Digitization of healthcare post COVID-19: Reimagining the role of health education and promotion

2021 ◽  
Vol 13 (2) ◽  
pp. 303-310 ◽  
Author(s):  
Chinwe Obuaku-Igwe

The digitization of health promotion and communication has become a major discourse in healthcare. This paper synthesizes my understanding of the role of health literacy, promotion, education and communication in ensuring effective digitization of healthcare and presents four key findings from a mental health promotion project. First, the pandemic has shown us more than ever how fragile we all are – health-seeking behaviour will increasingly take centre stage over the next decade. Second, why do people refuse to wear masks even though it increases the risk of mortality? Why are individuals not motivated to exercise despite downloading free health apps? Why do people keep eating unhealthy food even when they can afford healthier options? Why? The numbers cannot tell the whole story. Similarly, the proliferation of digital health technology cannot convince people to modify their behaviours nor promote meaningful use of e/m-health apps. Third, deliberate digital health promotion and communication is needed to leverage opportunities in health technology. Fourth, the world needs researchers and experts who understand the broader determinants of health attitudes and are knowledgeable in synthesizing valid health information across various technological platforms, in support of health system needs. I address the implications of my findings and discuss future directions for policy and practitioners.

10.2196/19778 ◽  
2020 ◽  
Vol 7 (8) ◽  
pp. e19778
Author(s):  
Aditya Vaidyam ◽  
Spencer Roux ◽  
John Torous

This patient perspective highlights the role of patients in the innovation and codesign of digital mental health technology. Though digital mental health apps have evolved and become highly functional, many still act as data collection silos without adequate support for patients to understand and investigate potentially meaningful inferences in their own data. Few digital health platforms respect the patient’s agency and curiosity, allowing the individual to wear the hat of researcher and data scientist and share their experiences and insight with their clinicians. This case is cowritten with an individual with lived experiences of schizophrenia who has decided to openly share their name and experiences to share with others the methods and results of their curiosity and encourage and inspire others to follow their curiosity as well.


2020 ◽  
Author(s):  
Aditya Vaidyam ◽  
Spencer Roux ◽  
John Torous

UNSTRUCTURED This patient perspective highlights the role of patients in the innovation and codesign of digital mental health technology. Though digital mental health apps have evolved and become highly functional, many still act as data collection silos without adequate support for patients to understand and investigate potentially meaningful inferences in their own data. Few digital health platforms respect the patient’s agency and curiosity, allowing the individual to wear the hat of researcher and data scientist and share their experiences and insight with their clinicians. This case is cowritten with an individual with lived experiences of schizophrenia who has decided to openly share their name and experiences to share with others the methods and results of their curiosity and encourage and inspire others to follow their curiosity as well.


2019 ◽  
Author(s):  
Brian Lo ◽  
Jenny Shi ◽  
Elisa Hollenberg ◽  
Alexxa Abi-Jaoudé ◽  
Andrew Johnson ◽  
...  

BACKGROUND Consumer-facing digital health interventions provide a promising avenue to bridge gaps in mental health care delivery. To evaluate these interventions, understanding how the target population uses a solution is critical to the overall validity and reliability of the evaluation. As a result, usage data (analytics) can provide a proxy for evaluating the engagement of a solution. However, there is paucity of guidance on how usage data or analytics should be used to assess and evaluate digital mental health interventions. OBJECTIVE This review aimed to examine how usage data are collected and analyzed in evaluations of mental health mobile apps for transition-aged youth (15-29 years). METHODS A scoping review was conducted using the Arksey and O’Malley framework. A systematic search was conducted on 5 journal databases using keywords related to usage and engagement, mental health apps, and evaluation. A total of 1784 papers from 2008 to 2019 were identified and screened to ensure that they included analytics and evaluated a mental health app for transition-aged youth. After full-text screening, 49 papers were included in the analysis. RESULTS Of the 49 papers included in the analysis, 40 unique digital mental health innovations were evaluated, and about 80% (39/49) of the papers were published over the past 6 years. About 80% involved a randomized controlled trial and evaluated apps with information delivery features. There were heterogeneous findings in the concept that analytics was ascribed to, with the top 3 being engagement, adherence, and acceptability. There was also a significant spread in the number of metrics collected by each study, with 35% (17/49) of the papers collecting only 1 metric and 29% (14/49) collecting 4 or more analytic metrics. The number of modules completed, the session duration, and the number of log ins were the most common usage metrics collected. CONCLUSIONS This review of current literature identified significant variability and heterogeneity in using analytics to evaluate digital mental health interventions for transition-aged youth. The large proportion of publications from the last 6 years suggests that user analytics is increasingly being integrated into the evaluation of these apps. Numerous gaps related to selecting appropriate and relevant metrics and defining successful or high levels of engagement have been identified for future exploration. Although long-term use or adoption is an important precursor to realizing the expected benefits of an app, few studies have examined this issue. Researchers would benefit from clarification and guidance on how to measure and analyze app usage in terms of evaluating digital mental health interventions for transition-aged youth. Given the established role of adoption in the success of health information technologies, understanding how to abstract and analyze user adoption for consumer digital mental health apps is also an emerging priority.


