Development and pre-evaluation of a "DiagNurse" mobile app to support nurses in clinical diagnosis using the ADDIE model

Healthcare workers are increasingly utilising cutting-edge technology, including mobile apps, to enhance patient health care and ensure efficient professional performance. The aim of this study was to design, develop and evaluate an educational mobile app dedicated towards being employed by nursing students and practicing nurses to support the clinical assessment of a patient's health condition in nursing care. In order to develop the mobile app, the Analysis, Design, Development, Implementation and Evaluation (ADDIE) model was employed. Between 2022 and 2023, a "Diagnostic Nurse" mobile app was developed in the "Android Application Package (APK)." The app's usability was tested in the laboratory by 20 participants. Three methods were employed in the study, that is, an eye-tracking technique, a qualitative evaluation and a quantitative evaluation. According to the System Usability Scale (SUS), the app test score for the nursing student group was assessed as 83.3 ± 8.9, and for the practicing nursing group, this was 84 ± 12.7. These results indicate that the mobile app's is highly usable. The app received high ratings in the "user-friendliness", "ease-of-use", and "user satisfaction" categories. The "DiagNurse" app makes it easier to learn how to conduct a clinical assessment of a patient's condition in nursing care, resulting in better information acquisition, assessment accuracy and speed. Given the low cost of the app development and the ADDIE model on which it is based, the app may be beneficial to nursing students, practicing nurses and other health-care professionals and students.

Effect of a Mobile Health Application With Nurse Support on Quality of Life Among Community-Dwelling Older Adults in Hong Kong: A Randomized Clinical Trial

IMPORTANCE

Mobile health (mHealth) smartphone apps are becoming increasingly popular among older adults, although the reactive care approach of these apps has limited their usability.

OBJECTIVE

To evaluate the effects of an interactive mHealth program supported by a health-social partnership team on quality of life (QOL) among community-dwelling older adults in Hong Kong.

DESIGN, SETTING, AND PARTICIPANTS

This was a 3-group, randomized clinical trial conducted in 5 community centers in Hong Kong from December 1, 2020, to April 30, 2022, with a last follow-up date of January 31, 2022. Participants included older adults aged at least 60 years who were living within the service area, used a smartphone, and had at least 1 of the following problems: chronic pain, hypertension, or diabetes. Data were analyzed from May 1 to 10, 2022.

INTERVENTIONS

Participants were randomly assigned to the mHealth with interactivity (mHealth+I) group, mHealth group, or control group. Participants in the mHealth+I group received the mHealth app and nurse case management supported by a health-social partnership team. The mHealth group received the mHealth app only. The control group received no mHealth app or health-social care services.

MAIN OUTCOMES AND MEASURES

The primary outcome was the change in QOL from baseline to 3 months after completion of the intervention.

RESULTS

Among 221 participants (mean [SD] age 76.6 [8.0] years; 185 [83.7%] women), 76 were randomized to the control group, 71 were randomized to the mHealth group, and 74 were randomized to the mHealth+I group. The most common chronic diseases or problems were hypertension (147 participants [66.5%]), pain (144 participants [65.2%]), cataracts (72 participants [32.6%]), and diabetes (61 participants [27.6%]). At 3 months after the intervention and compared with the intervention group, there were no statistically significant differences in either the physical component summary (mHealth+I: β = -1.01 [95% CI, -4.13 to 2.11]; P = .53; mHealth: β = 0.22 [95% CI, -3.07 to 3.50]; P = .90) or the mental component summary (mHealth+I: β = -0.87 [95% CI, -4.42 to 2.69]; P = .63; mHealth: β = 1.73 [95% CI, -1.89 to 5.34]; P = .35) QOL scores. Only secondary outcomes, including self-efficacy (β = -2.31 [95% CI, -4.26 to -0.36]; P = .02), systolic blood pressure (β = -2.30 [95% CI, -5.00 to -0.13]; P = .04), pain levels (β = 1.18 [95% CI, 0.52 to 2.00]; P = .02), and health services utilization (β = 0.98 [95% CI, 0.32 to 2.09]; P = .048) improved in the mHealth+I group compared with the control group.

