This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright and license information must be included.
Behavioral science is now being integrated into diabetes self-management interventions. However, the challenge that presents itself is how to translate these knowledge resources during care so that primary care practitioners can use them to offer evidence-informed behavior change support and diabetes management recommendations to patients with diabetes.
The aim of this study was to develop and evaluate a computerized decision support platform called “Diabetes Web-Centric Information and Support Environment” (DWISE) that assists primary care practitioners in applying standardized behavior change strategies and clinical practice guidelines–based recommendations to an individual patient and empower the patient with the skills and knowledge required to self-manage their diabetes through planned, personalized, and pervasive behavior change strategies.
A health care knowledge management approach is used to implement DWISE so that it features the following functionalities: (1) assessment of primary care practitioners’ readiness to administer validated behavior change interventions to patients with diabetes; (2) educational support for primary care practitioners to help them offer behavior change interventions to patients; (3) access to evidence-based material, such as the Canadian Diabetes Association’s (CDA) clinical practice guidelines, to primary care practitioners; (4) development of personalized patient self-management programs to help patients with diabetes achieve healthy behaviors to meet CDA targets for managing type 2 diabetes; (5) educational support for patients to help them achieve behavior change; and (6) monitoring of the patients’ progress to assess their adherence to the behavior change program and motivating them to ensure compliance with their program. DWISE offers these functionalities through an interactive Web-based interface to primary care practitioners, whereas the patient’s self-management program and associated behavior interventions are delivered through a mobile patient diary via mobile phones and tablets. DWISE has been tested for its usability, functionality, usefulness, and acceptance through a series of qualitative studies.
For the primary care practitioner tool, most usability problems were associated with the navigation of the tool and the presentation, formatting, understandability, and suitability of the content. For the patient tool, most issues were related to the tool’s screen layout, design features, understandability of the content, clarity of the labels used, and navigation across the tool. Facilitators and barriers to DWISE use in a shared decision-making environment have also been identified.
This work has provided a unique electronic health solution to translate complex health care knowledge in terms of easy-to-use, evidence-informed, point-of-care decision aids for primary care practitioners. Patients’ feedback is now being used to make necessary modification to DWISE.
An estimated 9 million Canadians are living with diabetes, prediabetes, or undiagnosed diabetes [
Although PCPs are heavily involved in the long-term care of their patients with diabetes, studies have shown suboptimal and nonstandardized diabetes care at the primary care level [
In this paper, we present an innovative computerized decision support platform to (1) assist PCPs in administering evidence-based behavior change strategies and CPG-based recommendations for diabetes management and (2) empower patients with the skills and knowledge required to self-manage and monitor their diabetes through planned, personalized, and pervasive behavior change strategies. The key research tasks pursued in this project include (1) the development of a behavior change strategy based on evidence-based theories to better engage, empower, and inform the PCPs and their patients about behavior change strategies pertaining to diabetes control; (2) formulation of a comprehensive and validated knowledge base (in terms of a high-level behavior change ontology) that encapsulates semantic associations between multiple elements, that is, patient profile, CPG-derived diabetes management recommendations, and behavioral theory constructs that are coupled with behavior change strategies; (3) implementation of an integrated clinical decision support and behavior change intervention planning framework called Diabetes Web-centric Information and Support Environment (DWISE) that leverages semantic Web technologies to computerize behavioral and clinical knowledge in terms of an ontological knowledge model and generate personalized behavior change strategies by reasoning over the computerized knowledge using the patient profile. DWISE can be accessed by PCPs via a secure Web interface, and patients can access it via the DWISE mobile app; (4) evaluation of DWISE in terms of its usefulness, usability, and functionality through qualitative studies involving PCPs and patients. In the subsequent sections, we discuss in detail the design, development, and evaluation of DWISE.
