Health Apps Research Articles

Application and Challenges of the Technology Acceptance Model in Elderly Healthcare: Insights from ChatGPT

The Technology Acceptance Model (TAM) plays a pivotal role in elderly healthcare, serving as a theoretical framework. This study aimed to identify TAM’s core components, practical applications, challenges arising from its applications, and propose countermeasures in elderly healthcare. This descriptive study was conducted by utilizing OpenAI’s ChatGPT, with an access date of 10 January 2024. The three open-ended questions administered to ChatGPT and its responses were collected and qualitatively evaluated for reliability through previous studies. The core components of TAMs were identified as perceived usefulness, perceived ease of use, attitude toward use, behavioral intention to use, subjective norms, image, and facilitating conditions. TAM’s application areas span various technologies in elderly healthcare, such as telehealth, wearable devices, mobile health apps, and more. Challenges arising from TAM applications include technological literacy barriers, digital divide concerns, privacy and security apprehensions, resistance to change, limited awareness and information, health conditions and cognitive impairment, trust and reliability concerns, a lack of tailored interventions, overcoming age stereotypes, and integration with traditional healthcare. In conclusion, customized interventions are crucial for successful tech acceptance among the elderly population. The findings of this study are expected to enhance understanding of elderly healthcare and technology adoption, with insights gained through natural language processing models like ChatGPT anticipated to provide a fresh perspective.

Examining health apps and wearable use in improving physical and mental well-being across U.S., China, and Singapore

Health apps and wearables are touted to improve physical health and mental well-being. However, it is unclear from existing research the extent to which these health technologies are efficacious in improving physical and mental well-being at a population level, particularly for the underserved groups from the perspective of health equity and social determinants. Also, it is unclear if the relationship between health apps and wearables use and physical and mental well-being differs across individualistic, collectivistic, and a mix of individual–collectivistic cultures. A large-scale online survey was conducted in the U.S. (individualist culture), China (collectivist culture), and Singapore (mix of individual–collectivist culture) using quota sampling after obtaining ethical approval from the Institutional Review Board (IRB-2021-262) of Nanyang Technological University (NTU), Singapore. There was a total of 1004 respondents from the U.S., 1072 from China, and 1017 from Singapore. Data were analyzed using multiple regression and negative binomial regression. The study found that income consistently had the strongest relationship with physical and mental well-being measures in all three countries, while the use of health apps and wearables only had a moderate association with psychological well-being only in the US. Health apps and wearables were associated with the number of times people spent exercising and some mental health outcomes in China and Singapore, but they were only positively associated with psychological well-being in the US. The study emphasizes the importance of considering the social determinants, social–cultural context of the population, and the facilitating conditions for the effective use of digital health technologies. The study suggests that the combined use of both health apps and wearables is most strongly associated with better physical and mental health, though this association is less pronounced when individuals use only apps or wearables.

Exploring the digital divide: results of a survey informing mobile application development.

Mobile health apps risk widening health disparities if they overlook digital inclusion. The digital divide, encompassing access, familiarity, and readiness, poses a significant barrier to medical interventions. Existing literature lacks exploration of the digital divide's contributing factors. Hence, data are needed to comprehend the challenges in developing inclusive health apps. We created a survey to gauge internet and smartphone access, smartphone familiarity, and readiness for using mobile health apps among caregivers of pediatric patients in tertiary care. Open-ended questions solicited feedback and suggestions on mobile health applications. Responses were categorized by similarity and compared. Developed with patient partners, the survey underwent cognitive testing and piloting for accuracy. Data from 209 respondents showed that 23% were affected by the digital divide, mainly due to unfamiliarity with digital skills. Among 49 short text responses about health app concerns, 31 mentioned security and confidentiality, with 7 mentioning the impersonal nature of such apps. Desired features included messaging healthcare providers, scheduling, task reminders, and simplicity. This study underscores a digital divide among caregivers of pediatric patients, with nearly a quarter affected primarily due to a lack of digital comfort. Respondents emphasized user-friendliness and online security for health apps. Future apps should prioritize digital inclusion by addressing the significant barriers and carefully considering patient and family concerns.

Evaluating the Energy Efficiency of Popular US Smartphone Health Care Apps: Comparative Analysis Study Toward Sustainable Health and Nutrition Apps Practices.

