Mobile health technology evaluation: the mHealth evidence workshop

Development and validation of the mobile adherence satisfaction scale (MASS) for medication adherence apps

OBJECTIVE

To develop and validate the Mobile Adherence Satisfaction Scale (MASS) for assessing user satisfaction with mobile health applications aimed to improve medication adherence.

METHODS

The study involved patients over 18 with asthma, hypertension, heart failure, or diabetes, who used the CareAide® app for six months. Scale development included a literature review, expert consultations, and patient interviews, initially identifying 129 items. These were refined to 27 using a two-round Delphi technique and grouped into six dimensions: user interface, perceived usability, system quality, service quality, feature satisfaction, and general satisfaction. A pilot study with 30 participants further refined the model, which was then validated with 135 participants using exploratory and confirmatory factor analyses in SPSS 29 and SmartPLS 4. Data were collected via self-administered questionnaires.

RESULTS

A total of 135 complete questionnaires were analysed. Respondents had an average age of 66.7 years (SD = 11.6) with 42.2 % male (n = 57) and 57.8 % female (n = 78). After removal of an item due to cross loading, exploratory factor analysis resulted six dimensions and 26 items with Kaiser-Meyer-Olkin measure of 0.837 and Bartlett's Test of Sphericity (χ2(n = 325) = 2085.673, P < 0.001). The confirmatory factor analysis confirmed high reliability and validity: Cronbach's alpha values > 0.70 for each dimension and an overall alpha of 0.89, with Composite Reliability and Average Variance Extracted both >0.70 and >0.50, respectively, for each dimension. Structural model indicated a significant positive impact of user interface (β = 0.226, P = 0.006) and feature satisfaction (β = 0.230, P = 0.002) on general satisfaction, explaining 23.1 % of the variance (R2 = 0.231).

CONCLUSION

The study developed and validated the MASS, a reliable tool for assessing user satisfaction with mHealth apps. User interface design and feature satisfaction are key for long-term engagement and consistent medication adherence.

Hybrid Integration of Wearable Devices for Physiological Monitoring

Wearable devices can provide timely, user-friendly, non- or minimally invasive, and continuous monitoring of human health. Recently, multidisciplinary scientific communities have made significant progress regarding fully integrated wearable devices such as sweat wearable sensors, saliva sensors, and wound sensors. However, the translation of these wearables into markets has been slow due to several reasons associated with the poor system-level performance of integrated wearables. The wearability consideration for wearable devices compromises many properties of the wearables. Besides, the limited power capacity of wearables hinders continuous monitoring for extended duration. Furthermore, peak-power operations for intensive computations can quickly create thermal issues in the compact form factor that interfere with wearability and sensor operations. Moreover, wearable devices are constantly subjected to environmental, mechanical, chemical, and electrical interferences and variables that can invalidate the collected data. This generates the need for sophisticated data analytics to contextually identify, include, and exclude data points per multisensor fusion to enable accurate data interpretation. This review synthesizes the challenges surrounding the wearable device integration from three aspects in terms of hardware, energy, and data, focuses on a discussion about hybrid integration of wearable devices, and seeks to provide comprehensive guidance for designing fully functional and stable wearable devices.

Modeling engagement with a digital behavior change intervention (HeartSteps II): An exploratory system identification approach

OBJECTIVE

Digital behavior change interventions (DBCIs) are feasibly effective tools for addressing physical activity. However, in-depth understanding of participants' long-term engagement with DBCIs remains sparse. Since the effectiveness of DBCIs to impact behavior change depends, in part, upon participant engagement, there is a need to better understand engagement as a dynamic process in response to an individual's ever-changing biological, psychological, social, and environmental context.

METHODS

The year-long micro-randomized trial (MRT) HeartSteps II provides an unprecedented opportunity to investigate DBCI engagement among ethnically diverse participants. We combined data streams from wearable sensors (Fitbit Versa, i.e., walking behavior), the HeartSteps II app (i.e. page views), and ecological momentary assessments (EMAs, i.e. perceived intrinsic and extrinsic motivation) to build the idiographic models. A system identification approach and a fluid analogy model were used to conduct autoregressive with exogenous input (ARX) analyses that tested hypothesized relationships between these variables inspired by Self-Determination Theory (SDT) with DBCI engagement through time.

RESULTS

Data from 11 HeartSteps II participants was used to test aspects of the hypothesized SDT dynamic model. The average age was 46.33 (SD=7.4) years, and the average steps per day at baseline was 5,507 steps (SD=6,239). The hypothesized 5-input SDT-inspired ARX model for app engagement resulted in a 31.75 % weighted RMSEA (31.50 % on validation and 31.91 % on estimation), indicating that the model predicted app page views almost 32 % better relative to the mean of the data. Among Hispanic/Latino participants, the average overall model fit across inventories of the SDT fluid analogy was 34.22 % (SD=10.53) compared to 22.39 % (SD=6.36) among non-Hispanic/Latino Whites, a difference of 11.83 %. Across individuals, the number of daily notification prompts received by the participant was positively associated with increased app page views. The weekend/weekday indicator and perceived daily busyness were also found to be key predictors of the number of daily application page views.

CONCLUSIONS

This novel approach has significant implications for both personalized and adaptive DBCIs by identifying factors that foster or undermine engagement in an individual's respective context. Once identified, these factors can be tailored to promote engagement and support sustained behavior change over time.

Impact of a pilot mHealth intervention on treatment outcomes of TB patients seeking care in the private sector using Propensity Scores Matching-Evidence collated from New Delhi, India

Mobile health applications called Digital Adherence Technologies (DATs), are increasingly used for improving treatment adherence among Tuberculosis patients to attain cure, and/or other chronic diseases requiring long-term and complex medication regimens. These DATs are found to be useful in resource-limited settings because of their cost efficiency in reaching out to vulnerable groups (providing pill and clinic visit reminders, relevant health information, and motivational messages) or those staying in remote or rural areas. Despite their growing ubiquity, there is very limited evidence on how DATs improve healthcare outcomes. We analyzed the uptake of DATs in an urban setting (DS-DOST, powered by Connect for LifeTM, Johnson & Johnson) among different patient groups accessing TB services in New Delhi, India, and subsequently assessed its impact in improving patient engagement and treatment outcomes. This study aims to understand the uptake patterns of a digital adherence technology and its impact in improving follow-ups and treatment outcomes among TB patients. Propensity choice modelling was used to create balanced treated and untreated patient datasets, before applying simple ordinary least square and logistic regression methods to estimate the causal impact of the intervention on the number of follow-ups made with the patient and treatment outcomes. After controlling for potential confounders, it was found that patients who installed and utilized DS-DOST application received an average of 6.4 (95% C.I. [5.32 to 7.557]) additional follow-ups, relative to those who did not utilize the application. This translates to a 58% increase. They also had a 245% higher likelihood of treatment success (Odds ratio: 3.458; 95% C.I. [1.709 to 6.996]).