CDA’s CPG [
To address the gaps in diabetes-related behavior change knowledge transfer, in this project, we demonstrate the applicability of digital health technologies to (1) provide decision support for PCPs to design and administer personalized behavior change strategies and (2) simultaneously provide motivational and educational support for patients with diabetes to self-manage their condition for improving diabetes control outcomes. In this regard, we present a knowledge management–based approach, together with its implementation and deployment, in terms of a DWISE that features the following functionalities: (1) assessment of PCPs’ readiness to administer validated behavior change interventions to patients with diabetes; (2) educational support for PCPs to help them offer behavior change interventions to patients with diabetes; (3) access to evidence-based material, such as the CDA’s CPG, to the PCPs; (4) development of personalized patient self-management programs to help patients with diabetes achieve healthy behaviors to meet CDA targets for managing type 2 diabetes; (5) educational support for patients to help them achieve behavior change; (6) monitoring the patients’ progress in adhering to their behavior change program and motivating them to be in compliance with their program. DWISE offers these functionalities to PCPs through an interactive Web-based interface, whereas the patient’s self-management program and associated behavior interventions are delivered through a mobile patient diary via mobile phones and tablets (
We contend that health education and support for chronic disease self-management should not just focus on changing the patient’s awareness of the disease but should also help to empower the patient to make the right choices to achieve effective disease management via self-management support mechanisms. In this regard, our solution approach is to incorporate validated behavior change theories—in our case social cognition theory (SCT) [
Diabetes Web-Centric Information and Support Environment (DWISE) framework overview. HbA1c: glycated hemoglobin.
The DWISE solution has 2 main elements: (1) behavior change strategies that are grounded in theoretical behavior change models [
Our solution involves modeling and computerization of diabetes management–related clinical and behavior change knowledge sources using semantic Web methods and then using digital health technologies to design personalized behavior change interventions and deliver behavior change support using Web and mobile interfaces [
To develop DWISE and, in particular, its knowledge backbone (ie, the BCO), we used an ontology-based information system design framework called Methontology [
The purpose of the behavior change knowledge modeling step is to develop specialized behavior change algorithms targeting the specific needs of both the PCPs and patients, which will be used to formulate theory-driven behavior change strategies. To develop behavior change algorithms based on our knowledge management approach, we abstracted and modeled key behavior change knowledge constructs from the available knowledge sources—the BCI strategies, diabetes CPG, and SCT model.
Knowledge modeling involved the abstraction of clinical and behavioral determinants from the paper-based knowledge sources that influence diabetes control outcomes. These determinants were then systematically linked and represented in terms of a rich multidimensional patient behavior profile. To enhance the ability of the patient’s behavior profile to personalize a behavior change strategy, the behavioral determinants were represented using multiple levels or ranges to capture the nonlinear nature of behavior change among different individuals. We developed 2 high-level behavior change algorithms, one each for PCPs and patients (as shown in
High-level PCP and patient behavior change algorithm. CPG: clinical practice guidelines; ; HbA1c: glycated hemoglobin; DWISE: Diabetes Web-Centric Information and Support Environment; PCP: primary care practitioner.
Each algorithm systematizes a variety of assessment tools based on behavioral determinants, range of PCP and patients’ inputs (in terms of observations, goals, and preferences), behavior change strategy options, behavior change strategy elements, motivational messages, and education material. The algorithms are based on 3 behavior change models that are described in the following paragraphs.
A behavior change readiness assessment model was developed by our team at the BCI to assess the readiness levels of both PCPs and patients toward behavior change programs. When used in the PCP’s behavior change strategy tool, our model assesses the readiness of a PCP to provide behavior counseling to help modify harmful behaviors in patients. When used in the patient’s behavior change support tool, the model measures the readiness of a patient to comply with recommended self-management support strategies. The behavior change readiness assessment model uses a systematic questionnaire (with responses of “yes,” “no,” and “maybe”) to categorize an individual into 3 stages of readiness, that is, ready, ambivalent, and not ready. As noted in other stage models, for instance, the transtheoretical model [
We used the decisional balance measure to determine an individual’s perception about the expected benefits (pros) of modifying a behavior as opposed to the disadvantages or costs (cons) of this behavior change. An individual who is deemed ambivalent or not ready for behavior change programs is required to undergo a decisional balance assessment, which includes up to 5 pros and 5 cons that measure positive and negative perceptions of PCPs in administering self-management behavior change support, and that of patients in adopting self-management behaviors. Decisional balance assessment is repeated after educating the ambivalent or not ready individual about the benefits of behavior change programs.
After the decisional balance assessment where the individual has been assessed to be ready for behavior change programs, a self-efficacy assessment is performed to measure a “ready” PCP’s degree of confidence that he or she can administer behavior change counseling, as well as a “ready” patient’s degree of confidence in complying with behavioral change strategies.
