Mobile-health: A review of current state in 2015

The impact of mobile health interventions on service users' health outcomes and the role of health professions: a systematic review of systematic reviews-protocol

BACKGROUND

Mobile health tools have gained prominence in global health care in recent years. Mobile health (mHealth) interventions have demonstrated their impact on managing healthcare service users' health. A pilot search revealed many systematic reviews on the effectiveness of mobile health tools on service users' health outcomes. However, how the role of healthcare professionals in promoting the adoption of mobile health may lead to improved outcomes needs to be clarified. Therefore, this systematic review aims to synthesise existing systematic reviews that examine both the impact of mobile health interventions on service users' outcomes and the role of healthcare professionals in facilitating the adoption of mobile health solutions.

METHODS

Five electronic databases will be searched: EMBASE, CINHAL Plus, MEDLINE, Web of Science, and the Cochrane Library for systematic reviews exploring the impact of mobile health interventions on service users' outcomes and the role of healthcare professionals in facilitating the adoption of mobile health solutions. Systematic reviews published in English dated from January 2015 to June 2024 will be included. Screening and selection of the reviews against inclusion and exclusion criteria will be performed by three independent reviewers, as well as data extraction and quality assessment.

DISCUSSION

Current systematic reviews in mHealth have primarily focused on assessing the effectiveness of mHealth interventions for managing a range of conditions. While these reviews provide valuable input into the outcomes for mHealth, more is needed to know about the impact of the involvement of health professions on service users' outcomes when adopting mHealth. This systematic review of systematic reviews aims to bridge this critical gap in the literature by critically appraising and synthesising the evidence of mHealth interventions' impact on service user outcomes and the level of involvement of health professionals.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD 42023414435.

Effects of mHealth Practice Patterns on Improving Metabolic Syndrome Using the Information-Motivation-Behavioral Skills Model

Chronic diseases contribute to 68% of global mortality, highlighting the importance of early detection and management of conditions such as metabolic syndrome. Effective lifestyle interventions, particularly through mobile health (mHealth), have shown potential in promoting health and reducing cardiometabolic risk. This study utilized mHealth data from public health centers in South Korea, targeting adults with risk factors for metabolic syndrome. The Intervention-Motivation-Behavioral skills (IMB) theoretical model was applied to categorize participants' practice patterns over time using the Group-Based Trend Model (GBTM). And the Generalized Estimating Equations (GEE) methodology was applied to confirm the effective practice patterns for improving metabolic syndrome. Data were collected over 24 weeks. The dataset encompasses life-log data capable of capturing changes in intervention, self-report surveys, and clinical measurements, all linked to personal identification keys and thereby integrated. Participants demonstrated improved health behaviors, with the healthy eating score increasing from 5.0 to 6.4 and physical activity rates rising from 41.5% to 59%. Health risk factors decreased significantly, with the mean number of risk factors dropping from 2.4 to 1.4. The percentage of subjects with three or more metabolic syndrome components decreased from 42.3% in the initial period to 19.2% in the final period. Practice patterns by IMB components were classified into three categories: continuous type, late decline type, and early decline type. Improvements in health behavior and metabolic syndrome were observed in the continuous type of each IMB component. The mHealth interventions were confirmed to be positively associated with improved health behavior and management of metabolic syndrome in the continuous practice patterns of IMB.

Evaluating usability of and satisfaction with mHealth app in rural and remote areas-Germany GIZ collaboration in Bosnia-Herzegovina to optimize type 1 diabetes care

Background

Type 1 diabetes mellitus (T1DM) management in children and adolescents requires intensive supervision and monitoring to prevent acute and late diabetes complications and to improve quality of life. Digital health interventions, in particular diabetes mobile health apps (mHealth apps) can facilitate specialized T1DM care in this population. This study evaluated the initial usability of and satisfaction with the m-Health intervention Diabetes: M app, and the ease of use of various app features in supporting T1DM care in rural and remote areas of Bosnia-Herzegovina with limited access to specialized diabetes care.

Methods

This cross-sectional study, performed in February-March 2023, evaluated T1DM pediatric patients who used the Diabetes: M app in a 3-month mHealth-based T1DM management program, along with their parents and healthcare providers (HCPs). All participants completed self-administered online questionnaires at the end of the 3-month period. Data were analyzed by descriptive statistics.

Results

The study population included 50 T1DM patients (children/parents and adolescents) and nine HCPs. The mean ± SD age of the T1DM patients was 14 ± 4.54 years, with 26 (52%) being female. The mean ± SD age of the HCPs was 43.4 ± 7.76 years; all (100%) were women, with a mean ± SD professional experience of 17.8 ± 8.81 years. The app was reported usable in the domains of ease-of-use and satisfaction by the T1DM children/parents (5.82/7.0), T1DM adolescents/young adults (5.68/7.0), and HCPs (5.22/7.0). Various app features, as well as the overall app experience, were rated positively by the participants.

Conclusion

The results strongly support the usability of mHealth-based interventions in T1DM care, especially in overcoming care shortage and improving diabetes management and communications between HCPs and patients. Further studies are needed to compare the effectiveness of apps used to support T1DM management with routine care.

Global Trends in mHealth and Medical Education Research: Bibliometrics and Knowledge Graph Analysis

Background

Mobile health (mHealth) is an emerging mobile communication and networking technology for health care systems. The integration of mHealth in medical education is growing extremely rapidly, bringing new changes to the field. However, no study has analyzed the publication and research trends occurring in both mHealth and medical education.

Objective

The aim of this study was to summarize the current application and development trends of mHealth in medical education by searching and analyzing published articles related to both mHealth and medical education.

Methods

The literature related to mHealth and medical education published from 2003 to 2023 was searched in the Web of Science core database, and 790 articles were screened according to the search strategy. The HistCite Pro 2.0 tool was used to analyze bibliometric indicators. VOSviewer, Pajek64, and SCImago Graphica software were used to visualize research trends and identify hot spots in the field.

Results

In the past two decades, the number of published papers on mHealth in medical education has gradually increased, from only 3 papers in 2003 to 130 in 2022; this increase became particularly evident in 2007. The global citation score was determined to be 10,600, with an average of 13.42 citations per article. The local citation score was 96. The United States is the country with the most widespread application of mHealth in medical education, and most of the institutions conducting in-depth research in this field are also located in the United States, closely followed by China and the United Kingdom. Based on current trends, global coauthorship and research exchange will likely continue to expand. Among the research journals publishing in this joint field, journals published by JMIR Publications have an absolute advantage. A total of 105 keywords were identified, which were divided into five categories pointing to different research directions.

Conclusions

Under the influence of COVID-19, along with the popularization of smartphones and modern communication technology, the field of combining mHealth and medical education has become a more popular research direction. The concept and application of digital health will be promoted in future developments of medical education.

Testing unit root non-stationarity in the presence of missing data in univariate time series of mobile health studies

The use of digital devices to collect data in mobile health studies introduces a novel application of time series methods, with the constraint of potential data missing at random or missing not at random (MNAR). In time-series analysis, testing for stationarity is an important preliminary step to inform appropriate subsequent analyses. The Dickey-Fuller test evaluates the null hypothesis of unit root non-stationarity, under no missing data. Beyond recommendations under data missing completely at random for complete case analysis or last observation carry forward imputation, researchers have not extended unit root non-stationarity testing to more complex missing data mechanisms. Multiple imputation with chained equations, Kalman smoothing imputation, and linear interpolation have also been used for time-series data, however such methods impose constraints on the autocorrelation structure and impact unit root testing. We propose maximum likelihood estimation and multiple imputation using state space model approaches to adapt the augmented Dickey-Fuller test to a context with missing data. We further develop sensitivity analyses to examine the impact of MNAR data. We evaluate the performance of existing and proposed methods across missing mechanisms in extensive simulations and in their application to a multi-year smartphone study of bipolar patients.

An Infrastructure Framework for Remote Patient Monitoring Interventions and Research

Remote patient monitoring (RPM) enables clinicians to maintain and adjust their patients' plan of care by using remotely gathered data, such as vital signs, to proactively make medical decisions about a patient's care. RPM interventions have been touted as a means to improve patient care and well-being while reducing costs and resource needs within the health care ecosystem. However, multiple interworking components must be successfully implemented for an RPM intervention to yield the desired outcomes, and the design and key driver of each component can vary depending on the medical context. This viewpoint and perspective paper presents a 4-component RPM infrastructure framework based on a synthesis of existing literature and practice related to RPM. Specifically, these components are identified and considered: (1) data collection, (2) data transmission and storage, (3) data analysis, and (4) information presentation. Interaction points to consider between components include transmission, interoperability, accessibility, workflow integration, and transparency. Within each of the 4 components, questions affecting research and practice emerge that can affect the outcomes of RPM interventions. This framework provides a holistic perspective of the technologies involved in RPM interventions and how these core elements interact to provide an appropriate infrastructure for deploying RPM in health systems. Further, it provides a common vocabulary to compare and contrast RPM solutions across health contexts and may stimulate new research and intervention opportunities.