CONCLUSIONS AND RELEVANCE

This randomized clinical trial found no difference in the primary outcome between the mHealth+I group and the control group confirming that there were no incremental benefits to adding interactivity in mHealth programs for older adults with chronic diseases.

TRIAL REGISTRATION

Clinicaltrials.gov Identifier: NCT03878212.

The development of My Care Hub Mobile-Phone App to Support Self-Management in Australians with Type 1 or Type 2 Diabetes

Non-adherence to self-management poses a serious risk to diabetes complications. Digital behavioural change interventions have the potential to provide education and motivate users to regularly engage with self-management of diabetes. This paper describes the development of My Care Hub mobile phone application (app) aimed at supporting self-management in people with type 1 or type 2 diabetes. The development of My Care Hub involved a comprehensive process of healthy behavioural change identification, end users’ needs, expert consensus, data security and privacy considerations. The app translation was a highly iterative process accompanied by usability testing and design modification. The app development process included: (1) behaviour change strategy selection; (2) users’ involvement; (3) expert advisory involvement; (4) data security and privacy considerations; (5) design creation and output translation into a smartphone app and (6) two usability testings of the app prototype version. The app features include self-management activities documentation, analytics, personalized and generalized messages for diabetes self-management as well as carbohydrate components of common foods in Australia. Twelve respondents provided feedback on the usability of the app. Initially, a simplification of the documentation features of the app was identified as a need to improve usability. Overall, results indicated good user satisfaction rate.

Mobile health for older adult patients: Using an aging barriers framework to classify usability problems

BACKGROUND

With populations aging, digital health tools and mobile health applications (mHealth) are becoming more common to assist older people in independent living and self-management of (chronic) illnesses. These mHealth services can be beneficial to older patients, provided that they are adjusted to their needs and characteristics, as the current mHealth landscape lacks user-friendly services for this target group. Understanding of intrinsic aging barriers, which cause and impact usability problems older patients encounter, is needed to achieve this.

OBJECTIVES

This study set out to assess usability problems older patients encounter in two mHealth apps and aims to show the value of MOLD-US, a recent aging barriers framework, as a classification tool to identify the intrinsic cause of these problems.

METHOD

A case-study design, with in-depth analysis of usability issues older adult patients' experience. Data on usability issues were collected using the Think Aloud Protocol for two mHealth apps. The MOLD-US framework and Nielsen's severity rating were used to classify identified issues and their potential impact.

RESULTS

In total 28 high severe usability issues of the mHealth apps were identified. Core natures of most issues were related to motivational and cognitive barriers of older adults. Participants had difficulties in understanding the navigation structure of the apps. Important text, buttons and icon elements were overseen.

CONCLUSION

Current knowledge on creating interfaces for older target groups is not well applied within the assessed mHealth designs. Specifically, design guidelines should address older adults' diminishing cognition skills, physical ability and motivational barriers. By classifying usability problems with MOLD-US, insights on these barriers can be enhanced to adequately address these issues in new designs. In addition, we propose that future research focuses on investigating suitable usability evaluation methods adapted to older patients' characteristics to ultimately be able to gain unbiased sight on usability issues older patients may experience while interacting with technology.

Mobile PHRs compliance with Android and iOS usability guidelines

Mobile Personal Health Records (PHRs) have achieved a particularly strong market share since the appearance of more powerful mobile devices and popular worldwide mobile application markets such as Apple's App Store and Android's Google Play. However, Android and Apple have a set of recommendations on design and usability targeted towards developers who wish to publish apps in their stores: Android Design Guidelines and iOS Human Interface Guidelines. This paper aims to evaluate compliance with these guidelines by assessing the usability recommendations of a set of 24 selected mobile PHR applications. An analysis process based on a well-known Systematic Literature Review (SLR) protocol was used. The results show that the 24 mobile PHR applications studied are not suitably structured. 46 % of these applications do not use any of the recommended patterns, using instead lists or springboards, which are deprecated patterns for top-level menus. 70 % of the PHRs require a registration to be able to test the application when these interactions should be delayed. Our study will help both PHR users to select user-friendly mobile PHRs and PHR providers and developers to identify the good usability practices implemented by the applications with the highest scores.