Using Wearable Devices and Speech Data for Personalized Machine Learning in Early Detection of Mental Disorders: Protocol for a Participatory Research Study.

BACKGROUND: Early identification of mental disorder symptoms is crucial for timely treatment and reduction of recurring symptoms and disabilities. A tool to help individuals recognize warning signs is important. We posit that such a tool would have to rely on longitudinal analysis of patterns and trends in the individual's daily activities and mood, which can now be captured through data from wearable activity trackers, speech recordings from mobile devices, and the individual's own description of their mental state. In this paper, we describe such a tool developed by our team to detect early signs of depression, anxiety, and stress. OBJECTIVE: This study aims to examine three questions about the effectiveness of machine learning models constructed based on multimodal data from wearables, speech, and self-reports: (1) How does speech about issues of personal context differ from speech while reading a neutral text, what type of speech data are more helpful in detecting mental health indicators, and how is the quality of the machine learning models influenced by multilanguage data? (2) Does accuracy improve with longitudinal data collection and how, and what are the most important features? and (3) How do personalized machine learning models compare against population-level models? METHODS: We collect longitudinal data to aid machine learning in accurately identifying patterns of mental disorder symptoms. We developed an app that collects voice, physiological, and activity data. Physiological and activity data are provided by a variety of off-the-shelf fitness trackers, that record steps, active minutes, duration of sleeping stages (rapid eye movement, deep, and light sleep), calories consumed, distance walked, heart rate, and speed. We also collect voice recordings of users reading specific texts and answering open-ended questions chosen randomly from a set of questions without repetition. Finally, the app collects users' answers to the Depression, Anxiety, and Stress Scale. The collected data from wearable devices and voice recordings will be used to train machine learning models to predict the levels of anxiety, stress, and depression in participants. RESULTS: The study is ongoing, and data collection will be completed by November 2023. We expect to recruit at least 50 participants attending 2 major universities (in Canada and Mexico) fluent in English or Spanish. The study will include participants aged between 18 and 35 years, with no communication disorders, acute neurological diseases, or history of brain damage. Data collection complied with ethical and privacy requirements. CONCLUSIONS: The study aims to advance personalized machine learning for mental health; generate a data set to predict Depression, Anxiety, and Stress Scale results; and deploy a framework for early detection of depression, anxiety, and stress. Our long-term goal is to develop a noninvasive and objective method for collecting mental health data and promptly detecting mental disorder symptoms. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48210.

Associations between Differential Aging and Lifestyle, Environment, Current, and Future Health Conditions: Findings from Canadian Longitudinal Study on Aging.

INTRODUCTION: An aging population will bring a pressing challenge for the healthcare system. Insights into promoting healthy longevity can be gained by quantifying the biological aging process and understanding the roles of modifiable lifestyle and environmental factors, and chronic disease conditions. METHODS: We developed a biological age (BioAge) index by applying multiple state-of-art machine learning models based on easily accessible blood test data from the Canadian Longitudinal Study of Aging (CLSA). The BioAge gap, which is the difference between BioAge index and chronological age, was used to quantify the differential aging, i.e., the difference between biological and chronological age, of the CLSA participants. We further investigated the associations between the BioAge gap and lifestyle, environmental factors, and current and future health conditions. RESULTS: BioAge gap had strong associations with existing adverse health conditions (e.g., cancers, cardiovascular diseases, diabetes, and kidney diseases) and future disease onset (e.g., Parkinson's disease, diabetes, and kidney diseases). We identified that frequent consumption of processed meat, pork, beef, and chicken, poor outcomes in nutritional risk screening, cigarette smoking, exposure to passive smoking are associated with positive BioAge gap ("older" BioAge than expected). We also identified several modifiable factors, including eating fruits, legumes, vegetables, related to negative BioAge gap ("younger" BioAge than expected). CONCLUSIONS: Our study shows that a BioAge index based on easily accessible blood tests has the potential to quantify the differential biological aging process that can be associated with current and future adverse health events. The identified risk and protective factors for differential aging indicated by BioAge gap are informative for future research and guidelines to promote healthy longevity.