Increasing adherence and collecting symptom-specific biometric signals in remote monitoring of heart failure patients: a randomized controlled trial

OBJECTIVES

Mobile health (mHealth) regimens can improve health through the continuous monitoring of biometric parameters paired with appropriate interventions. However, adherence to monitoring tends to decay over time. Our randomized controlled trial sought to determine: (1) if a mobile app with gamification and financial incentives significantly increases adherence to mHealth monitoring in a population of heart failure patients; and (2) if activity data correlate with disease-specific symptoms.

MATERIALS AND METHODS

We recruited individuals with heart failure into a prospective 180-day monitoring study with 3 arms. All 3 arms included monitoring with a connected weight scale and an activity tracker. The second arm included an additional mobile app with gamification, and the third arm included the mobile app and a financial incentive awarded based on adherence to mobile monitoring.

RESULTS

We recruited 111 heart failure patients into the study. We found that the arm including the financial incentive led to significantly higher adherence to activity tracker (95% vs 72.2%, P = .01) and weight (87.5% vs 69.4%, P = .002) monitoring compared to the arm that included the monitoring devices alone. Furthermore, we found a significant correlation between daily steps and daily symptom severity.

DISCUSSION AND CONCLUSION

Our findings indicate that mobile apps with added engagement features can be useful tools for improving adherence over time and may thus increase the impact of mHealth-driven interventions. Additionally, activity tracker data can provide passive monitoring of disease burden that may be used to predict future events.

Mobile Health Interventions for Substance Use Disorders

Substance use disorders (SUDs) have an enormous negative impact on individuals, families, and society as a whole. Most individuals with SUDs do not receive treatment because of the limited availability of treatment providers, costs, inflexible work schedules, required treatment-related time commitments, and other hurdles. A paradigm shift in the provision of SUD treatments is currently underway. Indeed, with rapid technological advances, novel mobile health (mHealth) interventions can now be downloaded and accessed by those that need them anytime and anywhere. Nevertheless, the development and evaluation process for mHealth interventions for SUDs is still in its infancy. This review provides a critical appraisal of the significant literature in the field of mHealth interventions for SUDs with a particular emphasis on interventions for understudied and underserved populations. We also discuss the mHealth intervention development process, intervention optimization, and important remaining questions.

ASHA-led community-managed intervention programme to improve maternal and neonatal outcomes in pregnant women with pregnancy hypertension: A study protocol

AIM

The objective is to use the available technology in conjunction with the peripheral health workers to identify the early warning signs of pregnancy-induced hypertension (PIH), provide appropriate referral services and closely monitor the patient thereafter with the aim of improving the prognosis of the condition.

STUDY DESIGN

Quasi-experimental design.

METHOD

The research will be carried out in Udupi District Karnataka, India. The study will involve 250 pregnant women in total as well as 50 ASHA workers. All the participants will undergo a PIH knowledge assessment, which will be followed by a PIH risk assessment for expectant mothers. There will be an implementation of the community-managed intervention programme (CMIP). The creation of a mobile application, ongoing prenatal follow-up and training for ASHAs on mobile app usage are all part of the CMIP. The results for mothers and newborns will be monitored and to learn more about the efficacy of CMIP and the difficulties ASHA workers and expectant mothers encounter in identifying the early warning signals of PIH a focused group discussion will be held.

DISCUSSION

A number of research on pregnancy-induced hypertension have demonstrated the necessity for community-based treatments to be developed in order to improve the outcomes for expectant mothers and newborns. These programmes assist in managing hypertension throughout pregnancy. Conversely, ASHA employees have had a favourable influence on community-level health outcome management. Currently, technology is being used extensively in healthcare and is receiving favourable reception. Thus, in an effort to improve maternal and newborn outcomes, this study attempts to incorporate mobile technologies in addition to ASHA workers and pregnant women.

IMPACT

If the CMIP proves to be beneficial, it might be implemented nationwide, particularly in isolated regions, to monitor expectant mothers and avoid PIH-related concerns.

Provider Adoption of mHealth in Rural Patient Care: Web-Based Survey Study

BACKGROUND

Physicians and patient-facing caregivers have increasingly used mobile health (mHealth) technologies in the past several years, accelerating during the COVID-19 pandemic. However, barriers and feedback surrounding adoption remain relatively understudied and varied across health systems, particularly in rural areas.

OBJECTIVE

This study aims to identify provider adoption, attitudes, and barriers toward mHealth in a large, multisite, rural US health care system. We investigated (1) mHealth apps that providers use for their own benefit and (2) mHealth apps that a provider uses in conjunction with a patient.

METHODS

We surveyed all patient-seeing providers within the Marshfield Clinic Health System with a brief, 16-item, web-based survey assessing attitudes toward mHealth, adoption of these technologies, and perceived barriers faced by providers, their peers, and the institution. Survey results were summarized via descriptive statistics, with log-binomial regression and accompanying pairwise analyses, using Kruskal-Wallis and Jonckheere-Terpstra tests for significance, respectively. Respondents were grouped by reported clinical role and specialty.

RESULTS

We received a 38% (n/N=916/2410) response rate, with 60.7% (n=556) of those sufficiently complete for analyses. Roughly 54.1% (n=301) of respondents reported mHealth use, primarily around decision-making and supplemental information, with use differing based on provider role and years of experience. Self-reported barriers to using mHealth included a lack of knowledge and time to study mHealth technologies. Providers also reported concerns about patients' internet access and the complexity of mHealth apps to adequately use mHealth technologies. Providers believed the health system's barriers were largely privacy, confidentiality, and legal review concerns.

CONCLUSIONS

These findings echo similar studies in other health systems, surrounding providers' lack of time and concerns over privacy and confidentiality of patient data. Providers emphasized concerns over the complexity of these technologies for their patients and concerns over patients' internet access to fully use mHealth in their delivery of care.

Just-in-Time Adaptive Intervention for Stabilizing Sleep Hours of Japanese Workers: Microrandomized Trial

BACKGROUND

Sleep disturbance is a major contributor to future health and occupational issues. Mobile health can provide interventions that address adverse health behaviors for individuals in a vulnerable health state in real-world settings (just-in-time adaptive intervention).

OBJECTIVE

This study aims to identify a subpopulation with vulnerable sleep state in daily life (study 1) and, immediately afterward, to test whether providing mobile health intervention improved habitual sleep behaviors and psychological wellness in real-world settings by conducting a microrandomized trial (study 2).

METHODS

Japanese workers (n=182) were instructed to collect data on their habitual sleep behaviors and momentary symptoms (including depressive mood, anxiety, and subjective sleep quality) using digital devices in a real-world setting. In study 1, we calculated intraindividual mean and variability of sleep hours, midpoint of sleep, and sleep efficiency to characterize their habitual sleep behaviors. In study 2, we designed and conducted a sleep just-in-time adaptive intervention, which delivered objective push-type sleep feedback messages to improve their sleep hours for a subset of participants in study 1 (n=81). The feedback messages were generated based on their sleep data measured on previous nights and were randomly sent to participants with a 50% chance for each day (microrandomization).

