Implementation Strategy for a Digital Health Tool Influences User Engagement

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1320-P
Author(s):  
MANSUR SHOMALI ◽  
MALINDA PEEPLES
Keyword(s):  
Implementation Strategy ◽  
Digital Health ◽  
User Engagement

scholarly journals Assessing Digital Health Implementation for a Pediatric Chronic Pain Intervention: Comparing the RE-AIM and BIT Frameworks Against Real-World Trial Data and Recommendations for Future Studies (Preprint)

2020 ◽  
Author(s):  
Rocio de la Vega ◽  
Lee Ritterband ◽  
Tonya M Palermo
Keyword(s):  
Chronic Pain ◽  
Real World ◽  
Digital Health ◽  
Controlled Trial ◽  
User Engagement ◽  
Maintenance Period ◽  
Treatment Implementation ◽  
Positive Attitudes ◽  
Pediatric Chronic Pain ◽  
Implementation Costs

BACKGROUND Digital health interventions have demonstrated efficacy for several conditions including for pediatric chronic pain. However, the process of making interventions available to end users in an efficient and sustained way is challenging and remains a new area of research. To advance this field, comprehensive frameworks have been created. OBJECTIVE The aim of this study is to compare the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) and Behavior Interventions using Technology (BIT) frameworks with data collected from the web-based management of adolescent pain (WebMAP Mobile; WMM) randomized controlled trial (RCT). METHODS We conducted a hybrid effectiveness-implementation cluster RCT with a stepped wedge design in which the intervention was sequentially implemented in 8 clinics, following a usual care period. Participants were 143 youths (mean age 14.5 years, SD 1.9; 117/143, 81.8% female) with chronic pain, from which 73 were randomized to receive the active intervention. Implementation outcomes were assessed using the RE-AIM and BIT frameworks. RESULTS According to the RE-AIM framework, the WMM showed excellent reach, recruiting a sample 19% larger than the size originally planned and consenting 79.0% (143/181) of eligible referred adolescents. Effectiveness was limited, with only global impression of change showing significantly greater improvements in the treatment group; however, greater treatment engagement was associated with greater reductions in pain and disability. Adoption was excellent (all the invited clinics participated and referred patients). Implementation was acceptable, showing good user engagement and moderate adherence and positive attitudes of providers. Costs were similar to planned, with a 7% increase in funds needed to make the WMM publicly available. Maintenance was evidenced by 56 new patients downloading the app during the maintenance period and by all clinics agreeing to continue making referrals and all, but one, making new referrals. According to the BIT, 82% (60/73) of adolescents considered the treatment acceptable. In terms of adoption, 93% (68/73) downloaded the app, and all of them used it after their first log-in. In terms of appropriateness at the user level, 2 participants were unable to download the app. Perceptions of the appearance, navigation, and theme were positive. Providers perceived the WMM as a good fit for their clinic, beneficial, helpful, and resource efficient. In terms of feasibility, no technical issues were reported. In terms of fidelity, 40% (29/73) completed the treatment. Implementation costs were 7% above the budget. With regard to penetration, 56 new users accessed the app during the maintenance period. In terms of sustainability, 88% (7/8) of clinics continued recommending the WMM after the end of the study. CONCLUSIONS For the first time, a real-world digital health intervention was used as a proof of concept to test all the domains in the RE-AIM and BIT frameworks, allowing for comparisons. INTERNATIONAL REGISTERED REPORT RR2-10.1016/j.cct.2018.10.003

scholarly journals Assessing Digital Health Implementation for a Pediatric Chronic Pain Intervention: Comparing the RE-AIM and BIT Frameworks Against Real-World Trial Data and Recommendations for Future Studies

10.2196/19898 ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. e19898 ◽  
Author(s):  
Rocio de la Vega ◽  
Lee Ritterband ◽  
Tonya M Palermo
Keyword(s):  
Chronic Pain ◽  
Real World ◽  
Digital Health ◽  
Controlled Trial ◽  
User Engagement ◽  
Maintenance Period ◽  
Treatment Implementation ◽  
Positive Attitudes ◽  
Pediatric Chronic Pain ◽  
Implementation Costs

