Abstract:BackgroundAlthough mobile health (mHealth) interventions can help improve outcomes among patients with chronic lower back pain (CLBP), many available mHealth apps offer content that is not evidence based. Limbr was designed to enhance self-management of CLBP by packaging self-directed rehabilitation tutorial videos, visual self-report tools, remote health coach support, and activity tracking into a suite of mobile phone apps, including Your Activities of Daily Living, an image-based tool for quantifying pain-r… Show more
“…Other studies suggest less of a benefit from tailoring messages to maintain users’ interest; despite a low attrition rate of 22% at 4 months and 1 year in two studies, respectively, an app and health counseling did not reduce hemoglobin A1c levels between the intervention and usual care groups [ 17 , 30 ]. In addition, self-management skills and the ability to contact health professionals were found to increase engagement, while users’ feedback input improved usability of apps and enhanced user experiences for daily self-reports [ 17 , 19 ]. Classifying different types of users may be important in improving long-term engagement.…”
Background
Chronic disease represents a large and growing burden to the health care system worldwide. One method of managing this burden is the use of app-based interventions; however attrition, defined as lack of patient use of the intervention, is an issue for these interventions. While many apps have been developed, there is some evidence that they have significant issues with sustained use, with up to 98% of people only using the app for a short time before dropping out and/or dropping use down to the point where the app is no longer effective at helping to manage disease.
Objective
Our objectives are to systematically appraise and perform a meta-analysis on dropout rates in apps for chronic disease and to qualitatively synthesize possible reasons for these dropout rates that could be addressed in future interventions.
Methods
MEDLINE (Medical Literature Analysis and Retrieval System Online), PubMed, Cochrane CENTRAL (Central Register of Controlled Trials), and Embase were searched from 2003 to the present to look at mobile health (mHealth) and attrition or dropout. Studies, either randomized controlled trials (RCTs) or observational trials, looking at chronic disease with measures of dropout were included. Meta-analysis of attrition rates was conducted in Stata, version 15.1 (StataCorp LLC). Included studies were also qualitatively synthesized to examine reasons for dropout and avenues for future research.
Results
Of 833 studies identified in the literature search, 17 were included in the review and meta-analysis. Out of 17 studies, 9 (53%) were RCTs and 8 (47%) were observational trials, with both types covering a range of chronic diseases. The pooled dropout rate was 43% (95% CI 29-57), with observational studies having a higher dropout rate (49%, 95% CI 27-70) than RCTs in more controlled scenarios, which only had a 40% dropout rate (95% CI 16-63). The studies were extremely varied, which is represented statistically in the high degree of heterogeneity (I2>99%). Qualitative synthesis revealed a range of reasons relating to attrition from app-based interventions, including social, demographic, and behavioral factors that could be addressed.
Conclusions
Dropout rates in mHealth interventions are high, but possible areas to minimize attrition exist. Reducing dropout rates will make these apps more effective for disease management in the long term.
Trial Registration
International Prospective Register of Systematic Reviews (PROSPERO) CRD42019128737; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019128737
“…Other studies suggest less of a benefit from tailoring messages to maintain users’ interest; despite a low attrition rate of 22% at 4 months and 1 year in two studies, respectively, an app and health counseling did not reduce hemoglobin A1c levels between the intervention and usual care groups [ 17 , 30 ]. In addition, self-management skills and the ability to contact health professionals were found to increase engagement, while users’ feedback input improved usability of apps and enhanced user experiences for daily self-reports [ 17 , 19 ]. Classifying different types of users may be important in improving long-term engagement.…”
Background
Chronic disease represents a large and growing burden to the health care system worldwide. One method of managing this burden is the use of app-based interventions; however attrition, defined as lack of patient use of the intervention, is an issue for these interventions. While many apps have been developed, there is some evidence that they have significant issues with sustained use, with up to 98% of people only using the app for a short time before dropping out and/or dropping use down to the point where the app is no longer effective at helping to manage disease.
Objective
Our objectives are to systematically appraise and perform a meta-analysis on dropout rates in apps for chronic disease and to qualitatively synthesize possible reasons for these dropout rates that could be addressed in future interventions.
Methods
MEDLINE (Medical Literature Analysis and Retrieval System Online), PubMed, Cochrane CENTRAL (Central Register of Controlled Trials), and Embase were searched from 2003 to the present to look at mobile health (mHealth) and attrition or dropout. Studies, either randomized controlled trials (RCTs) or observational trials, looking at chronic disease with measures of dropout were included. Meta-analysis of attrition rates was conducted in Stata, version 15.1 (StataCorp LLC). Included studies were also qualitatively synthesized to examine reasons for dropout and avenues for future research.
Results
Of 833 studies identified in the literature search, 17 were included in the review and meta-analysis. Out of 17 studies, 9 (53%) were RCTs and 8 (47%) were observational trials, with both types covering a range of chronic diseases. The pooled dropout rate was 43% (95% CI 29-57), with observational studies having a higher dropout rate (49%, 95% CI 27-70) than RCTs in more controlled scenarios, which only had a 40% dropout rate (95% CI 16-63). The studies were extremely varied, which is represented statistically in the high degree of heterogeneity (I2>99%). Qualitative synthesis revealed a range of reasons relating to attrition from app-based interventions, including social, demographic, and behavioral factors that could be addressed.
Conclusions
Dropout rates in mHealth interventions are high, but possible areas to minimize attrition exist. Reducing dropout rates will make these apps more effective for disease management in the long term.