RESULTS

In study 1, we applied hierarchical clustering to dichotomize the population into 2 clusters (group A and group B) and found that group B was characterized by unstable habitual sleep behaviors (large intraindividual variabilities). In addition, linear mixed-effect models showed that the interindividual variability of sleep hours was significantly associated with depressive mood (β=3.83; P=.004), anxiety (β=5.70; P=.03), and subjective sleep quality (β=-3.37; P=.03). In study 2, we found that providing sleep feedback prolonged subsequent sleep hours (increasing up to 40 min; P=.01), and this effect lasted for up to 7 days. Overall, the stability of sleep hours in study 2 was significantly improved among participants in group B compared with the participants in study 1 (P=.001).

CONCLUSIONS

This is the first study to demonstrate that providing sleep feedback can benefit the modification of habitual sleep behaviors in a microrandomized trial. The findings of this study encourage the use of digitalized health intervention that uses real-time health monitoring and personalized feedback.

Development of an epilepsy self-management mobile health app framework: Content validity study results

BACKGROUND

Mobile health (mHealth) applications (apps) show promise in supporting epilepsy self-management (eSM). To delve deeper into this potential, we conducted a systematic review of epilepsy mHealth apps available on both iOS and Android platforms, examining articles related to eSM. This review allowed us to identify important domains related to eSM. Furthermore, based on the findings, we developed an epilepsy mHealth app framework that aims to improve self-management for the local population. This study aims to assess the practicality and usability of the proposed mHealth app framework designed to improve eSM. We will conduct an expert panel review to evaluate the effectiveness and feasibility of the framework.

MATERIAL AND METHODS

Content validity was assessed by an expert panel comprising epileptologists and pharmacists. The validation process involved scoring the items within each domain of the framework to evaluate their practicality and usability (quantitative component). In addition, a panel discussion was conducted to further explore and discuss the qualitative aspects of the items.

RESULTS

A total of 4 domains with 15 items were highly rated for their practicality and usefulness in eSM.

CONCLUSIONS

The locally validated framework will be useful for developing eSM mobile apps. Seizure Tracking, Medication Adherence, Treatment Management, and Healthcare Communication emerged as the most crucial domains for enhancing eSM.

Utilizing Telemedicine Applications in Celiac Disease and Other Gluten-Free-Diet-Dependent Conditions: Insights from the COVID-19 Pandemic

BACKGROUND

Globally, approximately 1.4% of people have celiac disease (CD), induced by gluten sensitivity. If left untreated, it causes small intestinal inflammation and villous atrophy, which can result in failure to thrive, anemia, osteoporosis, malabsorption, and even malignancy. The only treatment option available is a gluten-free diet (GFD). Few studies have looked at the role and perception of telehealth in relation to CD and selective nutrition both before and after the COVID-19 pandemic.

AIM

Our goal was to screen and investigate the research conducted both before and after the COVID-19 pandemic concerning the utilization of telehealth applications and solutions in CD and other GFD-dependent circumstances.

METHODS

We employed a narrative review approach to explore articles that were published in scholarly journals or organizations between the years 2000 and 2024. Only English-language publications were included. PubMed and Google Scholar searches were mainly conducted using the following keywords: telemedicine, telehealth, telecare, eHealth, m-health, COVID-19, SARS-CoV-2, celiac disease, and gluten-free diet (GFD). Manual searches of the references in the acquired literature were also carried out, along with the authors' own personal contributions of their knowledge and proficiency in this field.

RESULTS

Only a few studies conducted prior to the COVID-19 outbreak examined the viewpoints and experiences of adult patients with CD with relation to in-person clinic visits, as well as other options such as telehealth. The majority of patients believed that phone consultations were appropriate and beneficial. Video conferencing and telemedicine became more popular during the COVID-19 pandemic, demonstrating the effectiveness of using these technologies for CD on a global basis. In recent years, urine assays for gluten identification have become accessible for use at home. These tests could be helpful for CD monitoring with telemedicine assistance.

CONCLUSIONS

The extended knowledge gathered from the COVID-19 pandemic is expected to complement pre-COVID-19 data supporting the usefulness of telemedicine even after the emergent pandemic, encouraging its wider adoption in standard clinical practice. The monitoring and follow-up of CD patients and other GFD-dependent conditions can greatly benefit from telemedicine.

A Pilot Randomized Controlled Trial of Augmented Reality Just-in-Time Guidance for the Performance of Rugged Field Procedures

INTRODUCTION

Medical resuscitations in rugged prehospital settings require emergency personnel to perform high-risk procedures in low-resource conditions. Just-in-Time Guidance (JITG) utilizing augmented reality (AR) guidance may be a solution. There is little literature on the utility of AR-mediated JITG tools for facilitating the performance of emergent field care.

STUDY OBJECTIVE

The objective of this study was to investigate the feasibility and efficacy of a novel AR-mediated JITG tool for emergency field procedures.

METHODS

Emergency medical technician-basic (EMT-B) and paramedic cohorts were randomized to either video training (control) or JITG-AR guidance (intervention) groups for performing bag-valve-mask (BVM) ventilation, intraosseous (IO) line placement, and needle-decompression (Needle-d) in a medium-fidelity simulation environment. For the interventional condition, subjects used an AR technology platform to perform the tasks. The primary outcome was participant task performance; the secondary outcomes were participant-reported acceptability. Participant task score, task time, and acceptability ratings were reported descriptively and compared between the control and intervention groups using chi-square analysis for binary variables and unpaired t-testing for continuous variables.

RESULTS

Sixty participants were enrolled (mean age 34.8 years; 72% male). In the EMT-B cohort, there was no difference in average task performance score between the control and JITG groups for the BVM and IO tasks; however, the control group had higher performance scores for the Needle-d task (mean score difference 22%; P = .01). In the paramedic cohort, there was no difference in performance scores between the control and JITG group for the BVM and Needle-d tasks, but the control group had higher task scores for the IO task (mean score difference 23%; P = .01). For all task and participant types, the control group performed tasks more quickly than in the JITG group. There was no difference in participant usability or usefulness ratings between the JITG or control conditions for any of the tasks, although paramedics reported they were less likely to use the JITG equipment again (mean difference 1.96 rating points; P = .02).

CONCLUSIONS

This study demonstrated preliminary evidence that AR-mediated guidance for emergency medical procedures is feasible and acceptable. These observations, coupled with AR's promise for real-time interaction and on-going technological advancements, suggest the potential for this modality in training and practice that justifies future investigation.

Effectiveness of Applying Green Heart, a Smartphone-Based Self-management Intervention to Control Smoking: A Randomized Clinical Trial

BACKGROUND

Cardiovascular diseases (CVDs) pose a significant global health concern and are the most common cause of death and disability, necessitating preventive interventions targeting modifiable risk factors. Recently, mobile-health technology has been developed to improve the delivery of cardiovascular prevention by risk factor modification. The "Green Heart" mobile application (app) was designed to aid in risk factor control among coronary artery disease (CAD) patients.