Background Digital health interventions have demonstrated efficacy for several conditions including for pediatric chronic pain. However, the process of making interventions available to end users in an efficient and sustained way is challenging and remains a new area of research. To advance this field, comprehensive frameworks have been created. Objective The aim of this study is to compare the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) and Behavior Interventions using Technology (BIT) frameworks with data collected from the web-based management of adolescent pain (WebMAP Mobile; WMM) randomized controlled trial (RCT). Methods We conducted a hybrid effectiveness-implementation cluster RCT with a stepped wedge design in which the intervention was sequentially implemented in 8 clinics, following a usual care period. Participants were 143 youths (mean age 14.5 years, SD 1.9; 117/143, 81.8% female) with chronic pain, from which 73 were randomized to receive the active intervention. Implementation outcomes were assessed using the RE-AIM and BIT frameworks. Results According to the RE-AIM framework, the WMM showed excellent reach, recruiting a sample 19% larger than the size originally planned and consenting 79.0% (143/181) of eligible referred adolescents. Effectiveness was limited, with only global impression of change showing significantly greater improvements in the treatment group; however, greater treatment engagement was associated with greater reductions in pain and disability. Adoption was excellent (all the invited clinics participated and referred patients). Implementation was acceptable, showing good user engagement and moderate adherence and positive attitudes of providers. Costs were similar to planned, with a 7% increase in funds needed to make the WMM publicly available. Maintenance was evidenced by 56 new patients downloading the app during the maintenance period and by all clinics agreeing to continue making referrals and all, but one, making new referrals. According to the BIT, 82% (60/73) of adolescents considered the treatment acceptable. In terms of adoption, 93% (68/73) downloaded the app, and all of them used it after their first log-in. In terms of appropriateness at the user level, 2 participants were unable to download the app. Perceptions of the appearance, navigation, and theme were positive. Providers perceived the WMM as a good fit for their clinic, beneficial, helpful, and resource efficient. In terms of feasibility, no technical issues were reported. In terms of fidelity, 40% (29/73) completed the treatment. Implementation costs were 7% above the budget. With regard to penetration, 56 new users accessed the app during the maintenance period. In terms of sustainability, 88% (7/8) of clinics continued recommending the WMM after the end of the study. Conclusions For the first time, a real-world digital health intervention was used as a proof of concept to test all the domains in the RE-AIM and BIT frameworks, allowing for comparisons. International Registered Report Identifier (IRRID) RR2-10.1016/j.cct.2018.10.003

scholarly journals ProACT - A Digital Platform to Support Self-Management of Multiple Chronic Conditions: Findings in Relation to Engagement during a one-year Proof-of-Concept Trial (Preprint)

2020 ◽  
Author(s):  
Julie Doyle ◽  
Emma Murphy ◽  
Shane Gavin ◽  
Alessandra Pascale ◽  
Stephane Deparis ◽  
...  
Keyword(s):  
Older Adults ◽  
Chronic Conditions ◽  
Digital Health ◽  
Self Management ◽  
Multiple Chronic Conditions ◽  
User Engagement ◽  
Proof Of Concept ◽  
Structured Interviews ◽  
Health Technologies ◽  
Care Approach

BACKGROUND Self-management, a core activity for older adults living with multiple chronic conditions (multimorbidity), is challenging, requiring the person to engage in multiple tasks such as symptom monitoring, recognition of exacerbations, medication adherence and inter-stakeholder communication. A digital, integrated care approach is a critical part of the solution, however, there is a dearth of literature on this topic. Furthermore, there is little research on older adults’ acceptability, usage and experiences of engaging with digital health technologies, particularly over long periods of time. OBJECTIVE The objectives were to (1) co-design and develop a digital health platform, called ProACT, to facilitate older adults self-managing multimorbidity, with support from their care network (CN); (2) evaluate end user engagement and experiences with the platform through a 12-month trial. METHODS The ProACT digital health platfrom is presented. The platform was evaluated in a year-long proof-of-concept (PoC) action research trial with 120 older persons with multimorbidity (PwMs) in Ireland and Belgium. Alongside the technology, participants had access to a clinical triage service responding to symptom alerts, and a technical helpdesk. Interactions with the platform during the PoC trial were logged to determine engagement, semi-structured interviews were conducted with participants and analysed using inductive thematic analysis methods, while usability and user burden were examined using validated questionnaires. RESULTS This article presents the ProACT platform and its components, along with findings on engagement with the platform and its usability. Of the 120 participants who took part, 24 withdrew before the end of the study while three passed away. The remaining 93 participants actively used the platform until the end of the trial, on average taking two or three health readings daily over the course of the trial, in Ireland and Belgium respectively. Participants reported ProACT to be usable and of low burden. Findings from interviews outline that participants experienced multiple benefits as a result of using ProACT, including improved self-management, improved health and wellbeing and support from the triage service. For those who withdrew, barriers to engagement were poor health and frustration when technology didn’t work as expected. CONCLUSIONS This is the first study to present findings from a longitudinal study of older adults using digital health technology to self-manage multiple chronic conditions. Our findings show that older adults sustained engagement with the technology and found it usable. Potential reasons for this include a strong focus on user-centred design and engagement throughout the project lifecycle, resulting in a platform that met user needs, as well as the integration of behavior change techniques and personal analytics into the platform. The provision of triage and technical support services alongside the platform during the trial were also important facilitators of engagement. INTERNATIONAL REGISTERED REPORT RR2-10.2196/preprints.22125