The emergence of smartphones has sparked a transformation across multiple fields, with health care being one of the most notable due to the advent of mobile health (mHealth) apps. As mHealth apps have gained popularity, there is a need to understand their energy consumption patterns as an integral part of the evolving landscape of health care technologies. This study aims to identify the key contributors to elevated energy consumption in mHealth apps and suggest methods for their optimization, addressing a significant void in our comprehension of the energy dynamics at play within mHealth apps. Through quantitative comparative analysis of 10 prominent mHealth apps available on Android platforms within the United States, this study examined factors contributing to high energy consumption. The analysis included descriptive statistics, comparative analysis using ANOVA, and regression analysis to examine how certain factors impact energy use and consumption. Observed energy use variances in mHealth apps stemmed from user interactions, features, and underlying technology. Descriptive analysis revealed variability in app energy consumption (150-310 milliwatt-hours), highlighting the influence of user interaction and app complexity. ANOVA verified these findings, indicating the critical role of engagement and functionality. Regression modeling (energy consumption = β₀ + β₁ × notification frequency + β₂ × GPS use + β₃ × app complexity + ε), with statistically significant P values (notification frequency with a P value of .01, GPS use with a P value of .05, and app complexity with a P value of .03), further quantified these bases' effects on energy use. The observed differences in the energy consumption of dietary apps reaffirm the need for a multidisciplinary approach to bring together app developers, end users, and health care experts to foster improved energy conservation practice while achieving a balance between sustainable practice and user experience. More research is needed to better understand how to scale-up consumer engagement to achieve sustainable development goal 12 on responsible consumption and production.

Predictors of physical activity and public safety perception regarding technology adoption for promoting physical activity in Jeddah, Saudi Arabia

BackgroundThis study aims to identify the predictors of levels of physical activity among the residents of Jeddah, Saudi Arabia. Additionally, it seeks to understand the public's safety perception regarding the adoption of technology for promoting physical activity. MethodThis is an analytical cross-sectional study using self-administered web-based survey. A stratified sampling technique was used to select participants from adult population in Jeddah and data collection took place from May 2023 to December 2023. Multivariable logistic regression models were applied to identify predictors of low-intensity (walking steps) and high-intensity physical activities. ResultA total of 462 participated in the study. Gender significantly influenced walking habits, with males more likely to walk than females (AOR = 2.37; 95 % CI: 1.55–3.62; P < 0.001). Smoking status was also a predictor, with smokers more inclined to walk compared to non-smokers (AOR = 2.15; 95 % CI: 1.20–3.82; P = 0.010). High-intensity physical activity strongly correlated with increased walking, especially among those active 3–7 days per week (AOR = 3.03; 95 % CI: 1.91–4.78; P < 0.001). Chronic diseases negatively impacted walking frequency (AOR = 0.57; 95 % CI: 0.34–0.95; P = 0.031). Furthermore, males were likelier to engage in high-intensity activities compared to females (AOR = 1.61; 95 % CI: 1.04–2.50; P = 0.033). Those walking ≥ 10,000 steps weekly were more likely to participate in high-intensity activities (AOR = 3.07; 95 % CI: 1.95–4.82; P < 0.001). Excellent self-rated health was associated with higher participation in such activities (AOR = 2.00; 95 % CI: 1.30–3.06; P = 0.002). Most respondents (84.9 %) felt safe on public walkways, and 78.1 % indicated safety perceptions influenced their walkway use. Technology use was divided, with about half (49.1 %) using apps for tracking physical activity. The majority (90.9 %) supported adding motivational features to the 'Sehhaty' app, and 73.6 % favored financial rewards for walking. However, only 45.5 % believed that public walkways are designed to encourage walking. ConclusionThe study highlights significant predictors of physical activity among general population in Jeddah. The study also revealed the impact of safety perceptions and technology use on physical activity, with strong support for motivational features in health apps. However, there is a need for improved design of public walkways to encourage walking.

Feasibility and Acceptability of a Mobile App-Based TEAM-CBT (Testing Empathy Assessment Methods-Cognitive Behavioral Therapy) Intervention (Feeling Good) for Depression: Secondary Data Analysis.

