Flourishing mental health despite disabling chronic pain: Findings from a nationally representative sample of Canadians with arthritis.

This study aims to determine the prevalence of, and factors associated with, the "absence of psychiatric disorders" (APD) and "complete mental health" (CMH) among individuals with arthritis who report disabling chronic pain. There are three aspects of CMH: a) APD; b) happiness and/or life satisfaction in the past month on a daily or almost daily basis, and c) high levels of psychological and social well-being. A secondary analysis of a nationally representative sample (n = 620) of individuals with arthritis who report chronic and debilitating pain was conducted. Data were drawn from the Canadian Community Health Survey-Mental Health. The results of this study indicate that many people with arthritis who are living with disabling chronic pain are free of psychiatric disorders (76%) and are in CMH (56%). Factors associated with higher odds of APD and CMH among the sample include having a confidant, being free from insomnia, and having no lifetime history of major depressive disorder and/or generalized anxiety disorder. White respondents were almost 3-fold more likely to be in a state of CMH compared to racialized individuals. Respondents in the top 50% of household incomes were almost 4-fold more likely to be APD compared to the lowest 10%. In conclusion, many individuals with arthritis have excellent mental health despite disabling pain. Clinicians should be attuned to the mental health of their patients, with particular focus on those who may be more vulnerable to adverse mental health outcomes, such as racialized individuals, those in impoverished households, and those who lack social support.

Flourishing despite Chronic Obstructive Pulmonary Disease (COPD): Findings from a Nationally Representative Survey of Canadians Aged 50 and Older.

Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of mortality and is often associated with serious disability and depression. Little is known about the characteristics of those who are in complete mental health (CMH) despite having COPD. This study's objectives are to: (1) estimate the prevalence and odds of absence of psychiatric disorders (APD) and CMH among older adults that reported having COPD, compared to their peers that did not; (2) identify factors associated with APD and with CMH. Bivariate and logistic regression analyses were conducted using the nationally representative Canadian Community Health Survey­Mental Health. The results indicate that there was a significantly (p < 0.001) lower prevalence of APD (86.7% vs. 95.0%) and CMH (66.7% vs. 77.0%) among older adults aged 50+ with COPD (n = 703) compared to those without COPD (n = 10,189). Half of the sample was female (50.5%) and the majority of whom were under age 70 (62.5%). Factors significantly (p < 0.05) associated with higher odds of APD and of CMH among older adults with COPD include being married, having a confidant, being physically active, and having no lifetime history of major depressive disorder or generalized anxiety disorder. For every additional adverse childhood experience, the odds of APD declined by 31%. The majority of those with COPD are mentally flourishing despite having this disabling and life-threatening disorder. These findings underline the importance of targeted interventions and outreach to those most vulnerable to poorer mental health outcomes including the socially isolated.

Interactive Visualization Applications in Population Health and Health Services Research: Systematic Scoping Review.

BACKGROUND: Simple visualizations in health research data, such as scatter plots, heat maps, and bar charts, typically present relationships between 2 variables. Interactive visualization methods allow for multiple related facets such as numerous risk factors to be studied simultaneously, leading to data insights through exploring trends and patterns from complex big health care data. The technique presents a powerful tool that can be used in combination with statistical analysis for knowledge discovery, hypothesis generation and testing, and decision support. OBJECTIVE: The primary objective of this scoping review is to describe and summarize the evidence of interactive visualization applications, methods, and tools being used in population health and health services research (HSR) and their subdomains in the last 15 years, from January 1, 2005, to March 30, 2019. Our secondary objective is to describe the use cases, metrics, frameworks used, settings, target audience, goals, and co-design of applications. METHODS: We adapted standard scoping review guidelines with a peer-reviewed search strategy: 2 independent researchers at each stage of screening and abstraction, with a third independent researcher to arbitrate conflicts and validate findings. A comprehensive abstraction platform was built to capture the data from diverse bodies of literature, primarily from the computer science and health care sectors. After screening 11,310 articles, we present findings from 56 applications from interrelated areas of population health and HSR, as well as their subdomains such as epidemiologic surveillance, health resource planning, access, and use and costs among diverse clinical and demographic populations. RESULTS: In this companion review to our earlier systematic synthesis of the literature on visual analytics applications, we present findings in 6 major themes of interactive visualization applications developed for 8 major problem categories. We found a wide application of interactive visualization methods, the major ones being epidemiologic surveillance for infectious disease, resource planning, health service monitoring and quality, and studying medication use patterns. The data sources included mostly secondary administrative and electronic medical record data. In addition, at least two-thirds of the applications involved participatory co-design approaches while introducing a distinct category, embedded research, within co-design initiatives. These applications were in response to an identified need for data-driven insights into knowledge generation and decision support. We further discuss the opportunities stemming from the use of interactive visualization methods in studying global health; inequities, including social determinants of health; and other related areas. We also allude to the challenges in the uptake of these methods. CONCLUSIONS: Visualization in health has strong historical roots, with an upward trend in the use of these methods in population health and HSR. Such applications are being fast used by academic and health care agencies for knowledge discovery, hypotheses generation, and decision support. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/14019.

Visual Analytic Tools and Techniques in Population Health and Health Services Research: Scoping Review.

BACKGROUND: Visual analytics (VA) promotes the understanding of data with visual, interactive techniques, using analytic and visual engines. The analytic engine includes automated techniques, whereas common visual outputs include flow maps and spatiotemporal hot spots. OBJECTIVE: This scoping review aims to address a gap in the literature, with the specific objective to synthesize literature on the use of VA tools, techniques, and frameworks in interrelated health care areas of population health and health services research (HSR). METHODS: Using the 2018 PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, the review focuses on peer-reviewed journal articles and full conference papers from 2005 to March 2019. Two researchers were involved at each step, and another researcher arbitrated disagreements. A comprehensive abstraction platform captured data from diverse bodies of the literature, primarily from the computer and health sciences. RESULTS: After screening 11,310 articles, findings from 55 articles were synthesized under the major headings of visual and analytic engines, visual presentation characteristics, tools used and their capabilities, application to health care areas, data types and sources, VA frameworks, frameworks used for VA applications, availability and innovation, and co-design initiatives. We found extensive application of VA methods used in areas of epidemiology, surveillance and modeling, health services access, use, and cost analyses. All articles included a distinct analytic and visualization engine, with varying levels of detail provided. Most tools were prototypes, with 5 in use at the time of publication. Seven articles presented methodological frameworks. Toward consistent reporting, we present a checklist, with an expanded definition for VA applications in health care, to assist researchers in sharing research for greater replicability. We summarized the results in a Tableau dashboard. CONCLUSIONS: With the increasing availability and generation of big health care data, VA is a fast-growing method applied to complex health care data. What makes VA innovative is its capability to process multiple, varied data sources to demonstrate trends and patterns for exploratory analysis, leading to knowledge generation and decision support. This is the first review to bridge a critical gap in the literature on VA methods applied to the areas of population health and HSR, which further indicates possible avenues for the adoption of these methods in the future. This review is especially important in the wake of COVID-19 surveillance and response initiatives, where many VA products have taken center stage. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/14019.