In practice, the PCP behavior change algorithm initially performs behavior change readiness assessment, decisional balance assessment, and self-efficacy assessment, and in response to the assessment, a range of targeted educational material is provided to the PCP. During a patient encounter, the PCP behavior change algorithm supports the design of a personalized behavior change strategy by providing targeted CPG-based recommendations, most suitable behavior to be targeted for a patient, and the corresponding behavior change strategy that is tailored based on the Specific, Measurable, Action-Oriented, Relevant, Timely (SMART) goals jointly set by the PCP and the patient and the patient profile.
The patient’s behavior change algorithm generates the patient support material based on the SMART behavior change goals to help the patient achieve the recommended HbA1c level. The patient behavior change algorithm operationalizes the personalized behavior change strategy to generate and deliver motivational messages, educational material, and recommendations for overcoming barriers to change so that patients can achieve their SMART goals.
To formally represent the behavior change knowledge model (and the algorithms), we developed a high-level BCO [
Information Personalization module that is used to create patient behavior change profiles, and it consists of 4 knowledge submodules:
Clinical Profile module represents clinical attributes derived from the CDA’s CPG, pertinent to describing the patient’s clinical medical profile with respect to diabetes control.
Readiness Assessment module represents the behavior change readiness assessment strategy for both PCPs and the patients, as developed by our team at BCI.
Decisional Balance Assessment module represents the positive and negative perceptions of “not ready” and “ambivalent” PCPs.
Self-Efficacy Assessment module represents the SCT-based self-efficacy assessments of PCPs and patients.
The patient behavior change profile is dynamically created when the information personalization module is executed using the patient’s attributes.
Domain Knowledge module that is used to represent the domain (ie, behavior change and self-management for diabetes control) knowledge, and it comprises 2 submodules:
Diabetes Domain module represents the evidence-based diabetes control recommendations as stipulated by CDA’s CPG.
Self-Management Domain module represents SCT-based self-management knowledge, for example, barriers to diabetes self-management and behavior change, self-management and behavior change support materials and strategies, and SMART goal setting support.
Information personalization and domain knowledge elements of Behavior Change Ontology.
A subset of readiness assessment module in Behavior Change Ontology, depicting procedural relationships between classes “Readiness Assessment” and “Readiness Assessment Result.”.
To develop the BCO, we used object properties to represent declarative and procedural relationships between classes. Axioms and rules were used to augment the procedural aspect of the BCO further.
Information personalization submodules—readiness assessment, decisional balance assessment, and self-efficacy assessment—computerize assessment questionnaires to identify the patient’s current behavioral predisposition. The questionnaires are represented as an object and the questions within them as their properties. The questions’ responses such as values from 1 to 4 are represented as datatype properties, whereas questions that require a predefined statement as a response (eg, what is the highest level of education you have achieved?) are represented as object type properties. Property restrictions, such as cardinality restrictions, range (both for object type and data type), and allowed values were used to ensure knowledge integrity. The Information Personalization module contains 10 classes (Barrier, Barrier to Change, Clinical Profile, Decisional Balance, Decisional Balance Result, Readiness Assessment, Readiness Assessment Result, Self-Efficacy Questionnaire, Self-Efficacy Result, and Prognostic Factors). In total, BCO represents 18 top-level classes, whereas the entire class hierarchy consists of 80 classes. There are 16 top-level object properties with 18 object subproperties and 7 top-level data type properties with 40 data type subproperties. Finally, BCO was instantiated using the content that was gathered and developed in the PCP and patient algorithms. We used Protégé 2000 knowledge acquisition tool (Stanford Center of Biomedical Informatics Research, Stanford University, Stanford, California) [
BCO was evaluated for (1) knowledge accuracy and utility by 3 domain experts (psychologist, endocrinologist, and a family physician) and (2) semantic accuracy to ensure logical consistency. Although experts generally agreed with the representations, they nevertheless suggested a few improvements, for example, better definition of the class Clinical_Profile in terms of its properties and relationship with the class Clinical_Parameter. Changes were made to BCO in terms of its concept description, relationships, and constraints after each evaluation event in response to the experts’ comments. The technical evaluation of BCO was carried out in accordance with the criteria suggested by Gomez Perez [
A prototype of DWISE framework consisting of the Web-based PCP interface and a mobile app for patients has been implemented. The overall technical architecture of DWISE framework is illustrated in
DWISE decision support framework consists of a PCP and a patient tool. DWISE PCP decision support tool (
DWISE patient support tool is implemented as both a Web-based system and a mobile app, with the functionality to deliver the following self-management support to patients: (1) behavior change strategies such as goal setting, behavior shaping, stimulus control, and reinforcement management; (2) context-aware motivational and behavior change educational messages; and (3) communication with care providers. The DWISE mobile app (
Two qualitative studies that incorporated Think Aloud Protocol (TAP) method [
For the usability study, we used a cognitive and usability engineering framework [
After ethics approval, we randomly recruited 10 PCPs (4 family physicians and 6 CDEs) for the PCP study and 11 patients for the patient study. The sample size estimate is based on the evidence that 70% of severe usability problems can be uncovered within the first 5 users, and up to 85% by the eighth user [
Diabetes Web-Centric Information and Support Environment (DWISE) technical architecture. BCI: Behavior Change Institute; CDA: Canadian Diabetes Association; CPG: clinical practice guidelines; PCP: primary care practitioner.