The Feeling Good App is an automated stand-alone digital mobile mental health tool currently undergoing beta testing with the goal of providing evidence-informed self-help lessons and exercises to help individuals reduce depressive symptoms without guidance from a mental health provider. Users work through intensive basic training (IBT) and ongoing training models that provide education regarding cognitive behavioral therapy principles from a smartphone. The key objective of this study was to perform a nonsponsored third-party academic assessment of an industry-generated data set; this data set focused on the safety, feasibility, and accessibility of a commercial automated digital mobile mental health app that was developed to reduce feelings associated with depression. The Feeling Good App development team created a waitlist cohort crossover design and measured symptoms of depression and anxiety using the Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and an app-specific measure of negative feelings called the 7 Dimension Emotion Slider (7-DES). The waitlist cohort crossover design divided the participants into 2 groups, where 48.6% (141/290) of the participants were given immediate access to the apps, while 51.4% (149/290) were placed on a 2-week waitlist before being given access to the app. Data collected by the Feeling Good App development team were deidentified and provided to the authors of this paper for analysis through a nonsponsored university data use agreement. All quantitative data were analyzed using SPSS Statistics (version 28.0; IBM Corp). Descriptive statistics were calculated for demographic variables. Feasibility and acceptability were descriptively assessed. All participants included in the quantitative data were given access to the Feeling Good App; this study did not include a control group. In terms of safety, there was no statistically significant change in suicidality from preintervention to postintervention time points (t288=0.0; P>.99), and there was a statistically significant decrease in hopelessness from preintervention to postintervention time points (F289=30.16; P<.01). In terms of acceptability, 72.2% (166/230) of the users who started the initial 2-day IBT went on to complete it, while 34.8% (80/230) of the users who started IBT completed the entirety of the apps' 4-week protocol (150/230, 65.22% dropout rate over 4 weeks). This study is the first reported proof-of-concept evaluation of the Feeling Good App in terms of safety, feasibility, and statistical trends within the data set. It demonstrates a feasible and novel approach to industry and academic collaboration in the process of developing a digital mental health technology translated from an existing evidence-informed treatment. The results support the prototype app as safe for a select nonclinical population. The app had acceptable levels of engagement and dropouts throughout the intervention. Those who stay engaged showed reductions in symptom severity of depression warranting further investigation of the app's efficacy.

Efficacy of the Flo App in Improving Health Literacy, Menstrual and General Health, and Well-Being in Women: Pilot Randomized Controlled Trial.

Reproductive health literacy and menstrual health awareness play a crucial role in ensuring the health and well-being of women and people who menstruate. Further, awareness of one's own menstrual cycle patterns and associated symptoms can help individuals identify and manage conditions of the menstrual cycle such as premenstrual syndrome (PMS) and premenstrual dysphoric disorder (PMDD). Digital health products, and specifically menstrual health apps, have the potential to effect positive change due to their scalability and ease of access. The primary aim of this study was to measure the efficacy of a menstrual and reproductive health app, Flo, in improving health literacy and health and well-being outcomes in menstruating individuals with and without PMS and PMDD. Further, we explored the possibility that the use of the Flo app could positively influence feelings around reproductive health management and communication about health, menstrual cycle stigma, unplanned pregnancies, quality of life, work productivity, absenteeism, and body image. We conducted 2 pilot, 3-month, unblinded, 2-armed, remote randomized controlled trials on the effects of using the Flo app in a sample of US-based (1) individuals who track their cycles (n=321) or (2) individuals who track their cycles and are affected by PMS or PMDD (n=117). The findings revealed significant improvements at the end of the study period compared to baseline for our primary outcomes of health literacy (cycle tracking: D̄=1.11; t311=5.73, P<.001; PMS or PMDD: D̄=1.20; t115=3.76, P<.001) and menstrual health awareness (D̄=3.97; t311=7.71, P<.001), health and well-being (D̄=3.44; t311=5.94, P<.001), and PMS or PMDD symptoms burden (D̄=-7.08; t115=-5.44, P<.001). Improvements were also observed for our secondary outcomes of feelings of control and management over health (D̄=1.01; t311=5.08, P<.001), communication about health (D̄=0.93; t311=2.41, P=.002), menstrual cycle stigma (D̄=-0.61; t311=-2.73, P=.007), and fear of unplanned pregnancies (D̄=-0.22; t311=-2.11, P=.04) for those who track their cycles, as well as absenteeism from work and education due to PMS or PMDD (D̄=-1.67; t144=-2.49, P=.01). These pilot randomized controlled trials demonstrate that the use of the Flo app improves menstrual health literacy and awareness, general health and well-being, and PMS or PMDD symptom burden. Considering the widespread use and affordability of the Flo app, these findings show promise for filling important gaps in current health care provisioning such as improving menstrual knowledge and health. OSF Registries osf.io/pcgw7; https://osf.io/pcgw7 ; OSF Registries osf.io/ry8vq; https://osf.io/ry8vq.

