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i n t e r n a t i o n a l j o u r n a l o f m e d i c a l i n f o r m a t i c s 8 0 ( 2 0 1 1 ) e203–e213
j ourna l homepage: www.i jmi journa l .com
esigning personal exercise monitoring employing multipleodes of delivery: Implications from a qualitative study on
eart rate monitoring
atarina Segerståhl ∗, Harri Oinas-Kukkonenniversity of Oulu, Department of Information Processing Science, P.O. Box 3000, FIN-90014 Oulu, Finland
r t i c l e i n f o
rticle history:
eceived 13 February 2011
eceived in revised form
3 August 2011
ccepted 26 August 2011
eywords:
onsumer Health Informatics
eart rate monitoring
nternet
uman–computer interaction
a b s t r a c t
Purpose: Various personal monitoring technologies have been introduced for supporting
regular physical activity, which is of critical importance in reducing the risks of several
chronic diseases. Recent studies suggest that combining multiple modes of delivery, such
as text messages and mobile monitoring devices with web applications, holds potential for
effectively supporting physical exercise. Of particular interest is how the functionality and
content of these systems should be distributed across the different modes for successful
outcomes.
Objectives: The aim of this study was to: (a) investigate how users incorporate a system
employing two modes of delivery – a wearable heart rate monitor and a web service – into
their training and (b) to analyze benefits and limitations in personal exercise monitoring
and how they relate to the different modes in use.
Methods: A qualitative field study employing diaries and semi-structured interviews was
carried out with 30 participants who used a heart rate monitoring system comprising a
wearable heart rate monitor, Polar FT60 and a web service, Polar Personal Trainer for a period
of 21 days. The data were systematically analyzed to identify specific benefits and limitations
associated with the system characteristics and modes as perceived by the end-users.
Results: The benefits include supporting exploratory learning, controlling target behavior,
rectifying behaviors, motivation and logging support. The limitations are associated with
information for validating the system, virtual coaching, task-technology fit, data integrity
and privacy concerns. Mobile interfaces enable exploratory learning and controlling of target
behaviors in situ, while web services can effectively support users’ need for cognition within
the early stages of adoption and long-term training with intelligent coaching functionality.
Conclusions: This study explains several benefits and limitations in personal exercise mon-
itoring. These can be addressed with crossmedial design, i.e., strategic distribution of
functionality and content across modes within the system. Our findings suggest that per-
sonal exercise monitoring systems may be improved by more systematically combining
mobile and web-based functionality.
∗ Corresponding author. Tel.: +358 405560512.E-mail addresses: [email protected], katarina.segerstahl@
386-5056/$ – see front matter © 2011 Elsevier Ireland Ltd. All rights resoi:10.1016/j.ijmedinf.2011.08.011
© 2011 Elsevier Ireland Ltd. All rights reserved.
gmail.com (K. Segerståhl).erved.
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commitment and positive exercise self-efficacy. This studyfeatures a system that focuses on supporting not only physicalactivity per se, but sustainable training practices.
1 The study protocol was approved by the Stanford University
e204 i n t e r n a t i o n a l j o u r n a l o f m e d i
1. Introduction
Today’s sedentary way of life facilitates several threats topublic health, including obesity, heart disease, hyperten-sion, diabetes, anxiety and depression. These threats couldbe significantly reduced with preventive behaviors, such asimproving nutrition and engaging in regular physical exercise[1]. However, achieving sustainable changes in lifestyles can bechallenging [2]. Ubiquitous computing, modern sensor tech-nologies and the popularization of the Internet have broughtforth a variety of applications aiming at promoting personalhealth and wellness [3–5]. In this work we focus on technologypromoting sustainable physical exercise.
There are many ways to track physical activity and exer-cise. Currently the most common technologies available forlaypeople include pedometry, heart rate monitoring and three-dimensional accelerometry [6]. In this study we investigatea case featuring heart rate monitoring, which is currentlyconsidered as a sufficiently accurate and technically reli-able measure of physical activity, is widely available and hasdemonstrated potential in promoting regular physical exer-cise [6–10]. Heart rate monitors for consumer use are generallymobile devices with wearable sensors that log heart rate dataduring physical activity. Many current mobile solutions arealso complemented with web services providing additionalsupport for logging, sharing and analyzing data.
Recent studies encourage the use of crossmedial config-urations – systems employing multiple modes of delivery– for more effective interventions [11–13]. The Internetis often referred to as a primary mode of delivery, withemails, telephone, Short Messaging Service (SMS), CD-ROMsor videoconferencing as supplementary modes of delivery[11]. Interactive data collection devices, such as pedometers,mobile phones and heart rate monitors may also be used asmodes of delivery [14]. They are particularly useful in situa-tions where access to the web is limited and where interfaceswith larger screens and input devices are not appropriate.When lifestyle interventions are based on mobile and wear-able technologies, the web in its conventional form (beingaccessed from personal computers and smart phones) is oftena supplementary mode. This study objectively investigates thecomplementary roles that modes may play.
