e t o to de ide hat as the est g aph a d hi h as the o st . The findings from this will hopefully be able to discover what, if any, are the downfalls of the

visualizations and graphs generated, as well as suggesting ways in which the generated graphs or the

information provided could be improved in the future.

Research Aims and Objectives

This dissertation aims to discover how wearable technology users access and assess the graphs and

visualizations produced by the technologies. It hopes to develop a fuller understanding in exactly

how users process the information produced and how they use their knowledge of health and living

an active lifestyle to disseminate the information and take actions on it. In order to address these

aims the following objectives will be challenged:

1) Discover if users who have had their device for longer look and disseminate the graphs

and visualizations differently to newer users: this will only be possible if the researcher is

able to recruit participants who have had their devices for a varying amount of time. Due to

this constraint this will not be the main focus of the research, however, findings from this

could be used to describe trends discovered in the dissemination process further on.

2) Gain an understanding of what external knowledge of health and wellbeing helps the user

make decisions based on the information available to them: by briefly gauging the users

knowledge and understanding levels of important health information, it should become

clear how much of a personal interest they have in health data beyond their own, as well as

if the k o hat the should e ai i g fo . Without this i fo atio the use understanding the graphs may be defunct if they are unable to gauge hat is good o ad .

3) Discover if users actually look at the visualizations and graphs: the soul purpose of this part

of the research is to identify if the users are assessing information differently and if it is due

to a lack of knowledge of the graphs they are assessing. By also collecting information on the

length of time users have had their devices information can be obtained on whether or not

users become more knowledgeable over time. However, as wearable technologies are

relatively new to the market, it may be difficult to recruit participants of a wide range of

ownership time.

4) Create and develop a model displaying the processes and steps a user goes through whilst

disseminating the information provided to them by the visualizations: this model should

display the findings from this research project in a clear and apt fashion, allowing for future

research to use this model as a guide on how participants in this study went about assessing

and disseminating the information provided to them within Fitbit graphs.

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Literature Review This literature review will look at aspects of what motivates wearable technology users to continue

to use their devices as well as follow their personal health graphs and visualizations. From here, the

literature will move on to cover the risks of associating those who cannot successfully read graphs as

illiterate or uneducated and as to why these labels are incorrect and how to avoid putting potential

users i to the o g atego .

It will also review the privacy issues with the use of wearable technologies, the challenges of

designing a visualization that users can interpret at speed as well as representing the business and

its aims.

Motivations for using Fitbit

Co petitio allo s the eight loss group to sur i e as a support group ithout osti g a ythi g K.

M. Stinson (2001).

Competition is an innate biological trait that all humans are born with, and something that could be

seen as a motivator for people, such as those in this research project, deciding to purchase a Fitbit. It

is a e effe ti e f ee ie oti ato fo fit ess p og a s, as suggested “ti so i he ook. Unlike competition, the ability to read statistical data (particularly in the formats we are used to

today) is not an innate trait, and something that throughout human history has not be readily

available or taught; because of this, there is no reason for humans to be able to understand graphs

intuitively M Galesic & R Garcia-Retamero (2011).

Competition, however, will not be a successful motivating factor if the users are unable to

understand or disseminate the health information provided to them. The fact that graphs are not

necessarily easily read is what this research project will focus on. Looking at how participants of this

study process information provided to them compared with knowledge of health data they already

have will allow for the development of a model describing the different ways in which participants

make decisions and the most common decision making path.

Illiteracy and the inability to read graphs

Something for this research to consider is that although at first it may be assumed that the inability

of reading a graph would render someone into the category of illiterate or uneducated, this is not

necessarily the case. It has been found that a person who can read complicated texts, and carry out

basic mathematical tasks may also not be able to interpret graphs correctly. The readability of a

piece of information is much more about the skills and background knowledge of the user as well as

their motivation to access the information Kindig D et al. (2014). Regarding this research, it could be

expected that the participants may have regular access to graphs (from their Fitbit app), meaning

they could believe they know how to disseminate the information provided to them. However, the

aforementioned research makes the valuable point that if people are unable to understand and

follow guideline information or graphs explaining outcomes, they may end up making the wrong

decisions and possibly do so completely unwillingly. By looking at what participants already know

about the health data, as this research does, and how this effects their chosen path to accessing the

information available, this research may provide a better answer than the assumption of a

pa ti ipa t just ei g illite ate , particularly in relations to graphical data – and that it is more likely

they are just without the necessary knowledge to make informed decisions.

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In contrast to the previous research, a different viewpoint is that of Gassimaier W et al. (2012). Their

research suggested that when presented with simple graphs (line graphs and bar graphs) or clear

visualizations depicting frequencies with human figures, patients of breast cancer were able to make

more informed decisions on treatment plans quicker. However, when presented with more

complicated graphs, the patients were unable to make informed decisions. Allowing patients access

to graphical visualizations will help them develop their knowledge and understanding of graphs, thus

improving their graph reading skills for the future, arguably making this a better solution for

managing patients graphicacy. Although Fitbit provides users with basic line graphs and bar charts,

it does not make use of basic visualizations as mentioned in this academic piece. Due to the wide

ranging users of Fitbit and their own statement of intent: help people lead healthier, more active

li es y e po eri g the ith data, i spiratio a d guida e to rea h their goals Fitbit (2016)

providing simple visualisations may actually benefit Fitbit users exponentially (especially those who

may be less graph literate or formally educated) compared with their current format of only

producing line and bar charts. Due to ethical implications, illiterate participants will not be used in

this research; however, by discovering how participants in this research project assess information

this may lead to an area for future and further research.

Similarly to the previous point Garcia-Retamero R et al. (2012) found, unsurprisingly that patients

with a lower sense of numeracy were more likely to not be able to asses the overall risks of not

going for screenings or other health related checks. They were also less likely to be able to explain

the information displayed to them at a later date, leaving them in a dangerous situation where they

could easily be exploited. The research suggests using icons alongside the information, as well as

background notations to explain percentages, helps acquire subjects i te est and makes them more

likely to try and correctly disseminate the information. As the participants in this research project

will all be actively using their activity trackers it will be likely they will be regularly looking at and

attempting to understand the graphs. However, this researches interest in how the participants

explain each graph and the order in which they are displayed will tie in with Garcia-‘eta e o et al. s research in the benefits of background notations and percentage explanations in helping users

assess the information reliably.

Historic use of graphs to display information

In 2001 an issue arose where regressions and other forms of statistical analysis had become so

prevalent in the area of psychology it was becoming inaccessible for those who were not

mathematically minded, including patients themselves. It was suggested that by using a graph

instead of other numerical statistical analysis you enable the nonlinear multivariate relationship to

be viewed by both the researcher and reader. This research concludes that when trying to display

market share breakdowns it is more easily accessible being visualised as a scatter graph than via the

traditional method of just listing figures Brown L.L & Svyantek D. J (2001).

Because of this paper s age it relates to an important era when businesses and researchers alike

looked to shift their information display mechanisms from just answers to giving proof of answers.

The te h olog fo i te a ti e g aphs o pa ti ula l p ett g aphs as et to e o e a aila le to the mainstream public but a need and want for better quality data presentation was beginning to

become key to high level decision making processes.

