Intervention and Evaluation of Mobile Health Technologies in Management of Patients Undergoing Chronic Dialysis: Scoping Review (Preprint)

BACKGROUND Studies have shown the effectiveness and user acceptance of mobile health (mHealth) technologies in managing patients with chronic kidney disease (CKD). However, incorporating mHealth technology into the standard care of patients with CKD still faces many challenges. To our knowledge, there are no reviews on mHealth interventions and their assessments concerning the management of patients undergoing dialysis. OBJECTIVE This study provided a scoping review on existing apps and interventions of mHealth technologies in adult patients undergoing chronic dialysis and identified the gaps in patient outcome assessment of mHealth technologies in the literature. METHODS We systematically searched PubMed (MEDLINE), Scopus, and the Cumulative Index to Nursing and Allied Health Literature databases, as well as gray literature sources. Two keywords, “mHealth” and “dialysis,” were combined to address the main concepts of the objectives. Inclusion criteria were as follows: (1) mHealth interventions, which are on a smartphone, tablet, or web-based portals that are accessible through mobile devices; and (2) adult patients (age ≥18 years) on chronic dialysis. Only English papers published from January 2008 to October 2018 were included. Studies with mHealth apps for other chronic conditions, based on e-consultation or videoconferencing, non-English publications, and review papers were excluded. RESULTS Of the 1054 papers identified, 22 met the inclusion and exclusion criteria. Most studies (n=20) were randomized controlled trials and cohort studies. These studies were carried out in 7 countries. The main purposes of these mHealth interventions were as follows: nutrition or dietary self-monitoring (n=7), remote biometric monitoring (n=7), web-based portal (n=4), self-monitoring of in-session dialysis-specific information (n=3), and self-monitoring of lifestyle or behavioral change (n=1). The outcomes of the 22 included studies were organized into five categories: (1) patient satisfaction and acceptance, (2) clinical effectiveness, (3) economic assessment, (4) health-related quality of life, and (5) impact on lifestyle or behavioral change. The mHealth interventions showed neutral to positive results in chronic dialysis patient management, reporting no to significant improvement of dialysis-specific measurements and some components of the overall quality of life assessment. Evaluation of these mHealth interventions consistently demonstrated evidence in patients’ satisfaction, high level of user acceptance, and reduced use of health resources and cost savings to health care services. However, there is a lack of studies evaluating safety, organizational, sociocultural, ethical, and legal aspects of mHealth technologies. Furthermore, a comprehensive cost-effectiveness and cost-benefit analysis of adopting mHealth technologies was not found in the literature. CONCLUSIONS The gaps identified in this study will inform the creation of health policies and organizational support for mHealth implementation in patients undergoing dialysis. The findings of this review will inform the development of a comprehensive service model that utilizes mHealth technologies for home monitoring and self-management of patients undergoing chronic dialysis.

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Intervention and Evaluation of Mobile Health Technologies in Management of Patients Undergoing Chronic Dialysis: Scoping Review

JMIR mhealth and uhealth ◽

10.2196/15549 ◽

2020 ◽

Vol 8 (4) ◽

pp. e15549

Author(s):

Yang Yang ◽

Helen Chen ◽

Hammad Qazi ◽

Plinio P Morita

Keyword(s):