Examining Patient Engagement in Chatbot Development Approaches for Healthy Lifestyle and Mental Wellness Interventions: Scoping Review.

BACKGROUND: Chatbots are growing in popularity as they offer a range of potential benefits to end users and service providers. OBJECTIVE: Our scoping review aimed to explore studies that used 2-way chatbots to support healthy eating, physical activity, and mental wellness interventions. Our objectives were to report the nontechnical (eg, unrelated to software development) approaches for chatbot development and to examine the level of patient engagement in these reported approaches. METHODS: Our team conducted a scoping review following the framework proposed by Arksey and O'Malley. Nine electronic databases were searched in July 2022. Studies were selected based on our inclusion and exclusion criteria. Data were then extracted and patient involvement was assessed. RESULTS: 16 studies were included in this review. We report several approaches to chatbot development, assess patient involvement where possible, and reveal the limited detail available on reporting of patient involvement in the chatbot implementation process. The reported approaches for development included: collaboration with knowledge experts, co-design workshops, patient interviews, prototype testing, the Wizard of Oz (WoZ) procedure, and literature review. Reporting of patient involvement in development was limited; only 3 of the 16 included studies contained sufficient information to evaluate patient engagement using the Guidance for Reporting Involvement of Patients and Public (GRIPP2). CONCLUSIONS: The approaches reported in this review and the identified limitations can guide the inclusion of patient engagement and the improved documentation of engagement in the chatbot development process for future health care research. Given the importance of end user involvement in chatbot development, we hope that future research will more systematically report on chatbot development and more consistently and actively engage patients in the codevelopment process.

Co-designing a Sexual Health App With Immigrant Adolescents: Protocol for a Qualitative Community-Based Participatory Action Research Study.

BACKGROUND: Canada is one of the world's most ethnically diverse countries, with over 7 million individuals out of a population of 38 million being born in a foreign country. Immigrant adolescents (aged 10 to 19 years) make up a substantial proportion of newcomers to Canada. Religious and cultural practices can influence adolescents' sexual attitudes and behaviors, as well as the uptake of sexual and reproductive health (SRH) services among this population. Adolescence is a time to establish lifelong healthy behaviors. Research indicates an alarming gap in adolescents' SRH knowledge, yet there is limited research on the SRH needs of immigrant adolescents in Canada. OBJECTIVE: The purpose of this study is to actively engage with immigrant adolescents to develop, implement, and evaluate a mobile health (mHealth) intervention (ie, mobile app). The interactive mobile app will aim to deliver accurate and evidence-based SRH information to adolescents. METHODS: We will use community-based participatory action research to guide our study. This research project will be conducted in 4 stages based on user-centered co-design principles. In Stage 1 (Empathize), we will recruit and convene 3 adolescent advisory groups in Edmonton, Toronto, and Vancouver. Members will be engaged as coresearchers and receive training in qualitative and quantitative methodologies, sexual health, and the social determinants of health. In Stage 2 (Define and Ideate), we will explore SRH information and service needs through focus group discussions with immigrant adolescents. In Stage 3 (Prototype), we will collaborate with mobile developers to build and iteratively design the app with support from the adolescent advisory groups. Finally, in Stage 4 (Test), we will return to focus group settings to share the app prototype, gather feedback on usability, and refine and release the app. RESULTS: Recruitment and data collection will be completed by February 2023, and mobile app development will begin in March 2023. The mHealth app will be our core output and is expected to be released in the spring of 2024. CONCLUSIONS: Our study will advance the limited knowledge base on SRH and the information needs of immigrant adolescents in Canada as well as the science underpinning participatory action research methods with immigrant adolescents. This study will address gaps by exploring SRH priorities, health information needs, and innovative strategies to improve the SRH of immigrant adolescents. Engaging adolescents throughout the study will increase their involvement in SRH care decision-making, expand efficiencies in SRH care utilization, and ultimately improve adolescents' SRH outcomes. The app we develop will be transferable to all adolescent groups, is scalable in international contexts, and simultaneously leverages significant economies of scale. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/45389.