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Research in 1975 suggested the first mainstream use of graphs in medicine was rare in the early 19th

century, however, one researcher in 1760 was regularly using graphs to explain his findings,

suggesting the printing was not the reason for limited graphs being found in mainstream scientific

pape s. The g aphs fou d o lose i spe tio look o e like ough otes take du i g the experimental process rather than the outcome of an experiment and most definitely not a method

of information portrayal or knowledge discovery Tilling L (1975).

Although at first the previously mentioned research may seem irrelevant to the graphs produced by

Fitbit with their colour coding and innovative designs, this research suggests that graphs are not

really the easiest way for humans to discover and interpret new information. This research suggests

the valuable point that any information gathered from a Fitbit graph is a highly skilled task and

actually the sign of a learnt behaviour, despite what may at first seem as a rather innate skill.

Designing a good visualization

The colour of something can have psychological effects on the way we see and feel about it. A

repeat study of a test to monitor the effects of colour on humans heart rate and GSR confirmed that

the colour red, and its shades promotes excitement inside the brain, whereas blue (the colours of

Fit it s isualizatio s p o otes the lo est e ite e t espo se of the fou p i a olours Jacobs

K.W & Hustmyer F.E (1974).

Data privacy and wearable technologies

Health data compared with other personal information, such as demographics is considered much

more personal and sensitive to individuals Bansal et al. (2010). Because of this, the perceived risk of

this highly private information becoming more available is something users have to carry out a risk-

benefit analysis when deciding to disclose this information or not Gao Y et al. (2015). However,

Bansal et al. (2010) do state that when you compare personal fitness information, the sort of

information Fitbit collects in this study, users are less concerned about their personal data than they

are with purely health related information.

The privacy concerns become more ethically challenging for wearable technologies when they are

used in conjunction with other services. For example, a company may promote their use for the

health lifestyle benefits whilst using the devices to track sick leave or the information could be

shared with insurance companies to help determine individual rates, each of which have their own

privacy and ethical implications to their uses Fernandez P (2014).

Literature relating to the methodology

Due to the proposed methodology of this research project, there is a potential issue with the data

and graphs being used by participants not containing their personal data. Although out-dated,

previous research has suggested that with smoking, a vast majority of heavy smoker participants

accept that smoking will reduce life expectancy, but they do not believe this will effect them and

overestimate how long they expect to live – despite admitting to being a heavy smoker and aware of

the negative effect this has on their health and longevity M Schoenbaum (1997). Similarly, the

attitude of ge e i health i fo atio ot elati g to the pa ti ipa t as also displa ed i a u h more recent study on graphs relating to health literacy levels. They found people do not fully accept

the risk messages associated with health information as they look at the information from a

spectator approach and do not accept it relates to them personally. The reasoning for dismissing the

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health i fo atio is fo a ious easo s i ludi g the u e s e e a iguous, ot that high o because not all the risk factors were relevant to themselves Damman OC et al. (2016). This

dismissive attitude can lead to highly relevant information being deemed inappropriate, thus

creating a disturbing trend of not accepting the risks of certain lifestyle choices.

Because of the phenomena described in the previous two research projects, it could be suggested

that i this esea h p oje t the data ei g e te al f o the pa ti ipa t a i flue e the a s e s given by users. However, using participants own personal data would not only be impractical it

would also raise considerable ethical issues.

When deciding what technologies to include in the research project, one recent research paper

looking at using technology to keep the elderly motivated, Fitbit was listed as the best choice device

fo a a e ess of fit ess le els Cho E & Ki M . It is e ause of this fa to , as ell as Fit it s position as the market leader Statista (2016) that it was decided the potential research population

would be reduced to those using Fitbit wristbands.

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Methodology To a s e this esea h s ai s a d o je ti es, formal interviews will be conducted. To ensure the

research produced from this project is of the highest standard, some practicalities have been taken

into account before the methodology is devised.

As the research is taking place in the summer when fewer potential participants are in Sheffield the

research will not be constricted to Sheffield alone. The collection of data will take place over a

month to allow for the optimum amount of data to be collected; this process will be discussed

further on in this chapter.

To reduce the size of the research population, this project will focus solely on Fitbit technologies and,

more specifically, the odels ith the apa ilit of t a ki g a use s hea t ate.

The full process of participant recruitment, data collection and analysis as well as the ethical

considerations for this project will be outlined in the following sections of this chapter.

Qualitative research, sampling and participant recruitment

Qualitative research

As this research is qualitative the sample will be selected based on what can be learnt from the

participants, with the understanding that the findings from this research project will not be able to

make inferences about the wider population A Pickard (2007).

Qualitative research is the study of different empirical matters, including: interviews, introspection

alongside observation to describe routine and problematic moments in individuals lives Denzin N.K

& Lincoln Y.S (2011). This research will use interviewing alongside observation of behaviours to gain

a better understanding of how users access, interoperate and understand the visualisations provided

to them by Fitbit.

Sampling and participant recruitment

As mentioned at the beginning of this chapter, this project was limited by size and the time available

for it to be completed within. Taking these limitations into account, the sampling method for this

research had to be considered for its ability to recruit participants quickly as well as managing the

fa to the o ious pool of pa ti ipa ts at the u i e sit as sig ifi a tl edu ed due to the summer holiday period.

Because of this, social media was decided upon as the main recruitment tool for potential

participants. The selection process was focused on an information-oriented selection allowing for

the maximum utility of information from a relatively small sample, with cases being selected on the

basis of their information content Denzin N.K & Lincoln Y.S (2011). Using Facebook as the main social

media recruitment tool does create a sampling bias as the sample will be made up of the majority of

the esea he s f ie ds , although Fa e ook s use of the te a e see as ei g a athe loose defi itio . Fa e ook f ie ds of the esea he ill also e a le to sha e the post ith thei Facebook friends, which will in turn widen the pool of potential participants. Due to the age of the

researcher and their Facebook friends age ranges the research was limited to users aged between 18

to 25 years old.

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The U i e sit s olu tee list ould ha e ee a si ila a of e uiti g pote tial pa ti ipa ts. However, due to ethical considerations this was not used during the process due to the potential of

these i di iduals ei g o e esea hed i hi h ase pa ti ipati g i esea h a e o e a burden for them RESPECT (2004).

O e the seed pa ti ipa ts a e gathe ed ia so ial media and interviewed they were asked if they

could suggest other information-rich cases. This method is known as traditional snowball sampling

Li ol Y.“., & Gu a, E.G. . Be ause of Fit it s f ie ds et o k he e use s a o e t ith other users via their phonebook or email address list and compare step counts), this method lends

itself pe fe tl to this p oje t. This ethod lead to t o seed i te ie ees ei g pla ted, o e i London and one in Sheffield from which all participants were sourced and interviewed.

Overall, 15 interviews and two pilot interviews, were conducted. The purpose of snowball sampling

is to maximise information yield, thus suggesting the termination of the sample only when no new

information is being collected making redundancy the criteria for the data collection to come to an

end Pickard A (2007). Lincoln and Guba however suggest that a dozen or so well selected interviews

should exhaust most available information and 20 interviews should reach well beyond the point of

redundancy. In this study 15 interviews were conducted due to the suggested interviewees ending in

Sheffield and London as well as no new information becoming apparent in the latter interviews.

The fi st t o seed i te ie ees e e a tuall used fo the pilot interviews; this was to reduce the

bias in the overall sample. The overall sample could be defined as a convenience sample Patton Q. M

(2002). This leads the research open to bias in its findings; however, due to time constrictions and

available finances for the study this bias just has to be taken into account during the analysis of

results and alongside the findings.