Tool for primary care practitioners assessing self-efficacy of the family physicians/certified diabetes educators.
Screenshots from Diabetes Web-Centric Information and Support Environment (DWISE) mobile apps depicting functionalities such as scheduling, notifications, barrier identification, and feedback.
Barriers to Diabetes Web-Centric Information and Support Environment (DWISE) usage
Facilitators to DWISE usage
Patient behavior change
Patient empowerment and education
Patient autonomy and preference
Patient-provider communication
Encounter-related issues
Professional roles and responsibilities
Usability- or acceptability-related issues
Patients were presented with a standard behavioral recommendation, that is, physical activity that they have hypothetically agreed to pursue in concert with their PCP/CDE. The patients then defined a specific target behavior, assessed their readiness, and received support in setting a goal for behavior change. This yielded 11 TAPs from 11 patients. During the interactions with DWISE, each participant was encouraged to think aloud. Participants’ screen activity and audio were recorded using the QuickTime player. The usability study design is presented in the study by Abidi et al [
For the focus group study, a purposive sampling strategy was used to recruit 4 patients and 3 PCPs, after acquiring the ethics approval. The purpose of this study was to engage patients and PCPs in shared decision-making environment to elicit (1) initial impression about the DWISE system; (2) advantages and disadvantages of DWISE in providing CPG-based recommendation and behavior change strategies to the PCPs and patients; (3) potential impact of DWISE on patient-provider communication and relationship around diabetes-related behavior change; and (4) suggestions to improve DWISE. The session was audio-recorded and transcribed verbatim and was supplemented by field notes, sketches, and observation logs. The experts on the team prepared a semistructured moderator’s guide based on their clinical and research experience and the review of the related literature. The guide included open-ended questions and problem-based representative scenarios related to various self-management processes to stimulate conversations in case of unresponsive participants. Content validity of the guide was established by review of the literature on diabetes self-management in populations that are culturally and socioeconomically similar to the population of interest. Further validity was established through critique, change, and consensus of the expert research team members.
Computer screen activity, audio files transcribed verbatim, field notes, and observation logs were analyzed in the ATLAS.Ti software (ATLAS.ti Scientific Software Development GmbH) using inductive thematic coding [
The background and demographic information of PCPs and patients, which was collected for the TAP study, is presented in detail in the study by Abidi et al [
The 7 participants for the focus group study included 3 CDEs and 4 patients. All 3 CDEs were females, and of 4 patients, 3 were females, and 1 was male. Ages for CDEs ranged from 29 to 55 years, and patients were aged between 49 and 64 years. All CDEs worked at DMCs. CDEs had a median of 11 years of experience (range 3-19 years). Patients had diabetes for a median of 13.5 years (range 2-25 years).
In total, 31 independent open codes based on usability issues were identified in TAPs by 30 PCPs. The detailed results are presented in the study by Abidi et al [
Patients’ TAPs yielded 17 open codes and 9 axial categories of usability issues. The detailed results are presented in study by Abidi et al [
Axial codes in a primary care practitioner;'s Think Aloud Protocol.
Axial category “Screen layout and design features” contain 6 open codes.
Each axial code represents areas for possible enhancement needed in DWISE content, screen layout and features, design, and other usability features. Sorting by theme and related codes and their frequency gives a detailed picture of the specific improvements and modifications that are needed before DWISE can be tested for its efficacy. The criticality of usability problems is based on the number of open codes in each category and the frequency of these codes in the quotations.
