Dataset Information

Quality of Life of Women After a First Diagnosis of Breast Cancer Using a Self-Management Support mHealth App in Taiwan: Randomized Controlled Trial.

ABSTRACT: BACKGROUND:There are over 2 million newly diagnosed patients with breast cancer worldwide with more than 10,000 cases in Taiwan each year. During 2017-2018, the National Yang-Ming University, the Taiwan University of Science and Technology, and the Taiwan Breast Cancer Prevention Foundation collaborated to develop a breast cancer self-management support (BCSMS) mHealth app for Taiwanese women with breast cancer. OBJECTIVE:The aim of this study was to investigate the quality of life (QoL) of women with breast cancer in Taiwan after using the BCSMS app. METHODS:After receiving a first diagnosis of breast cancer, women with stage 0 to III breast cancer, who were recruited from social networking sites or referred by their oncologists or oncology case managers, were randomized 1:1 into intervention and control groups. Intervention group subjects used the BCSMS app and the control group subjects received usual care. Two questionnaires-the European Organization for Research and Treatment of Cancer (EORTC) Quality-of-Life Questionnaire Core 30 (QLQ-C30) and the EORTC Breast Cancer-Specific Quality-of-Life Questionnaire (QLQ-BR23)-were distributed to subjects in both arms. Paper-based questionnaires were used at baseline; paper-based or Web-based questionnaires were used at 1.5-month and 3-month follow-up evaluations. All evaluations were self-assessed and anonymous, and participants were blinded to their allocation groups. Descriptive analysis, the Pearson chi-square test, analysis of variance, and the generalized estimating equation were used to analyze the data. Missing values, with and without multi-imputation techniques, were used for sensitivity analysis. RESULTS:A total of 112 women were enrolled and randomly allocated to either the experimental group (n=53) or control group (n=59). The follow-up completion rate was 89.3% (100/112). The demographic data showed homogeneity between the two groups in age (range 50-64 years), breast cancer stage (stage II), marital status (married), working status (employed), and treatment status (receiving treatments). The mean total QoL summary scores from the QLQ-C30 (83.45 vs 82.23, P=.03) and the QLQ-BR23 (65.53 vs 63.13, P=.04) were significantly higher among the experimental group versus the control group, respectively, at 3 months. CONCLUSIONS:This research provides support for using a mobile health care app to promote the QoL among women in Taiwan after a first diagnosis of breast cancer. The BCSMS app could be used to support disease self-management, and further evaluation of whether QoL is sustained is warranted. TRIAL REGISTRATION:ClinicalTrials.gov NCT004174248; https://clinicaltrials.gov/ct2/show/NCT04174248.

SUBMITTER: Hou IC

PROVIDER: S-EPMC7081131 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Quality of Life of Women After a First Diagnosis of Breast Cancer Using a Self-Management Support mHealth App in Taiwan: Randomized Controlled Trial.

Hou I-Ching IC Lin Hsin-Yi HY Shen Shan-Hsiang SH Chang King-Jen KJ Tai Hao-Chih HC Tsai Ay-Jen AJ Dykes Patricia C PC

JMIR mHealth and uHealth 20200304 3

<h4>Background</h4>There are over 2 million newly diagnosed patients with breast cancer worldwide with more than 10,000 cases in Taiwan each year. During 2017-2018, the National Yang-Ming University, the Taiwan University of Science and Technology, and the Taiwan Breast Cancer Prevention Foundation collaborated to develop a breast cancer self-management support (BCSMS) mHealth app for Taiwanese women with breast cancer.<h4>Objective</h4>The aim of this study was to investigate the quality of lif ...[more]