Exploring the demand, practicality, and acceptability of a mental health application intervention for students at a South African university

Mobile health (mHealth) interventions for mental health and well-being have increased exponentially in recent years. In this digital era, mHealth interventions are proving to be a useful tool in the promotion of mental health for university students. This mixed-methods study explored the feasibility, practicality, and acceptability of a mental health application (app) designed to address mental health challenges among university students. Overall, a total of 1100 participants completed an online survey, and data were analysed using statistical analytics software. Most of the participants were female (72.73%) within the 18–20 age group (64.64%) and in their first year of study (46.18%). The results show that at least 98.7% of the participants owned a smartphone, 80.8% had access to mobile data, 66.9% used Android software, 20.09% had historically been diagnosed with a mental health challenge, and 26.6% had used an online health app. Sixty-two participants were enrolled across 16 focus group discussions. Qualitative data were analysed using thematic analysis, which revealed four facilitators of app acceptability (exposure to mental health apps, convenience, accessibility, and confidentiality) and three barriers to app acceptability (preference for face-to-face therapy, overreliance on app, and fear of misdiagnosis). The findings suggest that an app that is convenient, accessible, confidential, and nonpathologising can be a feasible and acceptable intervention to address mental health challenges.

BraNet: a mobil application for breast image classification based on deep learning algorithms

Mobile health apps are widely used for breast cancer detection using artificial intelligence algorithms, providing radiologists with second opinions and reducing false diagnoses. This study aims to develop an open-source mobile app named “BraNet” for 2D breast imaging segmentation and classification using deep learning algorithms. During the phase off-line, an SNGAN model was previously trained for synthetic image generation, and subsequently, these images were used to pre-trained SAM and ResNet18 segmentation and classification models. During phase online, the BraNet app was developed using the react native framework, offering a modular deep-learning pipeline for mammography (DM) and ultrasound (US) breast imaging classification. This application operates on a client–server architecture and was implemented in Python for iOS and Android devices. Then, two diagnostic radiologists were given a reading test of 290 total original RoI images to assign the perceived breast tissue type. The reader’s agreement was assessed using the kappa coefficient. The BraNet App Mobil exhibited the highest accuracy in benign and malignant US images (94.7%/93.6%) classification compared to DM during training I (80.9%/76.9%) and training II (73.7/72.3%). The information contrasts with radiological experts’ accuracy, with DM classification being 29%, concerning US 70% for both readers, because they achieved a higher accuracy in US ROI classification than DM images. The kappa value indicates a fair agreement (0.3) for DM images and moderate agreement (0.4) for US images in both readers. It means that not only the amount of data is essential in training deep learning algorithms. Also, it is vital to consider the variety of abnormalities, especially in the mammography data, where several BI-RADS categories are present (microcalcifications, nodules, mass, asymmetry, and dense breasts) and can affect the API accuracy model.Graphical abstract

Diversity, equity and inclusion considerations in mental health apps for young people: protocol for a scoping review

IntroductionAfter COVID-19, a global mental health crisis affects young people, with one in five youth experiencing mental health problems worldwide. Delivering mental health interventions via mobile devices is a promising...

