Functional and Technical Aspects of Self-management mHealth Apps: Systematic App Search and Literature Review

Alwakeel, Lyan; Lano, Kevin

doi:10.2196/29767

Cited by 5 publications

(3 citation statements)

References 58 publications

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“…The impact of these modifications and improvements was highlighted by the continuous increase in perceived experience with the app. Future research should focus on investigating the functional perspectives of mHealth apps, with a specific emphasis on introducing tasks into the everyday life of patients as nonintrusively as possible [ 123 ]. The second limitation relates to the errors in speech recognition.…”

Section: Discussionmentioning

confidence: 99%

Multilingual Framework for Risk Assessment and Symptom Tracking (MRAST)

Šafran,

Lin,

Nateqi

et al. 2024

Sensors

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The importance and value of real-world data in healthcare cannot be overstated because it offers a valuable source of insights into patient experiences. Traditional patient-reported experience and outcomes measures (PREMs/PROMs) often fall short in addressing the complexities of these experiences due to subjectivity and their inability to precisely target the questions asked. In contrast, diary recordings offer a promising solution. They can provide a comprehensive picture of psychological well-being, encompassing both psychological and physiological symptoms. This study explores how using advanced digital technologies, i.e., automatic speech recognition and natural language processing, can efficiently capture patient insights in oncology settings. We introduce the MRAST framework, a simplified way to collect, structure, and understand patient data using questionnaires and diary recordings. The framework was validated in a prospective study with 81 colorectal and 85 breast cancer survivors, of whom 37 were male and 129 were female. Overall, the patients evaluated the solution as well made; they found it easy to use and integrate into their daily routine. The majority (75.3%) of the cancer survivors participating in the study were willing to engage in health monitoring activities using digital wearable devices daily for an extended period. Throughout the study, there was a noticeable increase in the number of participants who perceived the system as having excellent usability. Despite some negative feedback, 44.44% of patients still rated the app’s usability as above satisfactory (i.e., 7.9 on 1–10 scale) and the experience with diary recording as above satisfactory (i.e., 7.0 on 1–10 scale). Overall, these findings also underscore the significance of user testing and continuous improvement in enhancing the usability and user acceptance of solutions like the MRAST framework. Overall, the automated extraction of information from diaries represents a pivotal step toward a more patient-centered approach, where healthcare decisions are based on real-world experiences and tailored to individual needs. The potential usefulness of such data is enormous, as it enables better measurement of everyday experiences and opens new avenues for patient-centered care.

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Section: Discussionmentioning

confidence: 99%

Multilingual Framework for Risk Assessment and Symptom Tracking (MRAST)

Šafran,

Lin,

Nateqi

et al. 2024

Sensors

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“…The Mobile Application Rating Scale is a valid and reliable tool designed to assess mobile health apps 22–24 . It has been used to evaluate apps targeting various health conditions and for general wellness 25 . The first part of the MARS is used to collect descriptive and technical information about each app (eg, app developer and version, date of last update, target users).…”

Section: Methodsmentioning

confidence: 99%

“…[22][23][24] It has been used to evaluate apps targeting various health conditions and for general wellness. 25 The first part of the MARS is used to collect descriptive and technical information about each app (eg, app developer and version, date of last update, target users). The second part of the MARS focuses on appraisal of the app.…”

Section: App Appraisalmentioning

confidence: 99%

Assessment of Mobile Health Applications for Management of Knee and/or Hip Osteoarthritis Using the Mobile Application Rating Scale