Personal monitoring technologies come with several limi-tations in terms of user acceptance, facilitation of long-termcommitment and suitability to different users, goals and activ-ities [9,15–17]. For example, it has been claimed that websitespromoting healthy behaviors require repeated visitation inorder to achieve sustainable changes [18]. However, studiesshow that visitation often decreases sharply after the initialweeks of participation and the majority of participants onlyvisit an intervention once [18]. Problems with mobile devicesinclude task-technology fit and limitations in tailoring andadapting guidance [9–10]. For example, mobile monitors mayonly be worn on selected occasions if they are perceived asuncomfortable or unsuitable, thus failing to record and sup-port the entirety of activities. Several studies investigate the
effectiveness of digital interventions but provide little insighton the designable characteristics that influence interventionefficacy [19–20]. A few studies report users’ experiences ofn f o r m a t i c s 8 0 ( 2 0 1 1 ) e203–e213
wellness applications (e.g., [43]). However, more informationof real-world use situations and the specific system charac-teristics that influence reported experiences is needed foridentifying concrete solutions that designers can apply inpractice.
This study features a heart rate monitoring system asan example case of a consumer-oriented health interventionemploying two modes of delivery, a wearable heart rate mon-itor (HRM) and a web service (WS). The aims of this study are to(1) reveal how designable characteristics of the HRM system influ-ence specific benefits and limitations in personal exercise monitoringin real-world use and (2) propose recommendations for design withmultiple modes of delivery. We will now describe the methodsapplied in this work. Then we will report our results andanalysis. After this we will discuss our findings and proposerecommendations for design.
2. Methods
We conducted a qualitative field study with 30 participantsusing a heart rate monitor and a web service in their trainingfor 21 days. The study duration was determined based on priorexperience from a 3-month long study [13] demonstratingthat in the case of this particular system, the most importantevents regarding adoption and utilization take place withinthe first 2–3 weeks of use. Data collection was carried out inStanford, CA, US during April and May 20091. The participantswere equipped with a Polar heart rate monitoring system, anddata about their experiences of training and use of the systemwere collected with diaries and semi-structured interviews.No additional information or briefing on the use of the systemwas provided to achieve a scenario close to one in which theparticipants would have purchased the system from a retailer.The subjects were briefed on filling in the research diaries andencouraged to relate to the technology as they would if theyhad just purchased it themselves. Here we will describe thesystem used in this study, the participant selection procedureand the methods applied in data collection.
2.1. System description
The focus of health interventions promoting physical activ-ity is often on sedentary individuals. However, targets just asimportant are people who are active, but subject to injury orrelapse due to errors in training. Individuals who have startedto exercise after a period of non-activity are particularly vul-nerable to relapses caused by lack of exercise self-efficacy,boredom and injury that commonly result from training toohard and monotonously [2]. The ability to control exerciseintensity is of utmost importance for grounding long-term
Institutional Review Board on March 23, 2009 [Assurance Num-ber FWA00000935 (SU)]. All applicants signed informed consentsto screening and all study, data collection and data handling pro-cedures.
i n t e r n a t i o n a l j o u r n a l o f m e d i c a l i n f o r m a t i c s 8 0 ( 2 0 1 1 ) e203–e213 e205
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and sharing training calendars. The WS also includes shortarticles (white papers) about training and applications, suchas a body mass index calculator.
Fig. 1 – Polar FT6
The Polar training system includes the Polar FT60 heart rateonitor (HRM) and the Polar Personal Trainer web service2
WS). The heart rate monitor is a mobile unit worn on therist similarly to a wristwatch. It is used together with a sen-
or strap worn around the chest. Exercise data can be loggedn the wrist unit and transferred to the web service for storagend analysis. The wrist unit essentially supports monitoringeart rate. Heart rate (HR) is a measurement of the work that
heart does and is generally expressed as the number ofeats per minute (bpm) or as a percentage of the age-basedaximum HR estimate. Target zones or HR limits are used
or guiding users towards an appropriate HR level (or trainingntensity level). The HRM determines the HR target zone limitsutomatically according to the age-based maximum HR esti-ate (220 minus age). The HRM displays a moving heart on
he training computer display (see Fig. 1, display 1) indicatingctivity within a specific target zone.
The HRM contains a personalized Polar STAR Training Pro-ram that gives weekly targets for training, including intensitynd duration. The time in each of the three (low, medium andigh intensity) target zones is cumulated when exercising andompared with weekly goals (see Fig. 1, display 2). When theser has successfully achieved weekly targets s/he is rewardedith stars or a trophy (see Fig. 1, display 3). If the user needs
o improve or change his/her performance, instructions forhis will be provided together with the weekly summary (seeig. 1, display 4).3 Each training session is stored on the HRMs a training file that includes information such as duration,aximum and average HR, consumed kilocalories (kcal), kcal
xpended from fat, and information about how much timeas spent in each target zone. Totals on the HRM include
raining data starting from the last reset and weekly historyisplays. The HRM also contains the Polar Fitness Test thatnables measuring aerobic fitness at home.
Data from the HRM can be transferred to the WS by usinghe FlowLink USB dock (see Fig. 2). Synchronization requiresnstalling a “bridge” application, the Polar WebSync on theomputer.4 After configuring the WebSync application, every
ime the wrist unit is placed on the dock, data is automaticallyransferred to the WS.2 http://www.polarpersonaltrainer.com.3 The training program is analyzed in more detail in [10] and willot be elaborated further in this article.4 Compatibility: PC with Windows XP/Vista 32-bit/Windows 7 32-it (with Microsoft SP), or Intel Mac OS X 10.5 (Leopard) or newer.
splay examples.