The effectiveness of green heart application to manage modifiable risk factors of coronary artery disease in Tehran Heart Center: Study protocol for a randomized controlled trial

The burden of cardiovascular disease (CVD) is diminishing in developed countries. However, in middle- and low-income countries the CVD death rates are growing. CVD is the most common cause of death and disability in Iran and accounts for nearly half of all mortalities in Iranians. Therefore, preventive strategies by risk factor modification are a top priority in the country. Recently, Mobile-Health (mHealth) technology has been the focus of increasing interest in improving the delivery of cardiovascular prevention, targeting a combination of modifiable risk factors. This parallel-group single-blinded randomized controlled trial study has been designed to evaluate the impact of using a mHealth application on risk factors control. Individuals aged between 25 and 75 years who have documented CVD by coronary angiography in Tehran Heart Center and have at least one uncontrolled risk factor from the three including hypertension, dyslipidemia, and current cigarette smoking will be included. We are going to randomize 1544 patients into two study arms as follows: 1- Intervention: usual care + mHealth 2- Control: usual care + paper-based recommendations and educational materials. After 3 and 6 months of follow-up, the status of risk factors will be determined through outpatient visits and face-to-face interviews for both arms. Outcome: Successful risk factor control will be measured after 3 and 6 months. Nowadays, mHealth is becoming increasingly popular, providing a good opportunity for constant monitoring of risk factors and changing health behavior in a target population. Meanwhile, providing evidence for the effectiveness of health intervention delivery using mobile technologies could help health providers encourage their at-risk population to stop smoking, control blood pressure and blood cholesterol, and participate in regular physical activity. While the burden of CVD is growing in developing countries, this type of intervention can be a cost-effective way to reduce it in these countries.

A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Health

Modern machine learning approaches have led to performant diagnostic models for a variety of health conditions. Several machine learning approaches, such as decision trees and deep neural networks, can, in principle, approximate any function. However, this power can be considered to be both a gift and a curse, as the propensity toward overfitting is magnified when the input data are heterogeneous and high dimensional and the output class is highly nonlinear. This issue can especially plague diagnostic systems that predict behavioral and psychiatric conditions that are diagnosed with subjective criteria. An emerging solution to this issue is crowdsourcing, where crowd workers are paid to annotate complex behavioral features in return for monetary compensation or a gamified experience. These labels can then be used to derive a diagnosis, either directly or by using the labels as inputs to a diagnostic machine learning model. This viewpoint describes existing work in this emerging field and discusses ongoing challenges and opportunities with crowd-powered diagnostic systems, a nascent field of study. With the correct considerations, the addition of crowdsourcing to human-in-the-loop machine learning workflows for the prediction of complex and nuanced health conditions can accelerate screening, diagnostics, and ultimately access to care.

Association of mobile health (mHealth) use with health status and COVID-19-related concerns by people with mobility impairments

PURPOSE

Mobile health (mHealth) technology has increased dramatically in the wake of the pandemic. Less research has focused on people with mobility impairing (PMI) disabilities. This study determined the prevalence of mHealth use among PMI adults during the COVID-19 escalation and examines demographic, health and COVID-19 concerns correlates.

METHODS

PMI adults (N = 304) completed an online survey investigating mHealth use and COVID-19 concerns related to food access in June of 2020. Smartphone and mHealth use were measured with an adapted version of the survey used in the Pew Internet & American Life project. Descriptive and multivariable analyses were conducted to determine associations of demographics, health status, and COVID-19 concerns with mHealth use. About two-thirds (N = 201) of the sample were mHealth users (owned a smartphone and engaged in health-promoting behaviors with the smartphone; e.g., sought online information, tracked health behaviors, used patient portals).

RESULTS

Having hypertension was associated with higher mHealth use, and having higher COVID-19 concerns about food access was associated with higher mHealth use. Those who used mHealth were also more engaged with smartphone apps for communication, services, and entertainment. Only the association between educational attainment and mHealth use remained significant after adjusting for other covariates in multivariable logistic regression models.

DISCUSSION

PMIs continue to need support in the use of mHealth technology to help maximize access to potentially important tools for rehabilitation and health management. There is a need to continue to investigate mHealth and its applications for people with disabilities.Implications for RehabilitationMany people with mobility impairing disabilities may be missing opportunities for mHealth rehabilitation and healthcare.COVID-19 has widened existing gaps in access and use of mHealth technology among people with mobility impairing disabilities.Focused education is needed to help people with disabilities exploit the full range of services of their smartphones to increase access to care, social connectivity, and other important goods and services to enhance rehabilitation and health management.

e-Health Literacy Status of Individuals with Multiple Sclerosis in Turkey

Background: This research aims to compare e-health literacy of technology users and nonusers in people with multiple sclerosis (MS) and to investigate whether there are correlations between age, duration of MS, gender, marital status, and e-health total scores. Methods: This descriptive study was carried out with a web-based questionnaire. The questionnaire was sent to 300 patients with MS who were registered at Istanbul University-Cerrahpasa Medical Faculty Neurology Department. Results: A total of 156 people (mean age: 35.33 ± 10.47 years) participated in the survey. Smartphone 98.1% (n = 153) was the mostly used device. Rate of using Google and recommended websites about MS was 94.25% (n = 145) and 73.9% (n = 113), respectively. e-Health literacy of both the tablet and recommended websites users significantly differed from that of nonusers (p = 0.007 for both). Participants' e-health literacy total score was found to weakly, but significantly, correlate with their age, marital status, and education level (rho: -0.161, p = 0.044; rho: 0.172, p = 0.032; rho: -0.192, p = 0.016, respectively). Conclusions: With developments in digital technologies, it is important to identify the access status of people with MS to improve daily clinical management and implement further motor and cognitive rehabilitation. Therefore, determining the health literacy of individuals with MS and providing education on this subject will reduce the information pollution.

Development of a customized m-Health-based intervention to reduce loss to follow-up among patients undergoing treatment for cervical lesions at a rural referral Hospital, South Western Uganda

Background

Loss to follow-up (LTFU) in individuals undergoing cervical cancer treatment is a major challenge in many low resource settings. We describe development of a customized and tailored mHealth intervention for reducing LTFU among patients undergoing cervical cancer treatment at Mbarara Regional Referral Hospital (MRRH).

Methods

We interviewed all health care providers (HCPs) at the cervical cancer clinic of MRRH, between April and May 2023. Transcripts were subsequently derived, reviewed and coded to generate themes and categories using inductive content analytic approach. Four medical experts used this data to develop relevant SMS content, which was incorporated into an app.

Results

HCPs had owned a phone for 13.8 ≤ years, had worked at the clinic for 5 ≤ years, and used text messages regularly. Qualitative data revealed that the main challenge to re-engagement was absence of a reminder mechanism between HCPs and patients. HCPs preferred text and or audio mode of messaging to improve health care responsiveness to LTFUs, awareness, continuity of care, and health service uptake among the majority illiterate population; though with potential constraints of costs and workload. Identified key messaging content included; the importance of attending scheduled follow-ups, follow up visit date and clinic customization and tailoring the message to the intended recipient. SMS content was uploaded onto the cc-follow-up app platform and customized according to preferred language, day, frequency and time of delivery.

Conclusion

Tailoring an mHealth messaging intervention could help re-engage and reduce LTFU through improved information sharing, awareness, responsiveness, care engagement and medical compliance. A pilot study is required for our intervention in South Western Uganda.

Self-Compassion, Health, and Empowerment: A Pilot Randomized Controlled Trial for Chinese Immigrant Women Experiencing Intimate Partner Violence

Chinese immigrant survivors of men's violence experience both significant mental health impacts from abuse and barriers to formal services. Therefore, we examined the preliminary efficacy of an innovative mobile-based empowerment-based intervention (self-compassion, health, and empowerment; SHE) that specifically focuses on abused Chinese immigrant women in the US. This pilot study used a two-arm randomized controlled design with repeated measures. A convenience sample (N = 50) of Chinese immigrant women who experienced past year intimate partner violence (IPV) were recruited online and randomly assigned to the intervention or control group (25 per group). We assessed IPV exposure, safety behaviors, depressive symptoms, anxiety symptoms, post-traumatic stress disorder (PTSD) symptoms, and self-compassion at baseline, post-intervention, and 8-week follow-up. Of 95 eligible participants, 50 (52.6%) agreed to participate and completed baseline data collection; intervention completion rate was 64%. We found a significant group and time interaction for self-judgment (a self-compassion component), with a significant reduction seen in the intervention group compared to the control group. Despite no other significant group differences observed over time, the intervention group showed consistent trends toward improvements in most outcome measures, including specific types of IPV (i.e., negotiation, psychological aggression, and sexual coercion), depressive and PTSD symptoms, self-compassion, and certain components of self-compassion (i.e., isolation and over-identification) when compared to the control group. Our findings suggest that the SHE intervention shows promise in improving the mental health well-being of Chinese immigrant survivors. However, a fully powered randomized controlled trial is warranted to determine its efficacy. Our intervention has the potential to be translated in the Chinese immigrant populations with the necessary organizational support.