Characteristic Latent Features for Analyzing Digital Mental Health Interaction and Improved Explainability (Preprint)

2021 ◽  
Author(s):  
Max-Marcel Theilig ◽  
Ashley A Knapp ◽  
Jennifer M Nicholas ◽  
Rüdiger Zarnekow ◽  
David C Mohr
Keyword(s):  
Mental Health ◽  
Data Science ◽  
Digital Health ◽  
A Priori ◽  
User Interaction ◽  
User Engagement ◽  
Behavioral Strategies ◽  
Data Set ◽  
Public Data ◽  
Latent Features

BACKGROUND Using mobile health technology has sparked a broad engagement of data science and machine learning methods to leverage the complex, assorted amount of data for mental health purposes. Despite many studies, there is a reported underdevelopment of user engagement concepts, and the desire for high accuracy or significance has shown to lead to low explicability and irreproducibility. OBJECTIVE To overcome such reasons of poor analysis input and facilitate the reproducibility and credibility of artificial intelligence applications, we aim to explore principal characteristics of user interaction with digital mental health. METHODS We generated five latent features based on previous research, expert opinions from digital mental health, and informed by data. The features were analyzed with descriptive statistics and data visualization. We carried out two rounds of evaluations with data from 12,400 users of IntelliCare, a mental health platform with 12 apps. First, we focused to proof concept and second, we assessed reproducibility by drawing conclusion from distribution differences. User data was drawn from both research trials and public deployment on Google Play. RESULTS Our algorithms showed advantages over commonly used concepts and reproduce in our public data set with different underlying behavioral strategies. These measures relate to the distribution of a user’s allocated attention, users’ circadian behavior, their consecutive commitment to a specific strategy, and users’ interaction trajectory. Because distributions between research trial and public deployment were similar, consistency was implied regarding the underlying behavioral strategies: psychoeducation and goal setting are used as a catalyst to overcome the users’ primary obstacles, sleep hygiene is addressed most regularly, while regular self-reflective thinking is avoided. Relaxation as well as cognitive reframing have increased variance in commitment among public users, indicating the challenging nature of these apps. The relative course of users’ engagement is similar in research and public data. CONCLUSIONS We argue that deliberate, a-priori feature engineering is essential for reproducible, tangible, and explainable study analyses. Our features enable improved results as well as interpretability, providing an increased understanding of how people engage with multiple mental health apps over time. Since we based the generation of features on generic interaction, these methods are applicable to further methods of study analysis and digital health.

scholarly journals Developing an implementation strategy for a digital health intervention: an example in routine healthcare

2018 ◽  
Vol 18 (1) ◽  
Author(s):  
Jamie Ross ◽  
Fiona Stevenson ◽  
Charlotte Dack ◽  
Kingshuk Pal ◽  
Carl May ◽  
...  
Keyword(s):  
Implementation Strategy ◽  
Digital Health ◽  
Health Intervention

scholarly journals Privacy Personas for IoT-Based Health Research: A Privacy Calculus Approach

2021 ◽  
Vol 3 ◽  
Author(s):  
Benjamin Maus ◽  
Carl Magnus Olsson ◽  
Dario Salvi
Keyword(s):  
Data Collection ◽  
Citizen Science ◽  
Health Research ◽  
Information Disclosure ◽  
Online Survey ◽  
Digital Health ◽  
Health Data ◽  
User Engagement ◽  
Privacy And Security ◽  
Privacy Calculus

The reliance on data donation from citizens as a driver for research, known as citizen science, has accelerated during the Sars-Cov-2 pandemic. An important enabler of this is Internet of Things (IoT) devices, such as mobile phones and wearable devices, that allow continuous data collection and convenient sharing. However, potentially sensitive health data raises privacy and security concerns for citizens, which research institutions and industries must consider. In e-commerce or social network studies of citizen science, a privacy calculus related to user perceptions is commonly developed, capturing the information disclosure intent of the participants. In this study, we develop a privacy calculus model adapted for IoT-based health research using citizen science for user engagement and data collection. Based on an online survey with 85 participants, we make use of the privacy calculus to analyse the respondents' perceptions. The emerging privacy personas are clustered and compared with previous research, resulting in three distinct personas which can be used by designers and technologists who are responsible for developing suitable forms of data collection. These are the 1) Citizen Science Optimist, the 2) Selective Data Donor, and the 3) Health Data Controller. Together with our privacy calculus for citizen science based digital health research, the three privacy personas are the main contributions of this study.