et al. 2022

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Background Mobile health applications (apps) can help individuals with knee and/or hip osteoarthritis (OA) learn about, monitor, and manage their condition. These apps have not been formally evaluated. Objective The aim of this study was to evaluate the publicly available mobile health apps for individuals with knee and/or hip OA using a systematic review. Methods We searched the Apple App Store, Android Google Play, and Amazon Appstore using the terms “arthritis,” “osteoarthritis,” “hip OA,” “knee OA,” “hip,” “knee,” “rehabilitation,” “rehab,” and “physical therapy” in December of 2021. Applications that met the inclusion/exclusion criteria were reviewed using the Mobile Application Rating Scale (MARS; 29 items across 6 sections, each rated at 1–5). Results Among 1104 identified apps, 94 met the inclusion/exclusion criteria for MARS appraisal. Fourteen apps met the predetermined score thresholds for final summary. Of the 14 apps appraised, the total overall mean app score on the MARS ranged from 3.12 to 4.20 (mean, 3.51 ± 0.37). Although app features varied, common features were symptom tracking, exercise recommendations, education, goal setting, and improving well-being. Many apps allowed for sharing with health care providers and included some measures to protect privacy. Jointfully Osteoarthritis was the top-rated app in both the Apple App Store and Android Google Play. Conclusions The majority of the apps we identified for knee and/or hip OA did not meet predetermined score thresholds for final summary. Many failed to provide comprehensive education and deliver management plans and lacked scientific testing. Future research should focus on apps that fit the needs of health care providers and patients including quality information, structured exercise programs tailored to individual needs, secure communication methods, and health information protection.

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‘Watkins’ & ‘Watkins2.0’: Smart phone applications (Apps) for gait-assessment in normal pressure hydrocephalus and decompensated long-standing overt ventriculomegaly

Tariq,

Thorne,

Toma

et al. 2024

Acta Neurochir

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Objective Gait disturbance is one of the features of normal pressure hydrocephalus (NPH) and decompensated long-standing overt ventriculomegaly (LOVA). The timed-up-and-go (TUG) test and the timed-10-m-walking test (10MWT) are frequently used assessments tools for gait and balance disturbances in NPH and LOVA, as well as several other disorders. We aimed to make smart-phone apps which perform both the 10MWT and the TUG-test and record the results for individual patients, thus making it possible for patients to have an objective assessment of their progress. Patients with a suitable smart phone can perform repeat assessments in their home environment, providing a measure of progress for them and for their clinical team. Methods 10MWT and TUG-test were performed by 50 healthy adults, 67 NPH and 10 LOVA patients, as well as 5 elderly patients as part of falls risk assessment using the Watkins2.0 app. The 10MWT was assessed with timed slow-pace and fast-pace. Statistical analysis used SPSS (version 25.0, IBM) by paired t-test, comparing the healthy and the NPH cohorts. Level of precision of the app as compared to a clinical observer using a stopwatch was evaluated using receiver operating characteristics curve. Results As compared to a clinical observer using a stopwatch, in 10MWT the app showed 100% accuracy in the measure of time taken to cover distance in whole seconds, 95% accuracy in the number of steps taken with an error ± 1–3 steps, and 97% accuracy in the measure of total distance covered with error of ± 0.25–0.50 m. The TUG test has 100% accuracy in time taken to complete the test in whole seconds, 97% accuracy in the number of steps with an error of ± 1–2 steps and 87.5% accuracy in the distance covered with error of ± 0.50 m. In the measure of time, the app was found to have equal sensitivity as an observer. In measure of number of steps and distance, the app demonstrated high sensitivity and precision (AUC > 0.9). The app also showed significant level of discrimination between healthy and gait-impaired individuals. Conclusion ‘Watkins’ and ‘Watkins2.0’ are efficient apps for objective performance of 10MWT and the TUG-test in NPH and LOVA patients and has application in several other pathologies characterised by gait and balance disturbance.

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Functional and Technical Aspects of Self-management mHealth Apps: Systematic App Search and Literature Review

Cited by 5 publications

References 58 publications

Multilingual Framework for Risk Assessment and Symptom Tracking (MRAST)

Multilingual Framework for Risk Assessment and Symptom Tracking (MRAST)

Assessment of Mobile Health Applications for Management of Knee and/or Hip Osteoarthritis Using the Mobile Application Rating Scale

‘Watkins’ & ‘Watkins2.0’: Smart phone applications (Apps) for gait-assessment in normal pressure hydrocephalus and decompensated long-standing overt ventriculomegaly

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