2021 ◽  
Author(s):  
Waqas Ullah Khan ◽  
Aviv Shachak ◽  
Emily Seto

UNSTRUCTURED The decision to accept or reject new digital health technologies remains an ongoing discussion. Over the past few decades, interest in understanding the choice to adopt technology has led to the development of numerous theories and models. In 1979, however, psychologists Kahneman and Tversky published their seminal research article that has pioneered the field of behavioural economics. They named their model the “prospect theory” and used it to explain decision making behaviours under conditions of risk and uncertainty as well as to provide an understanding of why individuals may make irrational or inconsistent decisions. Although the prospect theory has been used to explain decision making in economics, law, political science, and clinically at the individual level, its application to understanding choice in the adoption of digital health technology has not been explored.


10.2196/15942 ◽  
2020 ◽  
Vol 7 (6) ◽  
pp. e15942
Author(s):  
Brian Lo ◽  
Jenny Shi ◽  
Elisa Hollenberg ◽  
Alexxa Abi-Jaoudé ◽  
Andrew Johnson ◽  
...  

Background Consumer-facing digital health interventions provide a promising avenue to bridge gaps in mental health care delivery. To evaluate these interventions, understanding how the target population uses a solution is critical to the overall validity and reliability of the evaluation. As a result, usage data (analytics) can provide a proxy for evaluating the engagement of a solution. However, there is paucity of guidance on how usage data or analytics should be used to assess and evaluate digital mental health interventions. Objective This review aimed to examine how usage data are collected and analyzed in evaluations of mental health mobile apps for transition-aged youth (15-29 years). Methods A scoping review was conducted using the Arksey and O’Malley framework. A systematic search was conducted on 5 journal databases using keywords related to usage and engagement, mental health apps, and evaluation. A total of 1784 papers from 2008 to 2019 were identified and screened to ensure that they included analytics and evaluated a mental health app for transition-aged youth. After full-text screening, 49 papers were included in the analysis. Results Of the 49 papers included in the analysis, 40 unique digital mental health innovations were evaluated, and about 80% (39/49) of the papers were published over the past 6 years. About 80% involved a randomized controlled trial and evaluated apps with information delivery features. There were heterogeneous findings in the concept that analytics was ascribed to, with the top 3 being engagement, adherence, and acceptability. There was also a significant spread in the number of metrics collected by each study, with 35% (17/49) of the papers collecting only 1 metric and 29% (14/49) collecting 4 or more analytic metrics. The number of modules completed, the session duration, and the number of log ins were the most common usage metrics collected. Conclusions This review of current literature identified significant variability and heterogeneity in using analytics to evaluate digital mental health interventions for transition-aged youth. The large proportion of publications from the last 6 years suggests that user analytics is increasingly being integrated into the evaluation of these apps. Numerous gaps related to selecting appropriate and relevant metrics and defining successful or high levels of engagement have been identified for future exploration. Although long-term use or adoption is an important precursor to realizing the expected benefits of an app, few studies have examined this issue. Researchers would benefit from clarification and guidance on how to measure and analyze app usage in terms of evaluating digital mental health interventions for transition-aged youth. Given the established role of adoption in the success of health information technologies, understanding how to abstract and analyze user adoption for consumer digital mental health apps is also an emerging priority.


2021 ◽  
Author(s):  
Waqas Ullah Khan ◽  
Aviv Shachak ◽  
Emily Seto

UNSTRUCTURED The decision to accept or reject new digital health technologies remains an ongoing discussion. Over the past few decades, interest in understanding the choice to adopt technology has led to the development of numerous theories and models. In 1979, however, psychologists Kahneman and Tversky published their seminal research article that has pioneered the field of behavioural economics. They named their model the “prospect theory” and used it to explain decision making behaviours under conditions of risk and uncertainty as well as to provide an understanding of why individuals may make irrational or inconsistent decisions. Although the prospect theory has been used to explain decision making in economics, law, political science, and clinically at the individual level, its application to understanding choice in the adoption of digital health technology has not been explored. Herein, we discuss how the prospect theory can provide valuable insight on why healthcare patients/clients, technology companies, and policymakers may decide to accept or reject digital health technologies.


2021 ◽  
Author(s):  
Sophia Siedlikowski ◽  
Louis-Philippe Noël ◽  
Stephanie Anne Moynihan ◽  
Marc Robin

UNSTRUCTURED There is an unprecedented demand for infodemic management due to rapidly evolving information about the novel COVID-19 pandemic. This viewpoint paper details the evolution of a Canadian digital information tool, <i>Chloe</i> for COVID-19, based on incremental leveraging of artificial intelligence techniques. By providing an accessible summary of <i>Chloe’s</i> development, we show how proactive cooperation between health, technology, and corporate sectors can lead to a rapidly scalable, safe, and secure virtual chatbot to assist public health efforts in keeping Canadians informed. We then highlight <i>Chloe’s</i> strengths, the challenges we faced during the development process, and future directions for the role of chatbots in infodemic management. The information presented here may guide future collaborative efforts in health technology in order to enhance access to accurate and timely health information to the public.


Sign in / Sign up

Export Citation Format

Share Document