Interview Process

The interviews were structured, except for the two task sections in which the participant would take

full control of the conversation, with the interviewer only intervening to clarify or ask questions at

the end of the process. This structure was chosen for a number of reasons, the lack of experience for

the researcher meant a structured interview relieved nerves and reduced the risk in little or no

information being taken away from the exercise due to inexperience in an informal interview setting

Pickard A (2007).

To reduce the nerves during the real interviews, the interviewer went through the process of

practicing interviews on generic topics with friends Pickard A (2007). These practice interviews were

seen as necessary as the real interviews are the only form of data collection for the research project,

and for them to not be conducted well or information to go uncollected could jeopardise the whole

project.

Interviewing was seen as the most suitable method of data collection for this project because of the

need for descriptive and in-depth data that is specific to the participants whilst being too

complicated to be answered easily Pickard A (2007). Particularly for the graph task sections the

ability to observe behaviours during the interview process made it the most suitable research

method for this project.

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Interview design

The process of designing the interviews for this project followed the seven stages of the interview

process: thematising, designing, interviewing, transcribing, analysing, verifying and reporting Kvale S

(1996). These stages will be outlined further below:

1. Thematising

The themes hoping to be gathered from these interviews can be broken down into two clear

sections.

The first section is for the collection of some general personal information as well as information on

how long the individual has had their Fitbit and what they use it for. The answers to these questions

will help answer some of the research objectives, as well as helping to build a bigger picture on each

individual user.

In the second section the main theme is to understand fully the steps users take to gain

understanding and knowledge from Fitbit visualisations. The findings from this theme will underpin

the whole research project, and the results from the previous theme will be used to inform any

discoveries within this section.

2. Designing

As mentioned previously, the interview will follow a structured approach, however, it will not

involve any predetermined questions or answers. This is to insure the user has the opportunity to

give whatever information they feel relevant to the researcher, without the interview being too

informal and being lead off topic or resulting in little relevant information being collected.

As an important part of this research will actually be through observation, the structure of the

interview; going from personal information questions to the graph tasks allows the researcher to

focus on noting the behaviours during the tasks without worrying about the personal information.

This order was discovered as the best option for data collection during the pilot interviews.

3. Interviewing

Not only did the pilot interviews allow for the order of the interview to be determined as well as

help edu e the ias taki g the seed i te ie ees out of the eal esea h, it also allowed

valuable practice in the process of conducting the interview.

The questions in the interview followed a standardized, open-ended interview method Pickard A

(2007). In this situation the participants are all asked the same questions but are free to answer the

question in any way they felt suitable and were given the opportunity to provide as much or as little

information as they felt relevant to answer the question. By hosting the interviews in this way it will

allow time for the researcher to witness how statements are being said, for example with what tone,

as well as how the participant is handling the tasks.

To fully engage with the participants thought process throughout the graph tasks the interviewer

must be able to and available to note the stages the interviewee is going through whilst attempting

to order the graphs. As well as this it is also worth noting their body language and other factors that

could either support or betray what they are verbally saying to the researcher.

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The decision to record the interviews was not taken lightly due to the considerable ethical issues

associated with doing so. By recording the interviews the researcher has less to worry about in

gathering the verbal dialect from the interview, allowing more time to focus on the participants

behaviours and mannerisms, of which the importance of these factors was mentioned previously.

Another issue with the decision to record the interviews was the discomfort factor it brings to the

interview process, particularly for the participant. All 15 participants were giving the opportunity to

have their interviews not recorded; however none of the participants took up this offer.

4. Transcribing

The interviews are each transcribed immediately after the interview ceases. This allows for the

mixture of observations and spoken texts to be mixed together. During the pilot interviews an

interview guide sheet was developed. This allows the interviewer to follow the order of the

questions, note responses and draw out diagrams of graph orders and any other information

deemed relevant whilst conducting the interviews, a copy of a completed one of these forms can be

found in the appendices.

Using these sheets alongside the audio recordings immediately after the interview has been

conducted allows for any patterns to emerge. The interview questions in the following interviews

were not influenced by the findings in the earlier interviews to reduce the likelihood of researcher

bias and a pattern being forced.

By transcribing each interview immediately after it took place it allowed for the interviews to be

terminated at 15 in the knowledge there was no change in behaviours being reported.

These transcriptions are all on the interview guide sheets, to reduce the amount of copies of the

interviews available reducing the chances of a copy going missing or being stolen – thus reducing the

ethical risk of this research.

5. Analysing

As mentioned briefly above, the analysis of the interviews will take place over the same period as

the transcription. This is particularly important when used alongside the snowball sampling

technique as patterns and trends can be identified and the data collection terminated when there is

no new information available.

6. Verifying

The participants will be contacted once their guide sheets have been completed with all notes on

what the researcher interpreted they said and meant during the interview. They will also have the

opportunity to see any information that had been gathered about them on the guide sheet once

their interview has finished.

None of the participants disagreed with the transcription and interpretations when contacted.

7. Reporting

The research will be reported in a fair and as unbiased way as possible with the use of direct quotes

from the interview section will allow for the findings to be supported with evidence Pickard A (2007).

As well as the method of storytelling to allow the reader to fully understand the participants being

discussed.

16 | P a g e

The graph tasks

The two tasks are really the core to this research project. The quality of these graphs is instrumental,

alongside the execution of the interviews for being able to answer arguably the most important

objective of this research, number four: reate a d de elop a odel displayi g the pro esses a d steps a user goes through whilst disseminating the information provided to them by the

visualisatio . Because of this the quality of the graphs used had to be as similar as possible to the

graphs users would be used to looking at, if they had ever accessed this information previously. The

graphs also had to offer different results, average step counts or days with goals met. This was in

order to give the participant enough of challenge to be able to order the graphs whilst explaining the

order they had decided upon without being too difficult that the participants were unable to order

them. If the challenges were too simple there would be a risk that the participants would just order

them and give basic, undetailed reasoning as to why they are in that order which would be

detrimental to the project.

Whilst reviewing the literature for this project the majority of graph types discussed were line

graphs and bar charts. Fitbit produces a wide range of visualisations including both line and bar

graphs but also pie charts, due to the literature it was decided that for this project the graphs used

during the tasks would be one bar chart and one line graph. These graphs were collected from three

unidentified Fitbit users who offered their data for both steps and resting heart rate over the period

of one month. The graphs chosen are displayed below:

Steps Graph A

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Steps Graph B

Steps Graph C

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Resting Heart Rate Graph A

Resting Heart Rate Graph B

19 | P a g e

The participants were asked questions to gage their knowledge of resting heart rates before being

asked to order the three heart rate graphs together, and then asked questions on recommended

daily step allowances. This was again to test their knowledge on daily average steps before being

asked to order the graphs.

Ethical considerations

As with all research projects, ethical considerations are highly important. As mentioned in the

introduction to this research this project does not involve any vulnerable participants, and does not

cover any highly sensitive or personal topics. Because of these factors the research is considered

lo isk ethi all . Ho e e , the e a e still ethi al issues a d o side atio s su ou di g this p oje t which must be discussed and adhered to. These issues and their solutions will be discussed during

this section.

