Canadian Digital Research Articles

Relationships between employment status with self-perceived mental and physical health in Canada.

The annual cost of mental illnesses in Canada is estimated to be $50 billion. Research from other countries have suggested that employment status is associated with mental and physical health. Within the Canadian context, there is a dearth of research on the relationship between employment and mental health. To explore the relationships between age, gender, income, and employment status on mental and physical health. The 2021 Canadian Digital Health Survey dataset was used for this study. Data records, which included responses for the questions on age, gender, income, employment status, mental, and physical health, were used in the analysis. Ordinal logistics regression was applied to investigate the associations that may exist between mental and physical health with the various sociodemographic factors. Descriptive statistics were also provided for the data. The total sample size included in the analysis was 10,630. When compared to respondents who had full-time employment, those who were unemployed were more likely to have lower self-perceived mental health (OR: 1.91; 95% CI: 1.55-2.34). Retired respondents were less likely to have worse mental health than respondents who were employed full-time (OR: 0.78; 95% CI: 0.68-0.90). Self-perceived physical health was more likely to be lower for those who were unemployed (OR: 1.74; 95% CI: 1.41-2.14) or retired (OR: 1.28; 95% CI: 1.12-1.48) when compared to respondents employed full-time. The likelihood of worsening mental and physical health was also found to be associated with age, gender, and income. Our findings support the evidence that different factors contribute to worsening mental and physical health. Full-time employment may confer some protective effects or attributes leading to an increased likelihood of having improved mental health compared to those who are unemployed. Understanding the complex relationships on how various factors impact mental health will help better inform policymakers, clinicians, and other stakeholders on how to allocate its limited resources.

Review: South Asian Canadian Digital Archive

Review: South Asian Canadian Digital Archive

South Asian Canadian Digital Archive:: Fostering Knowledge Diversity and Equity Through Multilingual Knowledge Infrastructures

Knowledge and its production is informed by the availability of and access to existing knowledge infrastructures. Historically, both the production of knowledge and knowledge infrastructures have been dominated and dictated by western1 schools of thoughts that elided, erased, neglected, and negated the existence of multiple epistemologies. This paper explores ways to understand the depth and breadth of global colonial legacies and epistemic coloniality—and locate the pathways out in the archives. Using South Asian Canadian Digital Archive (https://sacda.ca) as a case study, the paper questions ways to rethink, redefine, and refine the methodologies of traditional archives to enable spaces for open and inclusive scholarship. It further frames SACDA (1897 to present) as an open tool for building multilingual knowledge infrastructures and to bring the larger community into the process of collective knowledge mobilization, creation, and dissemination.

The Intersection of the COVID-19 Pandemic and the 2021 Heat Dome in Canadian Digital News Media: A Content Analysis.

During the 2021 Heat Dome, 619 people in British Columbia died due to the heat. This public health disaster was made worse by the ongoing COVID-19 pandemic. Few studies have explored the intersection of heat with COVID-19, and none in Canada. Considering that climate change is expected to increase the frequency of extreme heat events, it is important to improve our understanding of intersecting public health crises. Thus, this study aimed to explore media-based public health communication in Canada during the COVID-19 pandemic and the 2021 Heat Dome. A qualitative content analysis was conducted on a subset of media articles (n = 520) related to the COVID-19 pandemic which were identified through a previous media analysis on the 2021 Heat Dome (n = 2909). Many of the articles provided conflicting health messages that may have confused the public about which health protective actions to take. The articles also showed how the COVID-19 pandemic may have exacerbated the health impacts of the 2021 Heat Dome, as pandemic-related public health measures may have deterred people away from protecting themselves from heat. This study, which provides novel insight into the prioritization of public health messaging when an extreme heat event occurs concurrently with a pandemic, supports the need for consistent heat health guidance.