In the WS, users can automatically make diary entries bytransferring training files from the HRM, or by manually insert-ing training data. The training diary is in the form of a calendarin which the user can add training plans and sessions andconfigure favorite workouts (Fig. 3).
Training data is stored and can be reviewed to track perfor-mance over time. Users can generate weekly or monthly viewsof several training variables (Fig. 4).
The WS provides a selection of training programs that canbe tailored to various fitness levels and development goals.The WS features a community section that contains an onlinediscussion forum and functionality for creating challenges
Fig. 2 – Polar FlowLink USB dock for synchronizing the HRMwith the WS.
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Fig. 3 – The training diary serves as the main interface for
managing workouts.2.2. Selection of participants
The subjects were recruited through Stanford Universitymailing lists and fitness and physical education facilities.Volunteers applied by filling out an online questionnairecollecting basic information such as age and gender, eligi-bility, training history and practices as well as familiaritywith different technologies. Within two weeks of recruitmentwe received a total of 60 applications. 30 participants wereselected by purposive intensity sampling [21]. Purposive inten-sity sampling is a method used in qualitative research toselect information rich cases that manifest a phenomenonintensely, but not extremely. It is particularly useful in studieswhere sample sizes are limited, as it increases the likeli-hood of obtaining rich, yet appropriately descriptive data. Wescreened participants for healthy, non-pregnant women andmen, between ages of 18 and 45. Using additional criteria con-cerning exercise background and motivations provided in amarket study by Polar, we formed a sample exemplifying theproduct’s target users, i.e., people, who would potentially buythe product.
2.3. Diary procedure
Diaries were used as instruments for extracting qualitative,subjective accounts of the users’ practices and experiences.Diaries are commonly used in the field of human computerinteraction and social sciences to collect rich qualitative dataand to obtain longitudinal, human-centered insight [22]. Theparticipants were asked to fill in semi-structured diaries on adaily basis, containing open-ended questions, to collect dataabout their training and use practices and experiences associ-ated with them. The diaries also contained thematic questionsthat varied from day to day. These were used to collect dataabout aspects of technology use, training and behavior change.A systematic scheme5 was constructed in a spreadsheet.
The spreadsheet was used for organizing questions accord-ing to the specific themes and positioning them across thetrial period. With the help of the scheme we were able to5 Available from authors upon request.
Fig. 4 – Progress charts to display longitudinal trends.
distribute the participants’ response efforts evenly across thestudy and increase the relevance of the questions within dif-ferent phases of the study. Diary booklets were generatedbased on the scheme and given to each participant when thestudy begun (see Appendix I for a structural description of thediary scheme and an example spread from the diary booklet).
2.4. Interview procedure
We conducted semi-structured interviews to complementdata collected with the diaries. A semi-structured interviewis a flexible research method that usually follows a frame-work or a guide containing specific themes to be explored[23]. Similarly to the diaries, the interviews were structuredaround two core themes: training and technology use. Withinthese, a total of 12 subthemes were used as guidance for theinterviews (see Appendix II for general objectives and themesfor the interviews). The interviews were scheduled individu-ally to take place at the end of the study. The intervieweesbrought along their HRMs and were provided with a computerfor demonstrating how they used the system. The duration ofeach interview ranged from 45 min to one hour. All interviewswere recorded and professionally transcribed.
3. Results and analysis
The data were extracted to spreadsheets and systematicallyanalyzed with interpretative methods [24]. In our analysisof benefits and limitations we applied a categorization sug-gested by Beaudin et al. [15]. The categorization summarizesthe benefits and concerns that were reported in a study inves-tigating longitudinal health monitoring concepts as perceivedby health professionals and laypeople. Because the systeminvestigated in this study was designed for laypeople (not forexample to be used by clinicians or health providers to monitortheir patients), we focused on benefits and limitations per-ceived by laypeople [15]. We adapted the categories for thecontext of this study and formed a scheme that was used in
systematic coding of the data. The findings from this analy-sis are summarized in Appendix III. We will now illustrate theparticipant profile and patterns in system use and training.Then we will focus on the benefits and limitations associated
i n f o r m a t i c s 8 0 ( 2 0 1 1 ) e203–e213 e207
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ith personal exercise monitoring identified in this study andescribe the situations in which they occurred.
.1. Participant profile
alf of the participants were men and half were women rep-esenting various ages between 20 and 45 (M = 30.0, SD = 6.3).ctivities that the participants included in their training esti-ates and descriptions included swimming, running, cycling,
trength training, climbing, horseback riding, walking (includ-ng walking to work or walking the dog), soccer, basketball andardening. It is important to note that the participants countedoth structured (e.g., training in the gym) and non-structured
e.g., gardening) activities into their weekly exercise.Three (10.0%) of the participants reported exercising
–3 h/wk, 10 (30.0%) exercised 4–6 h/wk, 10 (30.0%) exercised–9 h/wk and 7 (23.0%) exercised 10 or more h/wk. The num-er of training sessions/occasions per week ranged from 3 to6 (M = 6.1, SD = 3.2). Half [n = 15] of the participants had a his-ory (past consecutive 6 months) of regular exercise and halfn = 15] had engaged in exercise periodically in the past. Com-
on problems in training were related to efficiency, progressnd commitment.