Before the interviews take place the researcher will collect signed forms stating clear informed

consent from all participants prior to the interviews. It is important that the consent gained from this

research is informed so as to make the dissertation as ethical as possible. There should be no

adverse effects on the research results from gaining informed consent as there is no deception

occurring in the methodology.

When devising the interview questions each question will be considered for its level of risk or ability

to cause harm or upset to the participant. There will be no mention of weight, BMI or personal

wellbeing brought up during the interviews. This is particularly important as it could make the

pa ti ipa t feel u o fo ta le a d ould ake this p oposed esea h high isk ethi all .

Resting Heart Rate Graph C

20 | P a g e

If at any point during the interview the participant decides they do not want to participant anymore

they are allowed to leave and any notes taken up to this point or audio recordings will be destroyed

and not included in the research. The only mention of these participants will be in the findings

report when the number of interviews completed is stated. There will be no mention as to why

these participants decided to abandon the interview.

To reduce the risk of participating in the research all interviews will take place in university buildings

during normal operational hours. In Sheffield these interviews will take place in the Information

Co o s li a a d i Lo do at I pe ial College Lo do s Ce t al Li a .

Due to the nature of the research style it is possible that participants may feel like they are being

tested du i g the g aph tasks. The ill e e i ded that it is ot a test a d the e is o ight o wrong answers, they will also be allowed to refuse to take part in one of the tests if they do not

want to do it without having to withdraw from the interview completely. If the participant is a

university student at Sheffield, they will be reminded their answers will not affect the outcome of

their degree they are working towards.

As the method of sampling for this research project is a snowball sample, there is the issue of if the

participant is offering to partake from their own consent or merely taking part because someone

else suggested it to them ESRC (2016). Because of this, when the participant is contacted and invited

to partake in the interview process it will be clearly explained that this is an optional event and there

is no requirement on their behalf to take up the invitation. They will also be reminded of this before

the interview begins.

The interview will be audio recorded (no video or pictures will be taken) to help with the note taking

process. Although this has ethical implications and may make the participants less likely to talk

openly because they may feel embarrassed or self-conscious it will help with the processing of the

interview notes and increase the quality of the findings from the interview process A Pickard (2007).

As stated before, if a participant decides they no longer want to partake in the interview process,

their audio recording will be deleted.

The issue of confidentiality will be managed during the transcribing section by giving participants

code names during the write-up; the participants names will not be collected during the interview

process to reduce the likelihood of anonymity being broken.

As previously mentioned in the data collection section of this chapter, there was originally a plan to

use the U i e sit of “heffield s stude t populatio fo the esea h. Ho e e the e is a ajor

ethical concern with doing so as the student population is likely to be classed as an over-researched

group ESRC (2016). Because of this, it was decided that all participant recruitment would take place

over social media and via a snowball sample where there are less ethical concerns.

All the data collected will be saved on the University of Sheffield managed Google Drive. This is

password protected to the researcher, and reduces the risk of data loss via theft of the data storage

device. The participants will be made aware of this storage procedure before storing the interview

process begins via the interview participation sheet, which is presented to the potential participant

before the interview begins. The recording from the focus group will be transcribed immediately

and then deleted once the transcript is uploaded onto Google Drive. Any hand-written notes made

21 | P a g e

during the interview, most notably on the interview guide sheets, will have a picture taken of them

and uploaded to Google Drive, with them being shredded once the photo is safely uploaded. These

steps ill p ote t the pa ti ipa t s ights to a o it a d e su e the data olle ted is sto ed safel and securely.

22 | P a g e

Results of the research project Overall, 15 participants were interviewed with each interview lasting roughly 20 minutes each. The

average age of participants was 21; the youngest participant was 19 years old and the eldest 24. All

participants were either studying for a degree or had already completed university level education.

On average, participants had had their device for seven months, with the participant owning theirs

for the longest having had it for 19 months and the participant with the shortest length of ownership

having had theirs for just one month. Overall there were seven females and eight males interviewed,

there was no conscious effort made by the researcher to keep this equal and this near equal split

came from the snowball sample. Six interviews took place in London; the other nine took place in

Sheffield.

There were only two interviews that fell through, both prior to the arranged interview day due to

illness (one in London and one in Sheffield); none of the interviews that began were terminated.

Three participants stories

The Interviewer asked the participant some focused questions and also allowed for the participant

to expand on their answers, as well as allow them to add any information they felt relevant to why

they held their views. From this, some interesting viewpoints and explanations unfolded, these are

outlined below; for ethical reasons all participants names have been changed.

The stories outlined below include information on why the participants purchased their Fitbit, as

well as their knowledge of recommended steps and dangerous resting heart rates.

Jane s story Jane is a 23-year-old young professional working as a graduate in London for a multinational health

lifestyle company. She regularly plays sport, keeps fit and regularly represents Team GB in ski racing

events as well as playing nationally in a number of other sports.

Jane was keen to partake in the interview process because she is fascinated by the power of her

Fitbit and the access to information it gives her. She bought a Fitbit off the recommendation of her

fathe ho lai ed it as the est p ese t he e e e ei ed f o his ife ; Ja e s ai oti atio for purchasing and using a Fitbit was to monitor her heart rate whilst she is playing sport.

At the time of interviewing Jane had been a Fitbit user for 12 months, and reported to regularly

check both her steps and heart rate daily. She had no hesitation when asked about both Fitbit and

the NHS recommended amount of daily steps, 10,000 a day and went as far to say she personally

feels on the weekends you should be aiming for 12,000.

When asked about resting heart rates, the reason she bought a Fitbit, she said she had no idea what

a dangerous resting heart rate is. Although she did know your heart rate is affected by your age and

fitness, once pushed for an answer she answered a resting heart rate above 55 an answer she got to

by thinking about her own heart rate, age and fitness. In reality a resting heart rate of 56-60 would

be viewed as very healthy and a heart rate of a particularly fit individual.

Dan s story Dan is a 22 year old whom has just finished his fifth year of medical school in Sheffield. He regularly

keeps active playing hockey at a high level, including regionally, regularly for three different teams.

23 | P a g e

At the time of interviewing he had been using his Fitbit for six months and was regularly checking

and tracking both his steps and heart rate every day.

Dan was honest in admitting his reasoning for purchasing his Fitbit was that really it was just an

impulse purchase, however he was intrigued in the data it would produce as well.

Despite having spent significant time studying medicine, Dan was unsure about what constituted a

dangerous heart rate. When pushed Dan hazarded a guess based on what he had seen previously

when looking at his own resting heart rate graphs and gave the answer of 80+ as what he would

constitute a dangerous heart rate.

When asked about step counts he was confident in his answer that Fitbit recommended users do

, a da , although he oted that this step ou t goal ould e edu ed fo those who struggle

to get 10,000 a day to a number more manageable to begin with. However when Dan was

questioned on the number of steps the NHS recommends he was unsure, his body language

suggested he was rather embarrassed at not immediately knowing the answer to this question.

He eventually gave the guesstimate of 6,000 steps per day, based on his knowledge that 10,000 is

hat Fit it e o e ds a d ge e all the NH“ offe s pitiful ad i e o e e ise a d fit ess, so it ill e sig ifi a tl elo , .

Matt s story Matt is 24 and currently looking for a job, previously he worked in health insurance. He has had his

Fitbit for nine months, and was given it through his previous job for a health policy; however he still

uses it as he finds the information it provides interesting and informative. He likes to keep fit and

occupies himself by regularly going to the gym as well as regularly playing sport on the weekends for

fun.

