Italian Version of the mHealth App Usability Questionnaire (Ita-MAUQ): Translation and Validation Study in People With Multiple Sclerosis.

Background: Telemedicine and mobile health (mHealth) apps have emerged as powerful tools in health care, offering convenient access to services and empowering participants in managing their health. Among populations with chronic and progressive disease such as multiple sclerosis (MS), mHealth apps hold promise for enhancing self-management and care. To be used in clinical practice, the validity and usability of mHealth tools should be tested. The most commonly used method for assessing the usability of electronic technologies are questionnaires. Objective: This study aimed to translate and validate the English version of the mHealth App Usability Questionnaire into Italian (ita-MAUQ) in a sample of people with MS. Methods: The 18-item mHealth App Usability Questionnaire was forward- and back-translated from English into Italian by an expert panel, following scientific guidelines for translation and cross-cultural adaptation. The ita-MAUQ (patient version for stand-alone apps) comprises 3 subscales, which are ease of use, interface and satisfaction, and usefulness. After interacting with DIGICOG-MS (Digital Assessment of Cognitive Impairment in Multiple Sclerosis), a novel mHealth app for cognitive self-assessment in MS, people completed the ita-MAUQ and the System Usability Scale, included to test construct validity of the translated questionnaire. Confirmatory factor analysis, internal consistency, test-retest reliability, and construct validity were assessed. Known-groups validity was examined based on disability levels as indicated by the Expanded Disability Status Scale (EDSS) score and gender. Results: In total, 116 people with MS (female n=74; mean age 47.2, SD 14 years; mean EDSS 3.32, SD 1.72) were enrolled. The ita-MAUQ demonstrated acceptable model fit, good internal consistency (Cronbach α=0.92), and moderate test-retest reliability (intraclass coefficient correlation 0.84). Spearman coefficients revealed significant correlations between the ita-MAUQ total score; the ease of use (5 items), interface and satisfaction (7 items), and usefulness subscales; and the System Usability Scale (all P values <.05). Known-group analysis found no difference between people with MS with mild and moderate EDSS (all P values >.05), suggesting that ambulation ability, mainly detected by the EDSS, did not affect the ita-MAUQ scores. Interestingly, a statistical difference between female and male participants concerning the ease of use ita-MAUQ subscale was found (P=.02). Conclusions: The ita-MAUQ demonstrated high reliability and validity and it might be used to evaluate the usability, utility, and acceptability of mHealth apps in people with MS.

Examining the Light Heart Mobile Device App for Assessing Human Pulse Interval and Heart Rate Variability: Validation Study.

BACKGROUND: Pulse interval is a biomarker of psychological and physiological health. Pulse interval can now be assessed using mobile phone apps, which expands researchers' ability to assess pulse interval in the real world. Prior to implementation, measurement accuracy should be established. OBJECTIVE: This investigation evaluated the validity of the Light Heart mobile app to measure pulse interval and pulse rate variability in healthy young adults. METHODS: Validity was assessed by comparing the pulse interval and SD of normal pulse intervals obtained by Light Heart to the gold standard, electrocardiogram (ECG), in 14 young healthy individuals (mean age 24, SD 5 years; n=9, 64% female) in a seated posture. RESULTS: Mean pulse interval (Light Heart: 859, SD 113 ms; ECG: 857, SD 112 ms) demonstrated a strong positive linear correlation (r=0.99; P<.001) and strong agreement (intraclass correlation coefficient=1.00, 95% CI 0.99-1.00) between techniques. The Bland-Altman plot demonstrated good agreement for the mean pulse interval measured with Light Heart and ECG with evidence of fixed bias (-1.56, SD 1.86; 95% CI -5.2 to 2.1 ms), suggesting that Light Heart overestimates pulse interval by a small margin. When Bland-Altman plots were constructed for each participant's beat-by-beat pulse interval data, all participants demonstrated strong agreement between Light Heart and ECG with no evidence of fixed bias between measures. Heart rate variability, assessed by SD of normal pulse intervals, demonstrated strong agreement between techniques (Light Heart: mean 73, SD 23 ms; ECG: mean 73, SD 22 ms; r=0.99; P<.001; intraclass correlation coefficient=0.99, 95% CI 0.97-1.00). CONCLUSIONS: This study provides evidence to suggest that the Light Heart mobile app provides valid measures of pulse interval and heart rate variability in healthy young adults.

Development of an mHealth App by Experts for Queer Individuals' Sexual-Reproductive Health Care Services and Needs: Nominal Group Technique Study.