Accès à l'éducation : équité, diversité et inclusion dans l'apprentissage en ligne

As Canadian post-secondary institutions emerge from the pandemic restrictions, they are in a historically unique position to assess how online education has both facilitated and hindered learning, and how the effects might be greater for some. In this study, open-ended comments from the Canadian Digital Learning Research Association 2022 Spring National Survey were analyzed to understand how online and/or hybrid learning both supported equity, diversity, and inclusion (EDI) and presented EDI-related challenges. The findings were that: (a) online and hybrid learning presents challenges of access for students marginalized by “race,” class, and location; (b) online and hybrid learning supports EDI by increasing access and flexibility; (c) pedagogy and course design are central to ensuring that online and/or hybrid learning supports EDI; and (d) student experiences and expectations around online learning indicate a need for support and flexibility. These findings highlight some of the promises of online and hybrid learning, but they also bring to light some of the challenges. This paper discusses three challenges, access, pedagogy, and technology, as well as flexibility, and recommendations that might begin to address EDI.

Exploring Differential Perceptions of Artificial Intelligence in Health Care Among Younger Versus Older Canadians: Results From the 2021 Canadian Digital Health Survey

The changing landscape of health care has led to the incorporation of powerful new technologies like artificial intelligence (AI) to assist with various services across a hospital. However, despite the potential outcomes that this tool may provide, little work has examined public opinion regarding their use. In this study, we aim to explore differences between younger versus older Canadians with regard to the level of comfort and perceptions around the adoption and use of AI in health care settings. Using data from the 2021 Canadian Digital Health Survey (n=12,052), items related to perceptions about the use of AI as well as previous experience and satisfaction with health care were identified. We conducted Mann-Whitney U tests to compare the level of comfort of younger versus older Canadians regarding the use of AI in health care for a variety of purposes. Multinomial logistic regression was used to predict the comfort ratings based on categorical indicators. Younger Canadians had greater knowledge of AI, but older Canadians were more comfortable with AI applied to monitoring and predicting health conditions, decision support, diagnostic imaging, precision medicine, drug and vaccine development, disease monitoring at home, tracking epidemics, and optimizing workflow to save time. Additionally, for older respondents, higher satisfaction led to higher comfort ratings. Only 1 interaction effect was identified between previous experience, satisfaction, and comfort with AI for drug and vaccine development. Older Canadians may be more open to various applications of AI within health care than younger Canadians. High satisfaction may be a critical criterion for comfort with AI, especially for older Canadians. Additionally, in the case of drug and vaccine development, previous experience may be an important moderating factor. We conclude that gaining a greater understanding of the perceptions of all health care users is integral to the implementation and sustainability of new and cutting-edge technologies in health care settings.

The Canadian Digital Services Tax

The Canadian Digital Services Tax

Determinants of e-Mental Health Use During COVID-19: Cross-sectional Canadian Study.

Access to mental health treatment across Canada remains a challenge, with many reporting unmet care needs. National and provincial e-Mental health (eMH) programs have been developed over the past decade across Canada, with many more emerging during COVID-19 in an attempt to reduce barriers related to geography, isolation, transportation, physical disability, and availability. The aim of this study was to identify factors associated with the utilization of eMH services across Canada during the COVID-19 pandemic using Andersen and Newman's framework of health service utilization. This study used data gathered from the 2021 Canadian Digital Health Survey, a cross-sectional, web-based survey of 12,052 Canadians aged 16 years and older with internet access. Bivariate associations between the use of eMH services and health service utilization factors (predisposing, enabling, illness level) of survey respondents were assessed using χ2 tests for categorical variables and t tests for the continuous variable. Logistic regression was used to predict the probability of using eMH services given the respondents' predisposing, enabling, and illness-level factors while adjusting for respondents' age and gender. The proportion of eMH service users among survey respondents was small (883/12,052, 7.33%). Results from the logistic regression suggest that users of eMH services were likely to be those with regular family physician access (odds ratio [OR] 1.57, P=.02), living in nonrural communities (OR 1.08, P<.001), having undergraduate (OR 1.40, P=.001) or postgraduate (OR 1.48, P=.003) education, and being eHealth literate (OR 1.05, P<.001). Those with lower eMH usage were less likely to speak English at home (OR 0.06, P<.001). Our study provides empirical evidence on the impact of individual health utilization factors on the use of eMH among Canadians during the COVID-19 pandemic. Given the opportunities and promise of eMH services in increasing access to care, future digital interventions should both tailor themselves toward users of these services and consider awareness campaigns to reach nonusers. Future research should also focus on understanding the reasons behind the use and nonuse of eMH services.