We considered the criticality of a code and the axial category to improve the design of DWISE. Any open code that occurred in a single quotation was discarded. In general, for the PCP tool, most problems were associated with the navigation of the tool and the presentation, formatting, understandability, and suitability of the content in the tool. For the patient support tool, most issues were related to the tool’s screen layout and design features, understandability of the content, clarity of the labels used, and navigation across the tool. We used this feedback from the qualitative study to modify DWISE in terms of its user interface design and its content.
In all, 73 open codes were discovered in data that were classified into 27 independent axial codes.
The PCPs appreciated that DWISE could be used as a teaching tool to teach diabetes-related self-management skills to their patients:
I try to guide my patients towards diabetes related self-management resources available...but really, there are silos of teaching that affects one’s ability to learn. DWISE is good...it is more comprehensive and is more relevant to a patient’s needs...this can help deal with these problems...I believe this should be accessible to most patients.
The participants felt that although there are many diabetes educational resources, they want DWISE type apps that consider a patient’s personal preferences and psychosocial concerns, when designing self-management strategies. Both patients and PCPs felt that there is more need for information about the psychological issues for patients with diabetes:
There should be apps that talk more about things like...distress, depression and psychology...I mean diabetes is hard, sometimes we are distressed and we need information and we rely a lot on Internet...
Finally, patients who were more engaged in their self-management felt that DWISE is an ideal tool for them, and they believed that using DWISE will be easier for them. Participants overwhelmingly stated that they would like some kind of technical support, such as online or face-to-face sessions on DWISE, to teach them how to use DWISE. They suggested that there should be a helpdesk or other resources to help them troubleshoot to facilitate use of DWISE.
From the PCPs’ perspective, time constraints were deemed to be a key barrier in the use of DWISE. PCPs felt that inclusion of DWISE-based intervention might not be feasible during the patient encounter because of the limited time that they have with their patients:
I love it...but can I do a good job with it? How can I incorporate this within the time restrictions?...at times it may not be conducive to my schedule...a patient gets just 15 minutes with the provider.
PCPs were also worried about liability related issues:
Ok, suppose I am using this app with my patients, what if I missed something or I fail to do what is expected of me? Would I be liable...what will be the impact?
PCPs also stated that including DWISE in their practice might result in additional work for them. Patients were worried that if they failed to achieve the goals that they have set through DWISE, they might lose respect in the eyes of the PCP, or disappoint them, and might feel burdened or stressed:
I mean respect is a two-way street...what if I don’t meet that goal...what would my doctor think about me?
Patients also stressed on preference for direct patient-provider contact:
Sometimes I just want to talk during an appointment with my doctors...maybe I don’t want to talk through an app during this time.
Axial codes in each category. DWISE: Diabetes Web-Centric Information and Support Environment; PCP: primary care practitioner.
A priori category | Axial codes (number of open codes contained in each axial category) |
Facilitators to DWISE usage | Technical support to facilitate DWISE usage (10) |
Teaching tool for patients (5) | |
Need for personalized diabetes self-management apps (4) | |
Need for information about psychological issues (2) | |
Compliance with DWISE easier for engaged patients (1) | |
Barriers to DWISE usage | Practicality of DWISE due to PCP time constraints (4) |
Impact on patients who fail to achieve DWISE set goals (4) | |
Age-related suitability (4) | |
Practicality of DWISE because of technically challenged users (3) | |
Preference for direct patient-PCP contact (3) | |
Additional work (1) | |
Liability-related issues (1) | |
Patient self-management | Potential to improve self-management and monitoring (3) |
Potential to modify behavior (1) | |
Patient education | Teaching tool for patients (5) |
Potential to improve patient awareness of disease (3) | |
Patient autonomy and preference | Patient autonomy in choosing self-management support delivery method (4) |
Power dynamic between patient and provider (2) | |
Potential to improve patient empowerment (3) | |
Patient-provider communication | Insight into patient’s self-management practices (2) |
Potential to improve patient-provider communication (3) | |
Preference for direct patient-provider contact (3) | |
Encounter-related issues | Impact on patient provider encounter (3) |
Practicality of DWISE due to PCP time constraints (4) | |
Professional roles and responsibilities | Professional roles and responsibilities around DWISE usage (2) |
Additional work (1) | |
Usability- or acceptability-related issues | Reminders to improve usability (1) |
System feedback (2) | |
Information presentation in DWISE (2) | |
Integration with other devices (2) | |
Need for personal features in DWISE (3) |
Both PCPs and patients felt that technology ineptness might be a deterrent to their use of DWISE:
One of my colleague is not tech savvy...there might be other providers like her. How can these people benefit from DWISE?...would they be interested?