Enhancing Energy Efficiency in Telehealth Internet of Things Systems Through Fog and Cloud Computing Integration: Simulation Study

BACKGROUND

The increasing adoption of telehealth Internet of Things (IoT) devices in health care informatics has led to concerns about energy use and data processing efficiency.

OBJECTIVE

This paper introduces an innovative model that integrates telehealth IoT devices with a fog and cloud computing-based platform, aiming to enhance energy efficiency in telehealth IoT systems.

METHODS

The proposed model incorporates adaptive energy-saving strategies, localized fog nodes, and a hybrid cloud infrastructure. Simulation analyses were conducted to assess the model's effectiveness in reducing energy consumption and enhancing data processing efficiency.

RESULTS

Simulation results demonstrated significant energy savings, with a 2% reduction in energy consumption achieved through adaptive energy-saving strategies. The sample size for the simulation was 10-40, providing statistical robustness to the findings.

CONCLUSIONS

The proposed model successfully addresses energy and data processing challenges in telehealth IoT scenarios. By integrating fog computing for local processing and a hybrid cloud infrastructure, substantial energy savings are achieved. Ongoing research will focus on refining the energy conservation model and exploring additional functional enhancements for broader applicability in health care and industrial contexts.

Evaluation of Patient-Facing Mobile Apps to Support Physiotherapy Care: Systematic Review

BACKGROUND

Mobile health interventions delivered through mobile apps are increasingly used in physiotherapy care. This may be because of the potential of apps to facilitate changes in behavior, which is central to the aims of care delivered by physiotherapists. A benefit of using apps is their ability to incorporate behavior change techniques (BCTs) that can optimize the effectiveness of physiotherapeutic interventions. Research continues to suggest that despite their importance, behavior change strategies are often missing in patient management. Evaluating mobile apps that physiotherapists can use to drive behavior change may inform clinical practice and potentially improve patient outcomes. Examining the quality of apps and exploring their key features that can support behavior change and physiotherapy care are important aspects of such an evaluation.

OBJECTIVE

The primary aim of this study was to describe the range of mobile apps in app stores that are intended for use by patients to support physiotherapy care. The secondary aims were to assess app quality, BCTs, and their behavior change potential.

METHODS

A systematic review of mobile apps in app stores was undertaken. The Apple App Store and Google Play were searched using a 2-step search strategy, using terms relevant to the physiotherapy discipline. Strict inclusion and exclusion criteria were applied: apps had to be intended for use by patients and be self-contained (or stand-alone) without the requirement to be used in conjunction with a partner wearable device or another plugin. Included apps were coded for BCTs using the Behavior Change Technique Taxonomy version 1. App quality was assessed using the Mobile App Rating Scale, and the App Behavior Change Scale was used to assess the app's potential to change behavior.

RESULTS

In total, 1240 apps were screened, and 35 were included. Of these 35 apps, 22 (63%) were available on both the Apple App Store and Google Play platforms. In total, 24 (69%) were general in their focus (eg, not condition-specific), with the remaining 11 (31%) being more specific (eg, knee rehabilitation and pelvic floor training). The mean app quality score (Mobile App Rating Scale) was 3.7 (SD 0.4) of 5 (range 2.8-4.5). The mean number of BCTs identified per app was 8.5 (SD 3.6). BCTs most frequently included in the apps were instruction on how to perform a behavior (n=32), action planning (n=30), and self-monitoring of behavior (n=28). The mean behavior change potential score (App Behavior Change Scale) was 8.5 (SD 3.1) of 21 (range 3-15).

CONCLUSIONS

Mobile apps available to support patient care received from a physiotherapist are of variable quality. Although they contain some BCTs, the potential for behavior change varied widely across apps.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/29047.

Mobile Health Application for Seizure Management: A Human-Systems Integration Approach

OBJECTIVE

The study aims to develop a mHealth application for seizure management based on the human system integration (HSI) approach.

BACKGROUND

Unmet healthcare needs among people with epilepsy continue to exist despite the advancement in healthcare technology. Current seizure management methods are found to be ineffective. Therefore, a more efficient strategy such as mHealth technology is necessary to aid seizure management.

METHOD

The needs identification phase involved identifying the user requirements by interviewing 10 stakeholders and conducting thematic analysis and needs interpretation technique. In the solution identification phase, the system requirements were derived using various human-centered design and systems engineering approaches and were evaluated through quality function deployment to determine design targets. For the design and evaluation phase, the design targets were reflected in the app through the iterative prototyping process, and the interface and functional design were evaluated by seven human factors and ergonomics experts and four stakeholders, respectively.

RESULTS

Three primary needs and ten user requirements were derived from the needs identification phase. Ten out of fifteen system requirements were selected as design targets to be included in the final prototype. Results of the evaluation showed that the interface design of the proposed app showed superior usability compared to a competitor app and that the app functions were beneficial for the stakeholders.

CONCLUSION

The mHealth app designed through the HSI framework showed good potential in addressing the main issues in seizure management.

APPLICATION

The mHealth app design methodology based on the HSI approach can be applied to the design of small-scale systems in various domains.

Development of GO Move: A Website for Children With Unilateral Cerebral Palsy

It is unknown if an online tool is wanted by therapists and parents of individuals with unilateral cerebral palsy (UCP) to support implementation of goal-directed home programs, and if wanted, the recommended features for the tool. The objective was to explore the experiences of therapists and parents who have implemented home programs, seek guidance on translating a paper-based home program toolbox into a mobile website, and develop the website. Qualitative descriptive methodology guided data collection using semi-structured interviews and thematic analysis, validated with field notes and member checking. A team science, iterative approach was used to integrate the themes into the development of the mobile website. Five primary themes including recommendations for the functionality, features, content, and naming of the mobile website were identified. Parents and therapists value home programs. Participants provided recommendations regarding content and features, and the GO Move mobile website was developed based on the recommendations.

A Fully Automated Mini-Mental State Examination Assessment Model Using Computer Algorithms for Cognitive Screening

Background

Rapidly growing healthcare demand associated with global population aging has spurred the development of new digital tools for the assessment of cognitive performance in older adults.

Objective

To develop a fully automated Mini-Mental State Examination (MMSE) assessment model and validate the model's rating consistency.

Methods

The Automated Assessment Model for MMSE (AAM-MMSE) was an about 10-min computerized cognitive screening tool containing the same questions as the traditional paper-based Chinese MMSE. The validity of the AAM-MMSE was assessed in term of the consistency between the AAM-MMSE rating and physician rating.

Results

A total of 427 participants were recruited for this study. The average age of these participants was 60.6 years old (ranging from 19 to 104 years old). According to the intraclass correlation coefficient (ICC), the interrater reliability between physicians and the AAM-MMSE for the full MMSE scale AAM-MMSE was high [ICC (2,1)=0.952; with its 95% CI of (0.883,0.974)]. According to the weighted kappa coefficients results the interrater agreement level for audio-related items showed high, but for items "Reading and obey", "Three-stage command", and "Writing complete sentence" were slight to fair. The AAM-MMSE rating accuracy was 87%. A Bland-Altman plot showed that the bias between the two total scores was 1.48 points with the upper and lower limits of agreement equal to 6.23 points and -3.26 points.

Conclusions

Our work offers a promising fully automated MMSE assessment system for cognitive screening with pretty good accuracy.

Heuristics used for evaluating the usability of mobile health applications: A systematic literature review

Objective

Mobile health applications hold immense potential for enhancing health outcomes. Usability is one of the main factors for the adoption and use of mobile health applications. However, despite the growing importance of mHealth applications, clear standards for their evaluation remain elusive. The present study aimed to determine heuristics for the usability evaluation of health-related applications.

Methods

We systematically searched multiple databases for relevant papers published between January 2008 and April 2021. Articles were reviewed, and data were extracted and categorized from those meeting inclusion criteria by two authors independently. Heuristics were identified based on statements, words, and concepts expressed in the studies. These heuristics were first mapped to Nielsen's heuristics based on their differences or similarities. The remaining heuristics that were very important for mobile applications were categorized into new heuristics.

Results

Seventeen studies met the eligibility criteria. Seventy-nine heuristics were extracted from the papers. After combining the items with the same concepts and removing irrelevant items based on the exclusion criteria, 20 heuristics remained. Common heuristics such as "Visibility of system status" and "Flexibility and efficiency of use" were categorized into 10 previously established heuristics and new heuristics like "Navigation" and "User engagement" were recognized as new ones.

Conclusions

In our study, we have meticulously identified 20 heuristics that hold promise for evaluating and designing mHealth applications. These heuristics can be used by the researchers for the development of robust tools for heuristic evaluation. These tools, when adapted or tailored for health domain applications, have the potential to significantly enhance the quality of mHealth applications. Ultimately, this improvement in quality translates to enhanced patient safety.