How a Government Organisation Evolved to Embrace Ethnographic Methods for Service (and Team) Resilience: The Case of the Canadian Digital Service

Government websites and online services are often built with limited input from the people they serve. This approach limits their ability to respond to ever changing needs and contexts. This case study describes a government digital team built from the ground‐up to embrace ethnographic methods to make government services more resilient.The case study begins by tracing the organisation's origins and relationship to other research‐driven parts of its government. Then it shows how the organisation's structure evolved as more projects included ethnography. It describes various approaches to locating skilled researchers within bureaucratic confines, as well as what responsibilities researchers took on as the organisation grew. It then summarises researchers' experiences with matrixed, functional and hybrid organisation schemes.The case study concludes explaining how embracing ethnographic approaches (and values) increased not only online service, but also organisational resilience. Teams who embraced ethnography had deeper and more thoughtful responses to the pandemic, and inclusivity challenges in the organisation. Lessons learned for other organisations attempting to scale an ethnographic research practice, and seize its benefits for resilience.

South Asian Canadian Digital Archive Thesaurus

The South Asian Canadian Digital Archive (SACDA) is a soon-to-be-released digital repository developed by the South Asian Studies Institute at the University of the Fraser Valley, located in Abbotsford, British Columbia, Canada. SACDA partners with memory institutions, individuals, families, and organizations to digitize, describe, and provide online public access to heritage materials created by, or relevant to, the South Asian Canadian diaspora. This project report will detail how SACDA is building a customized thesaurus to classify its digitized archival holdings, augment existing subject headings and thesauri, and fill in taxonomical gaps. Building on prior work done by alternative thesauri like the Homosaurus, Association for Manitoba Archives Indigenous Subject Headings, Australian Institute of Aboriginal and Torres Strait Islander Studies (AIATSIS) Thesauri, and the International Thesaurus of Refugee Terminology, among others, the SACDA thesaurus intends to fill in a vital gap in South Asian Studies subject control, particularly from a Canadian perspective.

Exploring younger versus older Canadians' perceptions of the use of AI in healthcare