BACKGROUND: Queer individuals continue to be marginalized in South Africa; they experience various health care challenges (eg, stigma, discrimination, prejudice, harassment, and humiliation), mental health issues (eg, suicide and depression), and an increased spread of HIV or AIDS and sexually transmitted illnesses (STIs; chlamydia, gonorrhea, and syphilis). Mobile health (mHealth) apps have the potential to resolve the health care deficits experienced by health care providers when managing queer individuals and by queer individuals when accessing sexual-reproductive health care services and needs, thus ensuring inclusivity and the promotion of health and well-being. Studies have proven that the nominal group technique (NGT) could be used to solve different social and health problems and develop innovative solutions. This technique ensures that different voices are represented during decision-making processes and leads to robust results. OBJECTIVE: This study aims to identify important contents to include in the development of an mHealth app for addressing the sexual-reproductive health care services and needs of queer individuals. METHODS: We invited a group of 13 experts from different fields, such as researchers, queer activists, sexual and reproductive health experts, private practicing health care providers, innovators, and private health care stakeholders, to take part in a face-to-face NGT. The NGT was conducted in the form of a workshop with 1 moderator, 2 research assistants, and 1 principal investigator. The workshop lasted approximately 2 hours 46 minutes and 55 seconds. We followed and applied 5 NGT steps in the workshop for experts to reach consensus. The main question that experts were expected to answer was as follows: Which content should be included in the mHealth app for addressing sexual-reproductive health care services and needs for queer individuals? This question was guided by user demographics and background, health education and information, privacy and security, accessibility and inclusivity, functionality and menu options, personalization and user engagement, service integration and partnerships, feedback and improvement, cultural sensitivity and ethical considerations, legal and regulatory compliance, and connectivity and data use. RESULTS: Overall, experts voted and ranked the following main icons: menu options (66 points), privacy and security (39 points), user engagement (27 points), information hub (26 points), user demographics (20 points), connectivity (16 points), service integration and partnerships (10 points), functionalities (10 points), and accessibility and inclusivity (7 points). CONCLUSIONS: Conducting an NGT with experts from different fields, possessing vast skill sets, knowledge, and expertise, enabled us to obtain targeted data on the development of an mHealth app to address sexual-reproductive health care services and needs for queer individuals. This approach emphasized the usefulness of a multidisciplinary perspective to inform the development of our mHealth app and demonstrated the future need for continuity in using this approach for other digital health care innovations and interventions.

mHealth app features that facilitate adolescent use for lifestyle management, and are endorsed by caregivers and health care providers.

Background: Mobile health (mHealth) apps are becoming a promising tool to motivate sustainable lifestyle and behavior changes, including modifications to diet and exercise. However, most current mHealth apps do not have meaningful, and sustained user acceptance, particularly, among adolescents. They perceive mHealth apps designed for adults to be tedious and visually unexciting, which discourage adolescent usage. Researchers and adolescent mHealth app developers would benefit from a foundational understanding of which functions and features adolescents feel would most motivate app use. Capturing caregivers' and health care providers' inputs are also important as both groups play an integral role in adolescent health care decision-making. The purpose of the study is to explore and analyze mHealth app features identified by adolescents, caregivers, and health care providers that have the potential to inspire continued use, thereby resulting in sustained health behavior changes in adolescents. Methods: We used inductive thematic analysis of qualitative data obtained from semi-structured focus groups conducted via Zoom©. Important features of mHealth apps that encourage adoption and continued use were explored with 25 participants, including adolescents, their caregivers, and health care providers. Results: Common features facilitating continual usage of mHealth apps that were identified as significant by participating adolescents, their caregivers and health care providers were: look and feel of the app, customization, educational information/recommendations, and integration with electronic health record. Features such as gamification and social interaction that are usually lacking in current adolescent mHealth apps were well recognized as meaningful for motivational purposes. Conclusions: The findings suggest that adolescents and caregivers identify an app as valuable when it is user-friendly and intuitive and appreciate features that are motivating and can engage users in positive behaviors. Health care providers prefer mHealth apps that are user-friendly and can be effectively integrated into the cycle of care, thereby enabling delivery of efficient and value-based health care. Thus, mHealth app designs that are informed by health care providers' clinical experience and needs, in combination with app features that are desired and supported by both adolescents and their caregivers, have the potential to motivate widespread adoption and long-term use, which could result in improved health behaviors and outcomes among adolescents.

Health service requirements of mHealth app users: evidence from Hangzhou, China.

PURPOSE: China's healthcare system is being burdened by the increasing prevalence of chronic diseases. Therefore, this study investigated the health service requirements of mobile health applications (mHealth apps) users in Hangzhou, China. This study aimed to propose suggestions and theoretical references to improve mHealth apps and promote their development, thereby meeting public medical and health needs and creating an efficient medical service system. DESIGN/METHODOLOGY/APPROACH: We constructed a model of health service demands using a literature review, network survey, and semi-structured interviews. We analyzed the demand attributes using the Kano model and Better-Worse index and obtained the priority ranking of demands. FINDINGS: The results revealed 25 demand elements in four dimensions: must-be (M), one-dimensional (O), attractive (A), and indifferent (I) requirements. The findings suggest that mHealth app developers can optimize health services by categorizing and managing health services, focusing on middle-aged users, enhancing the professionalism of health service providers, and improving the feedback mechanism. ORIGINALITY/VALUE: Studies on mHealth apps user demands, particularly on health service needs, remain scarce. This study employed a mixed-methods approach, integrating both qualitative and quantitative research techniques, to establish a priority ranking of user health service needs for mHealth apps. The study offers recommendations and theoretical references to optimize and improve mHealth app services. HIGHLIGHTS: Construct a better health service requirements model for mHealth app users.Obtain the prioritization of demand elements in the model.Propose some management suggestions to improve mHealth apps.