Implementation and evaluation of a pain assessment app and novel community platform for long-term care health professionals.

OBJECTIVE: A tablet app, based on the Pain Assessment Checklist for Seniors with Limited Ability to Communicate-II (PACSLAC-II), has been shown to have clinical utility and unique advantages. We aimed to replicate and extend the previous validation of the app through the implementation and evaluation of a new community platform involving a quality indicator (QI) monitoring feature and a resource community portal (CP) that work in conjunction with an updated version of the app. METHODS: We employed a mixed-methods multiple-baseline design across 11 long-term care (LTC) units. Units were randomly assigned to conditions which varied in number of app features available. Data included unit-level QIs as well as questionnaires and semi-structured interviews with health professionals. RESULTS: Following use of the app, we found improvements in unit-level QIs regardless of availability of the QI/CP features. During interviews, participants expressed a preference for the app over a paper version of the PACSLAC-II due to reasons such as the app's ability to summarize information. Utilization of the community portal websites was unrelated to staff questionnaire-assessed stress/burnout. CONCLUSIONS: Despite the positive effects on the care of residents, the COVID-19 pandemic presented challenges and interfered with the long-term maintenance of the QI results.

Developing, Implementing, and Evaluating an Artificial Intelligence-Guided Mental Health Resource Navigation Chatbot for Health Care Workers and Their Families During and Following the COVID-19 Pandemic: Protocol for a Cross-sectional Study.

BACKGROUND: Approximately 1 in 3 Canadians will experience an addiction or mental health challenge at some point in their lifetime. Unfortunately, there are multiple barriers to accessing mental health care, including system fragmentation, episodic care, long wait times, and insufficient support for health system navigation. In addition, stigma may further reduce an individual's likelihood of seeking support. Digital technologies present new and exciting opportunities to bridge significant gaps in mental health care service provision, reduce barriers pertaining to stigma, and improve health outcomes for patients and mental health system integration and efficiency. Chatbots (ie, software systems that use artificial intelligence to carry out conversations with people) may be explored to support those in need of information or access to services and present the opportunity to address gaps in traditional, fragmented, or episodic mental health system structures on demand with personalized attention. The recent COVID-19 pandemic has exacerbated even further the need for mental health support among Canadians and called attention to the inefficiencies of our system. As health care workers and their families are at an even greater risk of mental illness and psychological distress during the COVID-19 pandemic, this technology will be first piloted with the goal of supporting this vulnerable group. OBJECTIVE: This pilot study seeks to evaluate the effectiveness of the Mental Health Intelligent Information Resource Assistant in supporting health care workers and their families in the Canadian provinces of Alberta and Nova Scotia with the provision of appropriate information on mental health issues, services, and programs based on personalized needs. METHODS: The effectiveness of the technology will be assessed via voluntary follow-up surveys and an analysis of client interactions and engagement with the chatbot. Client satisfaction with the chatbot will also be assessed. RESULTS: This project was initiated on April 1, 2021. Ethics approval was granted on August 12, 2021, by the University of Alberta Health Research Board (PRO00109148) and on April 21, 2022, by the Nova Scotia Health Authority Research Ethics Board (1027474). Data collection is anticipated to take place from May 2, 2022, to May 2, 2023. Publication of preliminary results will be sought in spring or summer 2022, with a more comprehensive evaluation completed by spring 2023 following the collection of a larger data set. CONCLUSIONS: Our findings can be incorporated into public policy and planning around mental health system navigation by Canadian mental health care providers-from large public health authorities to small community-based, not-for-profit organizations. This may serve to support the development of an additional touch point, or point of entry, for individuals to access the appropriate services or care when they need them, wherever they are. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/33717.

A Virtual Community of Practice to Support Physician Uptake of a Novel Abortion Practice: Mixed Methods Case Study.

