The role of digital health technology in rural cancer care delivery: A systematic review

2021 ◽  
Author(s):  
Bonny B. Morris ◽  
Brianna Rossi ◽  
Bernard Fuemmeler
Keyword(s):  
Systematic Review ◽  
Cancer Care ◽  
Care Delivery ◽  
Digital Health ◽  
Health Technology

scholarly journals When disaster strikes: The role of disaster planning and management in cancer care delivery

Cancer ◽  
2020 ◽  
Vol 126 (15) ◽  
pp. 3388-3392 ◽  
Author(s):  
Liora Sahar ◽  
Leticia M. Nogueira ◽  
Isaac Ashkenazi ◽  
Ahmedin Jemal ◽  
K. Robin Yabroff ◽  
...  
Keyword(s):  
Cancer Care ◽  
Care Delivery ◽  
Disaster Planning ◽  
Planning And Management

scholarly journals Cancer Care Delivery and Women’s Health: The Role of Patient Navigation

2016 ◽  
Vol 6 ◽  
Author(s):  
Jessica L. Krok-Schoen ◽  
Jill M. Oliveri ◽  
Electra D. Paskett
Keyword(s):  
Women’S Health ◽  
Women's Health ◽  
Cancer Care ◽  
Patient Navigation ◽  
Care Delivery

scholarly journals Surveying the Role of Analytics in Evaluating Digital Mental Health Interventions for Transition-Aged Youth: Scoping Review (Preprint)

2019 ◽  
Author(s):  
Brian Lo ◽  
Jenny Shi ◽  
Elisa Hollenberg ◽  
Alexxa Abi-Jaoudé ◽  
Andrew Johnson ◽  
...  
Keyword(s):  
Mental Health ◽  
Scoping Review ◽  
Care Delivery ◽  
Digital Health ◽  
Controlled Trial ◽  
Health Interventions ◽  
Health Apps ◽  
Mental Health Interventions ◽  
Usage Data

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.

Understanding Decision Making in the Adoption of Digital Health Technology: The Role of Behavioural Economics’ Prospect Theory (Preprint)

2021 ◽  
Author(s):  
Waqas Ullah Khan ◽  
Aviv Shachak ◽  
Emily Seto
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Digital Health ◽  
Health Technology ◽  
Behavioural Economics ◽  
Individual Level ◽  
Health Technologies ◽  
Research Article ◽  
The Individual

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.

scholarly journals Surveying the Role of Analytics in Evaluating Digital Mental Health Interventions for Transition-Aged Youth: Scoping Review

10.2196/15942 ◽  
2020 ◽  
Vol 7 (6) ◽  
pp. e15942
Author(s):  
Brian Lo ◽  
Jenny Shi ◽  
Elisa Hollenberg ◽  
Alexxa Abi-Jaoudé ◽  
Andrew Johnson ◽  
...  
Keyword(s):  
Mental Health ◽  
Scoping Review ◽  
Care Delivery ◽  
Digital Health ◽  
Controlled Trial ◽  
Health Interventions ◽  
Health Apps ◽  
Mental Health Interventions ◽  
Usage Data

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.

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
Keyword(s):  
Health Promotion ◽  
Digital Health ◽  
Health Technology ◽  
Health Attitudes ◽  
Health Seeking ◽  
Future Directions ◽  
Health Apps ◽  
Risk Of Mortality ◽  
Technological Platforms

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.

Understanding Decision Making in the Adoption of Digital Health Technology: The Role of Behavioural Economics’ Prospect Theory (Preprint)

2021 ◽  
Author(s):  
Waqas Ullah Khan ◽  
Aviv Shachak ◽  
Emily Seto
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Digital Health ◽  
Health Technology ◽  
Behavioural Economics ◽  
Valuable Insight ◽  
Individual Level ◽  
Health Technologies ◽  
The Individual

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.

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