Characteristics of mHealth therapy app engagement by young adults with OUD.

While rates of opioid use disorder (OUD) continue to rise across the country, young adults with OUD are at particular risk as they have poorer treatment outcomes and lack developmentally appropriate treatment options. The introduction of mobile applications for OUD present a new avenue to improve treatment outcomes for young adults. One such app, reSET® provides app users with weekly cognitive behavioral therapy lessons focusing on addiction with built in contingency management for completion of lessons and negative urine drug screens. This exploratory study aimed to identify the characteristics of patients who engaged with the application, reSET®, as well as to describe potential differences in treatment outcomes between engagers and non-engagers. This observational cohort study analyzed clinical and other program data from 35 young adults between the ages of 20-28 that were involved in the care and prescribed medications for OUD in Baltimore, Maryland during the 12-week period of app prescription. Results indicated that young adults had dichotomous levels of engagement, with almost 30% engaging highly with the app, completing >90% of lessons, and approximately 70% having low engagement, completing <25% of lessons. There were no differences in mental health outcomes, but engagers were more likely to be retained in care at the end of the 12-week prescription as compared to non-engagers. Overall, results suggest that mHealth apps targeted for OUD treatment offer potential treatment benefits for young adults, especially regarding treatment retention. Future studies should investigate the treatment and mental health impacts of reSET® and other mHealth apps within this population.

Mobile Health App (DIGICOG-MS) for Self-Assessment of Cognitive Impairment in People With Multiple Sclerosis: Instrument Validation and Usability Study.

BACKGROUND: Mobile health (mHealth) apps have proven useful for people with multiple sclerosis (MS). Thus, easy-to-use digital solutions are now strongly required to assess and monitor cognitive impairment, one of the most disturbing symptoms in MS that is experienced by almost 43% to 70% of people with MS. Therefore, we developed DIGICOG-MS (Digital assessment of Cognitive Impairment in Multiple Sclerosis), a smartphone- and tablet-based mHealth app to self-assess cognitive impairment in MS. OBJECTIVE: This study aimed to test the validity and usability of the novel mHealth app with a sample of people with MS. METHODS: DIGICOG-MS includes 4 digital tests assumed to evaluate the most affected cognitive domains in MS (visuospatial memory [VSM], verbal memory [VM], semantic fluency [SF], and information processing speed [IPS]) and inspired by traditional paper-based tests that assess the same cognitive functions (10/36 Spatial Recall Test, Rey Auditory Verbal Learning Test, Word List Generation, Symbol Digit Modalities Test). Participants were asked to complete both digital and traditional assessments in 2 separate sessions. Convergent validity was analyzed using the Pearson correlation coefficient to determine the strength of the associations between digital and traditional tests. To test the app's reliability, the agreement between 2 repeated measurements was assessed using intraclass correlation coefficients (ICCs). Usability of DIGICOG-MS was evaluated using the System Usability Scale (SUS) and mHealth App Usability Questionnaire (MAUQ) administered at the conclusion of the digital session. RESULTS: The final sample consisted of 92 people with MS (60 women) followed as outpatients at the Italian Multiple Sclerosis Society (AISM) Rehabilitation Service of Genoa (Italy). They had a mean age of 51.38 (SD 11.36) years, education duration of 13.07 (SD 2.74) years, disease duration of 12.91 (SD 9.51) years, and a disability level (Expanded Disability Status Scale) of 3.58 (SD 1.75). Relapsing-remitting MS was most common (68/92, 74%), followed by secondary progressive (15/92, 16%) and primary progressive (9/92, 10%) courses. Pearson correlation analyses indicated significantly strong correlations for VSM, VM, SF, and IPS (all P<.001), with r values ranging from 0.58 to 0.78 for all cognitive domains. Test-retest reliability of the mHealth app was excellent (ICCs>0.90) for VM and IPS and good for VSM and SF (ICCs>0.80). Moreover, the SUS score averaged 84.5 (SD 13.34), and the mean total MAUQ score was 104.02 (SD 17.69), suggesting that DIGICOG-MS was highly usable and well appreciated. CONCLUSIONS: The DIGICOG-MS tests were strongly correlated with traditional paper-based evaluations. Furthermore, people with MS positively evaluated DIGICOG-MS, finding it highly usable. Since cognitive impairment poses major limitations for people with MS, these findings open new paths to deploy digital cognitive tests for MS and further support the use of a novel mHealth app for cognitive self-assessment by people with MS in clinical practice.