BACKGROUND: Virtual communities of practice (VCoPs) have been used to support innovation and quality in clinical care. The drug mifepristone was introduced in Canada in 2017 for medical abortion. We created a VCoP to support implementation of mifepristone abortion practice across Canada. OBJECTIVE: The aim of this study was to describe the development and use of the Canadian Abortion Providers Support-Communauté de pratique canadienne sur l'avortement (CAPS-CPCA) VCoP and explore physicians' experience with CAPS-CPCA and their views on its value in supporting implementation. METHODS: This was a mixed methods intrinsic case study of Canadian health care providers' use and physicians' perceptions of the CAPS-CPCA VCoP during the first 2 years of a novel practice. We sampled both physicians who joined the CAPS-CPCA VCoP and those who were interested in providing the novel practice but did not join the VCoP. We designed the VCoP features to address known and discovered barriers to implementation of medication abortion in primary care. Our secure web-based platform allowed asynchronous access to information, practice resources, clinical support, discussion forums, and email notices. We collected data from the platform and through surveys of physician members as well as interviews with physician members and nonmembers. We analyzed descriptive statistics for website metrics, physicians' characteristics and practices, and their use of the VCoP. We used qualitative methods to explore the physicians' experiences and perceptions of the VCoP. RESULTS: From January 1, 2017, to June 30, 2019, a total of 430 physicians representing all provinces and territories in Canada joined the VCoP and 222 (51.6%) completed a baseline survey. Of these 222 respondents, 156 (70.3%) were family physicians, 170 (80.2%) were women, and 78 (35.1%) had no prior abortion experience. In a survey conducted 12 months after baseline, 77.9% (120/154) of the respondents stated that they had provided mifepristone abortion and 33.9% (43/127) said the VCoP had been important or very important. Logging in to the site was burdensome for some, but members valued downloadable resources such as patient information sheets, consent forms, and clinical checklists. They found email announcements helpful for keeping up to date with changing regulations. Few asked clinical questions to the VCoP experts, but physicians felt that this feature was important for isolated or rural providers. Information collected through member polls about health system barriers to implementation was used in the project's knowledge translation activities with policy makers to mitigate these barriers. CONCLUSIONS: A VCoP developed to address known and discovered barriers to uptake of a novel medication abortion method engaged physicians from across Canada and supported some, including those with no prior abortion experience, to implement this practice. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2018-028443.

Social Media and the Transformation of the Physician-Patient Relationship: Viewpoint.

As many as 80% of internet users seek health information online. The social determinants of health (SDoH) are intimately related to who has access to the internet and health care as a whole. Those who face more barriers to care are more likely to benefit from accessing health information online, assuming the information they are retrieving is accurate. Virtual communities on social media platforms are beginning to serve as venues for seeking health information online because peers have been shown to influence health behavior more than almost anything else. As a positive mediator of health, social media can be used as a direct or indirect mode of communication between physicians and patients, a venue for health promotion and health information, and a community support network. However, false or misleading content, social contagion, confirmation bias, and security and privacy concerns must be mitigated to realize the full potential of social media as a positive mediator of health. This paper presents the shifting dynamics of how such communities are affecting physician-patient relationships. With the intersections between the SDoH, social media, and health evolving, physicians must take into consideration these factors when establishing their relationships with patients. We argue a paradigm shift in the physician-patient relationship is warranted, one where physicians acknowledge the impacts of the SDoH on information-seeking behavior, recognize the positive and negative roles of social media as a mediator of health through the lens of the SDoH, and use social media to catalyze positive changes in the physician-patient relationship. We discuss how the physician-patient relationship must evolve to accommodate for the ever-increasing role of social media in health and to best use social media as a tool to improve health outcomes. Finally, we present a fluid and multicomponent diagram that we believe will assist in framing future research in this area. We conclude that it is ineffective and even counterproductive for physicians to ignore the relationship between social media, the SDoH and health, their impact on one another, and the effect it has on designing the medical encounter and the delivery of care under the definition of precision medicine.

Towards a Simulation Framework for Smart Indoor Spaces.