Protocol Registration

(10.17605/OSF.IO/PZJ7H).

Preferences in the Willingness to Download an mHealth App: Discrete Choice Experimental Study in Spain, Germany, and the Netherlands

BACKGROUND

Despite the worldwide growth in mobile health (mHealth) tools and the possible benefits for both patients and health care providers, the adoption of mHealth is low, and only a limited number of studies have examined the intention to download mHealth apps.

OBJECTIVE

In this study, we investigated individuals' preferences in the adoption of a health app.

METHODS

We conducted a discrete choice experimental study in 3 countries (Spain: n=800, Germany: n=800, and the Netherlands: n=416) with 4 different attributes and levels (ie, price: €1.99 vs €4.99 [a currency exchange rate of €1=US $1.09 is applicable] vs for free, data protection: data protection vs no information, recommendation: patients' association vs doctors, and manufacturer: medical association vs pharmaceutical company). Participants were randomly assigned. For the analyses, we used the conditional logistic model separately for each country.

RESULTS

The results showed that price and data protection were considered important factors that significantly increased the probability to download an mHealth app. In general, the source of the recommendation and the manufacturer affected the probability to download the mHealth app less. However, in Germany and the Netherlands, we found that if the app was manufactured by a pharmaceutical company, the probability to download the mHealth app decreased.

CONCLUSIONS

mHealth tools are highly promising to reduce health care costs and increase the effectiveness of traditional health interventions and therapies. Improving data protection, reducing costs, and creating sound business models are the major driving forces to increase the adoption of mHealth apps in the future. It is thereby essential to create trustworthy standards for mobile apps, whereby prices, legislation concerning data protection, and health professionals can have a leading role to inform the potential consumers.

An umbrella review of effectiveness and efficacy trials for app-based health interventions

Health interventions based on mobile phone or tablet applications (apps) are promising tools to help patients manage their conditions more effectively. Evidence from randomized controlled trials (RCTs) on efficacy and effectiveness of such interventions is increasingly available. This umbrella review aimed at mapping and narratively summarizing published systematic reviews on efficacy and effectiveness of mobile app-based health interventions within patient populations. We followed a pre-specified publicly available protocol. Systematic reviews were searched in two databases from inception until August 28, 2023. Reviews that included RCTs evaluating integrated or stand-alone health app interventions in patient populations with regard to efficacy/effectiveness were considered eligible. Information on indications, outcomes, app characteristics, efficacy/effectiveness results and authors' conclusions was extracted. Methodological quality was assessed using the AMSTAR2 tool. We identified 48 systematic reviews published between 2013 and 2023 (35 with meta-analyses) that met our inclusion criteria. Eleven reviews included a broad spectrum of conditions, thirteen focused on diabetes, five on anxiety and/or depression, and others on various other indications. Reported outcomes ranged from medication adherence to laboratory, anthropometric and functional parameters, symptom scores and quality of life. Fourty-one reviews concluded that health apps may be effective in improving health outcomes. We rated one review as moderate quality. Here we report that the synthesized evidence on health app effectiveness varies largely between indications. Future RCTs should consider reporting behavioral (process) outcomes and measures of healthcare resource utilization to provide deeper insights on mechanisms that make health apps effective, and further elucidate their impact on healthcare systems.

Modelling the Predictors of Mobile Health (mHealth) Adoption among Healthcare Professionals in Low-Resource Environments

This study was conducted with objectives to measure and validate the unified theory of the acceptance and use of technology (UTAUT) model as well as to identify the predictors of mobile health (mHealth) technology adoption among healthcare professionals in limited-resource settings. A cross-sectional survey was conducted at the six public and private hospitals in the two districts (Lodhran and Multan) of Punjab, Pakistan. The participants of the study comprised healthcare professionals (registered doctors and nurses) working in the participating hospitals. The findings of the seven-factor measurement model showed that behavioral intention (BI) to mHealth adoption is significantly influenced by performance expectancy (β = 0.504, CR = 5.064, p < 0.05) and self-concept (β = 0.860, CR = 5.968, p < 0.05) about mHealth technologies. The findings of the structural equation model (SEM) showed that the model is acceptable (χ2 (df = 259) = 3.207; p = 0.000; CFI = 0.891, IFI = 0.892, TLI = 0.874, RMSEA = 0.084). This study suggests that the adoption of mHealth can significantly help in improving people's access to quality healthcare resources and services as well as help in reducing costs and improving healthcare services. This study is significant in terms of identifying the predictors that play a determining role in the adoption of mHealth among healthcare professionals. This study presents an evidence-based model that provides an insight to policymakers, health organizations, governments, and political leaders in terms of facilitating, promoting, and implementing mHealth adoption plans in low-resource settings, which can significantly reduce health disparities and have a direct impact on health promotion.

The Potential of Digital Screening Tools for Childhood ADHD in School Environments: A Preliminary Study

Attention deficit hyperactivity disorder (ADHD) is a highly prevalent developmental disorder in children. However, accurately identifying ADHD in early childhood remains a crucial challenge. Electronic health (e-health) systems offer promising possibilities to enhance the diagnostic process for ADHD, particularly concerning the executive functions (EFs) that play a direct role. This study aims to validate an evidence-based tool for screening ADHD through EFs in the school environment. The tool, named Sendero Gris, is designed for tablet devices and is based on a previously validated test with the same name. To ensure its validity, a comparison was made between the results obtained from the tool to be validated and the original format of the test. The analysis revealed no statistically significant differences between the two approaches at a 90% confidence level (p-value = 0.49). Moreover, a user experience study focusing on usability was conducted to assess the children's inclination to use the developed tool, yielding highly positive results. The implementation of Sendero Gris on a tablet device, with its objective and versatile nature, seems to maintain the potential of the original format as a screening tool for ADHD.

Effectiveness of an Integrated Mobile Application for Lifestyle Modifications in Overweight Women with Polycystic Ovarian Syndrome: A Randomized Controlled Trial

Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women, characterized by hormonal imbalances and metabolic disturbances. Lifestyle modifications, including weight loss, are crucial for the management of PCOS symptoms. Mobile applications have emerged as promising tools to support lifestyle modifications. This study aimed to evaluate the effectiveness of a 12-week integrated lifestyle modification program, which used a mobile application, among overweight women with PCOS. A randomized controlled trial was conducted with 28 participants, who were assigned to either treatment group, which received a 12-week lifestyle modification program facilitated by a mobile application, or the control group, who were instructed to maintain their usual lifestyle and received an evidence-based leaflet containing information on PCOS. The primary outcome measure was a change in weight over 12 weeks. Insulin resistance, levels of sex hormones, hirsutism, acne, and depressive symptoms were measured as secondary outcomes. The results showed significant weight loss in the treatment group compared to the control group (3.19 vs. 0.79 kg; p < 0.05). Similarly, significant improvements were observed across time in postprandial insulin levels (22.25 vs. 9.29 μIU/mL), hirsutism (2.98 vs. -0.16 points), and depression (7.73 vs. 1.7 points) (p < 0.05) between the two groups. This study highlights the potential benefits of using a mobile application to support lifestyle modifications, including weight loss and improvement in depressive symptoms, in overweight women with PCOS. Further research is needed to explore the long-term effects and incorporation of advanced technologies to enhance PCOS management outcomes. Mobile applications for lifestyle modifications offer a promising avenue for addressing the unique challenges faced by women with PCOS and provide accessible and personalized support for their health needs.

A Survey on Autism Care, Diagnosis, and Intervention Based on Mobile Apps Focusing on Usability and Software Design

This article presents a systematic review on autism care, diagnosis, and intervention based on mobile apps running on smartphones and tablets. Here, the term "intervention" means a carefully planned set of activities with the objective of improving autism symptoms. We guide our review on related studies using five research questions. First, who benefits the most from these mobile apps? Second, what are the primary purposes of these mobile apps? Third, what mechanisms have been incorporated in these mobiles apps to improve usability? Fourth, what guidelines have been used in the design and implementation of these mobile apps? Fifth, what theories and frameworks have been used as the foundation for these mobile apps to ensure the intervention effectiveness? As can be seen from these research questions, we focus on the usability and software development of the mobile apps. Informed by the findings of these research questions, we propose a taxonomy for the mobile apps and their users. The mobile apps can be categorized into autism support apps, educational apps, teacher training apps, parental support apps, and data collection apps. The individuals with autism spectrum disorder (ASD) are the primary users of the first two categories of apps. Teachers of children with ASD are the primary users of the teacher training apps. Parents are the primary users of the parental support apps, while individuals with ASD are usually the primary users of the data collection apps and clinicians and autism researchers are the beneficiaries. Gamification, virtual reality, and autism-specific mechanisms have been used to improve the usability of the apps. User-centered design is the most popular approach for mobile app development. Augmentative and alternative communication, video modeling, and various behavior change practices have been used as the theoretical foundation for intervention efficacy.