He came across as confident when stating that a resting heart rate of 90 or above is dangerous and

notes that he regularly checks his heart rate, although he did also mention that he does not sleep

with his Fitbit on (Fitbit recommend users wear their Fitbit to bed to help the device determine an

accurate reading of the users resting heart rate).

Despite admitting to tracking his steps at least daily he also admitted to not knowing the amount of

recommended steps for the NHS or Fitbit. He correctly guessed that Fitbit recommended 10,000

based on his knowledge that 10,000 steps per day is the first goal Fitbit sets users, although he

upped his step goal to 12,500 due to the requirements for his health policy that gave him his device.

He guessed the NH“ s ta get at , steps pe da ased o the elief that it ould e a sig ifi a t amount, ut also a easil a agea le a ou t of steps .

The above three cases were all pinnacle cases in this research project and were picked for their

unique and interesting factors. There are obvious similarities between these cases, as well as there

being similarities with the results from some of the other interviews. These factors will be discussed

in the next chapter: the discussion and analysis of results (page 30).

24 | P a g e

Results from the graph tasks

The results from both graph tasks will be outlined below. The meaning of these results and as to how

or why they were selected will be outlined in the following chapter (page 30).

Resting heart rate graphs task results (line graph page 18-19)

Overall these graphs were only sorted into two orders by the participants, despite there being the

pote tial fo si diffe e t o i atio s. E e pa ti ipa t put g aph C as ha i g the est esti g heart rate, it was then between graphs A and B as to which was the second best. The researcher

noted three participants looking stressed or nervous over this decision; however only one said they

felt the ould ot a s e ut if pushed the d go fo esti g hea t ate g aph A ut fo o easo other than instinct.

Table showing the frequencies of orders of Resting Heart Rate graphs participants gave during this

research project

Combination with the best graph being shown first

Amount of times given Percentage of answers

C - A - B 10 66%

C - B - A 5 34%

Once these answers were given, finalized and the order checked to reduce the chance of the

interviewer having misunderstood or written the results down wrong the interviewer asked the

participant to explain what factor was the most important consideration for them whilst ordering

the graphs followed by their second consideration etc. In the resting heart rate task four participants

had no second considerations; none of the participants in this task had a third consideration. The

eakdo s of people s o siderations are outlined in the table below:

Again, these results will be discussed in the next chapter the discussion of results.

Table showing the breakdowns of participants first and second considerations when ordering the

resting heart rate graphs

Consideration Amount of times

given as a 1st

consideration

Percentage of 1st

considerations

Amount of times

given as a 2nd

consideration

Percentage of 2nd

Considerations

Average value of

the HR

7 47% 1 7%

Range of the HR 1 7% 5 33%

Consistency 5 33% 4 27%

A downward

trend (the RHR is

decreasing)

2 13% 1 7%

No second stage

of consideration

4 26%

25 | P a g e

Step graphs task results (bar chart page 16-17)

Unlike the resting heart rate graphs the participants sorted these graphs into four different orders,

again there was a possible six different combinations the graphs could have been ordered into. The

vast majority of participants were able to agree on graph B having the best step graph over the

period; however two participants put A as being the best graph.

There were no obvious signs of stress from any of the participants during this task, and only one

participant struggled to give an answer. However, given time to think about it they were able to

order the graphs although admitted they were not wholly convinced they knew the difference

between the graphs they had positioned in second and third place.

Table showing the frequencies of orders of step bar chart graphs participants gave during this

research project

Combination with the best graph being shown first

Amount of times given Percent of answers

B - C - A 7 46%

B - A - C 6 40%

A - C - B 1 7%

A - B - C 1 7%

In the same fashion as the resting heart rate task once the answers were given, finalized and the

order checked to reduce the chance of the interviewer having misunderstood or written the results

down wrong the interviewer asked the participant to explain what factor was the most important

consideration for them whilst ordering the graphs followed by their second consideration etc. In the

step task four participants had no second considerations, three of these four had no second

considerations on the resting heart rate graphs as well; as with the resting heart rate tasks none of

the pa ti ipa ts i this task had a thi d o side atio . The eakdo s of people s o side atio s are outlined on the table on the next page.

26 | P a g e

How Jane, Dan and Matt responded to the tasks

Presented below is a detailed description of how the three participants discussed at the beginning of

this chapter answered and went about the two tasks. These three participants were chosen to be

focused on as their results were of particular interest as well as representing the overall research

group, with their generic information.

Jane s tasks On seeing the heart rate graphs before her Jane was immediately embarrassed at her remark that a

hea t ate a o e a e u health I assu e ou e o l used graphs from vaguely healthy

i di iduals as he fi st espo se. Whe o de i g oth sets of g aphs, her passion for fitness and

exercise was obvious with the heart rate graph, her first consideration being that the heart rate

graph should be getting lower and then that it was gaining a consistent trend.

Despite putting graph A as second, she admitted it could be getting worse by the fact it was

beginning to increase again. Whereas with graph B, which Jane considered to be the worse of the

three, she noted that this person was likely to be getting fitter by the fact the trend was downward

but the resting heart rate was beginning to rise again. As the participants were told, there is no right

or wrong order for the graphs as all the graphs were taken from healthy active humans. This is

Table showing the breakdowns of participants first and second considerations when ordering the

resting heart rate graphs

Consideration Amount of times

given as a 1st

consideration

Percentage of 1st

considerations

Amount of times

given as a 2nd

consideration

Percentage of 2nd

Considerations

Consistency of

reaching goal

13 86% 2 13%

Highest average

step count

1 7% 1 7%

Consistency of

having a high step

count

1 7% 0 n/a

How close they

were to reaching

their goal

0 n/a 7 47%

How often signs

of exercise are

shown

0 n/a 1 7%

No second stage

of consideration

4 26%

27 | P a g e

important to note, as it makes the participants ordering being similar a positive result as it suggest

the participants do have an understanding as a whole of what makes a more healthy human.

Jane noted that in her case, a high esti g hea t ate fo he suggested she d had a st essful da at work and that this could be used to explain why some of the graphs fluctuate so vastly.

During the step task Jane again showed her prowess for sports and exercise. She was confident in

answering and able to give full explanations for each of her answers she positioned the graphs in the

order of B -> C -> A. Her reasoning for this followed her clear motto of 1) how consistently someone

is in meeting their target 10,000 steps followed by 2) how often in a week they exercise. When

positio i g A as the least est she ade the poi t that although thei o th sta ted phe o e all ell, utti g do to so little e e ise so sha pl is e gi g o ei g u health .

Dan s tasks As mentioned in the previous extract about Dan, despite studying medicine and keeping active

himself he does not know a huge amount about health data and statistics. Dan approached the heart

rate task with a basic approach; you want a low heart rate preferably without many fluctuations in

its rate. From this formula he was able to easily decipher that graph C with its low heart rate and

very few fluctuations was the best followed by A and then B. Some participants struggled to pick

between A and B; however Dan was able to consolidate his decision with the statement that

although g aphs A a d B a e si ila i o siste , o e all A al a s has a lo e hea t ate tha B .

In the step task Dan again went about the task by defining himself a formula to follow and then

ordering the graphs to match what he thought were the two key things to having a healthy step

graph. Firstly, the person should be consistent in their daily steps and secondly they should be doing

as near to 10,000 steps a day as possible. From this formula he was able to sort the graphs into the

order of B -> C -> A, picking graph C as better than A because he believed it was more consistent

than A.