The effectiveness of sensor-based applications for smart homes and smart buildings is conditioned upon the deployment configuration of their underlying sensors. Real-world evaluation of alternative possible sensor-deployment configurations is labor-intensive, costly, and time-consuming, which implies the need for a simulation-based methodology. In this work, we report on such a methodology that supports the modeling of indoor spaces, the activities of their occupants, and the behaviors of different types of sensors. We argue that, in order for a simulation to be useful for the purpose of evaluating a sensor deployment configuration, it has to generate realistic event streams of individual sensors over time, as well as realistic compositions of sensor events within a time window. We have evaluated our simulator for smart indoor spaces, SIMsis toolkit, in the context of our Smart-Condo ambient-assisted living platform, supporting the observation and analysis of activities of daily living (ADLs). Our findings indicate that SIMsis produces realistic agent traces and sensor readings, and has the potential to support the process of developing and deploying sensor-based applications.

Behavioral Pain Assessment Implementation in Long-Term Care Using a Tablet App: Case Series and Quasi-Experimental Design.

BACKGROUND: Pain is often underassessed and undertreated among long-term care (LTC) residents living with dementia. When used regularly, the Pain Assessment Checklist for Seniors With Limited Ability to Communicate (PACSLAC) scales have been shown to have beneficial effects on pain assessment and management practices and stress and burnout levels in frontline staff in LTC facilities. Such scales, however, are not utilized as often as recommended, which is likely to be related to additional record-keeping and tracking over time involved with their paper-and-pencil administration. OBJECTIVE: Using implementation science principles, we assessed the introduction of the PACSLAC-II scale by comparing two methods of administration-a newly developed tablet app version and the original paper-and-pencil version-with respect to the frequency of pain assessment and facility staff feedback. METHODS: Using a case series approach, we tracked pain-related quality indicators at baseline, implementation, and follow-up periods. A quasi-experimental design was used to evaluate the effect of the method of administration (ie, paper-and-pencil only [n=18], tablet only [n=12], paper-and-pencil followed by tablet app [n=31], and tablet app followed by paper-and-pencil [n=31]) on pain assessment frequency and frontline staff stress and burnout levels. Finally, semistructured interviews were conducted with frontline staff to obtain perspectives on each method of administration. RESULTS: The implementation effort resulted in a great increase in pain assessment frequency across 7 independent LTC units, although these increases were not maintained during the follow-up period. Frontline staff reported lower levels of workload in the paper-and-pencil followed by tablet app condition than those in the paper-and-pencil only (P<.001) and tablet app followed by paper-and-pencil (P<.001) conditions. Frontline staff also reported lower levels of workload in the tablet-only condition than those in the paper-and-pencil only condition (P=.05). Similarly, lower levels of emotional exhaustion were reported by frontline staff in the paper-and-pencil followed by tablet app condition than those in the paper-and-pencil only (P=.002) and tablet app followed by paper-and-pencil (P=.002) conditions. Finally, frontline staff reported higher levels of depersonalization in the paper-and-pencil only condition than those in the tablet app only (P=.008), paper-and-pencil followed by tablet app (P<.001), and tablet app followed by paper-and-pencil (P<.001) conditions. Furthermore, narrative data from individual interviews with frontline staff revealed a preference for the tablet app over the paper-and-pencil method of administration. CONCLUSIONS: This study provides support for the use of either the tablet app or the paper-and-pencil version of the PACSLAC-II to improve pain-related quality indicators, but a reported preference for and lower levels of stress and burnout with the use of the tablet app method of administration suggests that the use of the tablet app may have more advantages compared with the paper-and-pencil method of administration.

Sensor-Data Fusion for Multi-Person Indoor Location Estimation.