Effectiveness of mHealth apps on adherence and symptoms to oral anticancer medications: a systematic review and meta-analysis.

PURPOSE: Despite the rapid expansion of mHealth apps, their adoption has not always been based on evidence of effectiveness on patient outcomes. This systematic review aimed to determine the effect of mHealth apps on adherence and symptom to oral anticancer medications (OAMs) and identify the app design that led to such effects. METHODS: Pubmed, Cochrane Central, PsycINFO, EMBASE, and WoS were searched from inception to April 2023. Randomised controlled trials (RCTs) that evaluated effects of mHealth apps on primary outcomes OAM adherence and symptom burden were included. Two reviewers independently assessed risk-of-bias using Cochrane Risk-of-Bias version 2 and extracted the data. Quality of evidence was assessed using GRADE. The protocol was registered in PROSPERO (CRD42023406024). RESULTS: Four RCTs involving 806 patients with cancer met the eligibility criteria. mHealth apps features included a combinations of symptom reporting, medication reminder, automated alert to care team, OAM and side effect information, one study implemented structured follow-up by a nurse. The intervention group showed no significant difference in OAM adherence (relative ratio 1.20; 95% CI 1.00 to 1.43), but significantly improved symptoms to OAMs with a lower standardised mean symptom burden score of 0.49 (SMD - 0.49; 95% CI - 0.93 to - 0.06), and a 25% lower risk of grade 3 or 4 toxicity (risk ratio 0.75; 95% CI 0.58 to 0.95) compared to usual care. CONCLUSION: These findings suggest a potential role for mHealth app in managing OAM side effect. Further research should explore the role of AI-guided algorithmic pathways on the interactive features of mHealth apps.

User-centered development of an mHealth app for cardiovascular prevention.

Background: Mobile health (mHealth) apps can be used for cardiovascular disease (CVD) prevention. User-centered design, evidence-based content and user testing can be applied to ensure a high level of usability and adequate app access. Objective: To develop and evaluate an mHealth app (HerzFit) for CVD prevention. Methods: HerzFit´s development included a user-centered design approach and guideline-based content creation based on the identified requirements of the target group. Beta testing and a preliminary usability evaluation of the HerzFit prototype were performed. For evaluation, German versions of the System Usability Scale (SUS) and the mHealth App Usability Questionnaire (GER-MAUQ) as well as free text feedback were applied. Results: User-centered design thinking led to the definition of four personas. Based on their requirements, HerzFit enables users to individually assess, monitor, and optimize their cardiovascular risk profile. Users are also provided with a variety of evidence-based information on CVD and their risk factors. The user interface and system design followed the identified functional requirements. Beta-testers provided feedback on the structure and functionality and rated the usability of HerzFit´s prototype as slightly above average both in SUS and GER-MAUQ rating. Participants positively noted the variety of functions and information presented in HerzFit, while negative feedback mostly concerned wearable synchronization. Conclusions: The present study demonstrates the user-centered development of a guideline-based mHealth app for CVD prevention. Beta-testing and a preliminary usability study were used to further improve the HerzFit app until its official release.

Exploring mHealth design opportunities for blind and visually impaired older users.

Background: Mobile health (mHealth) applications (apps) are crucial in delivering health information and services to older adults. Despite their importance, blind and visually impaired (BVI) older individuals often face significant challenges in app accessibility and usability. This study delves into the design preferences and expectations of BVI older users and underscores the necessity of user-centered design for inclusive mHealth apps. Methods: Conducted in September 2023, the study comprised six focus group interviews. Each session involved two to four participants who began with self-introductions, followed by discussions centered on three open-ended interview questions. Results: The study involved 14 participants: four with severe low vision and 10 totally blind. The primary design principles highlighted were "customizability" and "simplicity". The participants stressed the importance of intuitively designed main pages aligning with user patterns. Further, the participants articulated the following mHealth app feature or menu recommendations: editable profiles, emergency contact access, adaptable data presentation, data exportation, audible color details, customizable colors for varying visual needs, audible error feedback, feasible data input methods, toolbars, and habit-establishing reminders. Discussions also touched on the vital role of clear health data visualizations and comprehensible app-based health information. Conclusions: The findings illuminate paths for software developers and health scientists working towards more inclusive mHealth solutions. It is essential during the development phase to prioritize app learnability to accommodate a broad range of users, ensuring that even those with disabilities can effectively use technological innovations to address health disparities.

Stimulating Preconception Care Uptake by Women With a Vulnerable Health Status Through a Mobile Health App (Pregnant Faster): Pilot Feasibility Study.