The development and evaluation of a social media-based HIV knowledge dissemination platform in China

Objective

This study aimed to introduce the development of a social media-based HIV knowledge dissemination platform and evaluate its dissemination effects, users' feedback, and preferences.

Methods

A social media-based HIV knowledge dissemination platform ("Lihui Space") was developed as a WeChat Official Account (WOA) to disseminate HIV-related information and knowledge to the public and answer subscribers' questions. A cross-sectional study was conducted on 784 platform subscribers between July 2021 and September 2021 to evaluate users' experiences with and preferences for the platform. This platform included three content levels about HIV-related information and knowledge: individual level (health self-management), community level (social function), and society level (news and policy), and dissemination information through texts, pictures, videos, and websites. A descriptive analysis was conducted to estimate the dissemination effects of the platform and evaluation scores.

Results

As of September 16, 2021, this platform's WeChat Communication Index (WCI) score was 923.60, the total number of users was 100,008, and the total views in one month was more than 724,000. Participants reported a high level of satisfaction with this platform in terms of overall evaluation (23.36 ± 3.06), readability (18.46 ± 2.63), function evaluation (13.93 ± 1.92), design and structure (22.96 ± 3.36), and interactivity (12.56 ± 2.69).

Conclusion

This social media-based platform is currently available in the WeChat application. It is a promising tool for HIV knowledge dissemination and addressing disparities in accessing health care resources.

Physicians' Online Writing Language Style and Patient Satisfaction: The Mediator of Depth of Physician-Patient Interactions

Online health counseling (OHC) is increasingly important in modern healthcare. This development has attracted considerable attention from researchers. However, the reality of the lack of physician-patient communication and dissatisfaction with online health services remains prevalent, and more research is needed to raise awareness about important issues related to OHC services, especially in terms of patient satisfaction and depth of interaction (i.e., the product of the number of interactions and the relevance of the content). This study constructs an empirical model to explore the relationship between physicians' online writing language style (inclusive language and emojis), depth of physician-patient interactions, and patient satisfaction. The study obtained 5064 online health counseling records from 337 pediatricians and analyzed them using text mining and empirical methods. The results showed that physicians' inclusive language (β = 0.3198, p < 0.05) and emojis (β = 0.6059, p < 0.01) had a positive impact on patient satisfaction. In addition, the depth of the physician-patient interaction partially mediated this effect. This study promotes a better understanding of the mechanisms of physician-patient interactions in online settings and has important implications for how online physicians and platforms can better provide online healthcare services.

Connected Insulin Pens and Caps: An Expert's Recommendation from the Area of Diabetes of the Spanish Endocrinology and Nutrition Society (SEEN)

Undoubtedly, technological advances have revolutionised diabetes management in recent years. The development of advanced closed hybrid loop insulin pumps or continuous glucose monitoring (CGM) systems, among others, have increased the quality of life and improved glycaemic control of people with diabetes. However, only some patients have access to such technology, and only some want to use it. CGM has become much more widespread, but in terms of insulin delivery, most people with type 1 diabetes (T1D) and almost all people with type 2 diabetes (T2D) on insulin therapy are treated with multiple-dose insulin injections (MDI) rather than an insulin pump. For these patients, using connected insulin pens or caps has shown benefits in reducing missed insulin injections and promoting correct administration over time. In addition, using these devices improves the quality of life and user satisfaction. The integration of insulin injection and CGM data facilitates both users and the healthcare team to analyse glucose control and implement appropriate therapeutic changes, reducing therapeutic inertia. This expert's recommendation reviews the characteristics of the devices marketed or in the process of being marketed and their available scientific evidence. Finally, it suggests the profile of users and professionals who would benefit most, the barriers to its generalisation and the changes in the care model that implementing these devices can bring with it.

Informal carers' information needs in managing behavioural and psychological symptoms of people with dementia and related mHealth applications: a systematic integrative review to inform the design of an mHealth application

OBJECTIVE

To review and synthesise the evidence on informal carers' information needs in managing behavioural and psychological symptoms of dementia (BPSD) of their care recipients and related mobile health (mHealth) applications to inform the design of an mHealth application.

DESIGN

This is a systematic integrative review guided by Whittemore and Knafl's five-stages framework. Six databases were searched: Cochrane, CINAHL, Embase, MEDLINE, ProQuest and PsycINFO. The key concepts included 'dementia', 'behavioural and psychological symptoms', 'informal carers' and ('information need' or 'mHealth application'). Peer-reviewed full-text articles published in English from 2000 to 2022 were included. The methodological rigour of studies was analysed using the Mixed Methods Appraisal Tool V.2018. Preferred Reporting Items for Systematic Reviews and Meta-Analyses-2020 reporting guidelines were followed.

RESULTS

This review included 34 studies, including quantitative (n=13), qualitative (n=17) and mixed-method (n=4) studies. Four major themes emerged from the reported studies: the need for addressing information needs on managing BPSD, the role of support systems in managing BPSD, self-care for carers and the role of mHealth applications in providing education and support for carers. In managing BPSD, carers seek knowledge about dementia and BPSD, the roles of the carers and misconceptions about BPSD. One study reported an mHealth application to monitor the behavioural issues of people with dementia.

CONCLUSION

Informal carers of people with dementia face a number of challenges when providing care for BPSD of their care recipients. The lack of knowledge on managing BPSD is a significant challenge. Support systems such as professional, social, residential, legal and eHealth have a significant role in managing the BPSD of people with dementia in the community. mHealth interventions are sparse to support BPSD management. These findings can be used in designing an mHealth application that addresses needs related to managing BPSD of informal carers of people with dementia.

PROSPERO REGISTRATION NUMBER

CRD42021238540.

Clinical, Economic, and Patient-Reported Benefits of Connected Insulin Pen Systems: A Systematic Literature Review

INTRODUCTION

The objective of this systematic literature review was to evaluate the available literature concerning the clinical, economic, and patient-reported benefits of insulin pen platforms, including connected insulin pens/caps/sleeves and insulin platforms, as well as mobile apps capable of receiving near real-time insulin dosing information.

METHODS

Medline and Embase databases and the Cochrane Library were searched for published literature between January 2015 and May 2021, and manual searches for conference abstracts from 2018 to May 2021 were performed. These searches were supplemented by internet searches for relevant literature and clinical trials. Study selection involved the population, intervention, comparator, outcomes, time frame, and study design outline. Included studies investigated connected insulin systems or connected caps/sleeves enabling pens to be connected, or apps able to connect to these systems, in individuals of all ages with type 1 or type 2 diabetes mellitus.

RESULTS

Searches identified a total of 26 publications (mostly observational studies and conference abstracts) for inclusion, representing ten unique, predominantly small studies. Evidence in this field is still in its early stages, and only two randomized controlled trials met our inclusion criteria. Available results showed that connected insulin pens and their systems potentially helped reduce suboptimal insulin use and may therefore improve glycemic control. Satisfaction of people with diabetes with the technologies used was high, and economic benefits were noted. Features of effective connected insulin pen devices include simplicity of use and data upload/sharing, useful "point-of-care" alerts, and simple and understandable data presentation to facilitate more effective consultations.

CONCLUSIONS

Connected insulin pen systems could be increasingly considered as part of routine clinical care for insulin-treated persons with diabetes who must manage the complexity of their daily insulin routine. Future research focusing on the way data obtained from these devices can be most effectively used alongside other information is urgently needed.

The willingness and attitudes of speech-language pathologists towards the use of mobile health technology: a survey study

BACKGROUND

Mobile health (mHealth) technology could be used in different ways to treat various speech and language disorders. The attitude of speech-language pathologists (SLPs) towards this technology and their willingness to use it can play a significant role in the success of the therapies they provide. This study was conducted to investigate the willingness and attitude of SLPs towards the use of mHealth technology.

METHODS

This cross-sectional study was conducted from September 2021 to April 2022 in Iran. A researcher-made questionnaire consisting of three parts (information related to demographic variables, attitude and willingness) was designed based on the past studies, and then given to all SLPs throughout Iran. Data were analyzed by SPSS software, using descriptive and inferential statistics (frequency, mean, Fisher's exact test, and analysis of variance). Also, the SLPs' willingness to use the desired technology was interpreted as a percentage as follows: 0-20% = not at all willing, 21-40% = slightly willing, 41-60% = moderately willing, 61-80% = highly willing, and above 80% = extremely willing.

RESULTS

One hundred sixty speech-language pathologists from all over Iran participated in this study. The results showed that the willingness of 65.25% of SLPs to use the mentioned technology was at a good level, and according to the mentioned category, they had a high willingness to use this technology. In regard to the attitude of SLPs, the findings showed that SLPs believed that patients receive a higher quality of care during in-person visits than through mHealth technology. Also, this survey showed that SLPs were more inclined to use this technology to answer patients' questions. Non-payment of services provided through mHealth technology and privacy concerns were the reasons for the lack of use of this technology by SLPs.