One of the patients said:
I am not technologically adept, these are new and exciting...I like help with managing my diabetes...but there might be big learning curve for me.
Participants felt that DWISE has the potential to improve diabetes self-management, especially given that mobile phones are ubiquitous and self-management plans formulated through DWISE can easily be integrated into the patients’ lives. Participants indicated that DWISE has the potential to improve diabetes-related monitoring:
Phone is ubiquitous, so more opportunities. I love apps for recording and monitoring...this can help me monitor my sugar.
One PCP remarked:
It helps me gain more information about diabetes-related behavior change and about my patient and both my patient and I can see if my patient is on the right track...we will have something to talk about next time we meet.
Participants felt that DWISE may help improve patient’s awareness of the disease and can be used as a teaching tool for patients:
DWISE makes me more aware...more informed...I feel like I want to know more so that I can better take care of myself.
Patients felt that they should have autonomy in choosing self-management support delivery method. One patient said:
I don't believe that one size fits all...it is good to have platforms like apps...DWISE is easily available...it should not be made mandatory for every patient...I mean it has to be my choice.
A patient also stated that DWISE has potential to improve power dynamics between the patient and PCP and help patients gain more control over their diabetes management:
I feel balance of power is always in favour of my doctor...it’s not bad...but I like to be more involved...make decisions that fits my life...DWISE can give me more control.
In general, participants felt that using a tool such as DWISE might make them feel more empowered to self-manage their condition.
Although appreciating that DWISE has the potential to provide better insights into their patients’ self-management practices, PCPs felt that DWISE could also improve communication between patients and PCPs around diabetes-related self-management. One of the PCPs said:
When a patient is first diagnosed with diabetes...DWISE can be a good avenue for discussion...about how a patient is feeling, what is it they want...how can they fit the self-management in their lives.
Patients also felt that DWISE could potentially help them to communicate personal issues that might affect their self-management practices and that otherwise would not come up during an appointment:
Doctors don’t live with diabetes...I live with diabetes...I have lived with diabetes for so long...this type of technology and apps can support me to better communicate with my doctor...what I am going through...why I am not able to follow proper diet or...not exercising...
Although some PCPs expressed that it might not be practical to use DWISE during the encounter because of PCPs’ time constraints, other PCPs and patients expressed that DWISE can have a positive impact on the patient-PCP encounter in terms of shared decision making around the setting of SMART goals. PCPs underscored that a patient might be more prepared during the encounter:
Every patient is different...and self-management requirements vary so much...so patients coming prepared will be so good for the appointment...I think appointment time will be better spent.
Patients expressed that they will be more motivated to comply with plan set through DWISE to have a meaningful encounter:
There are higher problems that are not in my control...that might mix the schedule...but I will still try to do this or change it to have a better appointment...I’ll go to the appointment with something...
PCPs were unsure about the professional roles and responsibilities pertaining to the usage of DWISE in a clinical setting. They wondered how doctors, CDEs, and nurses would coordinate and collaborate to ensure that a tool such as DWISE can be used effectively:
How would this work...I mean how do we collaborate...should this be administered through a doctor or a nurse educator...who would monitor.
Finally, participants offered some feedback regarding issues related to the usability and acceptability of DWISE. Although some participants suggested that there should be more reminders to help them comply with self-management plans and upcoming activities, others suggested that a user should be able to disable the reminder when he or she feels like. Participants commented on the information presentation in DWISE and suggested that there should be a better layout, too much text should be avoided, and it should be replaced by user-friendly features such as pictures and figures. They suggested that a good feature would be to have a space for users to type their notes in free text. Participants also expressed their desire to have some personal features included in the app, such as provision to include their “profile picture,” “personal profile information,” and “personal diabetes story.” Participants further suggested that DWISE should be integrated with other data collection devices, such as Fitbit, smart watch, and so on.