We consider the problem of estimating the location of people as they move and work in indoor environments. More specifically, we focus on the scenario where one of the persons of interest is unable or unwilling to carry a smartphone, or any other "wearable" device, which frequently arises in caregiver/cared-for situations. We consider the case of indoor spaces populated with anonymous binary sensors (Passive Infrared motion sensors) and eponymous wearable sensors (smartphones interacting with Estimote beacons), and we propose a solution to the resulting sensor-fusion problem. Using a data set with sensor readings collected from one-person and two-person sessions engaged in a variety of activities of daily living, we investigate the relative merits of relying solely on anonymous sensors, solely on eponymous sensors, or on their combination. We examine how the lack of synchronization across different sensing sources impacts the quality of location estimates, and discuss how it could be mitigated without resorting to device-level mechanisms. Finally, we examine the trade-off between the sensors' coverage of the monitored space and the quality of the location estimates.

Improved A1C Levels in Type 1 Diabetes with Smartphone App Use.

OBJECTIVES: Smartphones are a potentially useful tool in diabetes care. We have developed an application (app) linked to a website, Intelligent Diabetes Management (IDM), which serves as both an insulin bolus calculator and an electronic diabetes diary. We have prospectively studied whether patients using this app improved control of their glucose levels. METHODS: Patients with type 1 diabetes were recruited. There was a 4-week observation period, midway during which we offered to review the participants' records. The app was then downloaded and participants' diabetes regimens entered on the synchronized IDM website. At 2, 4, 8, 12 and 16 weeks of the active phase, their records were reviewed online, and feedback was provided electronically. The primary endpoint was change in levels of glycated hemoglobin (A1C). RESULTS: Of the 31 patients recruited, 18 completed the study. These 18 made 572±98 entries per person on the IDM system over the course of the study (≈5.1/day). Their ages were 40.0±13.9 years, the durations of their diabetes were 27.3±14.9 years and 44% used insulin pumps. The median A1C level fell from 8.1% (7.5 to 9.0, IQ range) to 7.8% (6.9 to 8.3; p<0.001). During the observation period, glucose records were reviewed for 50% of the participants. In the active phase, review of the glucose diaries took less time on the IDM website than using personal glucose records in the observation period, median 6 minutes (5 to 7.5 IQ range) vs. 10 minutes (7.5 to 10.5 IQ range; p<0.05). CONCLUSIONS: Our smartphone app enables online review of glucose records, requires less time for clinical staff and is associated with improved glucose control.

Users' Attitudes Towards Personal Health Records: A Cross-Sectional Pilot Study.

BACKGROUND: Prevention and management of chronic conditions is a priority for many healthcare systems. Personal health records have been suggested to facilitate implementation of chronic care programs. However, patients' attitude towards personal health records (PHRs) can significantly affect the adoption rates and use of PHRs. OBJECTIVES: to evaluate the attitude of patients with Type II diabetes towards using a PHR to manage their condition. METHODS: We used a cross-sectional exploratory pilot study. Fifty-four (54) patients used a PHR to monitor and record their blood glucose levels, diet, and activities for 30 days, and to communicate with their clinicians. At the end of the study, patients responded to a survey based on three constructs borrowed from different technology acceptance frameworks: relative advantage, job fit, and perceived usefulness. A multivariate predictive model was formed using partial least squaring technique (PLS) and the effect of each construct on the patients' attitude towards system use was evaluated. Patients also participated in a semi-structured interview. RESULTS: We found a significant positive correlation between job fit and attitude (JF → ATT = +0.318, p<0.01). There was no statistical evidence of any moderating or mediating effect of other main constructs or any of the confounding factors (i.e., age, gender, time after diagnosed) on attitude. CONCLUSION: The attitude of patients towards using PHR in management of their diabetes was positive. Their attitude was mainly influenced by the extent to which the system helped them better perform activities and self-manage their condition.

Smart homes and home health monitoring technologies for older adults: A systematic review.

