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In a growing number of intervention studies, mobile phones are used to support self-management of people with Type 2 diabetes mellitus (T2DM). However, it is difficult to establish knowledge about factors associated with intervention effects, due to considerable differences in research designs and outcome measures as well as a lack of detailed information about participants’ engagement with the intervention tool.
To contribute toward accumulating knowledge about factors associated with usage and usability of a mobile self-management application over time through a thorough analysis of multiple types of investigation on each participant’s engagement.
The Few Touch application is a mobile-phone–based self-management tool for patients with T2DM. Twelve patients with T2DM who have been actively involved in the system design used the Few Touch application in a real-life setting from September 2008 until October 2009. During this period, questionnaires and semistructured interviews were conducted. Recorded data were analyzed to investigate usage trends and patterns. Transcripts from interviews were thematically analyzed, and the results were further analyzed in relation to the questionnaire answers and the usage trends and patterns.
The Few Touch application served as a flexible learning tool for the participants, responsive to their spontaneous needs, as well as supporting regular self-monitoring. A significantly decreasing (
Many grounded design implications were identified through a thorough analysis of results from multiple types of investigations obtained through a year-long field trial of the Few Touch application. The study showed the importance and value of involving patient-users in a long-term trial of a tool to identify factors influencing usage and usability over time. In addition, the study confirmed the importance of detailed analyses of each participant’s usage of the provided tool for better understanding of participants’ engagement over time.
For effective medical care of chronic illness, such as Type 2 diabetes mellitus (T2DM), adequate and sustainable self-management initiated by patients is important [
We recently conducted a literature review based on search criteria used previously [
Regardless of study design, if patients are involved in a longitudinal trial of a self-management tool, mechanisms of their engagement with the tool over the period should be analyzed to identify factors associated with usage [
The authors of this paper have developed ICT systems to support sustainable self-management of T2DM, emphasizing unobtrusiveness in patients’ daily life and simplicity for ease of use. From a very early stage, the design process has involved patients with T2DM as prospective users. A self-management tool, the Few Touch application, was developed for continuous use with the purpose of improving users’ blood glucose management by increasing physical activity and encouraging a healthier diet. The feasibility of the application was tested by the 12 participants in their real-life settings for half a year as the final part of the design process [
The Few Touch application was tested for 1 year by 12 individuals with T2DM (4 men and 8 women; age ranged from 44 to 70 with a mean age of 55.1 (SD: 9.6) and mean disease duration was 8.1 (SD 3.8) years at the beginning of the long-term trial) who had been involved in the design process. We use the term “participants” for these 12 individuals. The local regional ethical committee approved the study protocol in 2006 (Regional komité for medisinsk forskningsetikk Nord, Ref. No. 13/2006). The recruitment process and other details about the participants are explained elsewhere [
The main component of the Few Touch application is the smartphone-based “Diabetes Diary”. Core features of the Few Touch application are: (1) automatic wireless data transmission from a blood glucose meter and a step counter, (2) nutrition habit recording enabled by few-touch operation on the smartphone, (3) feedback with simple analysis of these three types of data shown by the Diabetes Diary, (4) goal-setting functions for step counts and nutrition habits, and (5) general tips function for self-management of diabetes.
The schedule for the long-term trial and the timing of data collection is summarized in
Schedule for the long-term trial and the timing of data collection.
Meetings | Time (month, year) | Events |
1 | September 2008 a | Introduction of the Few Touch application (except physical activity sensor system and tips function) |
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Questionnaire 5 |
2 | October 2008 (7 weeks after Meeting 1) | Introduction of tips function |
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Focus group sessions (the participants were divided into two groups) |
3 | December 2008b, January 2009c | Introduction of physical activity sensor system |
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Individual semistructured interview |
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Questionnaires 4 and 7 |
4 | March 2009 | Focus group sessions (the participants were divided into two groups) |
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Questionnaires 1, 2, 4-8 |
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System Usability Scale (SUS) [ |
5 | June 2009 | Focus group sessiond |
6 | October 2009 | Focus group sessions (the participants were divided into two groups) |
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Questionnaires 3-7, 9 |
aFor P07 and P11, the application was introduced on October 1 and 7, 2008, respectively
bTwo participants attended an individual meeting.
cTen participants attended an individual meeting.
dTen participants attended the focus group session.
Screen design and structure of Diabetes Diary (“Diabetesdagbok”).