INADEQUATE CARE OF HYPERTENSION AND OTHER NON-COMMUNICABLE DISEASES DURING THE COVID-19 PANDEMIC IN SOUTH AFRICA

Objective: In the setting of an already overburdened healthcare system, South Africa has a high burden of hypertension and other non-communicable diseases (NCDs), and the country experienced a high COVID-19 caseload. The aim of this study was to examine the perceptions and experiences of 1) healthcare professionals (HPs) on the preparedness of health systems to provide NCD care and of NCD management during the COVID-19 pandemic, and 2) people living with NCDs (PLWNCDs) on the care they received for hypertension and other NCDs during the COVID-19 pandemic in South Africa. Design and method: Across the country, we recruited a convenience sample of 1) HPs who worked in healthcare management i.e., public health officials and healthcare workers who provided care and engaged with patients in any healthcare capacity, and 2) PLWNCDs with at least 1 NCD. Questionnaires included quantitative and open-ended follow-up questions. Quantitative analyses were conducted using SPSS. The qualitative open-ended questions were evaluated using content analysis with inductive reasoning. Results: There were 31 HPs and 79 PLWNCDs (59 with hypertension) included in this cross-sectional study. HPs perceived COVID-19 care to be adequate, while NCD care was poor during the pandemic. There were service disruptions including for emergency and specialised NCDs care. Strategies for the care of non-COVID-19 illnesses during the pandemic were absent. This would have serious long-term consequences for PLWNCDs and the healthcare system. Perceptions of inadequate hypertension and other NCD care were reiterated by PLWNCDs; 49% felt they received ’very little’ or no adequate care. 18% had a scheduled appointment cancelled. Additionally, many PLWNCDs (52%) felt anxious, lonely, or frightened during the pandemic and 15% felt their mental health had deteriorated. The utility of digital health in future was positively perceived by both HPs and PLWNCDs and may be able to improve health provision during crises. Conclusions: Policies are required 1) so that NCD care will not be overlooked during future crises and 2) to encourage PLWNCDs to timeously access healthcare services during such periods. Such strategies may incorporate digital health apps to improve care and target the mental healthcare needs of PLWNCDs.

Age Unplugged: A Brief Narrative Review on the Intersection of Digital Tools, Sedentary and Physical Activity Behaviors in Community-Dwelling Older Adults.

This brief narrative review assesses how digital technologies-such as wearables, mobile health apps, and various digital tools such as computers, game consoles, tablets, smartphones, and extended reality systems-can influence sedentary and physical activity behaviors among community-dwelling older adults. Each section highlights the central role of these technologies in promoting active aging through increased motivation, engagement and customized experiences. It underlines the critical importance of functionality, usability and adaptability of devices and confirms the effectiveness of digital interventions in increasing physical activity and reducing sedentary behavior. The sustainable impact of these technologies needs to be further investigated, with a focus on adapting digital health strategies to the specific needs of older people. The research advocates an interdisciplinary approach and points out that such collaborations are essential for the development of accessible, effective and ethical solutions. This perspective emphasizes the potential of digital tools to improve the health and well-being of the aging population and recommends their strategic integration into health promotion and policy making.

Digital Remote Monitoring Using an mHealth Solution for Survivors of Cancer: Protocol for a Pilot Observational Study.

Healthy lifestyle interventions have a positive impact on multiple disease trajectories, including cancer-related outcomes. Specifically, appropriate habitual physical activity, adequate sleep, and a regular wholesome diet are of paramount importance for the wellness and supportive care of survivors of cancer. Mobile health (mHealth) apps have the potential to support novel tailored lifestyle interventions. This observational pilot study aims to assess the feasibility of mHealth multidimensional longitudinal monitoring in survivors of cancer. The primary objective is to test the compliance (user engagement) with the monitoring solution. Secondary objectives include recording clinically relevant subjective and objective measures collected through the digital solution. This is a monocentric pilot study taking place in Bangor, Wales, United Kingdom. We plan to enroll up to 100 adult survivors of cancer not receiving toxic anticancer treatment, who will provide self-reported behavioral data recorded via a dedicated app and validated questionnaires and objective data automatically collected by a paired smartwatch over 16 weeks. The participants will continue with their normal routine surveillance care for their cancer. The primary end point is feasibility (eg, mHealth monitoring acceptability). Composite secondary end points include clinically relevant patient-reported outcome measures (eg, the Edmonton Symptom Assessment System score) and objective physiological measures (eg, step counts). This trial received a favorable ethical review in May 2023 (Integrated Research Application System 301068). This study is part of an array of pilots within a European Union funded project, entitled "GATEKEEPER," conducted at different sites across Europe and covering various chronic diseases. Study accrual is anticipated to commence in January 2024 and continue until June 2024. It is hypothesized that mHealth monitoring will be feasible in survivors of cancer; specifically, at least 50% (50/100) of the participants will engage with the app at least once a week in 8 of the 16 study weeks. In a population with potentially complex clinical needs, this pilot study will test the feasibility of multidimensional remote monitoring of patient-reported outcomes and physiological parameters. Satisfactory compliance with the use of the app and smartwatch, whether confirmed or infirmed through this study, will be propaedeutic to the development of innovative mHealth interventions in survivors of cancer. PRR1-10.2196/52957.