BACKGROUND: A low socioeconomic status is associated with a vulnerable health status (VHS) through the accumulation of health-related risk factors, such as poor lifestyle behaviors (eg, inadequate nutrition, chronic stress, and impaired health literacy). For pregnant women, a VHS translates into a high incidence of adverse pregnancy outcomes and therefore pregnancy-related inequity. We hypothesize that stimulating adequate pregnancy preparation, targeting lifestyle behaviors and preconception care (PCC) uptake, can reduce these inequities and improve the pregnancy outcomes of women with a VHS. A nudge is a behavioral intervention aimed at making healthy choices easier and more attractive and may therefore be a feasible way to stimulate engagement in pregnancy preparation and PCC uptake, especially in women with a VHS. To support adequate pregnancy preparation, we designed a mobile health (mHealth) app, Pregnant Faster, that fits the preferences of women with a VHS and uses nudging to encourage PCC consultation visits and engagement in education on healthy lifestyle behaviors. OBJECTIVE: This study aimed to test the feasibility of Pregnant Faster by determining usability and user satisfaction, the number of visited PCC consultations, and the course of practical study conduction. METHODS: Women aged 18-45 years, with low-to-intermediate educational attainment, who were trying to become pregnant within 12 months were included in this open cohort. Recruitment took place through social media, health care professionals, and distribution of flyers and posters from September 2021 until June 2022. Participants used Pregnant Faster daily for 4 weeks, earning coins by reading blogs on pregnancy preparation, filling out a daily questionnaire on healthy lifestyle choices, and registering for a PCC consultation with a midwife. Earned coins could be spent on rewards, such as fruit, mascara, and baby products. Evaluation took place through the mHealth App Usability Questionnaire (MAUQ), an additional interview or questionnaire, and assessment of overall study conduction. RESULTS: Due to limited inclusions, the inclusion criterion "living in a deprived neighborhood" was dropped. This resulted in the inclusion of 47 women, of whom 39 (83%) completed the intervention. In total, 16 (41%) of 39 participants visited a PCC consultation, with their main motivation being obtaining personalized information. The majority of participants agreed with 16 (88.9%) of 18 statements of the MAUQ, indicating high user satisfaction. The mean rating was 7.7 (SD 1.0) out of 10. Points of improvement included recruitment of the target group, simplification of the log-in system, and automation of manual tasks. CONCLUSIONS: Nudging women through Pregnant Faster to stimulate pregnancy preparation and PCC uptake has proven feasible, but the inclusion criteria must be revised. A substantial number of PCC consultations were conducted, and this study will therefore be continued with an open cohort of 400 women, aiming to establish the (cost-)effectiveness of an updated version, named Pregnant Faster 2. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/45293.

Problems and Barriers Related to the Use of mHealth Apps From the Perspective of Patients: Focus Group and Interview Study.

BACKGROUND: Since fall 2020, mobile health (mHealth) apps have become an integral part of the German health care system. The belief that mHealth apps have the potential to make the health care system more efficient, close gaps in care, and improve the economic outcomes related to health is unwavering and already partially confirmed. Nevertheless, problems and barriers in the context of mHealth apps usually remain unconsidered. OBJECTIVE: The focus groups and interviews conducted in this study aim to shed light on problems and barriers in the context of mHealth apps from the perspective of patients. METHODS: Guided focus groups and individual interviews were conducted with patients with a disease for which an approved mHealth app was available at the time of the interviews. Participants were recruited via self-help groups. The interviews were recorded, transcribed, and subjected to a qualitative content analysis. The content analysis was based on 10 problem categories ("validity," "usability," "technology," "use and adherence," "data privacy and security," "patient-physician relationship," "knowledge and skills," "individuality," "implementation," and "costs") identified in a previously conducted scoping review. Participants were asked to fill out an additional questionnaire about their sociodemographic data and about their use of technology. RESULTS: A total of 38 patients were interviewed in 5 focus groups (3 onsite and 2 web-based) and 5 individual web-based interviews. The additional questionnaire was completed by 32 of the participants. Patients presented with a variety of different diseases, such as arthrosis, tinnitus, depression, or lung cancer. Overall, 16% (5/32) of the participants had already been prescribed an app. During the interviews, all 10 problem categories were discussed and considered important by patients. A myriad of problem manifestations could be identified for each category. This study shows that there are relevant problems and barriers in the context of mHealth apps from the perspective of patients, which warrant further attention. CONCLUSIONS: There are essentially 3 different areas of problems in the context of mHealth apps that could be addressed to improve care: quality of the respective mHealth app, its integration into health care, and the expandable digital literacy of patients.

Factors associated with usability of the EMPOWER-SUSTAIN Self-management mobile app© among individuals with cardiovascular risk factors in primary care.