The participants’ professional and educational back-rounds varied, including students in medicine, biology andomputer science, a safety officer, maintenance personnel, arimary education teacher, a department secretary, a histo-ian and a salesperson. The participants were fairly computeriterate (on a scale from 1 = “no experience” to 7 = “very experi-nced”) with an average rating of 6.5 (range = 1–7, SD = 0.31) onasic use of common IT appliances (PC/laptop, mobile phone,igital camera), 6.1 (range = 1–7, SD = 0.65) on Internet relatedasks (email, browsing, banking, shopping and socializing) and.7 (range = 1–7, SD = 2.40) on cross-platform tasks (synchro-izing cameras, mp3 players and phones with PC/laptops androwsing the web and reading email on mobile phones). 20
66.7%) participants had some experience of using a HRM inheir training. 15 (50.0%) participants had previously owned aRM. Reported models/brands included Polar (n = 10), Timex
ronman (n = 1), Garmin Forerunner (n = 2), Nike (n = 1), andeebok (n = 1). When the study begun, 10 (33.3%) participantsere not familiar at all with using heart rate as guidance in
raining. All participants were at a point in which personalonitoring technology was welcomed to help them take train-
ng to the next level, to learn more about exercising or to avoidlateaus and boredom.
.2. Training and system use
ere we will summarize general trends and patterns in usageo provide an overview of how the system was adopted overhe first three weeks. In this case, the three weeks appearedo be sufficient for uncovering main events associated withechnology adoption and benefits and limitations that needo be addressed early on in order to improve the chances of auccessful intervention. Fig. 5 illustrates the trends in system
se and training over the trial period.In the beginning, there is a notable peak in system use,hich is explained by participants exploring system function-
lity. After the initial days, there is a fairly steady period of
Fig. 5 – Training and system use throughout the study.
usage that is in line with the training trend. However, thisphase only lasts a little over a week, after which we see asalient drop in system usage indicating potential problemswith task-technology fit. After this weeklong period the trendsmeet again, but a larger gap between system use and trainingappears to take form.
The HRM was used in 291 (76.0%) of all 383 reported trainingsessions. A total of 92 (24.0%) reported sessions were carriedout without the HRM. The most common reasons for non-useof the HRM were the inconvenience or awkwardness associ-ated with the chest strap when it was used in situations whereothers would see it (such as public swimming pools), the per-ceived unsuitability of heart rate monitoring for specific sportssuch as rock climbing or windsurfing, occasional lack of time,or forgetting to bring the HRM or the chest strap along whenexercising. Yet, the majority of the participants, 28 out of 30(93.0%), chose to use the HRM regularly for specific activities.The WS was used in 28 sessions. Seven (23.3%) participantsnever signed up for the web service. Five (16.7%) participantssigned up, but did not synchronize the HRM with it. Six (20.0%)participants synchronized the HRM with the WS once and 12(40.0%) participants ended up synchronizing the HRM withthe WS several times. Those who did not end up using theWS either did not perceive it as useful enough [n = 16], hadtechnical difficulties in uploading their information online[n = 1], or refused to use it altogether due to privacy concerns[n = 2]. Usability as such was not a significant issue, which canbe partially explained by the participants’ computer literacy.However, several [n = 11] stated that using the WS is too timeconsuming due to its focus on detail and the abundance ofinformation elements. Based on the data obtained from theinterviews and research diaries, we will now investigate andsummarize the benefits and concerns that were identified inthis study, when the participants incorporated the system intotheir training.
3.3. How heart rate monitoring benefits training
The main benefits realized in this case were associated with:(1) exploratory learning; understanding cause and effect (2)
controlling target behavior; achieving “optimal state” or “peakcondition”, (3) rectifying behaviors; challenging/validating sub-jective feelings, identifying ineffective/detrimental behaviors,(4) motivation; feeding curiosity, fun and interest, promoting
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inaccurate summaries, and (5) privacy concerns; concerns aboutwhich parties have access to personal physiological data.
e208 i n t e r n a t i o n a l j o u r n a l o f m e d i
a positive self-image and sense of accomplishment, and (5)logging support; documentation/backup for memory.
The HRM provided means for gauging training intensity,which was essential in establishing control over the targetbehavior. Through gauging and exploratory use the partici-pants learned about cause and effect in exercise behaviors, HR,and physical responses. As described by a 30-year-old woman:
“Before I had a heart rate monitor, I would train just as hardas I could. My heart would be working so fast that I wouldhave to stop because I felt like I was about to pass out. Sonow with the heart rate monitor, I’m just like, okay, I justhave to stay within this interval.”
Using the HRM also enabled the users to optimize theirperformance. A 33-year old man would use it for achievingthe optimal intensity level in triathlons. He used the HR infor-mation to make sure that his body would be performing atmaximum efficiency, but he would still be able to utilize hisenergy reserves:
“When I’m racing, and I was, so this last race, I knew, whenI was on the bike, I was like, alright, I’m at 162. I have tobring this down a little bit, because I’m going to eat here,[. . .] I need to be able to digest this food, whereas, you know,where I’m at 145, where I can go harder and still, can still(have food). So, that’s a very important, that’s actually very,very important. That’s honestly the reason why I wear aheart rate monitor in a race. More so than anything else.”