<h3>Introduction</h3> With the adoptation of telemedicine in the healthcare system, many health services, programs and tools are now offered virtually. In this study, we aim to explore any differences between younger and older Canadians with regard to level of comfort and perceptions around the adoption and use of AI technology in healthcare settings. Our primary objective to compare perceptions of the use of AI in healthcare among younger versus older Canadians. We hypothesize that younger people, who are generally more exposed to emerging technology, will have more favorable opinions and responses to the use of AI in healthcare compared to older people. <h3>Methods</h3> We analyzed data from the 2021 Canadian Digital Health Survey which is a national open dataset. Upon identifying the items that address our objectives we grouped participants by age, into a younger (16-54 yo) and older group (>54 yo). To test our objective, we conducted Mann Whitney U tests to compare the level of comfort of younger versus older Canadians regarding the use of AI in healthcare for a variety of purposes. <h3>Results</h3> The average rank of artificial intelligence knowledge was significantly higher for younger participants (6296.97) than for older participants (5557.48), <i>Mann Whitney U</i> = 14779930.50, <i>n</i>1= 7644 <i>n</i>2 = 4408, <i>p</i> < .001. The average rank of comfort using personal data with informed consent was significantly higher for younger participants (5976.91) than for older participants (6112.49), <i>Mann Whitney U</i> = 16468338.00, <i>n</i>1= 7644 <i>n</i>2 = 4408, <i>p</i> < .30. The average rank of comfort using personal data without informed consent was significantly higher for younger participants (6182.54) than for older participants (5755.90), <i>Mann Whitney U</i> = 15654590.50, <i>n</i>1= 7644 <i>n</i>2 = 4408, <i>p</i> < .001. There was no significant difference in mean rank in older participants' (6096.18) comfort with AI as a major potential tool to process large amounts of data when compared to younger participants (5986.32), <i>Mann Whitney U = </i>16540240.00<i>, p</i> = .079. The average rank of comfort for the uses of AI within healthcare in monitoring and predicting health conditions was significantly higher for older participants (6194.98) than for younger participants (5929.35), <i>Mann Whitney U</i> = 16104735.50, <i>n</i>1= 7644 <i>n</i>2 = 4408, <i>p</i> < .001. The average rank of comfort for the uses of AI within healthcare in decision support was significantly higher for older participants (6335.80) than for younger participants (5848.14), <i>Mann Whitney U</i> = 15483997.00, <i>n</i>1= 7644 <i>n</i>2 = 4408, <i>p</i> Mann Whitney U = 15662216.00, <i>n</i>1= 7644 <i>n</i>2 = 4408, <i>p</i> < .001 . The average rank of comfort for the uses of AI within healthcare in precision medicine was significantly higher for older participants (6274.31) than for younger participants (5883.60), <i>Mann Whitney U</i> = 15755037.00, <i>n</i>1= 7644 <i>n</i>2 = 4408, <i>p</i> < .001. The average rank of comfort for the uses of AI within healthcare in drug and vaccine development was significantly higher for older participants (6417.87) than for younger participants (5800.81), <i>Mann Whitney U</i> =15122200.00, <i>n</i>1= 7644 <i>n</i>2 = 4408, <i>p</i> < .001 .The average rank of comfort for the uses of AI within healthcare in disease monitoring at home was significantly higher for older participants (6182.88) than for younger participants (5936.32), <i>Mann Whitney U</i> = 16158032.00, <i>n</i>1= 7644 <i>n</i>2 = 4408, <i>p</i> < .001 . The average rank of comfort for the uses of AI within healthcare in tracking epidemics was significantly higher for older participants (6363.68) than for younger participants (5832.06), <i>Mann Whitney U</i> = 15361074.50, <i>n</i>1= 7644 <i>n</i>2 = 4408, <i>p</i> < .001. Finally, the average rank of comfort for the uses of AI within healthcare in optimising workflow to save time for healthcare was significantly higher for older participants (6172.83) than for younger participants (5942.12), <i>Mann Whitney U</i> = 16202367.50, <i>n</i>1= 7644 <i>n</i>2 = 4408, <i>p</i> < 001. <h3>Conclusions</h3> The results show that despite being less knowledgable about AI, older adults are significantly more comfortable with AI being applied in specific branches of healthcare compared to younger Canadians. <h3>Secondary Rationale</h3> Exploring older adults' opinions and perceptions around the use of AI in the healthcare system is cruicial for understanding and evaluating the use and effectiveness of different telemedicine practices. This will also allow researchers and clinicians to better communicate and educate different patient populations on the use of technology in medical contexts and to ensure that all patients can access the most appropriate and feasible healthcare services with ease. <h3>This research was funded by</h3> No funding was used for this study.