scholarly journals Characteristic Latent Features for Analyzing Digital Mental Health Interaction and Improved Explainability

2020 ◽  
Author(s):  
Max-Marcel Theilig ◽  
Ashley Arehart Knapp ◽  
Jennifer Nicholas ◽  
Rüdiger Zarnekow ◽  
David Curtis Mohr
Keyword(s):  
Mental Health ◽  
Data Science ◽  
Digital Health ◽  
A Priori ◽  
Sensor Technology ◽  
User Engagement ◽  
Behavioral Strategies ◽  
Data Set ◽  
Public Data ◽  
Latent Features

Abstract Background: Using smartphones and wearable sensor technology has sparked a broad engagement of data science and machine learning methods to leverage the complex, assorted amount of data. Despite verified processes, there is a reported underdevelopment of user engagement concepts, and the desire for high accuracy or significance has shown to lead to low explicability and irreproducibility. To overcome these issues, we aim to analyze principal characteristics of everyday behavior in digital mental health. Methods: We generated five latent features based on previous research, expert opinions from digital mental health, and informed by data. The features were analyzed with descriptive statistics and data visualization. We carried out two rounds of evaluations with data from 12,400 users of IntelliCare, a mental health platform with 12 apps. First, we focused to proof concept and second, we assessed reproducibility by drawing conclusion from distribution differences. User data was drawn from both research trials and public deployment on Google Play. Results: Our algorithms showed increased rationale for the basic usage of apps with different underlying behavioral strategies. Measures of the distribution of user’s allocated attention, the user’s circadian behavior, their consecutive commitment to a specific strategy, and users’ interaction trajectory are perceived as transferable to the public data set. Because distributions between research trial and public deployment were similar, consistency was shown regarding the underlying behavioral strategies: psychoeducation and goal setting are used as a catalyst to overcome the users’ primary obstacles, sleep hygiene is addressed most regularly, while regular self-reflective thinking is avoided. Relaxation as well as cognitive reframing have increased variance in commitment among public users, indicating the challenging nature of these apps. The relative course of the engagement (learning curve) is similar in research and public data. Conclusions: The deliberate, a-priori engineered features were reproducible across app users from both data sets. These features led to improved results as well as increased interpretability, providing an increased understanding of how people engage with multiple mental health apps over time. Since we based the generation of features on generic interaction proxies, these methods are applicable to other cases in artificial intelligence and digital health.

scholarly journals Assessing the Food and Drug Administration’s Risk-Based Framework for Software Precertification With Top Health Apps in the United States: Quality Improvement Study

10.2196/20482 ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. e20482
Author(s):  
Noy Alon ◽  
Ariel Dora Stern ◽  
John Torous
Keyword(s):  
United States ◽  
Quality Improvement ◽  
Health Information ◽  
Digital Health ◽  
The United States ◽  
Health Condition ◽  
User Engagement ◽  
Regulatory Review ◽  
Regulatory Guidance ◽  
Health Apps

Background As the development of mobile health apps continues to accelerate, the need to implement a framework that can standardize the categorization of these apps to allow for efficient yet robust regulation is growing. However, regulators and researchers are faced with numerous challenges, as apps have a wide variety of features, constant updates, and fluid use cases for consumers. As past regulatory efforts have failed to match the rapid innovation of these apps, the US Food and Drug Administration (FDA) has proposed that the Software Precertification (Pre-Cert) Program and a new risk-based framework could be the solution. Objective This study aims to determine whether the risk-based framework proposed by the FDA’s Pre-Cert Program could standardize categorization of top health apps in the United States. Methods In this quality improvement study during summer 2019, the top 10 apps for 6 disease conditions (addiction, anxiety, depression, diabetes, high blood pressure, and schizophrenia) in Apple iTunes and Android Google Play Store in the United States were classified using the FDA’s risk-based framework. Data on the presence of well-defined app features, user engagement methods, popularity metrics, medical claims, and scientific backing were collected. Results The FDA’s risk-based framework classifies an app’s risk by the disease condition it targets and what information that app provides. Of the 120 apps tested, 95 apps were categorized as targeting a nonserious health condition, whereas only 7 were categorized as targeting a serious condition and 18 were categorized as targeting a critical condition. As the majority of apps targeted a nonserious condition, their risk categorization was largely determined by the information they provided. The apps that were assessed as not requiring FDA review were more likely to be associated with the integration of external devices than those assessed as requiring FDA review (15/58, 26% vs 5/62, 8%; P=.03) and health information collection (24/58, 41% vs 9/62, 15%; P=.008). Apps exempt from the review were less likely to offer health information (25/58, 43% vs 45/62, 72%; P<.001), to connect users with professional care (7/58, 12% vs 14/62, 23%; P=.04), and to include an intervention (8/58, 14% vs 35/62, 55%; P<.001). Conclusions The FDA’s risk-based framework has the potential to improve the efficiency of the regulatory review process for health apps. However, we were unable to identify a standard measure that differentiated apps requiring regulatory review from those that would not. Apps exempt from the review also carried concerns regarding privacy and data security. Before the framework is used to assess the need for a formal review of digital health tools, further research and regulatory guidance are needed to ensure that the Pre-Cert Program operates in the greatest interest of public health.