Monitoring also made the patterns in training behaviorsmore evident and supported challenging or validating beliefs.This was particularly important in identifying behaviors suchas overtraining. As a 24-year-old woman described her real-ization:
“I didn’t think, unless I was sweating, or unless I was work-ing really, really hard at working out, then I wouldn’t reachmy goals. But then I realized what am I doing? And, withthe heart rate monitor, it was just like, okay, you’re killingyourself here. You’re not supposed to be in the 200’s.”
By quantifying performance, the system allowed the par-ticipants to evaluate how their behaviors influenced theirphysique. Some of the participants [n = 5] explicitly stated thatthey feel better about training now that they have learned toincorporate a more diverse exercise regimen. As a 26-year-oldwoman described her experience:
“. . . And also, [. . .] when I did the long runs, and tried to stayslow, I felt much better at the end of the long run than I feltwhen I would just run. . . [. . .] I felt definitely tired at theend. Well, you know, like eight or nine miles, you’re goingto feel tired walking that. . . [. . .] So, and when I ran at myregular pace, I would feel like I was about to die at the end,but then, when I found this one, I was like, you know, I stillfeel okay.”
The HRM system also had a significant role in motivating
exercise. One participant compared this to Weight Watch-ers weigh-ins and emphasized the importance of being ableto see the difference or improvement by means of distinctindicators, in this case the fitness test result. Tracking inn f o r m a t i c s 8 0 ( 2 0 1 1 ) e203–e213
general was perceived as motivating. As a 31-year-old mandescribed:
“And I think for me actually that was pretty motivating,just having, feeling something’s keeping track of you was agood reason. [. . .] on like the days where I was like: shouldI go to the gym or not. And knowing if I go and then I’ll getcloser to meeting the goal on machine.”
Monitoring added a fun factor to exercise. The majorityof the participants [n = 24] reported heart rate monitoring asentertaining. In cases where the system feedback was con-sidered appropriate and fitting, the system’s goal-setting andfeedback mechanism facilitated a sense of accomplishment.A 43-year-old woman described her experience:
“I was very happy when it told me I’d done well at the endof the week, beeped and gave me two stars! Enjoy watchingthe time mount up – it’s like it ‘counts more’.”
The majority of the participants [n = 27] occasionallybrowsed through recent or past workouts on the HRM forreflecting, fun, or a sense of accomplishment. A 29-year-oldwoman described her experience as follows:
“And then, just, the ability to store the data, so, like. . . Ialways have the watch [the HRM] on my night stand, so[when it displays the message] it’s kind of like, I’ll (ignite),or whatever, like, I’m just like, oh, what have I done thisweek? [Laughs]”
Being able to log exercises automatically was consideredimportant. The participants seemed to enjoy the fact that theirtraining was recorded in general. Illustrating this, here is anexcerpt from an interview with a 31-year-old man:
“I never used to document my training [before]. Now thewatch does it automatically so I still don’t really do any-thing. I do however try to use the system whenever I workout so it is documented.”
A few of the participants [n = 3] explicitly reported that theywere not doing anything specific with the information yet, butstill liked the fact that it was stored. Some of the participants[n = 6] stated that the ability to just back up exercise data wasthe primary reason for using the WS.
3.4. Limitations in system functionality and content
The main limitations recognized in this case were associatedwith (1) responding to users’ need for cognition6; lack of suffi-cient information for users to validate system guidance andfeedback, (2) virtual coaching: lack of valuable, new or action-able information/content in terms of planning and analysis,(3) task-technology fit; unsuitability of the HRM to distinct sit-uations, (4) data integrity; incompleteness of data resulting to
6 In this article need for cognition is used for describing users’ needto find background information about system functionality andHR-based training for validating the intervention.
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In 16 [53.3%] out of the 30 cases, the participants expressedhat they were not sure about the appropriateness of the guid-nce provided by the HRM. A 43-year-old woman described heroncern as follows:
“I am concerned about the guidance it’s offering. It is tellingme to exercise less hard than I usually do, in order toimprove my fitness. So I tried that and didn’t push myselfas hard during step class, but I’ve still used up all of myzone 3 min for the week. Does it know best or do I? Am Iworking too hard to get the results I want and really couldbe more efficient doing less? What if I want better fitnessand to lose weight?”
Some participants felt that the guidance provided by theRM was too general and that it would not apply to them asuch. A 41-year-old man characterized it as being “. . .rathereneric since it doesn’t really explain why the program does whatt does”. Finding information that would help determine theppropriateness of the guidance was difficult. As the 43-year-ld woman from the previous excerpt continued:
“And yeah, they don’t really explain, okay, so here’s why wehave each of these profiles. Here’s the research that makesus think that it’s useful. I did look at the website, they didlist a lot of research articles, but you couldn’t, there weren’tlinks to them. You couldn’t click on any of them, they justsaid, oh, here are some articles that, you know, we thinkare, that we used in our background. . .”
The information provided in the WS and other materialsuch as user manuals was considered superficial and did notatch what the users were really looking for. A 28-year oldoman described her experience as follows:
“The manual does give you basic instructions but I felt like Iwas following a recipe without knowing what I was baking.I could do what it told me to do but I didn’t have a contextthat explained why or how it worked that way.”