Matt s tasks

Matt was very confident in how he handled the heart rate graph tasks, following on from his

confidence i his k o ledge of a good esti g hea t ate. He sa C as ei g the est hea t ate graph due to its position as the lowest heart rate out of the three as well as its consistency

compared to the other two. He positioned B as second best because of its downward trend and

oted that A s hea t ate as all o e the pla e a d sho ed little t e d o o siste .

For the step graph challenge Matt was again sure of his approach, but not as confident as he had

been with the heart rate graphs. Matt made the decision that step graphs should be ordered as B ->

C -> A due to his process that the best graph would be consistently meeting or beating its step goal

and the second would be how close to beating their target they were (i.e more active regularly).

The similarities and differences between these approaches will be discussed in more detail in the

next chapter.

Other notable findings

Beyond the findings listed above, there were other findings discovered in this research. These will be

described in this section.

28 | P a g e

Participants health data knowledge

Some of the questions in this research enabled the researcher to discover more about the

pa ti ipa t s k o ledge of health data, the esults f o these ha e ee dis ussed a d i luded as key factors of Jane, Dan and Matt s sto ies. Ho e e , this i fo atio as olle ted fo all participants and is presented below.

Knowledge of a dangerous resting heart rate

A normal resting heart rate is between 60- eats pe i ute p , if a pe so s esti g hea t rate is constantly above 120bpm they should seek medical advice, although this may still be normal

NHS (2015). For the purpose of this research a resting heart rate of above 100 will be considered

dangerous, as the participants were all regularly partaking in sport and it would be unlikely they

would ever experience a heart rate of this level.

The range of answers given to this question goes from 55 avg. bmp to 120 avg. bmp, with the modal

response was 90 avg. bmp. Overall there were only five correct answers given to this question.

Knowledge of the NHS and Fitbit’s recommended daily step goals Both the NHS and Fitbit recommend adults should aim to do 10,000 steps every day. When the

participants were questioned on each of these guidelines their responses were as follows:

From this table it is obvious that the participants were more confident and clearly knew more about

Fit it s guideli es tha the NH“ s despite all pa ti ipa ts ha i g li ed i the UK.

Participant Number NHS Guideline Fitbit Guideline

1 10,000* 10,000

2 6,000 10,000

3 10,000 10,000

4 10,000 10,000

5 12,000 10,000

6 7,000 10,000

7 10,000 10,000

8 10,000 9,500

9 5,000 10,000

10 10,000 10,000

11 10,000 10,000

12 10,000 10,000

13 10,000 10,000

14 10,000 10,000

15 10,000 10,000 Number of correct answers 11 14

*text in italics indicates where the participant stated their answer was a guess

29 | P a g e

Reason for the participant purchasing/using their Fitbit

Originally, this was just purchasing however, the research showed the majority of participants were

actually given their Fitbit as a gift. To allow for this, after responded the Fitbit was a gift or given to

them for another reason they were asked why they used it still, the breakdown of both of these

questions can be seen in the tables below:

Fitbit was a gift Purchased the Fitbit

themselves

Given to them not as a gift

(e.g. for a company health

policy)

9 4 2

The easo s h pa ti ipa ts o ti ued to use thei Fit it s e e a ied, ut ha e ee so ted i to a table below:

Reason for use given Number of participants mentioning this reason

Useful for tracking health information 5

Intrigued in my health info/how active I am 3

Help me monitor my activity levels 3

Wanted to get fit 1

Help monitor my HR during sport 1

I a ted to e pa t of the lu 1

It s a it of fu 1

30 | P a g e

Discussion of the results In this chapter the results from this research project outlined in the previous section are discussed in

detail with relation to both similar literature and theories as to why the results are the way they are.

There will also be discussion of any biases within the research that may have affected the results of

this project during this section.

Discussion of the importance of the three participants

The previous chapter explained in detail the interviews carried out with three particularly interesting

participants. Although Jane, Dan and Matt are all older than the average age of the participants they

are good representations of the 15 interviewees: highly educated, regularly active as well as offering

a range of responses throughout the tasks.

The importance of Jane

In comparison with the sample Jane had been a Fitbit user for a significant amount of time (five

months more than the average). She made it very clear her Fitbit was purchased for the purpose of

tracking her heart rate, and when asked to clarify this after the write up of the results chapter she

agreed that the heart rate monitor is and was the most important feature of her Fitbit. However, out

of all of the participants she fared the worst on the heart rate knowledge question. This could be

explained by point made in the literature chapter of this research project: participants may feel

detached from the graphs provided and this could influence their views. In this case Jane used her

prior knowledge of her heart rate graphs to answer a question she was unsure about, which lead her

to provide an incorrect answer.

Although this lead to Ja e s espo se ei g i o e t, it is ot e essa il a egati e pa t of Ja e s psychology. So long as Jane continued to monitor her own resting heart rate she could live a healthy

lifestyle, with her resting heart rate gradually increasing with her age and fluctuating with her

various levels of fitness throughout her life. Here is an area for further research, to understand if

Jane would know when her heart rate had reach a dangerous level or if the incline was steady she

would just ignore it and assume it to be the norm, which following the logic used by herself is a very

viable outcome of her method of discovery. This result, however, could also suggest that Jane may

be able to live a healthy and active lifestyle without ever actually knowing how to use her health

information correctly.

When completing the heart rate tasks Jane stuck to her belief that the lower the heart rate the

better, and made this her first consideration when ordering the heart rate challenge information.

This decision solidified what Jane had suggested when questioned on her knowledge that a low

heart rate is the key to a healthy heart rate – i Ja e s ind. When justifying the graphs she again

related to her own experiences form the previous year of tracking her heart rate noting that

fluctuations could be the result of particularly stressful days, something she has noticed affects her

own heart rate daily.

Her habit of relating her decisions and views to her own experiencing continued into the step graph

halle ges he e he se o d o side atio poi t as ho ofte i a eek the e e ise . Making

the point that living a healthy lifestyle, in her view point, is about being active constantly for

example, doing an extra 2,000 steps per day on the weekends when she has more time.

31 | P a g e

The importance of Dan

Da s ho est a out his easo i g fo pu hasi g his Fit it ei g as a i pulse pu hase is hat made his interview special. Like Jane he is regularly active and has a real motivation, in his high level

sporting achievements, for keeping himself healthy. However, again, when asked about dangerous

resting heart rates he faltered and relied on his knowledge from his own Fitbit visualisations for the

information on which to form the knowledge of a dangerous resting heart rate rather than that of

his highly relevant degree.

Having purchased his Fit it o i pulse it ould e suggested it as the o elt feel of the Fitbit

that intrigued him originally. Another participant stated the novelty feeling as their reason for

continued use of their device. The access to constantly fluctuating data makes the device more like a

toy than just a health care device was reported as a reason why the uptake and regular continual use

of Fitbit technologies are so good Gao Y et al. (2015). When Dan was approached for clarification on

his motivation of purchasing his Fitbit he mentioned the ease of constant access as fuelling his

intrigue.