CONCLUSIONS

SLPs are willing to use mHealth technology after solving the related challenges, including payment of costs and privacy concerns. However, SLPs believed that this technology will not be a suitable alternative to face-to-face sessions.

A tale of two applications: lessons learned from national LMIC COVID applications

Mobile health (mHealth) technologies in low- and middle-income countries (LMICs) have received increased attention for the significant potential benefits they can bring to underserved populations. As smartphones are becoming increasingly accessible, many stakeholders in the mHealth space have begun exploring smartphone applications as a means to impact individuals living within LMICs. With the COVID-19 pandemic straining healthcare systems around the world, many governments in LMICs turned to use smartphone applications to help support and manage their pandemic responses. By analyzing national COVID-19 applications created and launched by the Indian and Vietnamese governments, we highlight effective application functions and strategies, summarizing best practices for future LMIC application development.

Validation of a multiple‑lead smartphone-based electrocardiograph with automated lead placement for layman use in patients with hypertrophic cardiomyopathy

BACKGROUND

A smartphone 12-Lead ECG that enables layman ECG screening is still lacking. We aimed to validate D-Heart ECG device, a smartphone 8/12 Lead electrocardiograph with an image processing algorithm to guide secure electrode placement by non-professional users.

METHODS

One-hundred-fourty-five patients with HCM were enrolled. Two uncovered chest images were acquired using the smartphone camera. An image with virtual electrodes placement by imaging processing algorithm software was compared to the 'gold standard' electrode placement by a doctor. D-Heart 8 and 12-Lead ECG were obtained, immediately followed by 12‑lead ECGs and were assessed by 2 independent observers. Burden of ECG abnormalities was defined by a score based on the sum of 9 criteria, identifying four classes of increasing severity.

RESULTS

A total of 87(60%) patients presented a normal/mildly abnormal ECG, whereas 58(40%) had moderate or severe ECG alteration. Eight(6%) patients had ≥1 misplaced electrode. D-Heart 8-Lead and 12‑lead ECGs concordance according to Cohen's weighted kappa test was 0,948 (p < 0,001, agreement of 97.93%). Concordance was high for the Romhilt-Estes score (k_w = 0,912; p < 0.01). Concordance between D-Heart 12-Lead ECG and standard 12-Lead ECG was perfect (k_w = 1). PR and QRS intervals measurements comparison with Bland-Altman method showed good accuracy (95% limit of agreement ±18 ms for PR and ± 9 ms for QRS).

CONCLUSIONS

D-Heart 8/12-Lead ECGs proved accurate, allowing an assessment of ECG abnormalities comparable to the standard 12‑lead ECG in patients with HCM. The image processing algorithm provided accurate electrode placement, standardizing exam quality, potentially opening perspectives for layman ECG screening campaigns.

Critical Criteria and Countermeasures for Mobile Health Developers to Ensure Mobile Health Privacy and Security: Mixed Methods Study

BACKGROUND

Despite the importance of the privacy and confidentiality of patients' information, mobile health (mHealth) apps can raise the risk of violating users' privacy and confidentiality. Research has shown that many apps provide an insecure infrastructure and that security is not a priority for developers.

OBJECTIVE

This study aims to develop and validate a comprehensive tool to be considered by developers for assessing the security and privacy of mHealth apps.

METHODS

A literature search was performed to identify papers on app development, and those papers reporting criteria for the security and privacy of mHealth were assessed. The criteria were extracted using content analysis and presented to experts. An expert panel was held for determining the categories and subcategories of the criteria according to meaning, repetition, and overlap; impact scores were also measured. Quantitative and qualitative methods were used for validating the criteria. The validity and reliability of the instrument were calculated to present an assessment instrument.

RESULTS

The search strategy identified 8190 papers, of which 33 (0.4%) were deemed eligible. A total of 218 criteria were extracted based on the literature search; of these, 119 (54.6%) criteria were removed as duplicates and 10 (4.6%) were deemed irrelevant to the security or privacy of mHealth apps. The remaining 89 (40.8%) criteria were presented to the expert panel. After calculating impact scores, the content validity ratio (CVR), and the content validity index (CVI), 63 (70.8%) criteria were confirmed. The mean CVR and CVI of the instrument were 0.72 and 0.86, respectively. The criteria were grouped into 8 categories: authentication and authorization, access management, security, data storage, integrity, encryption and decryption, privacy, and privacy policy content.

CONCLUSIONS

The proposed comprehensive criteria can be used as a guide for app designers, developers, and even researchers. The criteria and the countermeasures presented in this study can be considered to improve the privacy and security of mHealth apps before releasing the apps into the market. Regulators are recommended to consider an established standard using such criteria for the accreditation process, since the available self-certification of developers is not reliable enough.

Mobile health community loyalty development process in China: an empirical study from information seeking perspective

Purpose

This study aims to investigate the process of developing loyalty in the Chinese mobile health community from the information seeking perspective.

Design/methodology/approach

A covariance-based structural equation model was developed to explore the mobile health community loyalty development process from information seeking perspective and tested with LISREL 9.30 for the 191 mobile health platform user samples.

Findings

The empirical results demonstrate that the information seeking perspective offers an interesting explanation for the mobile health community loyalty development process. All hypotheses in the proposed research model are supported except the relationship between privacy and trust. The two types of mobile health community loyalty—attitudal loyalty and behavioral loyalty are explained with 58 and 37% variance.

Originality/value

This paper has brought out the information seeking perspective in the loyalty formation process in mobile health community and identified several important constructs for this perspective for the loyalty formation process including information quality, communication with doctors and communication with patients.

Digital Interventions for Social Participation in Adults with Long-term Physical Conditions: A Systematic Review

This review aims to identify and evaluate digital interventions for social participation in the growing population of adults with long-term physical conditions. Articles were sourced from MEDLINE, EMBASE, CINAHL and PsycINFO databases using subject headings and keywords related to "social participation" and "digital technology". Studies that adopted digital technology interventions to improve social participation in adults with long-term physical conditions were included. Data on study methodology, participant and digital intervention characteristics, and findings related to social participation were extracted. The search yielded a total of 4646 articles and 14 articles met criteria for final review with five randomized controlled trials, two non-randomized clinical trials and seven one-group pretest-posttest clinical trials. Studies were organized based on the digital intervention strategy implemented to improve social participation: group support (n = 4), individual skill training or counseling (n = 6), education and support (n = 3), and mixed intervention (n = 1). The group support interventions developed a social network among participants through videoconference, app, or virtual reality platform. Three studies reported positive improvements in different aspects of social participation. Individual skill training or counseling mainly utilized phone calls to help participants cope with activity participation and interpersonal relationship issues. Only two studies demonstrated benefits for social participation. The education and support intervention, which used messages and website information to increase participants' knowledge and provide support, showed positive findings in three studies. This review suggests digital interventions for improving social participation in adults with long-term physical conditions are feasible and the effectiveness of different strategies may vary.Registration: This review was prospectively registered on the International Prospective Register of Systematic Reviews (PROSPERO) (registry number: CRD42021254105).

A GDPR-Compliant Dynamic Consent Mobile Application for the Australasian Type-1 Diabetes Data Network

Australia has a high prevalence of diabetes, with approximately 1.2 million Australians diagnosed with the disease. In 2012, the Australasian Diabetes Data Network (ADDN) was established with funding from the Juvenile Diabetes Research Foundation (JDRF). ADDN is a national diabetes registry which captures longitudinal information about patients with type-1 diabetes (T1D). Currently, the ADDN data are directly contributed from 42 paediatric and 17 adult diabetes centres across Australia and New Zealand, i.e., where the data are pre-existing in hospital systems and not manually entered into ADDN. The historical data in ADDN have been de-identified, and patients are initially afforded the opportunity to opt-out of being involved in the registry; however, moving forward, there is an increased demand from the clinical research community to utilise fully identifying data. This raises additional demands on the registry in terms of security, privacy, and the nature of patient consent. General Data Protection Regulation (GDPR) is an increasingly important mechanism allowing individuals to have the right to know about their health data and what those data are being used for. This paper presents a mobile application being designed to support the ADDN data collection and usage processes and aligning them with GDPR. The app utilises Dynamic Consent-an informed specific consent model, which allows participants to view and modify their research-driven consent decisions through an interactive interface. It focuses specifically on supporting dynamic opt-in consent to both the registry and to associated sub-projects requesting access to and use of the patient data for research purposes.

The use of mobile health technology in the management of osteoarthritis: A scoping review with scientometric analyses

INTRODUCTION

Although mHealth technology is an emerging approach for enabling self-management/education of hip/knee osteoarthritis (OA) that may reduce burdens in primary and secondary care, no scoping review has been conducted to comprehensively review the scope of mHealth technology in managing hip/knee OA. This scoping review and scientometric analyses aimed to summarize the current state of research on the use of mHealth technology (mobile applications/web-based interventions) for self-management/education of adults with hip/knee OA, identify key research activities, and provide future directions on the development/usage of mHealth technology.