More information about the actual target behavior was alsoeeded. This is illustrated in the following excerpt from an
nterview with a 26-year-old woman:
“Well, I’ve been trying to follow the guidance, but it seemstoo slow. Perhaps my max heart rate is incorrect or maybeit’s even measuring it wrong. [. . .] I wish there was moreexplanation why, or if it’s common to have this much diffi-culty keeping one’s heart rate down.”
A key drawback associated with the usefulness of the WSas in how the data was presented and how it comparedith the functionality on the HRM. The 26-year-old woman
ontrasts the WS and the HRM as follows:
“I was just like, oh, okay, here it is now [data on the web].It’s a little easier to navigate around, and check the days.But that’s pretty much the extent of it. It’s just kind of like,another way to store the data. Instead of just, checking onmy watch, I was able to check it on the [web] interface.”
The participants expected the WS to take on a more activeole in supporting planning and analyzing training. However,he summaries and charts that it provided had to be generatednd interpreted by the user. The WS was more focused on
o r m a t i c s 8 0 ( 2 0 1 1 ) e203–e213 e209
organizing raw data and did not provide sufficient support forsense-making or intelligent analyses. As a 32-year old womanstated:
“I wish it helped me more with planning my training regi-men. I felt like I was left to determine that on my own andthe monitor were just auxiliary to that.”
As reported afore, 24.0% of the reported training sessionswere carried out without the HRM. The HRM was simply notperceived as suitable for all of the different situations in whichtraining took place. In addition, the WS lacked quick and easyto use functionality for manual logging. This was evident in adiary insert by a 28-year old woman:
“I love the fact [that] the system keeps track of my achieve-ments in a pretty simple way. I really don’t have to inputmuch EXCEPT when I don’t use the HRM during training →then the website needs some improvements: maybe a mod-ule that pops up to help me approximate # calories burnt”
Several users [n = 11] thought that using the WS was tootime consuming and tedious with all the detail it seemed torequire. A significant limitation that ultimately followed prob-lems associated with logging is the incompleteness of data.When the HRM was not used in all sessions, the summativevalues that it provided were based on incomplete logs and theguidance based on these values was perceived as misleading.As a 23-year old man describes:
“It [HRM] usually says I should be training more becauseI log 2.5–3 h per week using the machine. Counting timespent on non-cardio activities in the gym would proba-bly add another 1.5–2 h to this number. It says my targetis something like 4.5 h, so the amount of exercise it thinks Iam receiving is downwardly biased because I don’t use thesystem all the time. So I guess I personally have to adjustfor this? If I were ‘truthful’ with it, I believe it would beappropriate.”
Privacy concerns did not exceed other issues in terms offrequency, but were in some cases critical enough to preventparticipants from signing into the WS altogether. As an exam-ple, a 46-year-old woman did not want to upload her fitnessinformation because she was worried that the service provideror other parties would be accessing it:
“It wasn’t clear to me, how much of it they were going to,you know, allow other companies access to, in an aggre-gated [anonymized] form or non-aggregated.”
Several of the participants [n = 8] perceived that they werenot properly informed about how their information was beinghandled and a few [n = 3] used false identities when signingin. Some were concerned that in the worst case, insurancecompanies or employers could, for example, use their personalhealth and fitness information in ways that would not be intheir best interest.
In this case, social functionality in the WS was not uti-lized. In addition to usability issues, a key threshold was
that the WS did not feature the users’ social graphs (whichsome had already established in other online services suchas Facebook and LinkedIn). The participants were still askedabout their willingness to share exercise data online with
e210 i n t e r n a t i o n a l j o u r n a l o f m e d i c a l i n f o r m a t i c s 8 0 ( 2 0 1 1 ) e203–e213
Table 1 – Potential distribution of roles and functionality across the HRM and the WS.
Heart rate monitor Web service
Learning A tool for facilitating exploration and experimentation thatsupports understanding cause and effect and experientiallearning of target behaviors.
A platform for providing material for validating theintervention and learning about the target behavior. Source ofeducational content.
Control A tool for controlling workout intensity on the run andprovision of useful and entertaining real-time feedback.
A platform for setting goals and provision of support for usingHR for specific purposes, such as optimizing performance,losing weight, etc.
Coaching A tool for logging workouts that provides motivating real-timerther
A platform for supporting analysis and provision of automated
guidance and feedback. Recorder for data that can be fuapplied in more elaborate analyses.friends. Some participants (n = 8) would not share their work-out data with anyone, considering it to be too personal. Several(n = 12) did not think sharing training data and experiencesonline would be useful as most social interactions associ-ated with training took place in real-world situations. Someparticipants (n = 3) also did not think their friends would beinterested in their training data. Other types of data, such asjogging/cycling routes or reviews of training programs werementioned as potentially more interesting items for shar-ing. Despite the reluctance in contributing data, participantsreported that they would still be interested in seeing others’workouts, in particular of those with expertise, such as pro-fessional athletes or training instructors. In addition, contentbased on data aggregated from masses of users was consid-ered to be potentially interesting. An aggregative approachto social functionality also seemed to be considered safer interms of privacy.