Dan was unsure about the NH“ s e o e ded step ou t, a d used his k o ledge f o his pe so al e pe ie e ith the NH“ alo gside his k o ledge of Fit it s e o e ded step ou t to formulate a guesstimate. Although his result was incorrect the method of recalling his knowledge of

e pe ie es a d i fo atio f o diffe e t sou es as i te esti g a d Da s esulti g o g answer not necessarily a negative effect of his knowledge, it was more that he had bared witness to

a negative experience that i pai ed his ie s o the NH“ s p o ess of issui g guideli es.

The importance of Matt

Similarly to Dan, Matt used his knowledge from his experience of using a Fitbit to answer the

questions on recommended daily step goals: as with Dan he associated Fit it s auto ati , steps a day goal as suggesting that is the amount of steps your Fitbit is programmed for when it is

first set up. Again much in the same way as Dan, Matt makes the assumption that the NHS guidelines

ould e lo e tha Fit it s , 0 as he expected the NHS to suggest a more manageable amount

of steps.

Matt s o e ts that he does ot sleep ith his Fit it o suggest he is ell i fo ed o the o e t practices for getting the best results from his device. At the beginning of the interview he mentioned

he had his Fitbit technology through a health policy for his previous job, during the literature review

process this was thrown up as an ethical and possible data protection issue with wearable

te h ologies. Matt s al ost defe si e ut informative suggestion that his heart rate tracker may not

e pe fe t e ause he does ot sleep ith it o ould suggest he felt p essu ed to ha e a good resting heart rate. This is an area of uncertain ethics and is an avenue for further research in this

area.

Findings from the heart rate graph tasks

E e pa ti ipa t put g aph C as ei g the est g aph out of the th ee i this task. G aph C s esti g heart rate is by far the lowest, even at its peak as well as having the least fluctuation as well as range

between the highest resting heart rate and the lowest. This is in agreement with the 47% of

participants who put the average value of the resting heart rate as their most important first

consideration when sorting the diagrams. The second most popular first consideration was the

32 | P a g e

consistency with 33% of participants stating it as their first choice, heart rate graph C is by far the

most consistent of the three graphs, so again this fits.

Two participants put a downward trend as their first consideration; this does not seem to fit with

graph C being their first choice graph (as it has to have been as no participants put C as their second

or third best graph). These two anomalies are the only results that do not fit in this part of the

research, as the participants were all asked to clarify their responses once written down it is possible

they were thinking ahead to their second stage whilst working on their first, but there is nothing in

this research to explain why these participants gave these answers.

26% of participants had no second considerations. This was a surprising result as it could have been

assumed that with 3 graphs there would be 3 different stages to ordering the graphs especially when

explaining for example: graph A is first e ause of XXXX, then graph B as it does XXXX, finally graph

C is the orst as it does XXXX hi h akes it the least fit i y opi io however, during the

i te ie s it t a spi ed that the pa ti ipa ts eated thei o ules as to hat justified hat a

good o a ad g aph i thei i ds a d the fitted the o de of the g aphs to thei pe so al formulae. This method allows for participants to order graphs by only one feature, although if this is

the best method for discovery or allows the graphs to be ordered in a fair method remains to be

seen.

The majority of participants (63%) put A as the second best graph followed by B. This roughly fits

ith the esults gi e i the o side atio s as g aph A s a e age heart rate is defiantly lower than

g aph B s. Whe eas % of pa ti ipa ts put g aph B as ette tha g aph A, % of pa ti ipa ts put consistency as their most important consideration when ordering the graphs – a perfect match.

This result suggests that when dealing with resting heart rate information as novices the most

important factor is consistency. These participants knew little about health data, however were able

to gather information from other similar situations to formulate an answer that suited them. This is

al ost a su i al e ha is , ith the pa ti ipa t doi g all the a to su i e the uestio , ith this research suggesting that in this case that mechanism is working and in doing so is allowing

participants to answer questions they otherwise might not know how to answer.

Findings from the step graph tasks

In contrast to the resting heart rate graphs there were a number of responses as to the potential

ordering of the step graphs. Interestingly this graph could have been plotted as a line graph as

number of steps per day is continuous data, for this project having the data produced as a line graph

may have produced better results as making the comparison over the whole month would have

been much easier and could have resulted in a response similar to the resting heart rate results

where participants were able to sort the graphs more easily. However, for day to day motivation the

bar chart produced by Fitbit is better as you can see a day as being a singular target with a beginning

an ending and a goal step count. This again is a possible area for further research.

The step graphs were chosen for this research as they form bar charts, which due to their popularity

and ease of showing information are regularly used in everyday life alongside line graphs University

of Leicester (unknown). Line graphs are a popular way of showing time-series data such as the

resting heart rate over the period of the month University of Leicester (unknown). As all of the

participants in this study were educated up to university level it a justified assumption they will have

33 | P a g e

at least a GCSE grade C in mathematics and thus will have had experience with both these forms of

data visualisations in the past.

The university level education could explain the lack of stress noted during the task, as the process

for decoding the graphs would be unfamiliar to any of the participants, and they had all seen a

similar graph of their own data before hand so understood the layout.

There were more considerations taken on board during this process than there were for the heart

rate challenge. This could possibly be linked to the fact it appeared that the participants knew more

about the steps in general than the resting heart rate (only five participants correctly answered the

question about a dangerous resting heart rate, compared to 14 knowing the Fitbit guideline for

steps).

The mixture of different results could also be explained by the colour scheme chosen by Fitbit for

their step bar graphs. The bars light up as green if the 10,000 step target has been met, but are a

grey colour if the target has not been met. A few participants had to be told there were bars where

the grey bars stood, as they were not easily seen against the white background of the chart. This

colour scheme made noting which graphs data had done exceptionally well very easy to spot,

however a graph that has maybe not reached 10,000 everyday but had done 9,999 every other day

could have been easily overlooked. Colour inclusions in bar charts have the ability to reduce the

number of eye movements between the bars a reader has to make to gather the data, however, in

this case those reduced eye movements may lead to information not being considered correctly

Stewart B.M et al. (2009).

13 out of the 15 participants put graph B as being the best, which directly aligns with 13 participants

listing consistency as being their 1st

consideration. The confidence displayed in consistency being key

also points towards the participants feeling more confident when completing this task than the heart

rate task. There is nothing in this research to suggest this is because of the bar chart format instead

of the line graphs, but the confidence in answer the step question would suggest not. However to be

certain this would need to be another area for potential further research.

Other notable findings discussed

The majority of these have already been discussed in contention with their relevant areas. However,

the reasons given for why participants use their Fitbits have produced some interesting results. This

research found that on average participants had had their device for seven months, nine participants

reported their Fitbit was a gift seven months prior to this research commencing was December 2015,

which could offer an explanation as to why the majority of participants received their device as a gift.

Because of this discovery the question about the reasoning for purchasing was shifted to the

participants reason for continued use instead.

The most popular reason for use was to track health information, however a significant amount

stated their intrigue into the information or to understand how active they are on a daily basis. This

i fo atio is eall a aila le usi g Fit it s full pa kage a d suggests use s a e i te ested i keeping a track of how healthy or active they are in exchange for making this, arguably very personal,

information readily available to Fitbit. However, two very honest participants gave their justifications

as it s a it of fu a d I a ted to e pa t of the lu . It is these t o justifi atio s that eall show why Fitbit is so successful at what it does – having a Fitbit is cool.