PMID: 32130181

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Project description:Background: Routine outcome monitoring (ROM) has been implemented across a range of addiction treatment services, settings and organisations. Mutual support groups are a notable exception. Innovative solutions are needed. SMART Track is a purpose built smartphone app designed to capture ROM data and provide tailored feedback to adults attending Australian SMART Recovery groups for addictive behaviour(s). Objective: Details regarding the formative stage of app development is essential, but often neglected. Improved consideration of the end-user is vital for curtailing app attrition and enhancing engagement. This paper provides a pragmatic example of how principles embedded in published frameworks can be operationalised to address these priorities during the design and development of the SMART Track app. Methods: Three published frameworks for creating digital health technologies ("Person-Based Approach," "BIT" Model and IDEAS framework) were integrated and applied across two stages of research to inform the development, design and content of SMART Track. These frameworks were chosen to ensure that SMART Track was informed by the needs and preferences of the end-user ("Person-Based"); best practise recommendations for mHealth development ("BIT" Model) and a collaborative, iterative development process between the multi-disciplinary research team, app developers and end-users (IDEAS framework). Results: Stage one of the research process generated in-depth knowledge to inform app development, including a comprehensive set of aims (clinical, research/organisation, and usage); clear articulation of the target behaviour (self-monitoring of recovery related behaviours and experiences); relevant theory (self-determination and social control); appropriate behavioural strategies (e.g., behaviour change taxonomy and process motivators) and key factors that may influence engagement (e.g., transparency, relevance and trust). These findings were synthesised into guiding principles that were applied during stage two in an iterative approach to app design, content and development. Conclusions: This paper contributes new knowledge on important person-centred and theoretical considerations that underpin a novel ROM and feedback app for people with addictive behaviour(s). Although person-centred design and best-practise recommendations were employed, further research is needed to determine whether this leads to improved usage outcomes. Clinical Trial Registration: Pilot Trial: http://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377336.

Project description: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-related disability.ObjectiveThe aim is to (1) describe patient engagement with the Limbr program, (2) describe patient-perceived utility of the Limbr program, and (3) assess the validity of the Your Activities of Daily Living module for quantifying functional status among patients with CLBP.MethodsThis was a single-arm trial utilizing a convenience sample of 93 adult patients with discogenic back pain who visited a single physiatrist from January 2016 to February 2017. Eligible patients were enrolled in 3-month physical therapy program and received the Limbr mobile phone app suite for iOS or Android. The program included three daily visual self-reports to assess pain, activity level, and medication/coping mechanisms; rehabilitation video tutorials; passive activity-level measurement; and chat-based health coaching. Patient characteristics, patient engagement, and perceived utility were analyzed descriptively. Associations between participant characteristics and program interaction were analyzed using multiple linear regression. Associations between Your Activities of Daily Living and Oswestry Disability Index (ODI) assessments were examined using Pearson correlation and hierarchical linear modeling.ResultsA total of 93 participants were enrolled; of these, 35 (38%) completed the program (age: mean 46, SD 16 years; female: 22/35, 63%). More than half of completers finished assessments at least every 3 days and 70% (19/27) used the rehabilitation component at least once a week. Among respondents to a Web-based feedback survey, 76% (16/21) found the daily notifications helped them remember to complete their exercises, 81% (17/21) found the system easy to use, and 62% (13/21) rated their overall experience good or excellent. Baseline Your Activities of Daily Living score was a significant predictor of baseline ODI score, with ODI increasing by 0.30 units for every 1-unit increase in Your Activities of Daily Living (P<.001). Similarly, hierarchical linear modeling analysis indicated that Your Activities of Daily Living daily assessment scores were significant predictors of ODI scores over the course of the study (P=.01).ConclusionsEngagement among participants who completed the Limbr program was high, and program utility was rated positively by most respondents. Your Activities of Daily Living was significantly associated with ODI scores, supporting the validity of this novel tool. Future studies should assess the effect of Limbr on clinical outcomes, evaluate its use among a wider patient sample, and explore strategies for reducing attrition.Trial registrationClinicalTrials.gov NCT03040310; https://clinicaltrials.gov/ct2/show/NCT03040310 (Archived by WebCite at http://www.webcitation.org/722mEvAiv).