Recorded data in the Diabetes Diary, comprising blood glucose measures and step counts that had automatically been transferred to the users’ smartphones and manually recorded nutrition habits, were collected in every meeting after each function became available. To explore usage trends over time, we defined “usage rate” as the number of days per week on which each function was used. For the physical activity system, unless participants reported any problems with it, we assumed that days with step counts greater than zero were the days on which the system was used, because the step counter automatically transmits data once a day at a regular time, even if it has not been used on that day. To evaluate usage trends (
Although the questionnaires that we used covered a variety of aspects, this paper focuses on reporting the results regarding the participants’ perception of usability and usefulness of the Few Touch application. Both standard and tailored questionnaires were administered. To evaluate the usability of the whole system, at Meeting 4 we administered the System Usability Scale (SUS) [
Satisfaction with 14 design elements of the Few Touch application (5-point Likert scale)
Agreement with motivational effect of each function on better self-management (5-point Likert scale)
Agreement with effect of using the Few Touch application on behavior change in activities for self-management of diabetes (5-point Likert scale)
Perceived usefulness of the Few Touch application. (7-point Likert scale)
Satisfaction level with knowledge about diabetes and with the skills in diabetes management (5-point Likert scale)
Expected frequency of usage of the Few Touch application in future (multiple choice from: Daily, Weekly, Monthly, or Seldom)
Satisfaction level with the tips function (5-point Likert scale)
Agreement with possible improvement of the Few Touch application by incorporating 10 potential functionalities (5-point Likert scale)
Agreement with actual improvement in medication, blood glucose control, physical activity level, and nutrition habits (yes/no)
Semistructured interviews were conducted at Meetings 2-6. The questions used in the interviews were designed to identify how the participants used and experienced the Few Touch application in relation to self-management activities in terms of the whole application, each function, and usability of both the application and the smartphone. All the interviews were voice recorded. Because the questions were strongly connected to the aim of the analysis, we examined data from interviews by following the framework suggested by Braun and Clarke [
In this section, we use the code “Pxx” to indicate a specific participant, where “xx” shows the participant’s ID number.
Results from the Mann-Kendall trend test on usage rates confirmed a significantly decreasing (
Results from Mann-Kendall trend test on usage rate.
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Blood glucose sensor system | Nutrition habit recording system | Physical activity sensor system | |||
Participant | Tau-value |
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Tau-value |
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Tau-value |
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P01 | -0.19 | .06 | -0.58 | <.001 | -0.57 | <.001 |
P02 | 0.22 | .03 | -0.01 | 0.91 | -0.10 | 0.46 |
P03 | -0.01 | .96 | 0.16 | 0.14 | 0.21 | 0.16 |
P04 | -0.35 | .002 | -0.37 | <.001 | -0.62 | <.001 |
P05 | -0.41 | <.001 | -0.18 | 0.07 | -0.16 | 0.18 |
P06 | -0.31 | .003 | -0.39 | <.001 | -0.43 | 0.001 |
P07 | -0.11 | .33 | -0.58 | <.001 | -0.58 | <.001 |
P08 | -0.06 | .56 | -0.34 | .002 | 0.12 | 0.47 |
P09a | -0.05 | .70 | -0.37 | .002 | -0.35 | 0.08 |
P10 | -0.54 | <.001 | -0.42 | <.001 | -0.35 | 0.01 |
P11 | -0.45 | <.001 | -0.71 | <.001 | -0.27 | 0.05 |
P12 | -0.63 | <.001 | -0.61 | <.001 | -0.07 | 0.69 |
aAll the recorded data on P09’s smartphone were accidentally deleted at Meeting 2, and only data recorded after Meeting 2 were used for analyses.
The numbers of days on which each function was used against a period in which each function was available.
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Blood glucose sensor system | Nutrition habit recording system | Physical activity sensor system | ||||||
Participant | Dra | Dab |
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Dr | Da |
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Dr | Da |
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P01d | 102 | 395 | (26%) | 101 | 395 | (26%) | 71 | 152 | (47%) |
P02d | 158 | 393 | (40%) | 51 | 393 | (13%) | 56 | 239 | (23%) |
P03d | 390 | 395 | (99%) | 365 | 395 | (92%) | 210 | 219 | (96%) |
P04 | 16 | 393 | (4%) | 11 | 393 | (3%) | 33 | 138 | (24%) |
P05d | 294 | 393 | (75%) | 277 | 393 | (70%) | 143 | 265 | (54%) |
P06 | 334 | 393 | (85%) | 323 | 393 | (82%) | 159 | 244 | (65%) |
P07d | 327 | 374 | (87%) | 98 | 374 | (26%) | 61 | 202 | (30%) |
P08d | 58 | 395 | (15%) | 357 | 395 | (90%) | 161 | 197 | (82%) |
P09c, d | 348 | 352 | (99%) | 8 | 352 | (2%) | 129 | 132 | (98%) |
P10d, e | 278 | 389 | (71%) | 88 | 393 | (22%) | 116 | 191 | (61%) |
P11d | 60 | 380 | (16%) | 152 | 380 | (40%) | 86 | 210 | (41%) |
P12 | 209 | 393 | (53%) | 240 | 393 | (61%) | 86 | 147 | (59%) |
aDr is the number of days on which records were made.