Integration of heterogeneous terrain data into Discrete Global Grid Systems

ABSTRACT The Canadian Digital Elevation Model (CDEM) and the High-Resolution Digital Elevation Model (HRDEM) released by Natural Resources Canada are primary terrain data sources in Canada. Due to their different coverage, datums, resolutions, and accuracies, a standardized framework for national elevation data across various scales is required. This study provides new insights into the adoption of Discrete Global Grid Systems (DGGS) to facilitate the integration of multi-source terrain data at various granularities. In particular, the Icosahedral Snyder Equal Area Aperture 3 Hexagonal Grid (ISEA3H) was employed, and quantization, integration, and aggregation were conducted on this framework. To demonstrate the modeling process, an experiment was undertaken for two areas in Ontario, taking advantage of parallel computing which was beneficial from the discreteness of DGGS cells. The accuracy of the modeled elevations was estimated by referring to the ground-surveyed values and was included in the spatially referenced metadata as an indicator of data quality. This research can serve as a guide for future development of a national elevation service, providing consistent, multi-resolution elevations and avoiding complex, duplicated pre-processing at the user’s end. Future investigation into an operational integration platform to support real-world decision-making, as well as the DGGS-powered geospatial datacube, is recommended.

Commentary on the Action Plan to Modernize Gender, Sex and Sexual Orientation Information Practices in Canadian Digital Health Systems

Commentary on the Action Plan to Modernize Gender, Sex and Sexual Orientation Information Practices in Canadian Digital Health Systems

An Analysis of Digital Education in Canada in 2017-2019

Digital education refers to in-person, blended, and fully online learning efforts, as well as attempts to capture a wide range of teaching and learning contexts which make use of digital technology. While digital education is pervasive in Canada, pan-Canadian data on digital education are relatively scarce. The Canadian Digital Learning Research Association/Association Canadienne de Recherche sur la Formation en Ligne conducted pan-Canadian surveys of higher education institutions (2017-2019), collecting data on the digital education landscape and publishing annual reports of its results. Previous analyses of the data have used quantitative approaches. However, the surveys also collected responses to open-ended questions. In this study, we report a systematic analysis of qualitative data exploring the digital education landscape in Canada and its changes over time. Findings shed light on the growth of digital education, the situated and multidimensional nature of digital education, the adoption of openness, quality, and rigour, and the development of alternative credentials.

Institutional Perspectives on Faculty Development for Digital Education in Canada

As digital education at the post-secondary level continues to grow, robust professional development that prepares faculty to teach in online and blended settings is necessary. In this study we analyze open-ended comments from the Canadian Digital Learning Research Association’s annual survey of Canadian post-secondary institutions (2017-2019) to deepen our understanding of faculty training and support for digital education as articulated by higher education institutions. We find that 1) digital education orientation or on-boarding processes for faculty vary widely; 2) institutions employ an extensive array of professional development practices for digital education; 3) institutions report culture change, work security, and unclear expectations as challenges in providing digital education training and support; and 4) institutions articulate aspirations and hopes around professional development investments in order to build digital education capacity. These findings have significant implications for research and practice and we describe these in the article.

The New Landsat Collection-2 Digital Elevation Model

The Landsat Collection-2 distribution introduces a new global Digital Elevation Model (DEM) for scene orthorectification. The new global DEM is a composite of the latest and most accurate freely available DEM sources and will include reprocessed Shuttle Radar Topographic Mission (SRTM) data (called NASADEM), high-resolution stereo optical data (ArcticDEM), a new National Elevation Dataset (NED) and various publicly available national datasets including the Canadian Digital Elevation Model (CDEM) and DEMs for Sweden, Norway and Finland (SNF). The new DEM will be available world-wide with few exceptions. It is anticipated that the transition from the Collection-1 DEM at 3 arcsecond to the new DEM will be seamless because processing methods to maintain a seamless transition were employed, void filling techniques were used, where persistent gaps were found, and the pixel spacing is the same between the two collections. Improvements to the vertical accuracy were realized by differencing accuracies of other elevation datasets to the new DEM. The greatest improvement occurred where ArcticDEM data were used, where an improvement of 35 m was measured. By using theses improved vertical values in a line of sight algorithm, horizontal improvements were noted in some of the most mountainous regions over multiple 30-m Landsat pixels. This new DEM will be used to process all of the scenes from Landsat 1-8 in Collection-2 processing and will be made available to the public by the end of 2020.