4. Discussion and recommendations
The HRM inspired exploratory behaviors, which were essentialfor learning about proper exercise intensities and developingcontrol over the target behavior. However, participants wereconcerned whether feedback from the HRM was appropri-ate for them and had trouble validating it. The WS could bemore effectively utilized for providing information about keyconcepts and theories constituting the proposed new train-ing philosophy and guidance. The WS should be used as achannel for openly and clearly communicating about the foun-dations behind system functionality (with original references)to increase its overall trustworthiness. Trustworthiness is oneof the key requirements for successful interventions [5]. TheHRM facilitated fun and entertainment in exercise. Mobileinteraction modes could be utilized more creatively to facil-itate entertaining and enjoyable experiences within targetbehaviors, e.g., with game-like features. Enjoyment is consid-ered at least as important in terms of technology adoption asusability and usefulness [25]. When data has been collectedover longer term, the WS could support virtual coaching,i.e., provide more intelligent analyses and support makingsense of the data in ways that may benefit future trainingand help users stay motivated as they progress. This, how-ever, will require significant advances in computation, as
guidance and analyses need to adapt to changes in users’condition, goals and life situations [15,26]. The WS did noteffectively support compensation of undocumented perfor-mances, as users perceived manual completion of data tediousor semi-automated coaching. Functionality aggregatinglongitudinal data and/or data from multiple users to generatetailored guidance.
and difficult due to all the required detail. This resulted inincomplete logs and inaccurate summaries. This problem hasalso been identified in related work as deceptive measure-ments – when monitoring technology is focused on collectingspecific type of data such as HR or step count, other relevantdata may be ignored [26]. When recording all relevant activi-ties or events is not possible, a highly detailed unit of analysismay become counteractive. If data could be easily comple-mented with estimates, the gap between actual and recordedtotals could be bridged. It is also useful for designers to con-sider a reasonable degree of base-line accuracy. A more generalunit of analysis such as the number of training sessions perweek or generalized activity types allow for more flexibilityas opposed to exact bpm values and calorie counts [see, e.g.http://en.heiaheia.com]. Our findings demonstrate some con-cern in sharing detailed exercise data. In order to incorporatesuccessful social features, a better understanding of what typeof data users would share and find useful is needed. Usersneed easy to use tools for controlling disclosure [27].
Our findings demonstrate how users’ experiences are con-nected with the different modes of delivery. Most of thebenefits identified here were associated with the HRM, andsome issues could have been better supported in the WS.By systematically employing available modes of delivery, theoverall user experience may be significantly improved. Regard-ing the distribution of roles among different modes of delivery,Table 1 summarizes how the HRM and the WS can be com-bined in supporting the various aspects of training; learningand the need for cognition, controlling target behavior andintelligent coaching.
We conclude our discussion with three main recommen-dations that concern the development and design of personalmonitoring technologies:
1. Various modes of delivery should be more systematicallycombined to provide optimized support for the differentaspects of an activity, e.g., mobile interfaces to enable con-trol and feedback on the run and web based services toprovide material for learning about the target behavior andvalidating the intervention.
2. Different modes of delivery can be used for addressing lim-itations that may occur when trade-offs need to be madein optimizing technology for distinct situations. An under-
standing of real-world use situations helps in determiningthe distribution of roles among the modes of delivery.3. Efforts should be targeted towards utilizing sensor dataand longitudinal data in the development of intelligent
i n t e r n a t i o n a l j o u r n a l o f m e d i c a l i n f
Summary pointsWhat was already known on the topic
• Personal monitoring technologies can be effective insupporting physical exercise.
• Opportunities and challenges associated with per-sonal monitoring technologies are varied.
• Using multiple modes, such as mobile devices, textmessages and emails together with web based soft-ware systems may contribute to improved behavioraloutcomes.
What this study added to our knowledge
• Advances understanding of how specific characteris-tics of a system employing multiple modes of deliveryinfluence personal exercise monitoring as perceived byusers.
• Design efforts should be targeted to (1) supportingusers’ need to validate the intervention within theearly stages of use, (2) developing methods for improv-ing data integrity (3) utilizing longitudinal sensory datafor intelligent coaching and personalized analyses.
• Demonstrates how various modes of delivery (HRMand WS) can be systematically combined to resolveissues in technology-mediated training.
fcprtpa
and adaptable coaching functionality to provide users withappropriate, personalized and useful guidance over time.
The methods applied in this study were well suitedor exploratory research. However, the data required time-onsuming and demanding analysis procedures. Com-liance was achieved by subjecting the participants toeasonable effort, the design of the diary booklet, and
hrough rapport that was established with the partici-ants at the beginning of the study. The participants werelso genuinely interested in using the system in theirAppendix I. Research diary structure and layout
Themes Daily questions
Training Daily training andexperience; backgroundand context; attitudeand behavior change
How do participants tratraining patterns, habitexperiences associatedexercising.
Technologyuse
Daily usage andexperience; pragmaticaspects; emotionalaspects
How do participants ustechnology and its feattheir daily training: utipatterns and experiencassociated with thetechnology.