bDa is the number of days when a function was available.
cAll the recorded data on P09’s smartphone were accidentally deleted at Meeting 2, and only data recorded after Meeting 2 were used for analyses.
dThe step counters had problems, so that there were periods when participants could not use their step counter.
eP10’s blood glucose sensor system did not function for 4 days.
Regarding nutrition habit recordings, we could observe a change in usage patterns for some participants (eg, P01, P07, and P11) in a relatively early phase (
Regarding the physical activity sensor system, 9 (P01, P02, P03, P05, P07, P08, P09, P10, and P11) of the 12 participants had problems and their step counters were repaired or replaced. The major problem was battery attrition of the step counter. A significant decreasing usage trend (
Distribution of blood glucose measurement frequency among days on which any blood glucose measurement was performed.
The Few Touch application was generally perceived as satisfactory. The perceived usefulness of the whole application by the participants remained considerably high over time (
Questionnaire 4—Distribution of the answers to questionnaire about perceived usefulness of the Few Touch application (1: Not useful at all, 7: Very useful).
Elapsed time / Usefulness of the application | 1-3 | 4 | 5 | 6 | 7 | Mean |
3-4 months (Meeting 3) | 0 | 1 | 0 | 6 | 5 | 6.3 |
6 months (Meeting 4) | 0 | 1 | 1 | 2 | 8 | 6.4 |
1 year (Meeting 6) | 0 | 0 | 1 | 4 | 7 | 6.5 |
The blood glucose sensor system was perceived as the most motivating, followed by the physical activity sensor system and the nutrition habit recording system (
The results of the questionnaire that addressed the participants’ preferences for potential functionalities of the Few Touch application are shown in
We could not observe any deterministic associations between answers to any questionnaires and usage of functions.
The mechanism of participants’ long-term engagement with the Few Touch application is illustrated in
First, we could identify a cycle of usage of the application, experience, and impact of using the application expressed as elements in a box with a dark background in
Mechanism of participants’ long-term engagement with the Few Touch application.
Despite generally high satisfaction with the application, experiences of problems were also reported. Problems that stemmed from outside the design concepts included battery attrition for a step counter and a Bluetooth adapter, some features of the provided smartphone that had taken some time to get used to for the first month, and problems with the smartphone. Other problems stemmed from a mismatch between design concepts and reality (
From data extracts relevant to the application design and results from questionnaires, we identified the following factors associated with usability and/or usage over time: (1) integration with everyday life, (2) automation, (3) balance between accuracy and meaningfulness of data with manual entry, (4) intuitive and informative feedback, and (5) rich learning materials, especially about foods.
Functions and features that caused deteriorated usability of the Few Touch application.