Digital health technologies have been effectively used for health information collection, information utilization, and sharing solutions. In this study, we have demonstrated that digital health applications can effectively and efficiently incorporate evidence-based health care knowledge to provide evidence-informed decisions or recommendations to support both health care professionals and patients. This is an ongoing work and DWISE is a proof of concept. Nevertheless, this work has provided a unique digital health solution to translate complex health care knowledge, that is, guidelines, clinical workflows, behavior models, educational content, and long-term care plans, in terms of easy-to-use, evidence-informed, point-of-care decision aids for both PCPs and patients. From a clinical perspective, the contribution of this research is the translation of specialized behavior change knowledge to family physicians and diabetes educators, thus enabling them to offer behavior change interventions to a larger population of patients with diabetes—at present, only one-third of Canadians with diabetes receive diabetes educational programs [
A unique aspect of this research is the integration of paper-based medical knowledge, behavior change models, health care knowledge management methods, and mobile technologies to develop “intelligent and adaptive” mobile patient-centered solutions that are customizable to specific care contexts, users’ knowledge, and interests. The project has contributed a generic digital health strategy and technology, based on theoretical models that can be applied to a range of medical conditions, to deliver intelligent and ubiquitous health educational and decision aids. In the long term, we plan to extend the research to other chronic diseases where we will account for different disease-specific factors pertaining to the personalization of behavior change strategies. In the medium term, we would augment the research scope to incorporate other related metabolic conditions that are characterized by hyperglycemia such as prediabetes.
The 3 qualitative studies included small sample sizes. However, for usability studies, a small number of participants are deemed sufficient for determining the major usability issues [
In this paper, we have presented a digital health solution to translate complex health care knowledge, that is, guidelines, clinical workflows, behavior change models, educational content, and long-term care plans, in terms of easy-to-use, evidence-informed, point-of-care decision aids for both PCPs and patients. The knowledge modeling methods and decision support technologies being developed are both scalable and generic in nature, such that they can be readily applied to computerize CPG for other chronic diseases to develop low-cost decision support aids that can standardize the care of chronic diseases and comorbidities at the primary care level.
DWISE has been evaluated for usability, functionality, usefulness, and acceptance in a shared decision-making environment through a series of qualitative studies. In general, for the PCP decision support tool, most usability problems were associated with the navigation of the tool and the presentation, formatting, understandability, and suitability of the content in the tool. For the patient support tool, most usability issues that were raised were related to the tool’s screen layout and design features, understandability of the content, clarity of the labels used, and navigation across the tool. With regard to the usefulness of DWISE in a shared decision-making environment, the most significant barrier from the PCPs’ perspective is the limited time PCPs have during an encounter and, and from patients’ perspective, the concern is the fear of failure to accomplish their goals to achieve diabetes control through behavior change interventions. In terms of facilitators, PCPs identified the potential of DWISE as a teaching tool for their patients, and the patients appreciated that DWISE provides personalized information especially on psychological issues that could be very useful to them. In general, participants felt that provision of technical support, especially to the elderly users and those who are not proficient in technology will facilitate the use of DWISE. Patients preferred that DWISE should not be made mandatory and should not completely replace the direct interactions with the PCPs, rather should be regarded as an additional support mechanism. Patients felt that DWISE may help them gain more control over their diabetes management, whereas PCPs suggested that it could assist them to gain more insight into a patient’s self-management practices. PCPs seemed unsure about their respective roles and responsibilities around DWISE usage. The results of these studies were used to guide the modification of DWISE in terms of its functionalities, screen layout and navigation, and content.
In conclusion, we contend that digital health technology, such as DWISE, that integrates a patient’s (clinical and behavioral) profile with CPG-based best evidence and SCT-based behavior change theories, when used in a shared decision-making environment, has the potential to improve self-management and increase sense of collaboration and trust in the care process. Our finding suggests a dynamic interplay between patients, PCPs, as well as systemic and technology factors in terms of the operationalization of the DWISE framework for diabetes management. However, we also believe that the implementation of an integrated framework such as DWISE, in a shared decision-making clinical environment, requires additional time for the technology to mature, technical innovation, organizational support for technology uptake, and a clear definition of professional roles and responsibilities.
Behavior Change Institute
Behavior Change Ontology
Canadian Diabetes Association
certified diabetes educators
clinical practice guidelines
Diabetes Management Centers
Diabetes Web-Centric Information and Support Environment
glycated hemoglobin
primary care practitioner
social cognition theory
Web Ontology Language
Specific, Measurable, Action-Oriented, Relevant, Timely
Think Aloud Protocol
The authors acknowledge the support of Canadian Institute of Health Research. The project was supported through an eHealth Innovation grant.