Fluvial inundation parameterization in climate model and its effects on regional climate: a case study of the 2009 Red River spring flood

This study introduces a simple and newly developed fluvial inundation parameterization using high-resolution climate model and investigates its impacts on regional climate. The 2009 Red River spring flood is selected as a case study and this approach is tested with the regional climate model, Global Environment Multiscale (GEM) version 4.8 with 10 km resolution, and Canadian Digital Surface Model (CDSM) elevation (~ 20 m). To investigate the impacts of fluvial inundation on regional climate, the sensitivity experiments using different initial conditions for soil moisture are conducted with 1 km resolution through a three-step one-way nesting approach. Generally, new approach can capture the development–decay of fluvial inundation, similar to MODIS observation. The reasonable statistic values (probability of detection, 0.71; false alarm ratio, 0.26) are found on April 15–22 when occurred the largest MODIS-observed fluvial inundation. In sensitivity experiments, the increase of soil moisture by flooding can induce the decrease of albedo, leading to the increase in absorbed solar radiation energy at surface. Most of the absorbed energy is used by the latent heat flux, inducing the temperature cooling and moisture increase. These changes are larger in daytime than nighttime and are statistically significant in only 2 months (May–June) from the flooding, which contribute to the improvement of temperature simulation. The significant decrease and increase of precipitation in northeastern and southeastern regions away from the flooded region, respectively, are noted post-flooding. These changes are closely associated with the decrease and increase of moist static energy by moisture divergence and convergence, respectively.

Canadian Digital and Data Strategy

Canadian Digital and Data Strategy

Mapping Forest Height from TanDEM-X Interferometric Coherence Data in Northwest Territories, Canada

In this paper, we demonstrate the feasibility of using TanDEM-X (TX) interferometric coherence data for mapping forest height with 25-m pixels across a study area near Fort Simpson, Northwest Territories (NWT), Canada. Our simplified RVOG model locally estimates forest height by combining an optimized estimation of TX interferometric coherence amplitude with the 20-m resolution Canadian Digital Elevation Model (CDEM) accounting for local slope variations. The initial map of TX height estimates provided R2 values of 0.78 and 0.88, mean errors (ME) of 1.66 m and 1.90 m, and root-mean-square errors (RMSE) of 2.7 m and 2.9 m when compared to independent height estimates derived from field plots and airborne LiDAR, respectively. We corrected the bias of TX height estimates using two variants of a LiDAR-based linear model. An application of three cover-specific linear adjustments provided the final TX height map with absolute ME ≤0.05 m and RMSE ≤2.09 m. The approach was tailored to poorly inventoried northern boreal regions through the use of archived TX data, the CDEM, a land cover map and airborne LiDAR transects. Our encouraging results support the perspective of wall-to-wall mapping of forest height across northern boreal forests in the NWT and beyond.

DEM Fusion of Elevation REST API Data in Support of Rapid Flood Modelling

Digital elevation models (DEM) are an integral part of flood modelling. High resolution DEM data are not always available or affordable for communities, thus other elevation data sources are explored. While the accuracy of some of these sources has been rigorously tested (e.g., SRTM, ASTER), others, such as Natural Resources Canada’s Canadian Digital Elevation Model (CDEM) and Google and Bings’ Elevation REST APIs, have not yet been properly evaluated. Details pertaining to acquisition source and accuracy are often unreported for APIs. To include these data in geospatial applications and test and reduce uncertainty, data fusion is explored. Thus, this paper introduces a new method of elevation data fusion. The novel method incorporates clustering and inverse distance weighting (IDW) concepts in the computation of a new fusion elevation surface. The results of the individual DEMs and fusion DEMs are compared to high-resolution Light Detection and Ranging (LiDAR) surface and flood inundation maps for two study areas in New Brunswick. Comparison of individual surfaces to LiDAR find that the results meet their posted accuracy specifications, with the Bing data computing the smallest mean bias and the CDEM the smallest RMSE. Fusion of all three surfaces via the proposed method increases the correlation and minimizes both RMSE and mean bias when compared to LiDAR, independent of the terrain, thus producing a more accurate DEM.