Digital Apps to Improve Mobility in Adults with Neurological Conditions: A Health App-Focused Systematic Review.

The provision of mobility exercises through a smartphone application (app) for people undertaking neurological rehabilitation may improve mobility outcomes. However, it is difficult for clinicians and consumers to select high-quality, appropriate apps. This review aimed to identify (1) which mobile health (mHealth) apps are suitable for prescribing mobility exercises for adults with neurological health conditions, (2) how well these apps incorporate telehealth strategies, and (3) how well these apps rate in terms of quality and capacity for behaviour change. The Australian Apple iTunes Store was systematically searched, by using a search code and manually, for apps suitable for training mobility in neurological rehabilitation. Additional searches were conducted in known app repositories and for web-based apps. Trained reviewers extracted data from the included apps, including population-specific characteristics; quality, by using the Mobile App Rating Scale (MARS); and behaviour change potential, by using the App Behaviour Change Scale (ABACUS). The included apps (n = 18) provided <50 to >10,000 exercises, many incurred a subscription fee (n = 13), and half included telehealth features. App quality was moderate (mean MARS score of 3.2/5 and SD of 0.5), and potential for behaviour change was poor (mean ABACUS score of 5.7/21 and SD of 2.1). A limited number of high-quality apps are available for the prescription of mobility exercises in people with neurological conditions.

Effectiveness of mHealth App-Based Interventions for Increasing Physical Activity and Improving Physical Fitness in Children and Adolescents: Systematic Review and Meta-Analysis.

The COVID-19 pandemic has significantly reduced physical activity (PA) levels and increased sedentary behavior (SB), which can lead to worsening physical fitness (PF). Children and adolescents may benefit from mobile health (mHealth) apps to increase PA and improve PF. However, the effectiveness of mHealth app-based interventions and potential moderators in this population are not yet fully understood. This study aims to review and analyze the effectiveness of mHealth app-based interventions in promoting PA and improving PF and identify potential moderators of the efficacy of mHealth app-based interventions in children and adolescents. We searched for randomized controlled trials (RCTs) published in the PubMed, Web of Science, EBSCO, and Cochrane Library databases until December 25, 2023, to conduct this meta-analysis. We included articles with intervention groups that investigated the effects of mHealth-based apps on PA and PF among children and adolescents. Due to high heterogeneity, a meta-analysis was conducted using a random effects model. The Cochrane Risk of Bias Assessment Tool was used to evaluate the risk of bias. Subgroup analysis and meta-regression analyses were performed to identify potential influences impacting effect sizes. We included 28 RCTs with a total of 5643 participants. In general, the risk of bias of included studies was low. Our findings showed that mHealth app-based interventions significantly increased total PA (TPA; standardized mean difference [SMD] 0.29, 95% CI 0.13-0.45; P<.001), reduced SB (SMD -0.97, 95% CI -1.67 to -0.28; P=.006) and BMI (weighted mean difference -0.31 kg/m2, 95% CI -0.60 to -0.01 kg/m2; P=.12), and improved muscle strength (SMD 1.97, 95% CI 0.09-3.86; P=.04) and agility (SMD -0.35, 95% CI -0.61 to -0.10; P=.006). However, mHealth app-based interventions insignificantly affected moderate to vigorous PA (MVPA; SMD 0.11, 95% CI -0.04 to 0.25; P<.001), waist circumference (weighted mean difference 0.38 cm, 95% CI -1.28 to 2.04 cm; P=.65), muscular power (SMD 0.01, 95% CI -0.08 to 0.10; P=.81), cardiorespiratory fitness (SMD -0.20, 95% CI -0.45 to 0.05; P=.11), muscular endurance (SMD 0.47, 95% CI -0.08 to 1.02; P=.10), and flexibility (SMD 0.09, 95% CI -0.23 to 0.41; P=.58). Subgroup analyses and meta-regression showed that intervention duration was associated with TPA and MVPA, and age and types of intervention was associated with BMI. Our meta-analysis suggests that mHealth app-based interventions may yield small-to-large beneficial effects on TPA, SB, BMI, agility, and muscle strength in children and adolescents. Furthermore, age and intervention duration may correlate with the higher effectiveness of mHealth app-based interventions. However, due to the limited number and quality of included studies, the aforementioned conclusions require validation through additional high-quality research. PROSPERO CRD42023426532; https://tinyurl.com/25jm4kmf.