Function and feature | Design concept | Reality | Affected components in usability |
User interaction design enabling nutrition habit recording completed by just one press on the appropriate category. |
Users would record each meal, snack and drink immediately. |
Participants made several records at a time or recorded nutrition habits at the end of the day to summarize their food intake so that they needed more operations at a time. (P01, P03, P05, P06, P08, P10 and P12, Meeting 2) |
Efficiency, flexibility |
Categorization of nutrition habit recording | Categories would correspond to types of eating habits that should be improved in context of T2DM, so that it encourages users to have a healthier diet. | The categorization was not precise enough for their reflective thinking, or it did not match the participants’ individual preferences based on their accumulated personal experiences. (P01, P02, P08, P11 and P012, Meeting 4) | Effectiveness, flexibility |
Step counter attached on belt | A physical activity sensor should be integrated with their daily tools and outfits. | One participant (P06) did not use a belt normally. P06 had used it in a bag, but it was easy for P06 to forget about using the step counter on the next day. (Meeting 6) | Satisfaction |
Step counter as a physical activity sensor | Physical activity sensor system should provide easily interpretable values to motivate a user to monitor. | The fact that other types of sports (skiing) or physical activities were not measured was disappointing. (P11, Meeting 4; [ |
Effectiveness, satisfaction |
User interface of tips function and its contents | Tips function would provide a user with concise information that can be shown on a screen without necessity of scrolling or more manual operation than one button press to access to a “tip of the day”. | Participants wanted better access to information that they want to read (P05, P08, and P09, Meeting 5) | Efficiency, satisfaction |
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Participants wanted more and richer information (P01, P03, P09, and P12, Meeting 4), preferably delivered by SMS with tailored contents based on user’s profile (P12 [ |
Satisfaction |
Diabetes Diary as a software on a smartphone | Users would easily access to their records and information relevant to self-management of diabetes by integrating necessary functionalities into a software application running on their personal mobile phone. | A participant (P04) stopped using the smartphone as his/her personal mobile phone, because it had problems as a mobile phone (Meeting 6) | Effectiveness, efficiency, satisfaction |
The participants generally appreciated the minimal effort required for keeping track of self-management activities and for referring to them, which is the design concept achieved in the user-involved design process. Instant access to the application on the smartphone that was used as a personal mobile phone played a great role in integrating the application use into everyday life. This is supported by the fact that no participants used the history view function on the blood glucose meter and by the fact that P04, who had problems with the provided smartphone, did not continue using the application.
Many of the issues listed in
Modified user interface for nutrition habit recording (left), and the tips function (right).
Automation of data transfer from the blood glucose meter and the step counter played a key role in making the use of the application as effortless as possible. The participants appreciated not only that they did not have to write down the values any more but also the fact that the graphical feedback was automatically prepared based on the transferred data. Results from Questionnaire 8 also support the importance of automation.
An interesting change over time in perceptions of usefulness was observed regarding automation of recording and data visualization. P10 told us in the Meeting 2 that s/he had used to write a very precise paper diary before the trial started, so s/he found no difference in the Diabetes Diary, and even the blood glucose graph did not provide anything new. However, at Meetings 3 and 4, P10 told us of now, unlike earlier, appreciating the blood glucose graph to see how his/her blood glucose varied and to relate it to food consumed. Finally, at Meeting 5, P10 told us that s/he had recently stopped writing down measurements manually, which s/he had continued just as a habit, due to now relying on the application. P03 admitted to continuing to write down blood glucose values for a while, but s/he became used to getting the values on the smartphone.
Although most of the participants liked and wanted to keep the simplicity of the system for nutrition habit recording, some of them found that the categorization for this system was not appropriate for their reflective thinking or that it did not match their individual preferences based on their accumulated personal experiences (
The participants showed different preferences for the design of feedback depending on function. At one of the focus group sessions in Meeting 4, all the participants stated that feedback showing progress toward goals was most important for encouraging daily physical activity and good nutrition habits. They also mentioned that they rarely used screen (h) in
Though some other participants stated that the system was simple enough for them to see that their self-management activities influenced their blood glucose levels, 2 participants (P05 and P11) clearly expressed their need for improvement of the feedback design so that it visually showed the relationship between the three components: blood glucose level, physical activity, and nutrition habits. Both participants mentioned their difficulty in maintaining their focus and motivation in continuing self-management activities. At Meeting 3, P05 also mentioned the importance of keeping a self-management tool simple so that s/he would not become confused with complicated information. One of the suggestions for improvement of the application included a function to show a filtered list of fasting blood glucose measurements only, which also illustrates a need for feedback to be more informative.
Most of the participants appreciated the tips about food, and even more enriched content was requested. Many of the suggestions for improvement of the application concerned functions or learning materials about foods.
Together with qualitative inquiries, detailed quantitative analyses on each participant’s usage of the provided tool gave us insights into mechanisms of participants’ engagement with the tool and led us to a better understanding of factors associated with usage and usability over time.
The Few Touch application served as a flexible learning tool for the participants depending on their spontaneous needs as well as for regular self-monitoring. Usage of the application was supported by the minimum effort required for keeping track of self-management activities and for referring to them, which was the design concept achieved in the user-involved design process. Except for a few participants, a decrease in the usage trend was generally observed. Having gained a sense of mastery over diabetes and experiences of problems were identified as reasons for decreased motivation to continue using the application. Some of the problems stemmed from a mismatch between design concepts and reality, even though the design concepts were obtained in a process involving the participants. The impact of such mismatches on usage and usability became critical over time among some participants.