Objective: This study aimed to determine the usability of the EMPOWER-SUSTAIN Self-Management Mobile App© and evaluate the factors associated with its usability among patients with cardiovascular risk factors in primary care. Methodology: This was a cross-sectional study, conducted among patients aged ≥ 18 years with cardiovascular risk factors attending a university primary care clinic. Patients were given the app to use for at least three months. Those who fulfilled the eligibility criteria were recruited. Data gathered were on sociodemographic, clinical characteristics, self-management support by doctors, utilisation of the app at home and social support in using the app. The previously translated and validated Malay version of the mHealth App Usability Questionnaire was used to measure usability. The mean usability score was calculated and linear regressions analysis was conducted to determine the factors associated with the usability of the app. Results: A total of 247 patients with at least one cardiovascular risk factor(s) were recruited. The mean age was 60.2 (±8.2). The majority were Malays (86.2%) and half of them were males (52.2%). The total mean (±SD) usability score was 5.26 (±0.67) indicating a high usability of the app. Usability of the app declined with increasing age in the simple linear regressions analysis. The multiple linear regressions yielded that being Malay (b = 0.31, 95% CI 0.08,0.54), using the app at home to understand their medications (b = 0.33, 95% CI 0.12,0.53) and having social support from family members and friends (b = 0.28, 95% CI 0.07,0.49) were significantly associated with higher usability of the app. Conclusion: The usability of the EMPOWER-SUSTAIN Self-Management Mobile App© was high among patients with cardiovascular risk factors in our primary care clinic. This finding supports the widespread use of this app among our patients. Involvement of family members and friends should be encouraged to improve the usability of the app.

App-Based Lifestyle Intervention (PINK! Coach) in Breast Cancer Patients-A Real-World-Data Analysis.

INTRODUCTION: Overweight and a lack of physical activity not only increase the risk of recurrence in breast cancer patients but also negatively impact overall and long-term survival, as well as quality of life. The results presented here are the first real-world data from the DiGA PINK! Coach examining the physical activity and BMI of app users. Based on the literature, an approximate weight gain of 10% over 6 months and a decrease in physical activity can be expected. The purpose of this study is to retrospectively investigate the effects of the PINK! Coach in a real-world setting on patients' BMI and physical activity level during acute therapies. such as chemotherapy (CHT) and antihormone therapy (AHT). MATERIAL AND METHODS: The PINK! Coach app accompanies breast cancer patients during and after acute therapy to bring about a sustainable lifestyle change. The patients are encouraged to establish a healthy diet, become physically active, and make informed decisions. In this study, real-world data from the app were analyzed over 6 months from baseline to T1 (after 12 weeks) and T2 (after 24 weeks). The patients were under acute therapy or in follow-up care receiving either CHT or AHT. RESULTS: The analyzed data indicate that all patients were able to maintain a consistent BMI over 6 months independent of pre-defined subgroups such as AHT, CHT, or BMI subgroups. In the subgroup of patients undergoing AHT, overweight patients were even able to significantly reduce their BMI by 1-score-point over 6 months (p < 0.01). The subgroup of patients undergoing CHT also showed an significant overall reduction in BMI (p = 0.01). All patients were also able to significantly increase their daily step count as well as their physical activity minutes per day. After the first 12 weeks, 41.4% of patients experienced weight gain, 33.4% were able to maintain their weight, and 24.2% reduced their weight. CONCLUSION: The presented data provides intriguing insights into the users of the PINK! Coach app and the impact of this usage in regards to BMI and physical activity. At the current time, there are only a few effective concepts for encouraging all breast cancer patients to engage in moderate physical activity and reduce body weight. Often, these concepts apply to selected patient groups. The data presented here include all age groups, tumor stages, and therapies, providing an initial insight into a comprehensive approach. Data over an even longer period would be one way to better contextualize the results in current research.

mHealth App to improve medication adherence among older adult stroke survivors: Development and usability study.

Background: Effective medication adherence is vital for older adult stroke survivors, yet 20-33% cease treatment within a year post-discharge, increasing risks of recurrent strokes and mortality. A mobile health (mHealth) app could be a novel tool to improve medication adherence among stroke survivors because of its potential to increase patient empowerment. A few stroke-related apps provide information and support to stroke survivors. However, none have focused on medication adherence and documented their development and evaluation process, particularly those focused on this older population. Objective: This study aims to design and develop a smartphone app called OASapp to improve medication adherence among older adult stroke survivors and evaluate its usability. Methods: OASapp was developed in a three-phase development process. Phase 1 is the exploration phase (including a cross-sectional survey, a systematic review, a search for stroke apps on the app stores of Apple App Store and Google Play Store, and a nominal group technique). In phase 2, a prototype was designed based on the Health Belief Model and Technology Acceptance Model. In phase 3, Alpha and Beta testing was conducted to validate the app. Results: Twenty-five features for inclusion in the app were collected in round one, and 14 features remained and were ranked by the participants during nominal group technique. OASapp included five core components (medication management, risk factor management, health information, communication, and stroke map). Users of OASapp were satisfied based on reports from Alpha and Beta testing. The mean Usability Metric for User Experience (UMUX) score was 71.4 points (SD 14.6 points). Conclusion: OASapp was successfully developed using comprehensive, robust, and theory-based methods and was found to be highly accepted by users. Further research is needed to establish the clinical efficacy of the app so that it can be utilized to improve clinically relevant outcomes.