METHODS

The Arksey and O'Malley methodological framework was employed, augmented with scientometric analyses. Six databases were searched from inception to 31 May 2021. Findings were reported according to the PRISMA extension for scoping review. Co-word, co-author, and co-citation scientometric analyses were conducted to examine the social and intellectual connections of the research field (e.g., research hotspots and researcher collaborations).

RESULTS

Twenty mHealth programs for promoting self-management of hip/knee OA were identified. The programs mainly included exercises or directives on performance of exercises. Compared to no interventions, mHealth technology was usable and might be more effective in improving pain, physical function, and quality of life in individuals with OA. The scientometric analyses identified multiple co-occurring keywords that reflected conceptual properties of this research domain. Although some intellectual connections among authors, research articles, and journals were noted, there were insufficient international collaborations in this field.

DISCUSSION

While individual small-scale studies highlighted promising short-term effects of mHealth technology in self-managing hip/knee OA, many mHealth technologies were developed without clinicians' and/or patients' contributions. Future mHealth programs should be developed based on a strong theoretical background and professional inputs. The long-term benefits and cost-effectiveness of mHealth technologies, user experience, as well as cross-cultural adaptation of these technologies should be evaluated.

SATO (IDEAS expAnded wiTh BCIO): Workflow for designers of patient-centered mobile health behaviour change intervention applications

Designing effective theory-driven digital behaviour change interventions (DBCI) is a challenging task. To ease the design process, and assist with knowledge sharing and evaluation of the DBCI, we propose the SATO (IDEAS expAnded wiTh BCIO) design workflow based on the IDEAS (Integrate, Design, Assess, and Share) framework and aligned with the Behaviour Change Intervention Ontology (BCIO). BCIO is a structural representation of the knowledge in behaviour change domain supporting evaluation of behaviour change interventions (BCIs) but it is not straightforward to utilise it during DBCI design. IDEAS (Integrate, Design, Assess, and Share) framework guides multi-disciplinary teams through the mobile health (mHealth) application development life-cycle but it is not aligned with BCIO entities. SATO couples BCIO entities with workflow steps and extends IDEAS Integrate stage with consideration of customisation and personalisation. We provide a checklist of the activities that should be performed during intervention planning with concrete examples and a tutorial accompanied with case studies from the Cancer Better Life Experience (CAPABLE) European project. In the process of creating this workflow, we found the necessity to extend the BCIO to support the scenarios of multiple clinical goals in the same application. To ensure the SATO steps are easy to follow for the incomers to the field, we performed a preliminary evaluation of the workflow with two knowledge engineers, working on novel mHealth app design tasks.

Incorporating new ways of doing by learning from everyday experiences and interactions using a multifactorial mHealth app

Background

Digital health innovations can support the prevention and management of risk factors for cardiovascular diseases, such as stroke. However, little is known about people's everyday experiences of digitally augmented stroke-prevention programmes combining onsite group sessions including peers and healthcare professionals with interaction and support from a multifactorial mHealth app.

Objective

The aim of this study was to explore how people with stroke risk experienced interaction with a multifactorial mHealth app as support in the make my day stroke-prevention programme.

Methods

Repeated interviews and observations with 12 adults with moderate to high stroke risk were analysed using a constant comparative method informed by constructive grounded theory.

Results

Incorporating new ways of doing into everyday life involves a process through which participants learn from both being and doing in different environments (e.g., digital, physical and social). Digital self-monitoring combined with seemingly trivial everyday experiences played central roles in the process of increasing awareness of health and stroke risks, and providing tools to support increased self-reflection on everyday behaviours. Adoption of positive health behaviours in everyday life was supported or hindered by how easy to use and personally relevant the mHealth app was perceived to be.

Conclusions

An experience-based group programme together with a personally relevant multifactorial mHealth app can be supportive in stroke prevention to increase general health literacy and stroke risk literacy, and promote the incorporation of new ways of doing in everyday life. Routines of doing digital self-monitoring and health-promoting activities were however strongly influenced by different environments in which choices are presented. It is therefore important to explore how both self-monitoring and health-promoting activities can be incorporated into everyday routines for different individuals. Research should also explore how personally relevant mHealth can be developed and integrated into prevention practices in primary healthcare.

A Study of the Ping An Health App Based on User Reviews with Sentiment Analysis

By mining the dimensional sentiment and dimension weight of the Ping An Health App reviews, this paper explores the changing trend of the influence of dimensions on user satisfaction and provides suggestions for the Ping An Health App operators to improve user satisfaction. Firstly, the topic model is used to identify the topic of user comments, and then the fine-grained sentiment analysis method is used to calculate the sentiment and weight of each dimension. Finally, the changing trend of the weight of each dimension and the changing trend of user satisfaction of each dimension are drawn. Based on the reviews of the Ping An Health App in the Apple App Store, users' concerns about Ping An Health App can be summarized into seven main dimensions: Usage, Bug report, Reliability, Feature information, Services, Other apps, and User Background. The "Feature information" dimension and "Reliability" dimension have a great impact on user satisfaction with the Ping An Health App, while the "Bug report" dimension has the lowest user satisfaction.

Heart Failure-Smart Life: a randomized controlled trial of a mobile app for self-management in patients with heart failure

BACKGROUND

It is an important strategy for healthcare providers to support heart failure patients with comprehensive aspects of self-management. A practical alternative to a comprehensive and user-friendly self-management program for heart failure patients is needed. This study aimed to develop a mobile self-management app program for patients with heart failure and to identify the impact of the program.

METHODS

We developed a mobile app, called Heart Failure-Smart Life. The app was to provide educational materials using a daily health check-up diary, Q & A, and 1:1 chat, considering individual users' convenience. An experimental study was employed using a randomized controlled trial to evaluate the effects of the program in patients with heart failure from July 2018 to June 2019. The experimental group (n = 36) participated in using the mobile app that provided feedback on their self-management and allowed monitoring of their daily health status by cardiac nurses for 3 months, and the control group (n = 38) continued to undergo their usual care. The differences in the physical, psychosocial, and behavioral factors between the two groups over time were analyzed using the analysis of covariance.

RESULTS

After 3 months of intervention, significant differences between experimental and control groups were shown in the New York Heart Association functional class (p = 0.003) and cardiac diastolic function (p = 0.024). The improvements over time in the experimental group tended to be higher than those in the control group in considered variables. However, no changes in psychosocial and behavioral variables were observed between the groups over time.

CONCLUSIONS

This study provides evidence that the mobile app program may provide benefits to its users, specifically improvements of symptom and cardiac diastolic function in patients with heart failure. Healthcare providers can effectively and practically guide and support patients with heart failure using comprehensive and convenient self-management tools such as smartphone apps.

Mobile healthcare platforms' sustainability: The perspective of health information quality

As an emerging form of medical organization, Chinese mobile healthcare (mHealth) platforms are inherently linked to the continuous use of users, which depends on the quality of the health information provided. However, improving the health information quality of mHealth platforms is still a problem that needs to be studied and solved in order to make the platforms sustainable. Based on the reputation mechanism, this study creates a behavioral evolutionary game model for health information providers (physicians) and managers (mHealth platforms), explores the evolution process and evolutionarily stable strategy of the behaviors in various situations, and uses numerical simulation technology to analyze mHealth platforms' constraints and the influencing factors of health information quality. This study presents three key findings. First, considering reputation, health information managers and mHealth platform providers should not unilaterally optimize health information. Instead, mHealth platforms should have active quality control, and physician groups should provide high-quality health information, which is the ideal evolution of the model. Second, the rewards that physicians receive from patients and mHealth platforms for providing quality health information, the reputation benefits, the penalties that physicians suffer for providing low-quality health information, and the increased probability and cost of rent-seeking behavior that physicians may choose can effectively promote the choice of physicians to provide high-quality health information. Third, the reputation gain of mHealth platforms, the probability of mHealth platforms being exposed, and increased losses suffered from exposure can effectively promote the choice of mHealth platforms to control the quality of health information. This study can provide a theoretical basis for mHealth platforms' health information quality control, which is conducive to the healthy and sustainable development of mHealth platforms and the improvement of user satisfaction.

A digital application and augmented physician rounds reduce postoperative pain and opioid consumption after primary total knee replacement (TKR): a randomized clinical trial

BACKGROUND

Severe postoperative pain not only is a considerable burden for patients but also leads to overprescription of opioids, resulting in considerable health concerns. The remarkable development of new technologies in the health care system provides novel treatment opportunities in this area and could exploit the additional placebo effect, provide added value for patients, and at the same time support hospital staff. We aimed to test the pain- and opioid intake-reducing effects of enhanced postoperative pain management by boosting pain medication by using a technical application and/or augmented physician rounds.