Evaluation of the Effectiveness of Mobile Health Apps in Improving Public Health Awareness in Indonesia

This study investigates the effectiveness of mobile health apps in enhancing public health awareness in Indonesia through a quantitative analysis. Using 170 participants, data was collected through surveys to assess mobile health app usage patterns and public health awareness levels. Results indicate that frequent use of mobile health apps is positively associated with higher public health awareness scores. Specifically, fitness tracking and nutrition apps were found to be significantly correlated with increased public health awareness. These findings highlight the potential of mobile health apps as tools for disseminating health information and empowering individuals to make informed decisions about their health. The study contributes to understanding the role of mobile technology in promoting public health awareness in Indonesia and underscores the importance of targeted interventions tailored to specific health needs and preferences.

Evaluating the World Health Organization's SkinNTDs App as a Training Tool for Skin Neglected Tropical Diseases in Ghana and Kenya: Cross-Sectional Study.

Neglected tropical diseases (NTDs) affect over 1.5 billion people worldwide, primarily impoverished populations in low- and middle-income countries. Skin NTDs, a significant subgroup, manifest primarily as skin lesions and require extensive diagnosis and treatment resources, including trained personnel and financial backing. The World Health Organization has introduced the SkinNTDs app, a mobile health tool designed to train and be used as a decision support tool for frontline health care workers. As most digital health guidelines prioritize the thorough evaluation of mobile health interventions, it is essential to conduct a rigorous and validated assessment of this app. This study aims to assess the usability and user experience of World Health Organization SkinNTDs app (version 3) as a capacity-building tool and decision-support tool for frontline health care workers. A cross-sectional study was conducted in Ghana and Kenya. Frontline health care workers dealing with skin NTDs were recruited through snowball sampling. They used the SkinNTDs app for at least 5 days before completing a web-based survey containing demographic variables and the user version of the Mobile Application Rating Scale (uMARS), a validated scale for assessing health apps. A smaller group of participants took part in semistructured interviews and one focus group. Quantitative data were analyzed using SPSS with a 95% CI and P≤.05 for statistical significance and qualitative data using ATLAS.ti to identify attributes, cluster themes, and code various dimensions that were explored. Overall, 60 participants participated in the quantitative phase and 17 in the qualitative phase. The SkinNTDs app scored highly on the uMARS questionnaire, with an app quality mean score of 4.02 (SD 0.47) of 5, a subjective quality score of 3.82 (SD 0.61) of 5, and a perceived impact of 4.47 (SD 0.56) of 5. There was no significant association between the app quality mean score and any of the categorical variables examined, according to Pearson correlation analysis; app quality mean score vs age (P=.37), sex (P=.70), type of health worker (P=.35), country (P=.94), work context (P=.17), frequency of dealing with skin NTDs (P=.09), and dermatology experience (P=.63). Qualitative results echoed the quantitative outcomes, highlighting the ease of use, the offline functionality, and the potential utility for frontline health care workers in remote and resource-constrained settings. Areas for improvement were identified, such as enhancing the signs and symptoms section. The SkinNTDs app demonstrates notable usability and user-friendliness. The results indicate that the app could play a crucial role in improving capacity building of frontline health care workers dealing with skin NTDs. It could be improved in the future by including new features such as epidemiological context and direct contact with experts. The possibility of using the app as a diagnostic tool should be considered. RR2-10.2196/39393.