Project description:BackgroundAlthough the past decade has witnessed the development of many self-management mobile health (mHealth) apps that enable users to monitor their health and activities independently, there is a general lack of empirical evidence on the functional and technical aspects of self-management mHealth apps from a software engineering perspective.ObjectiveThis study aims to systematically identify the characteristics and challenges of self-management mHealth apps, focusing on functionalities, design, development, and evaluation methods, as well as to specify the differences and similarities between published research papers and commercial and open-source apps.MethodsThis research was divided into 3 main phases to achieve the expected goal. The first phase involved reviewing peer-reviewed academic research papers from 7 digital libraries, and the second phase involved reviewing and evaluating apps available on Android and iOS app stores using the Mobile Application Rating Scale. Finally, the third phase involved analyzing and evaluating open-source apps from GitHub.ResultsIn total, 52 research papers, 42 app store apps, and 24 open-source apps were analyzed, synthesized, and reported. We found that the development of self-management mHealth apps requires significant time, effort, and cost because of their complexity and specific requirements, such as the use of machine learning algorithms, external services, and built-in technologies. In general, self-management mHealth apps are similar in their focus, user interface components, navigation and structure, services and technologies, authentication features, and architecture and patterns. However, they differ in terms of the use of machine learning, processing techniques, key functionalities, inference of machine learning knowledge, logging mechanisms, evaluation techniques, and challenges.ConclusionsSelf-management mHealth apps may offer an essential means of managing users' health, expecting to assist users in continuously monitoring their health and encourage them to adopt healthy habits. However, developing an efficient and intelligent self-management mHealth app with the ability to reduce resource consumption and processing time, as well as increase performance, is still under research and development. In addition, there is a need to find an automated process for evaluating and selecting suitable machine learning algorithms for the self-management of mHealth apps. We believe that these issues can be avoided or significantly reduced by using a model-driven engineering approach with a decision support system to accelerate and ameliorate the development process and quality of self-management mHealth apps.

Project description:BackgroundAnxiety and depressive disorders are the most common mental health conditions among African American women. Despite the need for mental health care, African American women significantly underuse mental health services. Previous mobile health studies revealed significant improvements in anxiety or depressive symptoms after intervention. The use of mobile apps offers the potential to eliminate or mitigate barriers for African American women who are seeking access to mental health services and resources.ObjectiveThis study aims to evaluate the usability of the prototype of an app that is designed for supporting the self-management of anxiety and depression in African American women.MethodsIndividual usability testing sessions were conducted with 15 participants in Chapel Hill, North Carolina. Cognitive walkthrough and think-aloud protocols were used to evaluate the user interface. Eye-tracking glasses were used to record participants' visual focus and gaze path as they performed the tasks. The Questionnaire for User Interface Satisfaction was administered after each session to assess the participants' acceptance of the app.ResultsParticipants rated the usability of the prototype positively and provided recommendations for improvement. The average of the mean scores for usability assessments (ie, overall reactions to the software, screen, terminology and app information, learning, and app capabilities) ranged from 7.2 to 8.8 on a scale of 0-9 (low to high rating) for user tasks. Most participants were able to complete each task with limited or no assistance. Design recommendations included improving the user interface by adding graphics and color, adding a tutorial for first-time users, curating a list of Black women therapists within the app, adding details about tracking anxiety and depression in the checkup graphs, informing users that they can use the talk-to-text feature for journal entries to reduce burden, relabeling the mental health information icon, monitoring for crisis support, and improving clickthrough sequencing.ConclusionsThis study provides a better understanding of user experience with an app tailored to support the management of anxiety and depression for African American women, which is an underserved group. As African American women have high rates of smartphone ownership, there is a great opportunity to use mobile technology to provide access to needed mental health services and resources. Future work will include incorporating feedback from usability testing and focus group sessions to refine and develop the app further. The updated app will undergo iterative usability testing before launching the pilot study to evaluate the feasibility and acceptability of the prototype.