scholarly journals Effort-Optimized-Intervention Model: A Framework for Building and Analyzing Digital Interventions that Require Minimal Effort for Health-Related Gains (Preprint)

2020 ◽  
Author(s):  
Amit Baumel ◽  
Frederick J. Muench
Keyword(s):  
Digital Health ◽  
Intervention Development ◽  
Ego Depletion ◽  
User Engagement ◽  
Competing Demands ◽  
Therapeutic Mechanism ◽  
Health Related ◽  
The Face ◽  
A Minor ◽  
Therapeutic Activities

UNSTRUCTURED The majority of digital health interventions lean on the promise of bringing health and self-care into people’s homes and hands. However, these interventions are delivered while people are in their triggering environment, which places competing demands on their attention. Individuals struggling to change or learn a new behavior have to work hard to achieve even a minor change because of the automatic forces propelling them back to their habitual behaviors. This paper posits that effort and burden should be explored at the outset and throughout the digital intervention development process as a core therapeutic mechanism, beyond the context of design or user experience testing. An effort-focused conceptualization assumes that, even though goals are rational and people want to achieve them, they are overtaken by competing cognitive, emotional and environmental processes. We offer the term “effort-optimized intervention” (EOI) to describe interventions that focus on user engagement in the face of competing demands. We describe design components based on a three-step process in the planning of an EOI sequence: 1) nurturing effortless cognitive and environmental salience to help people keep effort-related goals prominent despite competition; 2) making it as effortless as possible to complete therapeutic activities to avoid ego depletion and self-efficacy reductions; and 3) turning the necessary effortful activities into sustainable assets. We conclude by presenting an example of designing a digital health intervention based on the EOI model.

scholarly journals Building MedVenture – A mobile health application to improve adolescent medication adherence – Using a multidisciplinary approach and academic–industry collaboration

2021 ◽  
Vol 7 ◽  
pp. 205520762110198
Author(s):  
Pooja Mehta ◽  
Susan L Moore ◽  
Sheana Bull ◽  
Bethany M Kwan
Keyword(s):  
Content Analysis ◽  
Medication Adherence ◽  
Mobile Health ◽  
Research Team ◽  
Qualitative Content Analysis ◽  
Digital Health ◽  
Healthcare Providers ◽  
User Engagement ◽  
Engagement Strategies ◽  
Industry Collaboration

Objective Mobile health (mHealth) tools are increasingly used to support medication adherence yet few have been designed specifically for the pediatric population. This paper describes the development of a medication adherence application ( MedVenture) using the integration of patient and healthcare provider input, health behavior theory, and user engagement strategies for adolescents with chronic gastrointestinal disease. Methods MedVenture was created by a multidisciplinary research team consisting of a gastroenterologist, a social health psychologist, software developers, and digital health researchers. Healthcare providers and adolescent patients were interviewed to identify barriers to medication adherence, explore ways that technologies could best support medication adherence for both patients and providers, and determine user requirements and core design features for a digital health tool. Intervention mapping was used to match themes from qualitative content analysis to known efficacious adherence strategies, according to a conceptual framework based on self-determination theory. Iterative design with review by the research team and two rounds of user testing informed the final prototype. Results Three themes were identified from content analysis: 1) lack of routine contributes to nonadherence, 2) adolescents sometimes purposefully forgo medications, and 3) healthcare providers would prefer a tool that promotes patient self-management rather than one that involves patient-provider interaction. These findings, combined with evidence-based adherence and user engagement strategies, resulted in the development of MedVenture – a game-based application to improve planning and habit formation. Conclusions Academic-industry collaboration incorporating stakeholders can facilitate the development of mobile health tools designed specifically for adolescents with chronic disease.

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