In the following sections, we will discuss our findings by comparing them with relevant studies.
The learning process based on personal experiences on top of necessary knowledge provided by diabetes education builds a foundation for designing the patient’s own self-management plan. It is also claimed in previous studies that a supporting tool for people with diabetes should facilitate this learning process [
A wide variety of patterns of engagement with the application observed in this study is in line with findings in the two deployment studies of a health monitoring application, MAHI (Mobile Access to Health Information). MAHI was originally designed with the focus on development of reflective thinking skills through social interaction for newly diagnosed individuals [
Decrease in usage after gaining a sense of mastery over diabetes is in line with findings by relevant studies [
The mobility and pervasiveness of the smartphone as a personal mobile phone played an important role in integration of the application into everyday life. The finding strengthens the conclusions in recent studies [
In the present study, automation was successfully employed only to reduce unnecessary burden in tracking self-management activities, such as transcribing data, so that it would support longitudinal use of the application as advocated by Mulvaney et al [
Accuracy of data obtained by a sensor is critical in terms of giving proper credit to users [
Findings by Kelders et al [
Findings by Kanstrup et al [
This study confirmed the importance of involving “patient-users”, not only in the specification-design phase but also in the trial phase of a working prototype in a real-life setting for enough time to clarify how the chosen design works in relation to expectations and how the design can be improved [
To achieve such involvement of patient-users requires their strong and long engagement in the process. The strong engagement of the participants in this study was achieved through a variety of efforts by the researchers [
Though the first author of this paper understands the Norwegian language, she is neither a Norwegian citizen nor a native Norwegian speaker. On the other hand, the second author is a native Norwegian, has T1DM himself, and has the same cultural background as the participants. In addition, the second author initiated the whole design process of the Few Touch application, from the recruitment of the participants to the development and testing of the application. The first author needed some help from the second author to interpret and understand better exactly what the participants meant in interviews. This might have caused a certain bias in the analysis.
The present study showed the importance of the following two factors: (1) a thorough analysis of results from multiple types of investigations focusing on each participant’s engagement with the tool over time, and (2) involving patient-users from an early phase of design-concept making to a longitudinal trial of the system. The value of these factors was shown by the ability to identify factors that influence usability and usage in real-life settings in a long-term perspective in relation to original design concepts.
The extent to which our findings can be generalized is limited by intrinsically high motivation among many of our participants as well as the small number of the participants. However, it is highly probable that the factors that this study identified as reducing usability or usage would do so when users were less motivated. A revised version of the Few Touch application was tested by a group of 11 patients with T2DM who were not involved in the design process in order to assess the validity of our findings, and it is now being used as an intervention tool in an ongoing randomized controlled trial [
Long-term usage rates of each function by the participants.
Kernel density estimates on distribution of time points at which blood glucose measurement occurred during the day along the trial duration.
Kernel density estimates on distribution of time points at which nutrition habit recordings occurred during the day along the trial duration.
Summary of answers to original questionnaires.
Summary of prominent themes, codes, and examples of quotes.
information and communications technology
mobile access to health information
personal digital assistant
System Usability Scale
Type 2 diabetes mellitus
Type 1 diabetes mellitus
This work was supported by the Centre for Research-based Innovation, Tromsø Telemedicine Laboratory (TTL), through Norwegian Research Council Grant No. 174934, and by the Research Program for Telemedicine, Helse Nord RHF, Norway, and the Norwegian health and rehabilitation foundation “Helse og Rehabilitering”. These financial sponsors had no influence on study design, on collection, analysis and interpretation of data, on writing of the manuscript, or on the decision to submit the manuscript for publication.
The authors would like to thank the developers of the systems presented: Niklas Andersson, Ragnhild Varmedal, Thomas Samuelsen, and Taridzo Chomutare. We also thank all the participants in the cohorts involved.
Authors' Contributions: The individual contribution of the authors is summarized in the following sections: (1) conception and design of the present work, namely analysis of the results from the long-term trial, (2) designing and performing the long-term trial, (3) developing protocols for data collection, (4) data collection, (5) data analysis, (6) writing and editing the article, and (7) revising the article critically and final approval of the version to be published. The first author contributed in all but (2) and was a main contributor in (6). The second author contributed in all sections. The third author contributed in (5), (6), and (7), particularly in the trend analysis of usage rates. The fourth author contributed in (6) and (7) and in revising the sections from (1) to (5).
Conflicts of Interest: None declared.