METHODS

This parallel-group, single-blinded randomized controlled trial enrolled 1590 CAD patients, including 668 current smokers, randomly assigned to control (paper-based education) and intervention (application-based) groups. The app encompassed three modules targeting smoking cessation, dyslipidemia control, and blood pressure management. This study evaluated the impact of the smoking cessation module on behavioral change among current smokers. Green Heart assesses nicotine dependence, offering personalized quit plans, educational content, motivational messages, and automated progress tracking. The odds of smoking behavior changes during the 24-week follow-up underwent assessment.

RESULTS

The intention-to-treat analysis highlighted significantly elevated rates of smoking cessation and reductions in the intervention group versus the control group. Adherence to the app (per-treatment analysis) also demonstrated significantly more favorable smoking behavior changes among the application users. Logistic regression emphasized higher odds of quitting and reduction in smoking in the application group, showing an odds ratio of 2.14 (95% CI: 1.16-3.97) compared to those not using the app (P=0.015).

CONCLUSION

Our results confirmed that complete adherence to the app for at least 24 weeks was linked to alterations in cigarette smoking behavior among CAD patients. Trial Registration Number: IRCT20221016056204N1.

The differences between adults and adolescents using a mobile health application for menstrual complaints: A usability and qualitative study

BACKGROUND

A "Menstruatie Educatie Kalender" application (Menstruation Education Calendar, (MEK-APP)) was developed for adults to evaluate menstrual complaints. The future aim of this app is to use it as a self-diagnostic instrument for menstrual abnormalities for both adults and adolescents. Early identification of the potential of an application for future use by both user groups would increase implementation success and adoption of the application.

OBJECTIVE

To compare differences in experienced usability by adults versus adolescents and to identify factors influencing future use for both age groups in one mHealth application (in this study the MEK-APP).

METHODS

This study consisted of three phases: (1) usability testing of the MEK-APP for iOS and Android by think-aloud method, (2) two-month daily use and (3) in-depth individual interview. During the think-aloud sessions, twelve tasks were performed in the application while they were thinking aloud. Usability problems were rated for their severity with Nielsen' Severity Scale. Both the think-aloud sessions and in-depth interviews were verbatim transcribed and thematically analyzed to determine the factors influencing future use for both groups. In addition, the System Usability Scale (SUS) and Intrinsic Motivation Inventory (IMI) questionnaires were filled out during the interviews.

RESULTS

Seven adults (>18 years) and seven adolescents (14-18 years) evaluated the MEK-APP. There were 14 usability issues and 16 bugs in both groups. There were no differences between adults and adolescents. In the thematic qualitative analysis, the following future use factors were identified: user-expectation, motivation, privacy, understandability, and user-experience. The user-expectation, motivation and privacy differed between both groups but did not influence usage. No differences were observed in SUS and IMI scores between both groups.

CONCLUSIONS

There are five factors influencing the future use of a menstrual-related mHealth application for both adults and adolescents. It is possible to serve different age groups with a single application.

Unraveling the role of cloud computing in health care system and biomedical sciences

Cloud computing has emerged as a transformative force in healthcare and biomedical sciences, offering scalable, on-demand resources for managing vast amounts of data. This review explores the integration of cloud computing within these fields, highlighting its pivotal role in enhancing data management, security, and accessibility. We examine the application of cloud computing in various healthcare domains, including electronic medical records, telemedicine, and personalized patient care, as well as its impact on bioinformatics research, particularly in genomics, proteomics, and metabolomics. The review also addresses the challenges and ethical considerations associated with cloud-based healthcare solutions, such as data privacy and cybersecurity. By providing a comprehensive overview, we aim to assist readers in understanding the significance of cloud computing in modern medical applications and its potential to revolutionize both patient care and biomedical research.

Methodological Frameworks and Dimensions to Be Considered in Digital Health Technology Assessment: Scoping Review and Thematic Analysis

BACKGROUND

Digital health technologies (dHTs) offer a unique opportunity to address some of the major challenges facing health care systems worldwide. However, the implementation of dHTs raises some concerns, such as the limited understanding of their real impact on health systems and people's well-being or the potential risks derived from their use. In this context, health technology assessment (HTA) is 1 of the main tools that health systems can use to appraise evidence and determine the value of a given dHT. Nevertheless, due to the nature of dHTs, experts highlight the need to reconsider the frameworks used in traditional HTA.

OBJECTIVE

This scoping review (ScR) aimed to identify the methodological frameworks used worldwide for digital health technology assessment (dHTA); determine what domains are being considered; and generate, through a thematic analysis, a proposal for a methodological framework based on the most frequently described domains in the literature.

METHODS

The ScR was performed in accordance with the guidelines established in the PRISMA-ScR guidelines. We searched 7 databases for peer reviews and gray literature published between January 2011 and December 2021. The retrieved studies were screened using Rayyan in a single-blind manner by 2 independent authors, and data were extracted using ATLAS.ti software. The same software was used for thematic analysis.

RESULTS

The systematic search retrieved 3061 studies (n=2238, 73.1%, unique), of which 26 (0.8%) studies were included. From these, we identified 102 methodological frameworks designed for dHTA. These frameworks revealed great heterogeneity between them due to their different structures, approaches, and items to be considered in dHTA. In addition, we identified different wording used to refer to similar concepts. Through thematic analysis, we reduced this heterogeneity. In the first phase of the analysis, 176 provisional codes related to different assessment items emerged. In the second phase, these codes were clustered into 86 descriptive themes, which, in turn, were grouped in the third phase into 61 analytical themes and organized through a vertical hierarchy of 3 levels: level 1 formed by 13 domains, level 2 formed by 38 dimensions, and level 3 formed by 11 subdimensions. From these 61 analytical themes, we developed a proposal for a methodological framework for dHTA.

CONCLUSIONS

There is a need to adapt the existing frameworks used for dHTA or create new ones to more comprehensively assess different kinds of dHTs. Through this ScR, we identified 26 studies including 102 methodological frameworks and tools for dHTA. The thematic analysis of those 26 studies led to the definition of 12 domains, 38 dimensions, and 11 subdimensions that should be considered in dHTA.

Identifying app components that promote physical activity: a group concept mapping study

Background

Digital interventions are a promising avenue to promote physical activity in healthy adults. Current practices recommend to include end-users early on in the development process. This study focuses on the wishes and needs of users regarding an a mobile health (mHealth) application that promotes physical activity in healthy adults, and on the differences between participants who do or do not meet the World Health Organization's recommendation of an equivalent of 150 minutes of moderate intensity physical activity.

Methods

We used a mixed-method design called Group Concept Mapping. In a first phase, we collected statements completing the prompt "In an app that helps me move more, I would like to see/ do/ learn the following…" during four brainstorming sessions with physically inactive individuals (n = 19). The resulting 90 statements were then sorted and rated by a new group of participants (n = 46). Sorting data was aggregated, and (dis)similarity matrices were created using multidimensional scaling. Hierarchical clustering was applied using Ward's method. Analyses were carried out for the entire group, a subgroup of active participants and a subgroup of inactive participants. Explorative analyses further investigated ratings of the clusters as a function of activity level, gender, age and education.