Mixed Method Approach towards Continuous Use of Chatbots in Healthcare Apps: An Integration of Humanizing Experience Theory

The unprecedented adoption of apps has transformed consumer interactions. Chatbots are revolutionizing healthcare apps, but more than their integration is needed to guarantee a seamless user experience. This study advances the technology acceptance model by including anthropomorphic elements that build trust in technology for continuous chatbot use in mobile health apps. It leverages the humanizing experience theory to comprehensively examine the boundary conditions that explain the effects of humanizing digital experiences, such as self-representation and intimacy, on utilitarian and hedonic conversational cues. This research contributes to interactive marketing and mobile commerce by offering insights into user behavior for continued usage of health apps.

Attributes, Quality, and Downloads of Dementia-Related Mobile Apps for Patients With Dementia and Their Caregivers: App Review and Evaluation Study.

The adoption of mobile health (mHealth) apps among older adults (>65 years) is rapidly increasing. However, use of such apps has not been fully effective in supporting people with dementia and their caregivers in their daily lives. This is mainly attributed to the heterogeneous quality of mHealth apps, highlighting the need for improved app quality in the development of dementia-related mHealth apps. The aims of this study were (1) to assess the quality and content of mobile apps for dementia management and (2) to investigate the relationship between app quality and download numbers. We reviewed dementia-related mHealth apps available in the Google Play Store and Apple App Store in Taiwan. The identified mobile apps were stratified according to a random sampling approach and evaluated by five independent reviewers with sufficient training and proficiency in the field of mHealth and the related health care sector. App quality was scored according to the user version of the Mobile Application Rating Scale. A correlation analysis was then performed between the app quality score and number of app downloads. Among the 17 apps that were evaluated, only one was specifically designed to provide dementia-related education. The mean score for the overall app quality was 3.35 (SD 0.56), with the engagement (mean 3.04, SD 0.82) and information (mean 3.14, SD 0.88) sections of the scale receiving the lowest ratings. Our analyses showed clear differences between the top three- and bottom three-rated apps, particularly in the entertainment and interest subsections of the engagement category where the ratings ranged from 1.4 to 5. The top three apps had a common feature in their interface, which included memory, attention, focus, calculation, and speed-training games, whereas the apps that received lower ratings were found to be deficient in providing adequate information. Although there was a correlation between the number of downloads (5000 or more) and app quality (t15=4.087, P<.001), this may not be a significant determinant of the app's perceived impact. The quality of dementia-related mHealth apps is highly variable. In particular, our results show that the top three quality apps performed well in terms of engagement and information, and they all received more than 5000 downloads. The findings of this study are limited due to the small sample size and possibility of disregarding exceptional occurrences. Publicly available expert ratings of mobile apps could help people with dementia and their caregivers choose a quality mHealth app.

Disease-Agnostic Electronic Adherence Aid for Subcutaneous at-Home and Self-Administration Devices-The Lowest Common Denominator Based on a Cross-Indication Survey.

The value of connected devices and health apps with features such as adherence trackers, dosing reminders, and remote communication tools for users and healthcare providers has been assessed to support home-based subcutaneous administration. A comprehensive survey was conducted with 605 participants, including users and caregivers, from eight countries. Medical conditions encompassed ankylosing spondylitis, asthma, cerebral palsy, cluster headaches, Crohn's disease, hemophilia, lupus, migraine, multiple sclerosis, Parkinson's disease, plaque psoriasis, psoriatic arthritis, rheumatoid arthritis, spasticity, spondyloarthritis, and ulcerative colitis. Utilizing a maximum difference scaling methodology, the survey gauged participant preferences regarding specific attributes and features of connected drug delivery devices. Irrespective of demographic factors like age, gender, nationality, or the specific medical condition, the device's ability to verify a successful injection stood out as universally valued. The second and third most valued attributes pertained to temperature-related indicators or warnings. These features do not necessitate the use of a connected device and can be integrated into existing autoinjector platforms. The survey findings support the development of a universal adherence tool for at-home subcutaneous dosing, independent of a specific medical condition. This tool may be gradually improved with disease-specific features. Once established as a platform, manufacturers can launch any subcutaneous medication and later integrate real-world evidence for enhanced educational, treatment, and diagnostic capabilities. This approach is crucial for advancing connected adherence tools in decentralized healthcare, aligning with user and healthcare system needs while translating scientific innovation into practical solutions.