The use of mHealth apps to improve hospital nurses' mental health and well-being: A systematic review.

BACKGROUND: Nursing well-being has become a heightened focus since the COVID-19 pandemic. Nurses are leaving the profession early in their careers or retiring sooner than expected. Those who remain in the workforce report higher levels of burnout, anxiety, depression, and exhaustion. There is concern that there may be a shortage of at least half a million nurses by 2030. AIMS: This systematic review aimed to investigate the evidence of using a mental health promotion mHealth app to improve the mental health of hospital nurses. METHODS: A systematic search was conducted in CINAHL Plus with Full Text, MEDLINE with Full Text, Professional Development Collection, Psychology and Behavioral Sciences Collection, Sociological Collection, PsycInfo, Embase, and PubMed with search dates of January 2012-November 15, 2022. The mHealth intervention needed to be asynchronously delivered through a smartphone with hospital nurse participants to be included in this review. RESULTS: Of the 157 articles screened for this review, six were included. Primary outcome variables were anxiety, burnout, coping, depression, self-efficacy, stress, well-being, and work engagement. Intervention types included mindfulness-based interventions (MBIs), cognitive behavioral therapy (CBT), stress inoculation therapy (SIT), psychoeducation, and stress management. Anxiety, depression, well-being, and burnout improved with MBIs; depression improved with CBT; and anxiety and active coping improved with SIT. LINKING EVIDENCE TO ACTION: This review demonstrated promising findings in using mHealth apps to improve the mental health of hospital nurses. However, more randomized controlled trials with larger sample sizes may reveal which type of mHealth app and how much exposure to the intervention is more effective in improving specific mental health symptoms. Longitudinal follow-up is also recommended to study sustainability of the mental health improvements.

Weight Loss Using an mHealth App Among Individuals With Obesity in Different Economic Regions of China: Cohort Study.

Background: With the increasing prevalence of obesity, weight loss has become a critical issue in China. Self-managed weight loss through a mobile health (mHealth) app may be a prospective method. However, its practicability in different economic regions of China is unknown. Objective: This study aims to evaluate the effectiveness of self-managed weight loss through an mHealth app among individuals with obesity in different economic regions of China and to demonstrate the feasibility of online self-management for weight loss. Methods: A total of 165,635 Chinese adults who signed up for the mHealth app were included to analyze the body composition characteristics of individuals from different economic regions by χ2 analyses. Furthermore, 2 types of participants with obesity using mHealth monitoring, including 74,611 participants with a BMI ≥24.0 kg/m2 and 22,903 participants with a normal BMI but an excessive percentage of body fat (PBF), were followed for 6 months to explore the weight loss and fat loss effects in different economic regions of China and to find independent predictors associated with weight loss success by 2-tailed Student t test and multivariable logistic regression analysis. Results: There were 32,129 users from low-income regions and 133,506 users from high-income regions. The proportion of users with obesity in low-income regions was higher than in high-income regions, both based on BMI (15,378/32,129, 47.9% vs 59,233/133,506, 44.4%; P<.001) and PBF classification (19,146/32,129, 59.6% vs 72,033/133,506, 54%; P<.001). Follow-up analyses showed that the weight loss effect among participants with overweight or obesity in low-income regions was greater than in high-income regions (mean -4.93, SD 6.41 vs mean -4.71, SD 6.14 kg; P<.001), while there was no significant difference in fat loss (mean -2.06%, SD 3.14% vs mean -2.04%, SD 3.19%; P=.54). In the population with normal-weight obesity, the weight loss (mean -2.42, SD 4.07 vs mean -2.23, SD 4.21 kg; P=.004) and fat loss effects (mean -1.43%, SD 2.73% vs mean -1.27%, SD 2.63%; P<.001) were stronger in high-income regions than in low-income regions. In addition, multivariable logistic regression analyses showed that age, baseline PBF, skeletal muscle rate, and measurement frequency were related to weight loss, whereas gender and baseline body metabolic rate only showed a correlation with weight loss in the population in high-income regions. Conclusions: This study found a high proportion of mHealth app users with obesity in low-income regions. Individuals with overweight and obesity in different economic regions of China experienced significant weight loss and fat loss using an mHealth app. Moreover, individuals in high-income regions paid more attention to body fat and had better fat reduction effects. Therefore, promoting self-monitoring of weight and PBF through an mHealth app could be an important intervention that could be implemented across all regions of China.

mHealth App Usability Questionnaire for Stand-Alone mHealth Apps Used by Health Care Providers: Canadian French Translation, Cross-Cultural Adaptation, and Validation (Part 1).