Project description:BackgroundTo support the self-management of heart failure, a team of hospital clinicians, patients, and family caregivers have co-designed the consumer mobile health app, Care4myHeart.ObjectiveThis research aimed to determine patient experiences of using the app to self-manage heart failure.MethodsPatients with heart failure used the app for 14 days on their own smart device in a home setting, following which a mixed-methods evaluation was performed. Eight patients were recruited, of whom six completed the Mobile Application Rating Scale and attended an interview.ResultsThe overall app quality score was "acceptable" with 3.53 of 5 points, with the aesthetics (3.83/5) and information (3.78/5) subscales scoring the highest. The lowest mean score was in the app-specific subscale representing the perceived impact on health behavior change (2.53/5). Frequently used features were weight and fluid restriction tracking, with graphical representation of data particularly beneficial for improved self-awareness and ongoing learning. The use of technology for self-management will fundamentally differ from current practices and require a change in daily routines. However, app use was correlated with potential utility for daily management of illness with benefits of accurate recording and review of personal health data and as a communication tool for doctors to assist with care planning, as all medical information is available in one place. Technical considerations included participants' attitudes toward technology, functionality and data entry issues, and relatively minor suggested changes.ConclusionsThe findings from this usability study suggest that a significant barrier to adoption is the lack of integration of technology into everyday life in the context of already established disease self-management routines. Future studies should explore the barriers to adoption and sustainability of consumer mobile health interventions for chronic conditions, particularly whether introducing such apps is more beneficial at the commencement of a self-management regimen.

Project description:BackgroundWith the rapid development of mobile health (mHealth) technology, many health apps have been introduced to the commercial market for people with back pain conditions. However, little is known about their content, quality, approaches to care for low back pain (LBP), and associated risks of use.ObjectiveThe aims of this research were to (1) identify apps for the self-management of LBP currently on the market and (2) assess their quality, intervention content, theoretical approaches, and risk-related approaches.MethodsThe UK iTunes and Google Play stores were initially searched for apps related to the self-management of LBP in May 2022. A repeat search in June 2023 was conducted to ensure that any relevant new apps developed in the last year were incorporated into the review. A total of 3 keywords recommended by the Cochrane Back and Neck Group were used to search apps "low back pain," "back pain," and "lumbago." The quality of the apps was assessed by using the 5-point Mobile App Rating Scale (MARS).ResultsA total of 69 apps (25 iOS and 44 Android) met the inclusion criteria. These LBP self-management apps mainly provide recommendations on muscle stretching (n=51, 73.9%), muscle strengthening (n=42, 60.9%), core stability exercises (n=32, 46.4%), yoga (n=19, 27.5%), and information about LBP mechanisms (n=17, 24.6%). Most interventions (n=14, 78%) are consistent with the recommendations in the National Institute for Health and Care Excellence (NICE) guidelines. The mean (SD) MARS overall score of included apps was 2.4 (0.44) out of a possible 5 points. The functionality dimension was associated with the highest score (3.0), whereas the engagement and information dimension resulted in the lowest score (2.1). Regarding theoretical and risk-related approaches, 18 (26.1%) of the 69 apps reported the rate of intervention progression, 11 (15.9%) reported safety checks, only 1 (1.4%) reported personalization of care, and none reported the theoretical care model or the age group targeted.ConclusionsmHealth apps are potentially promising alternatives to help people manage their LBP; however, most of the LBP self-management apps were of poor quality and did not report the theoretical approaches to care and their associated risks. Although nearly all apps reviewed included a component of care listed in the NICE guidelines, the model of care delivery or embracement of care principles such as the application of a biopsychosocial model was unclear.

Dataset Information

Quality of Life of Women After a First Diagnosis of Breast Cancer Using a Self-Management Support mHealth App in Taiwan: Randomized Controlled Trial.

Publications

Quality of Life of Women After a First Diagnosis of Breast Cancer Using a Self-Management Support mHealth App in Taiwan: Randomized Controlled Trial.

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