METHODS

In a four-arm, randomized clinical trial, 96 patients (24 patients per group) scheduled for a total knee replacement (TKR) were randomized into four groups for four postoperative days: an "application" group (APP) with information via an iPad-based application; a "doctor" group (DOC) with augmented physician rounds; a combination group (APP+DOC), which received both interventions; and a "treatment as usual" group (TAU) as a baseline with no additional intervention besides the standard care which consists of standardized medication, regular physician rounds, and physiotherapy. Postoperative pain and opioid requirements pre- and postoperatively until hospital discharge were recorded.

RESULTS

The difference between post- and preoperative pain was significantly different between the groups (P=.02, partial η²=.10). APP+DOC experienced greater postoperative pain relief than DOC (mean: 2.3 vs. 0.7, 95% CI: 0.08-3.09; P=.04) and TAU (mean 2.3 vs. 0.1; 95% CI: 0.69-3.71; P=.005), respectively, the difference compared to APP (mean 2.3 vs. 1.7; 95% CI -1.98-1.76) was not significant. Opioid consumption differed significantly between groups (P=.01, partial η²=.12). APP+DOC (72.9 mg) and DOC (75.4 mg) consumed less oxycodone than APP (83.3 mg) and TAU (87.9 mg; 95% CI: 2.9-22.1; P=.003). APP+DOC consumed significantly less oxycodone than DOC (d=0.2-0.4). There were no significant group differences in NSAID and Morphine sulfate consumption. Patients in APP+DOC were more satisfied with their treatment than patients in TAU (P=.03, partial η²=.09).

CONCLUSIONS

The combination of an innovative digital app, which implements open drug administration and augmented physician rounds that support the doctor-patient relationship can significantly improve postoperative pain management.

TRIAL REGISTRATION

The protocol was approved by the local ethics committee of the ethical commission of the German Psychological Society (Deutsche Gesellschaft für Psychologie; DGPs). The study was registered at DRKS.de (identifier: DRKS00009554).

Analysis of intention and influencing factors on mobile information follow-up service in HIV/AIDS in a city in China

Objectives

This study aimed to evaluate the willingness of patients with HIV/AIDS in Henan province to accept mobile information follow-up, to find the key factors that affect behavioral willingness to accept such follow-up, to explore the internal mechanism of the mobile service, and to provide a theoretical rationale for the further promotion of mobile follow-up.

Methods

This study used the technology acceptance model (TAM) as its main theoretical tool, which adopted a stratified random sampling method, and investigated 284 patients with HIV/AIDS in area six of Sanmenxia City. An on-site questionnaire survey method was adopted for this study. Confirmatory factor analysis was used for structural validity, with Cronbach's coefficient used for reliability. Data analysis mainly used SPSS23.0 and AMOS23.0 software.

Results

The acceptance rate of the HIV/AIDS mobile follow-up service was 68.53%. In the study, product factors (PFs) were considered important in the indirect path of the TAM. Our TAM model suggested that high perceived usefulness (PU), perceived ease of use (PEU), and perceived innovativeness (PI) of the service were significant in improving mobile health (mHealth) acceptance among patients with HIV/AIDS in China. Subjective norms (SNs) also contributed to popularizing the service in the HIV/AIDS community. The model fitting was considered acceptable (root mean square error of approximation, RMSEA = 0.074; goodness of fit index, GFI = 0.905; comparative fit index, CFI = 0.963, and Tucker-Lewis index, TLI = 0.593).

Conclusion

PFs and SNs exerted an important influence on the behavioral intentions of the patients with HIV/AIDS who accepted mobile health. PU was another important factor affecting behavioral intention. The practicality of mHealth services was crucial. Convenience and the innovativeness of the experience with the service will be conducive to the promotion and use of mHealth follow-up services.

The Receptivity to Safety-Related Mobile Apps Among Commercial Fishing Captains: Descriptive Exploratory Study

BACKGROUND

Mobile apps addressing a variety of workplace safety issues have proliferated over the last decade as mobile technology has advanced and smartphone ownership has increased. Workplace safety interventions are often designed for a specific work site. However, some of the most dangerous jobs are ones in which workers frequently change field locations, such as commercial fishing. Mobile apps may be particularly suitable for delivering safety interventions to these workers.

OBJECTIVE

We sought to gauge the potential for using mobile apps to deliver safety interventions to commercial fishing workers. The purpose of this paper is to describe how fishermen use their mobile devices during fishing operations and identify any mobile apps they already use for safety.

METHODS

Participants comprised commercial fishing captains who already owned an iOS or Android smartphone or tablet. They completed a questionnaire that asked about their current mobile device use and their use of safety-related mobile apps, in addition to questions about their fishing operations. We performed descriptive analyses of the data.

RESULTS

A total of 61 participants completed the questionnaire. The most common types of mobile devices participants reported owning were iPhones (n=36, 59%) and Android phones (n=24, 39%). Most participants (n=53, 87%) reported using their mobile device for both work and personal purposes, including while out at sea (n=52, 85%). Over half of the participants reported that they had either safety-related apps (n=17, 28%) or apps that help them with their work (n=35, 57%). The types of apps most frequently mentioned were apps for weather, wind, tides, and navigation.

CONCLUSIONS

The results of this study indicate that some commercial fishing captains who own a mobile device are receptive to using safety-related apps for work. Apps that help avoid hazards by monitoring environmental conditions and apps optimized for use on smartphones may be most likely to be adopted and used. Overall, these results suggest that mobile apps are a promising avenue for improving safety among workers in commercial fishing and similar occupations.

Automated selection of changepoints using empirical P-values and trimming

OBJECTIVES

One challenge that arises when analyzing mobile health (mHealth) data is that updates to the proprietary algorithms that process these data can change apparent patterns. Since the timings of these updates are not publicized, an analytic approach is necessary to determine whether changes in mHealth data are due to lifestyle behaviors or algorithmic updates. Existing methods for identifying changepoints do not consider multiple types of changepoints, may require prespecifying the number of changepoints, and often involve nonintuitive parameters. We propose a novel approach, Automated Selection of Changepoints using Empirical P-values and Trimming (ASCEPT), to select an optimal set of changepoints in mHealth data.

MATERIALS AND METHODS

ASCEPT involves 2 stages: (1) identification of a statistically significant set of changepoints from sequential iterations of a changepoint detection algorithm; and (2) trimming changepoints within linear and seasonal trends. ASCEPT is available at https://github.com/matthewquinn1/changepointSelect.

RESULTS

We demonstrate ASCEPT's utility using real-world mHealth data collected through the Precision VISSTA study. We also demonstrate that ASCEPT outperforms a comparable method, circular binary segmentation, and illustrate the impact when adjusting for changepoints in downstream analysis.

DISCUSSION

ASCEPT offers a practical approach for identifying changepoints in mHealth data that result from algorithmic updates. ASCEPT's only required parameters are a significance level and goodness-of-fit threshold, offering a more intuitive option compared to other approaches.

CONCLUSION

ASCEPT provides an intuitive and useful way to identify which changepoints in mHealth data are likely the result of updates to the underlying algorithms that process the data.

Impacts of Internet Use on Chinese Patients' Trust-Related Primary Healthcare Utilization

Background: The internet has greatly improved the availability of medical knowledge and may be an important avenue to improve patients’ trust in physicians and promote primary healthcare seeking by reducing information asymmetry. However, very few studies have addressed the interactive impacts of both patients’ internet use and trust on primary healthcare-seeking decisions. Objective: To explore the impact of internet use on the relationship between patients’ trust in physicians and primary healthcare seeking among Chinese adults 18 years of age and older to understand the varieties of effects in different cities. Methods: Generalized linear mixed models were applied to investigate the interactive impacts of internet use and patients’ trust in physicians on primary healthcare seeking using pooled data from the China Family Panel Study of 2014 to 2018. We also compared these effects based on different levels of urbanization, ages, and PHC services. Results: Overall, a higher degree of patients’ trust (p < 0.001) was able to directly predict better primary healthcare seeking, and internet use significantly increased the positive effect of patients’ trust on primary healthcare seeking (p < 0.001). However, the marginal effect analysis showed that this effect was related to the level of patients’ trust and that internet use could reduce the positive effect of patients’ trust on primary healthcare seeking when the individual had a low level of trust (≤ 3 units). Further, the heterogeneity analysis indicated that the benefits from internet use were higher in cities with high urbanization, high aging, and high PHC service levels compared to cities with low levels of these factors. Conclusions: The internet use may enhance patients’ trust-related PHC utilization. However, this impact is effective only if patients’ benchmark trust remains at a relatively high level. Comparatively, the role of internet use is more effective in areas with high urbanization, high aging and high PHC level. Thus, with increasing accessibility to the internet, the internet should be regulated to disseminate correct healthcare information. Moreover, in-depth integration of the internet and PHC should be promoted to provide excellent opportunities for patient participation, and different strategies should be set according to each city’s characteristics.