BACKGROUND: An increasing number of health care professionals are using mobile apps. The mHealth App Usability Questionnaire (MAUQ) was designed to evaluate the usability of mobile health apps by patients and providers. However, this questionnaire is not available in French. OBJECTIVE: This study aims to translate (from English to Canadian French), cross-culturally adapt, and initiate the validation of the original version of MAUQ for stand-alone mobile health apps used by French-speaking health care providers. METHODS: A cross-cultural research study using a well-established method was conducted to translate MAUQ to Canadian French by certified translators and subsequently review it with a translation committee. It was then back translated to English. The back translations were compared with the original by the members of the committee to reach consensus regarding the prefinal version. A pilot test of the prefinal version was conducted with a sample of 49 potential users and 10 experts for content validation. RESULTS: The statements are considered clear, with interrater agreement of 99.14% among potential users and 90% among experts. Of 21 statements, 5 (24%) did not exceed the 80% interrater agreement of the experts regarding clarity. Following the revisions, interrater agreement exceeded 80%. The content validity index of the items varied from 0.90 to 1, and the overall content validity index was 0.981. Individual Fleiss multirater κ of each item was between 0.89 and 1, showing excellent agreement and increasing confidence in the questionnaire's content validity. CONCLUSIONS: This process of translation and cultural adaptation produced a new version of MAUQ that was validated for later use among the Canadian French-speaking population. An upcoming separate study will investigate the psychometric properties of the adapted questionnaire.

The German version of the mHealth App Usability Questionnaire (GER-MAUQ): Translation and validation study in patients with cardiovascular disease.

Objective: In Germany, only a few standardized evaluation tools for assessing the usability of mobile Health apps exist so far. This study aimed to translate and validate the English patient version for standalone apps of the mHealth App Usability Questionnaire (MAUQ) into a German version. Methods: Following scientific guidelines for translation and cross-cultural adaptation, the patient version for standalone apps was forward and back-translated from English into German by an expert panel. In total, 53 participants who were recruited as part of the beta testing process of the recently developed mHealth app HerzFit, answered the questions of the German version of the MAUQ (GER-MAUQ) and the System Usability Scale. Subsequently, a descriptive as well as a psychometric analysis was performed to test validity and reliability. Results: After conducting three cognitive interviews, five items were modified. The values for Cronbach alpha for the entire questionnaire and the three subscales (0.966, 0.814, 0.910, and 0.909) indicate strong internal consistency. The correlation analysis revealed that the scores of the GER-MAUQ, the subscales and the SUS were strongly correlated with each other. The correlation coefficient of the SUS and the GER-MAUQ overall score was r = 0.854, P < 0.001 and the coefficients of the subscales and the SUS were r = 0.642, P < 0.001; r = 0.866, P < 0.001 and r = 0.643, P < 0.001. Conclusions: We have developed a novel German version of the MAUQ and demonstrated it as a reliable and valid measurement tool for assessing the usability of standalone mHealth apps from the patients' perspective. The GER-MAUQ allows a new form of standardized assessment of usability of mHealth apps for patients with cardiovascular disease in Germany. Further research with a larger sample and other samples is recommended.

"Keep It Short and Simple": Perceptions of patients and healthcare professionals on the use of a mobile health app in the care for patients undergoing radical prostatectomy.

Background: Patients undergoing radical prostatectomy for localised prostate cancer generally have good long-term survival rates. However, late recurrences can occur and require lifelong follow-up. Objective: This research aims to investigate different stakeholders' perceptions on the use of mobile health (mHealth) applications for prostate cancer follow-up after radical prostatectomy. Methods: A cross-sectional qualitative study was conducted to explore stakeholders' perceptions of an mHealth application for follow-up after radical prostatectomy. Urologists, nurses, and patients treated with radical prostatectomy were interviewed, and data were transcribed and analysed using thematic analysis according to Qualitative Analysis Guide of Leuven. Recommended features for an ideal mHealth application were grouped according to the Persuasive Systems Design model. Results and Limitations: A total of 30 stakeholders, consisting of nurse specialists (n = 7), urologists (n = 8), and patients (n = 15), were interviewed. Expected benefits and barriers were mentioned and grouped in five overarching themes: healthcare optimisation, disease management, app compliance, legal and organisational requirements, and patient-mHealth interaction. Stakeholders provided a multitude of suggestions for an ideal mHealth app. Yet, not all types of stakeholders were interviewed, and patient selection limited generalisability of findings. Conclusions: Stakeholders indicate that an mHealth app in the care for post-prostatectomy patients can improve patient care and promote disease management but consider app compliance as a major challenge. Patient Summary: We interviewed patients, nurses, and urologists about using an mHealth application for follow-up after radical prostatectomy. The participants agreed that an mHealth app could improve care optimisation and disease management, but some concerns and barriers were expressed. This resulted in a list of recommended features for an ideal app.