Trial Registration
International Prospective Register of Systematic Reviews (PROSPERO) CRD42019128737; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019128737
“…This paper presented the design and use of the HCF-based telehealth program for patients with CHF. Similar to other pilot studies [20], we focused on user perceptions and experience because user perspective was the most important dimension in the development phase of telehealth projects [21,22]. According to the interviews of participants, their family members, and physicians, they were generally satisfied with the service.…”
BackgroundAn increasing number of patients with chronic heart failure (CHF) are demanding more convenient and efficient modern health care systems, especially in remote areas away from central cities. Telehealth is receiving increasing attention, which may be useful to patients with CHF.ObjectiveThis study aimed to evaluate the feasibility of a hospital-community-family (HCF)–based telehealth program, which was designed to implement remote hierarchical management in patients with CHF.MethodsThis was a single-arm prospective study in which 70 patients with CHF participated in the HCF-based telehealth program for remote intervention for at least 4 months. The participants were recruited from the clinic and educated on the use of smart health tracking devices and mobile apps to collect and manually upload comprehensive data elements related to the risk of CHF self-care management. They were also instructed on how to use the remote platform and mobile app to send text messages, check notifications, and open video channels. The general practitioners viewed the index of each participant on the mobile app and provided primary care periodically, and cardiologists in the regional central hospital offered remote guidance, if necessary. The assessed outcomes included accomplishments of the program, usability and satisfaction, engagement with the intervention, and changes of heart failure–related health behaviors.ResultsAs of February 2018, a total of 66 individuals, aged 40-79 years, completed the 4-month study. Throughout the study period, 294 electronic medical records were formed on the remote monitoring service platform. In addition, a total of 89 remote consultations and 196 remote ward rounds were conducted. Participants indicated that they were generally satisfied with the intervention for its ease of use and usefulness. More than 91% (21/23) of physicians believed the program was effective, and 87% (20/23) of physicians stated that their professional knowledge could always be refreshed and enhanced through a library hosted on the platform and remote consultation. More than 60% (40/66) of participants showed good adherence to the care plan in the study period, and 79% (52/66) of patients maintained a consistent pattern of reporting and viewing their data over the course of the 4-month follow-up period. The program showed a positive effect on self-management for patients (healthy diet: P=.046, more fruit and vegetable intake: P=.02, weight monitoring: P=.002, blood pressure: P<.001, correct time: P=.049, and daily dosages of medicine taken: P=.006).ConclusionsThe HCF-based telehealth program is feasible and provided researchers with evidence of remote hierarchical management for patients with CHF, which can enhance participants’ and their families’ access and motivation to engage in self-management. Further prospective studies with a larger sample size are necessary to confirm the program’s effectiveness.
“…A mobile health (mHealth) intervention is one approach to encourage proactive self-management skills and improve well-being to reduce the development of secondary complications and health care costs [18-20]. Several studies have evaluated the benefit of mHealth in managing chronic conditions [21-24], and the results indicated that mHealth could provide better adherence to intervention regimens, such as compliance with taking medications, and better self-tracking capability to support self-management. Therefore, mHealth showed promise in promoting health-related activities.…”
Background
Persons with chronic conditions and disabilities (PwCCDs) are vulnerable to secondary complications. Many of these secondary complications are preventable with proactive self-management and proper support. To enhance PwCCDs' self-management skills and conveniently receive desired support, we have developed a mobile health (mHealth) system called iMHere. In 2 previous clinical trials, iMHere was successfully used to improve health outcomes of adult participants with spina bifida and spinal cord injury. To further expand use of iMHere among people with various types of disabilities and chronic diseases, the system needs to be more adaptive to address 3 unique challenges: 1) PwCCDs have very diverse needs with regards to self-management support, 2) PwCCDs’ self-management needs may change over time, and 3) it is a challenge to keep PwCCDs engaged and interested in long-term self-management.
Objective
The aim of this study was to develop an
adaptive
mHealth system capable of supporting long-term self-management and adapting to the various needs and conditions of PwCCDs.
Methods
A scalable and adaptive architecture was designed and implemented for the new version, iMHere 2.0. In this
scalable
architecture, a set of mobile app modules was created to provide various types of self-management support to PwCCDs with the ability to add more as needed. The
adaptive
architecture empowers PwCCDs with personally relevant app modules and allows clinicians to adapt these modules in response to PwCCDs’ evolving needs and conditions over time. Persuasive technologies, social support, and personalization features were integrated into iMHere 2.0 to engage and motivate PwCCDs and support long-term usage. Two initial studies were performed to evaluate the usability and feasibility of the iMHere 2.0 system.
Results
The iMHere 2.0 system consists of cross-platform client and caregiver apps, a Web-based clinician portal, and a secure 2-way communication protocol for providing interactions among these 3 front-end components, all supported by a back-end server. The client and caregiver apps have 12 adaptive app modules to support various types of self-management tasks. The adaptive architecture makes it possible for PwCCDs to receive personalized app modules relevant to their conditions with or without support from various types of caregivers. The personalization and persuasive technologies in the architecture can be used to engage PwCCDs for long-term usage of the iMHere 2.0 system. Participants of the usability study were satisfied with the iMHere 2.0 client app. The feasibility evaluation revealed several practical issues to consider when implementing the system on a large scale.
Conclusions
We developed an adaptive mHealth system as a novel method to support diverse needs in self-management for PwCCDs that can dynam...
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