34 | P a g e

Similarly to the Charlotte Crosby and Holly Hagen effect mentioned in the introduction section,

being physically fit and leading a healthy lifestyle is becoming more of a status symbol and the

ultimate accessory to this is a wearable health device, most notably a Fitbit. The comment of

e o i g pa t of the lu is ith ega ds the Fit it app. The app allo s use s to o e t thei devices together and compete over the number of steps each can do over a set period of time, as

ell as o pili g a li e eekl step ou t leade oa d.

This esea h did ot take i to o side atio the ool fa to . Fo as lo g as Fit it, a d the healthy

lifestyle movement are seen as the lifestyle goal of 2015/16 and possibly 2017 there is little value in

users understanding their heart rate information as this research does not suggest that is why users

are actually purchasing their devices for. If they were interested in their health information they

would be more informed about dangerous heart rates, when in reality the only participant who

really suggested they completely subscribed to their Fitbit heart rate information was Jane.

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Conclusion This research took place over a three-month period with the two weeks focused on participant

recruitment, completion of the interviews and confirmation of the interview notes. By having these

stages compacted into a shorter amount of time it allowed the researcher to make links and

discoveries whilst all the interviews were still a recent memory.

Some of the methods used during this dissertation caused ethical issues and increased risks of bias in

the results. However, these have been discussed at length within the methodology section and

elsewhere and, overall, with the time frame available and the limited amount of available

participants due to the timing of the research (taking place over the summer holidays) as well as the

financial restrictions of not being able to offer expenses for participants to take part in this research

the results achieved, are good quality and fair.

Despite the above the project did provide some relevant and reliable (within reason) results as well

as areas of possible further research. The final aim of this project was to create a model of how Fitbit

users access and disseminate information from their visualizations, this suggested model based on

these findings will be displayed in this chapter as well as conclusions from the findings and possible

further research opportunities.

Conclusion of the findings

The majority of the participants were unsure about resting heart rate graphs, despite having tracked

their own heart rates for varied amounts of time. There was no indication that having had a Fitbit for

longer made the participant more confident when working with the heart rate graphs. However,

when participants were unsure their first method for calculating an answer was to use prior

knowledge and apply it to the situation, for example when Dan used his personal experience with

the NHS to answer the step question or Jane using her detailed knowledge of her own heart rate to

make a guestimate on what a dangerous resting heart rate would be.

A moderately concerning finding was also born from this research in that by regularly tracking health

i fo atio use s ould sleep alk i to a da ge ous situatio e t e el high esti g hea t ate without noticing that their heart rate is at an unhealthy level. As this was only found with one

participant and other interviews only showed vague continuations of this trend this finding cannot

be confirmed from this research alone. The same phenomena could also suggest that, contrary to

the literature, a user may continue to live a healthy and balanced lifestyle without good knowledge

of what a healthy heart rate is.

When disseminating the graphs produced by Fitbit the participants created their own formulas to

which they were able list the graphs by following. This was a rather surprising result as explained in

the discussion of the results PAGE, however shows that when the participants were unsure they

were always able to produce answers even if these came from prior knowledge or other sources

without relying on purposely learnt information.

The ool fa to as so ethi g dis ussed i the dis ussio of the esults PAGE as so ethi g this research had not considered. Had the methodology accounted for this factor it is possible this result

could have been seen more widely across all participants.

36 | P a g e

Suggested model of how participants gather information from the

visualizations

From the results and by analysis of the interviews this research suggested that participants had two

routes to developing their answer to the graph challenges. These two routes can be seen below, the

most notable difference between these two routes is that some participants found it easier to

position the worst graph first instead of the best. This was not included in the results section as it

was dee ed to e o e of a glass half e pt o half full effe t athe tha a a tual logi al o purposeful decision by the participants.

The arrows between the decision boxes show the process of the participants justifying their

decisions, with the dotted arrows displaying the important point that independent of whether the

participant started from the worst or the best graph, they were constantly questioning and

rethinking their decision.

This model could be used or developed in the future to explain how Fitbit users go about accessing,

disseminating and understanding their personalized visualizations – the main aim of this research

project. Although this project has its own biases and flaws within its methodology, a further

development of a similar methodology and experiment could be used to add to this model.

How this research met its aims and objectives

Here the objectives outlined in the introduction (page 5) will be discussed in how this research has

met them to answer the research question.

1) Discover if users who have had their device for longer look and disseminate the graphs

and visualizations differently to newer users: due to the participants recruited this was

unable to be fully researched. However, with the range of the participants available it was

found that there was no correlation with how long the user had their device for and the

method at which they went about examining the graphs.

2) Gain an understanding of what external knowledge of health and wellbeing helps the user

make decisions based on the information available to them: this aim developed into being

one of the most interesting parts of this research project and enabled the researcher to

37 | P a g e

make some of the more interesting discoveries around the lack of knowledge of resting

heart rates. As well as the higher level of interest shown by participants in the step graph

challenges, most probably due to their better understanding of this area.

This research showed that their knowledge from their everyday lives was where the

participants gathered the most information for disseminating the graphs, and would suggest

that in the future Fit it should do a ui k lesso o u a Massi e O li e Open Course

(MOOC) in health information for users to gain the knowledge they need to use their device

effectively. Especially as all participants in this research were educated to a high level and

still struggled with the knowledge required.

3) Discover if users actually look at the visualizations and graphs: every user in this study

claimed to regularly look at their visualizations. However, few were able to actually use this

regular access to explain the graph tasks. The findings from this would also point towards a

MOOC or one off lesson for new users to gage the importance of this highly personal

information prior to regular use and potential dependency on the information.

4) Create and develop a model displaying the processes and steps a user goes through whilst

disseminating the information provided to them by the visualizations: This model is

presented above, and shows how the participants came about answering the graph tasks. It

is discussed in detail on page 34. It is worth noting that further research would be required

to confirm the results found and displayed in the model as well as to develop the model

further in the future.

Overall this research did reach its overall aim of discovering how users of wearable technologies

access disseminate and develop understandings of the visualisations. However, a lot of the findings

need further research to insure they are not one off occurrences as well as to reduce the bias in the

research methodologies.

Further research opportunities

Fo this esea h s findings to be widely accepted the experiment would need to be retested to

ensure its findings accurate and not subject to chance, this is the first and most obvious further

research to be required from this project. Beyond this however, a significant amount of different

research areas have arisen from the results of this project, these could be used as avenues for future

research.

O e of the o e i te esti g a eas fo fu the esea h a e f o Ja e s dis ussio a out ho she uses her Fitbit to monitor her heart rate. Her discussion of how she regularly follows her heart rate,

to the point she is aware if she has had a particularly stressful day, could lead you to believe she is

ready to track her heart rate to the grave. Understanding if or when Jane would realize her heart

rate is dangerous is an interesting avenue for further research, and is important to the wider

literature in this fast growing field of study, as it is something that has not yet been considered.

Matt s i te ie also ielded a othe dis o e fo hi h fu the esea h ould e i te esti g o necessary in where the devices are used as part of health policies or in the work place. Not only does

this raise an ethical dilemma that need researching and critically analysed, Matt s de isio to i fo the researcher that he does not sleep with his Fitbit on thus affecting his heart rate monitors

elia ilit suggests he a feel p essu ed i to ha i g a good hea t ate fo this health poli . Raising more ethical issues around this area, as well as another possible avenue for future research.

Word count: 13,424

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Appendices

Letter of ethical approval

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Copy of a completed interview guide sheet

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