Quality Of Life ◽

Mobile Health ◽

Scoping Review ◽

Behavioral Change ◽

User Acceptance ◽

Adult Patients ◽

Chronic Dialysis ◽

Self Monitoring ◽

Web Based

Background Studies have shown the effectiveness and user acceptance of mobile health (mHealth) technologies in managing patients with chronic kidney disease (CKD). However, incorporating mHealth technology into the standard care of patients with CKD still faces many challenges. To our knowledge, there are no reviews on mHealth interventions and their assessments concerning the management of patients undergoing dialysis. Objective This study provided a scoping review on existing apps and interventions of mHealth technologies in adult patients undergoing chronic dialysis and identified the gaps in patient outcome assessment of mHealth technologies in the literature. Methods We systematically searched PubMed (MEDLINE), Scopus, and the Cumulative Index to Nursing and Allied Health Literature databases, as well as gray literature sources. Two keywords, “mHealth” and “dialysis,” were combined to address the main concepts of the objectives. Inclusion criteria were as follows: (1) mHealth interventions, which are on a smartphone, tablet, or web-based portals that are accessible through mobile devices; and (2) adult patients (age ≥18 years) on chronic dialysis. Only English papers published from January 2008 to October 2018 were included. Studies with mHealth apps for other chronic conditions, based on e-consultation or videoconferencing, non-English publications, and review papers were excluded. Results Of the 1054 papers identified, 22 met the inclusion and exclusion criteria. Most studies (n=20) were randomized controlled trials and cohort studies. These studies were carried out in 7 countries. The main purposes of these mHealth interventions were as follows: nutrition or dietary self-monitoring (n=7), remote biometric monitoring (n=7), web-based portal (n=4), self-monitoring of in-session dialysis-specific information (n=3), and self-monitoring of lifestyle or behavioral change (n=1). The outcomes of the 22 included studies were organized into five categories: (1) patient satisfaction and acceptance, (2) clinical effectiveness, (3) economic assessment, (4) health-related quality of life, and (5) impact on lifestyle or behavioral change. The mHealth interventions showed neutral to positive results in chronic dialysis patient management, reporting no to significant improvement of dialysis-specific measurements and some components of the overall quality of life assessment. Evaluation of these mHealth interventions consistently demonstrated evidence in patients’ satisfaction, high level of user acceptance, and reduced use of health resources and cost savings to health care services. However, there is a lack of studies evaluating safety, organizational, sociocultural, ethical, and legal aspects of mHealth technologies. Furthermore, a comprehensive cost-effectiveness and cost-benefit analysis of adopting mHealth technologies was not found in the literature. Conclusions The gaps identified in this study will inform the creation of health policies and organizational support for mHealth implementation in patients undergoing dialysis. The findings of this review will inform the development of a comprehensive service model that utilizes mHealth technologies for home monitoring and self-management of patients undergoing chronic dialysis.

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Supporting Self-Management and Quality of Life in Bipolar Disorder with the Beta PolarUs App: Protocol for a Mixed-Methods Study (Preprint)

10.2196/preprints.36213 ◽

2022 ◽

Author(s):

Erin E Michalak ◽

Steven J Barnes ◽

Emma Morton ◽

Heather O'Brien ◽

Greg Murray ◽

...

Keyword(s):

Quality Of Life ◽

Mixed Methods ◽

Management Strategies ◽

Community Based Participatory Research ◽

Self Management ◽

Community Based ◽

Self Monitoring ◽

Web Based ◽

Beta Version

BACKGROUND Quality of life (QoL) is increasingly recognised as a key outcome of self-management interventions for bipolar disorder (BD). Mobile phone applications (apps) can increase access to evidence-based self-management strategies and provide real-time support. However, while individuals with lived experience desire support with monitoring and improving broader health domains, existing BD apps largely target mood symptoms only. Further, evidence from the broader mHealth literature has shown that the desires and goals of end-users are not adequately taken into account during app development, and as a result engagement with mental health apps is suboptimal. To capitalise on the potential of apps to optimise wellness in BD, there is a need for interventions developed in consultation with real-world users that are designed to support QoL self-monitoring and self-management. Objective: This mixed methods pilot study is designed to evaluate the beta version of the newly developed PolarUs app, which aims to support QoL self-monitoring and self-management in people with BD. Developed using a community-based participatory research framework, the PolarUs app builds on the web-based adaptation of a BD-specific QoL self-assessment measure, and integrates material from a web-based portal providing information on evidence-informed self-management strategies in BD. OBJECTIVE The primary objectives of this project are to: (1) evaluate PolarUs app feasibility (via behavioral usage metrics); (2) evaluate PolarUs impact (via the Brief Quality of Life in Bipolar Disorders, QoL.BD scale, our primary outcomes measure); and (3) explore engagement with the PolarUs app (via both quantitative and qualitative methods). METHODS Study participants will be North American residents (N=150) aged 18-65 years with a DSM-5 diagnosis of BD-I, BD-II or BD not otherwise specified (NOS) as assessed by a structured diagnostic interview. An embedded mixed-methods research design will be adopted; qualitative interviews with a purposefully selected sub-sample (~n=30) of participants will be conducted to explore in more depth feasibility, impact and engagement with the PolarUs app over the 12-week study period. RESULTS At the time of publication of this protocol, the development of the beta version of the PolarUs app is complete. Participant enrollment is expected to begin in February 2022. Data collection is expected to be completed by December 2022. CONCLUSIONS Beyond contributing knowledge on the feasibility and impacts of a novel app to support QoL and self-management in BD, this study is also expected to provide new knowledge on engagement with mHealth apps. Furthermore, it is expected to function as a case study of successful co-design between individuals living with BD, clinicians who specialise in the treatment of BD, and BD researchers, providing a template for future use of community-based participatory research frameworks in mHealth intervention development. Results will be used to further refine the PolarUs app and inform the design of a larger clinical trial.