BACKGROUND: Around the world, populations are aging and there is a growing concern about ways that older adults can maintain their health and well-being while living in their homes. OBJECTIVES: The aim of this paper was to conduct a systematic literature review to determine: (1) the levels of technology readiness among older adults and, (2) evidence for smart homes and home-based health-monitoring technologies that support aging in place for older adults who have complex needs. RESULTS: We identified and analyzed 48 of 1863 relevant papers. Our analyses found that: (1) technology-readiness level for smart homes and home health monitoring technologies is low; (2) the highest level of evidence is 1b (i.e., one randomized controlled trial with a PEDro score ≥6); smart homes and home health monitoring technologies are used to monitor activities of daily living, cognitive decline and mental health, and heart conditions in older adults with complex needs; (3) there is no evidence that smart homes and home health monitoring technologies help address disability prediction and health-related quality of life, or fall prevention; and (4) there is conflicting evidence that smart homes and home health monitoring technologies help address chronic obstructive pulmonary disease. CONCLUSIONS: The level of technology readiness for smart homes and home health monitoring technologies is still low. The highest level of evidence found was in a study that supported home health technologies for use in monitoring activities of daily living, cognitive decline, mental health, and heart conditions in older adults with complex needs.

Developing interprofessional health competencies in a virtual world.

BACKGROUND: Virtual worlds provide a promising means of delivering simulations for developing interprofessional health skills. However, developing and implementing a virtual world simulation is a challenging process, in part because of the novelty of virtual worlds as a simulation platform and also because of the degree of collaboration required among technical and subject experts. Thus, it can be difficult to ensure that the simulation is both technically satisfactory and educationally appropriate. METHODS: To address this challenge, we propose the use of de Freitas and Oliver's four-dimensional framework as a means of guiding the development process. We give an overview of the framework and describe how its principles can be applied to the development of virtual world simulations. RESULTS: We present two virtual world simulation pilot projects that adopted this approach, and describe our development experience in these projects. We directly connect this experience to the four-dimensional framework, thus validating the framework's applicability to the projects and to the context of virtual world simulations in general. CONCLUSIONS: We present a series of recommendations for developing virtual world simulations for interprofessional health education. These recommendations are based on the four-dimensional framework and are also informed by our experience with the pilot projects.

Home care and technology: a case study.

Health care aides (HCAs) are the backbone of the home care system and provide a range of services to people who, for various reasons related to chronic conditions and aging, are not able to take care of themselves independently. The demand for HCA services will increase and the current HCA supply will likely not keep up with this increasing demand without fundamental changes in the current environment. Information and communication technology (ICT) can address some of the workflow challenges HCAs face. In this project, we conducted an ethnographic study to document and analyse HCAs' workflows and team interactions. Based on our findings, we designed an ICT tool suite, integrating easily available existing and newly developed (by our team) technologies to address these issues. Finally, we simulated the deployment of our technologies, to assess the potential impact of these technological solutions on the workflow and productivity of HCAs, their healthcare teams and client care.

MeRiTS: simulation-based training for healthcare professionals.

Simulation-based training has been used in numerous settings for procedural training. In this research, we focus on a method of simulation-based procedural skills training that uses virtual worlds. This method, implemented in our MeRiTS software system, models procedures using executable workflows, which are enacted by the trainee in a virtual world. The workflows may be defined by educators, or demonstrated by experts and then extracted from system logs. To demonstrate the utility of the system, we have created a scenario for training EMTs in patient rescue and transition procedures. We have pilot tested this scenario with students at a polytechnical institute, and will be conducting more rigorous testing with a range of students and institutions in the near future.

Medical education through virtual worlds: the HLTHSIM project.

Training tools using virtual reality (VR) are becoming more popular and cost-effective to develop and are increasingly adopted; yet there is no systematic means for evaluating their usability and pedagogical effectiveness. There are a wide range of training scenarios that can be scripted, from high level simulations of emergency response systems where participants using their avatars have to make complex decisions and communicate with each other, to low-level sensor-motor skills-based trainers where surgeons can practice suturing and cutting. We propose a classification framework for simulator-based training, associating each type of simulation with a specification of the types of skills it is designed to exercise and a corresponding evaluation plan. In this framework, objective measures involving task time and error rates can be formalized at the lower levels, and related subjective and objective measures can be identified at the top. Our framework is being implemented under the auspices of a recently funded New Media project in Canada (GRAND NCE) that spans two health training and simulation facilities (CSTAR and HSERC).