Questions were structured to identify patterns and associated experiences
o r m a t i c s 8 0 ( 2 0 1 1 ) e203–e213 e211
training. Quite understandably our findings are limited in thatthey are characteristic of the particular pool of users enrolledin this study. Our sample features people that are healthy andphysically active and therefore recommendations presentedin this work should be cautiously applied with other typesof target groups. Yet our sample was successful in represent-ing real end-users of the investigated system and in revealingissues that are critical to sustainable and healthy trainingpractices. As this study features only one type of a system,one needs to exercise caution in generalizing the implications.More research is needed to understand functionality of otherpotential combinations and modes in health promotion.
Authors’ contributions
Katarina Segerståhl and Harri Oinas-Kukkonen carried out thework described in this article collaboratively, with KatarinaSegerståhl taking the lead in protocol design, data collection,analysis and authoring of this article.
Conflict of interest
There are no known conflicts of interest.
Acknowledgements
We acknowledge the RichWeb project, National TechnologyAgency of Finland (TEKES), Academy of Finland, Gradu-ate School on Software Systems and Engineering (SoSE),Oulu University Scholarship Foundation and Tauno TönningFoundation for funding parts of this research. We greatlyappreciate Polar Electro Oy for collaboration. We also thankStanford H-STAR research institute for enabling this studyand the Stanford HCI Group and the Ubiquitous InteractionGroup at Helsinki Institute for Information Technology HIITfor collaboration and support. We thank Marja Harjumaa andAntti Oulasvirta for their intellectual support and the review-ers of this article for providing constructive comments on themanuscript.
Thematic questions
in:s and
with
(1) Background: subjects’ training history,self-image and attitudes towards physicalexercise. (2) Behavior change: how trainingrelated attitudes and behaviors are shapedthrough technology use.
e theures inlizationes
(1) Adoption and usage: use and non-use indistinct situations and interactions with boththe heart rate monitor and the web service. (2)Experiential aspects: usability, learnability,
enjoyability, suitability to training andassociated situations and usefulness.in training and utilization.
ormation/content/
e212 i n t e r n a t i o n a l j o u r n a l o f m e d i c a l i n f o r m a t i c s 8 0 ( 2 0 1 1 ) e203–e213
An example spread from the diary: left side is used for daily questions and right side for thematic questions.
Appendix II. Interview goals and themes
Inte rview goals In vite per son al stories of parti cipa nts’ training bac kgrou nd, motivation
and views and experiences of technology . Encou rage parti cipants to tell ab out sp ecific exper iences with the
technol ogy (first tim e use, most me mora ble/awkwa rd/rewa rding use situation or the most recen t experi enc e)
Encou rage par ticipan ts to desc ribe the contextual fact ors associa ted with tra ini ng and techn ology use (such as social co ntext, fac ilities, surro und ings and li fe sit uation)
Encou rage par ticipa nts to thin k about and express their view of the under lying re asons for use and non- use of the syst em as well as for particular ex periences.
Themes concernin g train ing Traini ng motiv ation Tr aining backg round Tr ain ing re gimens /habit s Training context Heart ra te base d tra ining Planning, trai ning, analysi s
Themes concernin g system use Re lation ship wi th tech nology Experience of other services /de vice s System us age Us e of th e heart rate monitor Us e of the web service Co mbi nator ial us e
Appendix III. Summary of benefits andlimitations
Perceived benefits: Personal exercise technology
• Giving a sense of accomplishment. (HRM• Helps understanding cause and effect
n = 1)• Validation of subjective feelings. (HRM: n• Supports evaluating success of int
n = 4/WS: n = 3)• Measuring progress. (HRM: n = 7/WS: n = 8• Time management. (HRM: n = 2/WS: n = 6• Achieving “optimal state” or “peak c
n = 9/WS: n = 12)• Understanding habits, traits and behavior
n = 3/WS: n = 6)• Identifying beneficial behaviors (HRM: n =• Identifying ineffective/detrimental behav• Identifying valuable improvisations. (HRM• Providing material for conversation w
n = 3/WS: n = 2)• Establishing a baseline for later compariso
n = 6)• Documentation/backup for memory (HRM
Perceived limitations: Personal exercise
ited in that it:
• Does not provide new information/con(i.e., “I already know this” or “I already gwhere”). (HRM: n = 2/WS: n = 8)
• Does not provide valuable inf
helps/supports• Promoting a positive self-image. (HRM: n = 13)• Feeding curiosity, fun, interesting. (HRM: n = 28/WS: n = 4)
: n = 11) (HRM: n = 27/WS:
= 5)ervention. (HRM:
))ondition”. (HRM:
s over time. (HRM:
14)iors (HRM: n = 5): n = 4)
ith others (HRM:
n. (HRM: n = 4/WS:
: n = 22/WS: n = 16)
technology is lim-
tent/functionalityet this from else-
functionality (i.e., “The information is there, but I cannotreally do much with it”) (HRM: n = 1/WS: n = 12)
• Offers information/content/functionality that is alreadytaken care of by something/someone. (HRM: n = 9/WS: n = 16)
i n f
•
•
mn
r
i n t e r n a t i o n a l j o u r n a l o f m e d i c a l
Does not provide solutions or actionable guidance (justmore information). (HRM: n = 1/WS n = 7)
Causes frustration when you do not know what to do orcannot do anything. (HRM: n = 3/WS: n = 2)
Perceived benefits and limitations in personal exerciseonitoring. HRM = heart rate monitor, WS = web service.
= number of subjects explicating the benefit/limitation.
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