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Experiences of a Web-Based Quality of Life Self-Monitoring Tool for Individuals With Bipolar Disorder: A Qualitative Exploration (Preprint)

10.2196/preprints.16121 ◽

2019 ◽

Author(s):

Emma Morton ◽

Rachelle Hole ◽

Greg Murray ◽

Simone Buzwell ◽

Erin Michalak

Keyword(s):

Quality Of Life ◽

Bipolar Disorder ◽

Assessment Tool ◽

Self Management ◽

Care Providers ◽

Self Assessment ◽

Self Monitoring ◽

Web Based ◽

Qualitative Exploration

BACKGROUND Self-monitoring of symptoms is a cornerstone of psychological interventions in bipolar disorder (BD), but individuals with lived experience also value tracking holistic outcomes, such as quality of life (QoL). Importantly, self-monitoring is not always experienced positively by people with BD and may have lower than expected rates of engagement. Therefore, before progressing into QoL tracking tools, it is important to explore user perspectives to identify possible risks and benefits, optimal methods to support engagement, and possible avenues to integrate QoL self-monitoring practices into clinical work. OBJECTIVE This study aimed to conduct a qualitative exploration of how individuals with BD engaged with a Web-based version of a BD-specific QoL self-monitoring instrument, the QoL tool. METHODS A total of 43 individuals with BD engaged with a self-management intervention with an optional Web-based QoL self-assessment tool as part of an overarching mixed method study. Individuals were later interviewed about personal experiences of engagement with the intervention, including experiences of gauging their own QoL. A thematic analysis was used to identify salient aspects of the experience of QoL self-monitoring in BD. RESULTS In total, 4 categories describing people’s experiences of QoL self-monitoring were identified: (1) breadth of QoL monitoring, (2) highlighting the positive, (3) connecting self-monitoring to action, and (4) self-directed patterns of use. CONCLUSIONS The findings of this research generate novel insights into ways in which individuals with BD experience the Web-based QoL self-assessment tool. The value of tracking the breadth of domains was an overarching aspect, facilitating the identification of both areas of strength and life domains in need of intervention. Importantly, monitoring QoL appeared to have an inherently therapeutic quality, through validating flourishing areas and reinforcing self-management efforts. This contrasts the evidence suggesting that symptom tracking may be distressing because of its focus on negative experiences and positions QoL as a valuable adjunctive target of observation in BD. Flexibility and personalization of use of the QoL tool were key to engagement, informing considerations for health care providers wishing to support self-monitoring and future research into Web- or mobile phone–based apps.

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Experiences of a Web-Based Quality of Life Self-Monitoring Tool for Individuals With Bipolar Disorder: A Qualitative Exploration

JMIR Mental Health ◽

10.2196/16121 ◽

2019 ◽

Vol 6 (12) ◽

pp. e16121 ◽

Cited By ~ 7

Author(s):

Emma Morton ◽

Rachelle Hole ◽

Greg Murray ◽

Simone Buzwell ◽

Erin Michalak

Keyword(s):

Quality Of Life ◽

Bipolar Disorder ◽

Assessment Tool ◽

Self Management ◽

Care Providers ◽

Self Assessment ◽

Self Monitoring ◽

Web Based ◽

Qualitative Exploration

Background Self-monitoring of symptoms is a cornerstone of psychological interventions in bipolar disorder (BD), but individuals with lived experience also value tracking holistic outcomes, such as quality of life (QoL). Importantly, self-monitoring is not always experienced positively by people with BD and may have lower than expected rates of engagement. Therefore, before progressing into QoL tracking tools, it is important to explore user perspectives to identify possible risks and benefits, optimal methods to support engagement, and possible avenues to integrate QoL self-monitoring practices into clinical work. Objective This study aimed to conduct a qualitative exploration of how individuals with BD engaged with a Web-based version of a BD-specific QoL self-monitoring instrument, the QoL tool. Methods A total of 43 individuals with BD engaged with a self-management intervention with an optional Web-based QoL self-assessment tool as part of an overarching mixed method study. Individuals were later interviewed about personal experiences of engagement with the intervention, including experiences of gauging their own QoL. A thematic analysis was used to identify salient aspects of the experience of QoL self-monitoring in BD. Results In total, 4 categories describing people’s experiences of QoL self-monitoring were identified: (1) breadth of QoL monitoring, (2) highlighting the positive, (3) connecting self-monitoring to action, and (4) self-directed patterns of use. Conclusions The findings of this research generate novel insights into ways in which individuals with BD experience the Web-based QoL self-assessment tool. The value of tracking the breadth of domains was an overarching aspect, facilitating the identification of both areas of strength and life domains in need of intervention. Importantly, monitoring QoL appeared to have an inherently therapeutic quality, through validating flourishing areas and reinforcing self-management efforts. This contrasts the evidence suggesting that symptom tracking may be distressing because of its focus on negative experiences and positions QoL as a valuable adjunctive target of observation in BD. Flexibility and personalization of use of the QoL tool were key to engagement, informing considerations for health care providers wishing to support self-monitoring and future research into Web- or mobile phone–based apps.

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