Results

Six clusters of statements were identified, namely 'Ease-of-use and Self-monitoring', 'Technical Aspects and Advertisement', 'Personalised Information and Support', 'Motivational Aspects', 'Goal setting, goal review and rewards', and 'Social Features'. The cluster 'Ease-of-use and Self-monitoring' was rated highest in the overall group and the active subgroup, whereas the cluster 'Technical Aspects and Advertisement' was scored as most relevant in the inactive subgroup. For all groups, the cluster 'Social Features' was scored the lowest. Explorative analysis revealed minor between-group differences.

Discussion

The present study identified priorities of users for an mHealth application that promotes physical activity. First, the application should be user-friendly and accessible. Second, the application should provide personalized support and information. Third, users should be able to monitor their behaviour and compare their current activity to their past performance. Fourth, users should be provided autonomy within the app, such as over which and how many notifications they would like to receive, and whether or not they want to engage with social features. These priorities can serve as guiding principles for developing mHealth applications to promote physical activity in the general population.

Incorporating nonparametric methods for estimating causal excursion effects in mobile health with zero-inflated count outcomes

In mobile health, tailoring interventions for real-time delivery is of paramount importance. Micro-randomized trials have emerged as the "gold-standard" methodology for developing such interventions. Analyzing data from these trials provides insights into the efficacy of interventions and the potential moderation by specific covariates. The "causal excursion effect," a novel class of causal estimand, addresses these inquiries. Yet, existing research mainly focuses on continuous or binary data, leaving count data largely unexplored. The current work is motivated by the Drink Less micro-randomized trial from the UK, which focuses on a zero-inflated proximal outcome, i.e., the number of screen views in the subsequent hour following the intervention decision point. To be specific, we revisit the concept of causal excursion effect, specifically for zero-inflated count outcomes, and introduce novel estimation approaches that incorporate nonparametric techniques. Bidirectional asymptotics are established for the proposed estimators. Simulation studies are conducted to evaluate the performance of the proposed methods. As an illustration, we also implement these methods to the Drink Less trial data.

Mobile-based ecological momentary assessment and intervention: bibliometric analysis

Objective

The aim of this article was to review existing documents in the field of mobile-based EMA and EMI, provide an overview of current hot topics, and predict future development trends.

Methods

We conducted a bibliometric study on mobile-based EMA and EMI publications that were collected from the Web of Science Core Collection database. Biblioshiny and CiteSpace were utilized to analyze scientific productions, leading sources, authors, affiliations, documents, research hot topics, keywords, and trend topics.

Results

A total of 2222 documents related to EMA and EMI published between 1992 and 2023 were retrieved. In recent years, scholarly publications have generally increased in mobile-based EMA and EMI research, particularly in the last decade. JMIR mHealth and uHealth (n=86), as well as JMIR (n=73), showed the highest number of publications. The United States (n=1038), Germany (n=218) and Netherlands (n=175) were leading countries. Regarding keyword co-occurrence and trend topics analysis, mental health, health behaviors, and feasibility were hot topics in mobile-based EMA and EMI research. Future research trends included using EMA for tailoring EMI, just-in-time adaptive interventions (JITAI), and digital phenotyping.

Conclusion

This bibliometric study on mobile-based EMA and EMI is a valuable resource for understanding the field's evolution and future trends. Our analysis indicates that EMA and EMI have great potential in health behaviors and mental health, but implementation should consider feasibility and reactivity issues carefully. Emerging trends include EMA-tailored EMI, JITAI, and digital phenotyping. In the future, strengthening multidisciplinary cooperation will be necessary to promote the continued development of the field.

Learnings From Implementation of Technology-Enabled Mental Health Interventions in India: Implementation Report

BACKGROUND

Recent years have witnessed an increase in the use of technology-enabled interventions for delivering mental health care in different settings. Technological solutions have been advocated to increase access to care, especially in primary health care settings in low- and middle-income countries, to facilitate task-sharing given the lack of trained mental health professionals.

OBJECTIVE

This report describes the experiences and challenges faced during the development and implementation of technology-enabled interventions for mental health among adults and adolescents in rural and urban settings of India.

METHODS

A detailed overview of the technological frameworks used in various studies, including the Systematic Medical Appraisal and Referral Treatment (SMART) Mental Health pilot study, SMART Mental Health cluster randomized controlled trial, and Adolescents' Resilience and Treatment Needs for Mental Health in Indian Slums (ARTEMIS) study, is provided. This includes the mobile apps that were used to collect data and the use of the database to store the data that were collected. Based on the experiences faced, the technological enhancements and adaptations made at the mobile app and database levels are described in detail.

IMPLEMENTATION (RESULTS)

Development of descriptive analytics at the database level; enabling offline and online data storage modalities; customizing the Open Medical Record System platform to suit the study requirements; modifying the encryption settings, thereby making the system more secure; and merging different apps for simultaneous data collection were some of the enhancements made across different projects.

CONCLUSIONS

Technology-enabled interventions prove to be a useful solution to cater to large populations in low-resource settings. The development of mobile apps is subject to the context and the area where they would be implemented. This paper outlines the need for careful testing using an iterative process that may support future research using similar technology.

TRIAL REGISTRATION

SMART Mental Health trial: Clinical Trial Registry India CTRI/2018/08/015355; https://ctri.nic.in/Clinicaltrials/pmaindet2.php?EncHid=MjMyNTQ=&Enc=&userName=CTRI/2018/08/015355. ARTEMIS trial: Clinical Trial Registry India CTRI/2022/02/040307; https://ctri.nic.in/Clinicaltrials/pmaindet2.php?EncHid=NDcxMTE=&Enc=&userName=CTRI/2022/02/040307.

Mobile health technologies to improve walking distance in people with intermittent claudication

BACKGROUND

Peripheral arterial disease (PAD) is the obstruction or narrowing of the large arteries of the lower limbs, which can result in impaired oxygen supply to the muscle and other tissues during exercise, or even at rest in more severe cases. PAD is classified into five categories (Fontaine classification). It may be asymptomatic or various levels of claudication pain may be present; at a later stage, there may be ulceration or gangrene of the limb, with amputation occasionally being required. About 20% of people with PAD suffer from intermittent claudication (IC), which is muscular discomfort in the lower extremities induced by exertion and relieved by rest within 10 minutes; IC causes restriction of movement in daily life. Treatment for people with IC involves addressing lifestyle risk factors. Exercise is an important part of treatment, but supervised exercise programmes for individuals with IC have low engagement levels and high attrition rates. The use of mobile technologies has been suggested as a new way to engage people with IC in walking exercise interventions. The novelty of the intervention, low cost for the user, automation, and ease of access are some of the advantages mobile health (mhealth) technologies provide that give them the potential to be effective in boosting physical activity in adults.

OBJECTIVES

To assess the benefits and harms of mobile health (mhealth) technologies to improve walking distance in people with intermittent claudication.

SEARCH METHODS

The Cochrane Vascular Information Specialist conducted systematic searches of the Cochrane Vascular Specialised Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and CINAHL, and also searched the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) and ClinicalTrials.gov. The most recent searches were carried out on 19 December 2022.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) in people aged 18 years or over with symptomatic PAD and a clinical diagnosis of IC. We included RCTs comparing mhealth interventions to improve walking distance versus usual care (no intervention or non-exercise advice), exercise advice, or supervised exercise programmes. We excluded people with chronic limb-threatening ischaemia (Fontaine III and IV).

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methods. Our primary outcomes were change in absolute walking distance from baseline, change in claudication distance from baseline, amputation-free survival, revascularisation-free survival. Our secondary outcomes were major adverse cardiovascular events, major adverse limb events, above-ankle amputation, quality of life, and adverse events. We used GRADE to assess the certainty of the evidence.

MAIN RESULTS

We included four RCTs involving a total of 614 participants with a clinical diagnosis of IC. The duration of intervention of the four included RCTs ranged from 3 to 12 months. Participants were randomised to either mhealth or control (usual care or supervised exercise programme). All four studies had an unclear or high risk of bias in one or several domains. The most prevalent risk of bias was in the area of performance bias, which was rated high risk as it is not possible to blind participants and personnel in this type of trial. Based on GRADE criteria, we downgraded the certainty of the evidence to low, due to concerns about risk of bias, imprecision, and clinical inconsistency. Comparing mhealth with usual care, there was no clear evidence of an effect on absolute walking distance (mean difference 9.99 metres, 95% confidence interval (CI) -27.96 to 47.93; 2 studies, 503 participants; low-certainty evidence). None of the included studies reported on change in claudication walking distance, amputation-free survival, or revascularisation-free survival. Only one study reported on major adverse cardiovascular events (MACE) and found no clear difference between groups (risk ratio 1.37, 95% CI 0.07 to 28.17; 1 study, 305 participants; low-certainty evidence). None of the included studies reported on major adverse limb events (MALE) or above-ankle amputations.

AUTHORS' CONCLUSIONS

Mobile health technologies can be used to provide lifestyle interventions for people with chronic conditions, such as IC. We identified a limited number of studies that met our inclusion criteria. We found no clear difference between mhealth and usual care in improving absolute walking distance in people with IC; however, we judged the evidence to be low certainty. Larger, well-designed RCTs are needed to provide adequate statistical power to reliably evaluate the effects of mhealth technologies on walking distance in people with IC.

The NLR SkinApp: Testing a Supporting mHealth Tool for Frontline Health Workers Performing Skin Screening in Ethiopia and Tanzania

Background: The prevalence of skin diseases such as leprosy, and limited dermatological knowledge among frontline health workers (FHWs) in rural areas of Sub-Saharan Africa, led to the development of the NLR SkinApp: a mobile application (app) that supports FHWs to promptly diagnose and treat, or suspect and refer patients with skin diseases. The app includes common skin diseases, neglected tropical skin diseases (skin NTDs) such as leprosy, and HIV/AIDS-related skin conditions. This study aimed to test the supporting role of the NLR SkinApp by examining the diagnostic accuracy of its third edition. Methods: A cross-sectional study was conducted in East Hararghe, Ethiopia, as well as the Mwanza and Morogoro region, Tanzania, in 2018-2019. Diagnostic accuracy was measured against a diagnosis confirmed by two dermatologists/dermatological medical experts (reference standard) in terms of sensitivity, specificity, positive predictive value, and negative predictive value. The potential negative effect of an incorrect management recommendation was expressed on a scale of one to four. Results: A total of 443 patients with suspected skin conditions were included. The FHWs using the NLR SkinApp diagnosed 45% of the patients accurately. The values of the sensitivity of the FHWs using the NLR SkinApp in determining the correct diagnosis ranged from 23% for HIV/AIDS-related skin conditions to 76.9% for eczema, and the specificity from 69.6% for eczema to 99.3% for tinea capitis/corporis. The inter-rater reliability among the FHWs for the diagnoses made, expressed as the percent agreement, was 58% compared to 96% among the dermatologists. Of the management recommendations given on the basis of incorrect diagnoses, around one-third could have a potential negative effect. Conclusions: The results for diagnosing eczema are encouraging, demonstrating the potential contribution of the NLR SkinApp to dermatological and leprosy care by FHWs. Further studies with a bigger sample size and comparing FHWs with and without using the NLR SkinApp are needed to obtain a better understanding of the added value of the NLR SkinApp as a mobile health (mHealth) tool in supporting FHWs to diagnose and treat skin diseases.

Feasibility and Usability of EnergyPoints: A Mobile Health App to Guide Acupressure Use for Cancer Symptom Management

OBJECTIVE

To examine the feasibility and usability of EnergyPoints™, an innovative mobile health app that teaches and guides people with cancer to implement daily acupressure to self-manage their fatigue and sleep disturbances.

METHODS AND INTERVENTION

The study used an integrated agile, human-centered approach. Adults (age 18 years and over) with cancer experiencing at least moderate fatigue, and living in the Greater New York City community, were recruited from social media, patient advocacy groups, and referrals. Twenty participants (in 3 sprints of 3, 5, and 12) were video-recorded thinking aloud while using the app for the first time. They then used the app at home to self-administer acupressure (twice daily for 1 week) while continuously wearing a fitness tracker. Each participant completed an exit interview and modified Computer System Usability Questionnaire post-participation.

RESULTS

Participants were ages 40 to 76 years and 65% female; 65% were non-Hispanic white. Mean pass rates per ritual exceeded 80%. Users completed (totally or partially) greater than 90% of stimulating acupressure and 70% of relaxing acupressure rituals. Sprint 3 SPs totally completed at least 1 ritual 87% of the time. The majority agreed or strongly agreed the app was easy to use (90%), easy to learn (85%), easy to understand (75%), and effective in helping perform self-acupressure (85%). In an analysis of ease of completing 5 key tasks, all successfully completed the tasks; 3 users required some assistance. Of 654 usability statements, those coded as personal experience/context (197), content related to acupressure learning (105), and content related to the onboarding/profile (71) were most frequent. The design team integrated recommendations into the app before the next sprint.

CONCLUSIONS

Findings supported feasibility and usability, as well as acceptability, and led to significant alterations and improvements. EnergyPoints™ offers an opportunity to mainstream acupressure and help cancer survivors self-manage their symptoms.

Telehealth Competencies: Training Physicians for a New Reality?

In North America, telehealth increased by 40% between 2019 and 2020 and stabilized at 40% in 2021. As telehealth becomes more common, it is essential to ensure that healthcare providers have the required skills to overcome the challenges and barriers of this new modality of care. While the COVID-19 pandemic has accelerated the design and implementation of telehealth curricula in healthcare education programs, its general adoption is still a major gap and an important barrier to ensuring scaling up and sustainability of the telesshealth practice. Lack of experienced faculty and limited curricular time are two of the most common barriers to expanding telehealth education. Overcoming the barriers of telehealth curricula implementation may require moving away from the classic expert model of learning in which novices learn from experts. As the adoption of telehealth curricula is still in its early stages, institutions may need to plan for faculty development and trainee education at the same time. Questions regarding the timing and content of telehealth education, the interprofessional development of curricula, and the identification of optimal pedagogical methods remain open and crucial. This article reflects on these questions and presents telesimulation as an ideal instructional method for the training of telehealth competencies. Telesimulation can provide opportunities for practical training across a range of telehealth competencies, fostering not only technical proficiency but also communication skills and interprofessional collaboration.

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.

The use of the Capability-Opportunity- Motivation Behavior (COM-B) model to identify barriers to medication adherence and the application of mobile health technology in adults with coronary heart disease: A qualitative study

Objective

Among patients with coronary heart disease, we sought to address the research questions of: 1) What is the acceptability of applying a technology-enabled approach to support medication adherence?; and 2) What are barriers to medication adherence using the Capability-Opportunity-Motivation Behavior (COM-B) model as a guiding framework?

Methods

Applying qualitative research methods, we employed a series of 3 focus groups per individual (total 9 sessions). Coded data from thematic analysis were mapped to the COM-B model components for meaningful associations.

Results

Fourteen participants were recruited (median age 69.5 ± 11, 50% female). Barriers to medication adherence were organized along these COM-B domains: psychological capability (forgetfulness, distractions, fear of side effects), physical opportunity (inaccessible medications, inability to renew prescriptions), reflective (burdening family members), and automatic motivation (medication fatigue, health decline).

Conclusions

Tailored text messaging and mobile phone apps were perceived as helpful tools for medication adherence. The COM-B model was useful to provide a comprehensive, theory-driven evaluation of patients' beliefs and motivations on whether to engage in medication adherence.

Innovation

To date, text messaging and mobile applications have not been widely implemented in the clinical setting and provide a major opportunity to innovate on approaches to address medication adherence.

Cost savings in male circumcision post-operative care using two-way text-based follow-up in rural and urban South Africa

Introduction

Voluntary medical male circumcision (VMMC) clients are required to attend multiple post-operative follow-up visits in South Africa. However, with demonstrated VMMC safety, stretched clinic staff in SA may conduct more than 400,000 unnecessary reviews for males without complications, annually. Embedded into a randomized controlled trial (RCT) to test safety of two-way, text-based (2wT) follow-up as compared to routine in-person visits among adult clients, the objective of this study was to compare 2wT and routine post-VMMC care costs in rural and urban South African settings.

Methods

Activity-based costing (ABC) estimated the costs of post-VMMC care, including counselling, follow-ups, and tracing in $US dollars. Transportation for VMMC and follow-up was provided for rural clients in outreach settings but not for urban clients in static sites. Data were collected from National Department of Health VMMC forms, RCT databases, and time-and-motion surveys. Sensitivity analysis presents different follow-up scenarios. We hypothesized that 2wT would save per-client costs overall, with higher savings in rural settings.

Results

VMMC program costs were estimated from 1,084 RCT clients: 537 in routine care and 547 in 2wT. On average, 2wT saved $3.56 per client as compared to routine care. By location, 2wT saved $7.73 per rural client and increased urban costs by $0.59 per client. 2wT would save $2.16 and $7.02 in follow-up program costs if men attended one or two post-VMMC visits, respectively.

Conclusion

Quality 2wT follow-up care reduces overall post-VMMC care costs by supporting most men to heal at home while triaging clients with potential complications to timely, in-person care. 2wT saves more in rural areas where 2wT offsets transportation costs. Minimal additional 2wT costs in urban areas reflect high care quality and client engagement, a worthy investment for improved VMMC service delivery. 2wT scale-up in South Africa could significantly reduce overall VMMC costs while maintaining service quality.

Detecting Social Contexts from Mobile Sensing Indicators in Virtual Interactions with Socially Anxious Individuals

Mobile sensing is a ubiquitous and useful tool to make inferences about individuals' mental health based on physiology and behavior patterns. Along with sensing features directly associated with mental health, it can be valuable to detect different features of social contexts to learn about social interaction patterns over time and across different environments. This can provide insight into diverse communities' academic, work and social lives, and their social networks. We posit that passively detecting social contexts can be particularly useful for social anxiety research, as it may ultimately help identify changes in social anxiety status and patterns of social avoidance and withdrawal. To this end, we recruited a sample of highly socially anxious undergraduate students (N=46) to examine whether we could detect the presence of experimentally manipulated virtual social contexts via wristband sensors. Using a multitask machine learning pipeline, we leveraged passively sensed biobehavioral streams to detect contexts relevant to social anxiety, including (1) whether people were in a social situation, (2) size of the social group, (3) degree of social evaluation, and (4) phase of social situation (anticipating, actively experiencing, or had just participated in an experience). Results demonstrated the feasibility of detecting most virtual social contexts, with stronger predictive accuracy when detecting whether individuals were in a social situation or not and the phase of the situation, and weaker predictive accuracy when detecting the level of social evaluation. They also indicated that sensing streams are differentially important to prediction based on the context being predicted. Our findings also provide useful information regarding design elements relevant to passive context detection, including optimal sensing duration, the utility of different sensing modalities, and the need for personalization. We discuss implications of these findings for future work on context detection (e.g., just-in-time adaptive intervention development).

Implementing text-messaging to support and enhance delivery of health behavior change interventions in low- to middle-income countries: case study of the Lifestyle Africa intervention

The prevalence of non-communicable diseases, such as diabetes and cardiovascular disease, is rising in low- and middle-income countries (LMICs). Health behavior change (HBC) interventions such as the widely used Diabetes Prevention Program (DPP) are effective at reducing chronic disease risk, but have not been adapted for LMICs. Leveraging mobile health (mHealth) technology such as text messaging (SMS) to enhance reach and participant engagement with these interventions has great promise, yet we lack evidence-informed approaches to guide the integration of SMS specifically to support HBC interventions in LMIC contexts. To address this gap, we integrated guidance from the mHealth literature with expertise and first-hand experience to establish specific development steps for building and implementing SMS systems to support HBC programming in LMICs. Specifically, we provide real-world examples of each development step by describing our experience in designing and delivering an SMS system to support a culturally-adapted DPP designed for delivery in South Africa. We outline eight key SMS development steps, including: 1) determining if SMS is appropriate; 2) developing system architecture and programming; 3) developing theory-based messages; 4) developing SMS technology; 5) addressing international SMS delivery; 6) testing; 7) system training and technical support; and 8) cost considerations. We discuss lessons learned and extractable principles that may be of use to other mHealth and HBC researchers working in similar LMIC contexts.Trial registration Clinicaltrials.gov, NCT03342274 . Registered 10 November 2017.

Bayesian continuous-time hidden Markov models with covariate selection for intensive longitudinal data with measurement error

Intensive longitudinal data collected with ecological momentary assessment methods capture information on participants' behaviors, feelings, and environment in near real-time. While these methods can reduce recall biases typically present in survey data, they may still suffer from other biases commonly found in self-reported data (e.g., measurement error and social desirability bias). To accommodate potential biases, we develop a Bayesian hidden Markov model to simultaneously identify risk factors for subjects transitioning between discrete latent states as well as risk factors potentially associated with them misreporting their true behaviors. We use simulated data to demonstrate how ignoring potential measurement error can negatively affect variable selection performance and estimation accuracy. We apply our proposed model to smartphone-based ecological momentary assessment data collected within a randomized controlled trial that evaluated the impact of incentivizing abstinence from cigarette smoking among socioeconomically disadvantaged adults. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Mobile Web App Intervention to Promote Breast Cancer Screening Among American Indian Women in the Northern Plains: Feasibility and Efficacy Study

BACKGROUND

Breast cancer is the most common cancer in the United States and the second leading cause of death for American Indian women. American Indian women have lower rates of breast cancer screening than other racial groups, and disparities in breast cancer mortality and survival rates persist among them. To address this critical need, a culturally appropriate, accessible, and personalized intervention is necessary to promote breast cancer screening among American Indian women. This study used mobile health principles to develop a mobile web app-based mammogram intervention (wMammogram) for American Indian women in a remote, rural community in the Northern Plains.

OBJECTIVE

This study aimed to assess the feasibility and efficacy of the wMammogram intervention, which was designed to motivate American Indian women to undergo breast cancer screening, as compared with the control group, who received an educational brochure.

METHODS

Using community-based participatory research (CBPR) principles and a multipronged recruitment strategy in a randomized controlled trial design, we developed the wMammogram intervention. This study involved 122 American Indian women aged between 40 and 70 years, who were randomly assigned to either the intervention group (n=62) or the control group (n=60). Those in the intervention group received personalized and culturally appropriate messages through a mobile web app, while those in the control group received an educational brochure. We measured outcomes such as mammogram receipt, intention to receive breast cancer screening after the intervention, and participants' satisfaction with and acceptance of the intervention.

RESULTS

A significantly higher proportion of women who received the wMammogram intervention (26/62, 42%; P=.009) completed mammograms by the 6-month follow-up than the control group (12/60, 20%). The wMammogram intervention group, compared with the control group, reported significantly higher ratings on perceived effectiveness of the intervention (t120=-5.22; P<.001), increase in knowledge (t120=-4.75; P<.001), and satisfaction with the intervention (t120=-3.61; P<.001). Moreover, compared with the brochure group, the intervention group expressed greater intention to receive a mammogram in the future when it is due (62/62, 100% vs 51/60, 85%) and were more willing to recommend the intervention they received to their friends (61/62, 98.4% vs 54/60, 90%) with statistically significant differences.

CONCLUSIONS

This study shows the feasibility and efficacy of the wMammogram intervention to promote breast cancer screening for American Indian women in a remote, rural community-based setting. Findings suggest that, with advancements in technology and the ubiquity of mobile devices, mobile web apps could serve as a valuable health intervention tool that builds upon low-cost technology and enhances accessibility and sustainability of preventive care to help reduce breast health disparities experienced in hard-to-reach American Indian populations.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05530603; https://clinicaltrials.gov/ct2/show/NCT05530603.

mHealth Impact on Gait and Dynamic Balance Outcomes in Neurorehabilitation: Systematic Review and Meta-analysis

Gait and dynamic balance are two main goals in neurorehabilitation that mHealth systems could address. To analyze the impact of using mHealth systems on gait and dynamic balance outcomes in subjects with neurological disorders. Randomized controlled trials (RCT) published in PubMed, Web of Science, Scopus, and PEDro databases were searched up to April 2023. Studies including adults with neurological disorders, analyzing the effectiveness of mHealth systems on gait and dynamic balance compared with conventional therapy and/or not intervention, were included. The PEDro scale and the Cochrane Collaboration's 2.0 tool were used for the methodological quality and risk of bias assessment. The Review Manager 5.4 software was used to obtain meta-analyses. 13 RCT were included in the systematic review and 11 in the meta-analyses, involving 528 subjects. A total of 21 mobile applications were identified for gait and balance training, and to enhance physical activity behaviors. There were significant differences in gait parameters, speed by 0.10 s/m (95% confidence interval (CI)=0.07,0.13;p<0.001), cadence by 8.01 steps/min (95%CI=3.30,12.72;p<0.001), affected step length by 8.89 cm (95%CI=4.88,12.90;p<0.001), non-affected step length by 8.08 cm (5%CI=2.64,13.51;p=0.004), and in dynamic balance, Timed Up and Go by -7.15 s (95%CI=-9.30,-4.99;p<0.001), and mobility subscale of Posture Assessment Scale for Stroke by 1.71 points (95%CI=1.38,2.04;p<0.001). Our findings suggested the use of mHealth systems for improving gait in subjects with neurological disorders, but controversial results on dynamics balance recovery were obtained. However, the quality of evidence is insufficient to strongly recommend them, so further research is needed.

Effectiveness of a gamified digital intervention based on lifestyle modification (iGAME) in secondary prevention: a protocol for a randomised controlled trial

INTRODUCTION

Combating physical inactivity and reducing sitting time are one of the principal challenges proposed by public health systems. Gamification has been seen as an innovative, functional and motivating strategy to encourage patients to increase their physical activity (PA) and reduce sedentary lifestyles through behaviour change techniques (BCT). However, the effectiveness of these interventions is not usually studied before their use. The main objective of this study will be to analyse the effectiveness of a gamified mobile application (iGAME) developed in the context of promoting PA and reducing sitting time with the BCT approach, as an intervention of secondary prevention in sedentary patients.

METHODS AND ANALYSIS

A randomised clinical trial will be conducted among sedentary patients with one of these conditions: non-specific low back pain, cancer survivors and mild depression. The experimental group will receive a 12-week intervention based on a gamified mobile health application using BCT to promote PA and reduce sedentarism. Participants in the control group will be educated about the benefits of PA. The International Physical Activity Questionnaire will be considered the primary outcome. International Sedentary Assessment Tool, EuroQoL-5D, MEDRISK Instruments and consumption of Health System resources will be evaluated as secondary outcomes. Specific questionnaires will be administered depending on the clinical population. Outcomes will be assessed at baseline, at 6 weeks, at the end of the intervention (12 weeks), at 26 weeks and at 52 weeks.

ETHICS AND DISSEMINATION

The study has been approved by the Portal de Ética de la Investigación Biomédica de Andalucía Ethics Committee (RCT-iGAME 24092020). All participants will be informed about the purpose and content of the study and written informed consent will be completed. The results of this study will be published in a peer-reviewed journal and disseminated electronically and in print.

TRIAL REGISTRATION NUMBER

NCT04019119.

Perceptions, Satisfaction, and Barriers to Telemedicine Use: A Community-Based Study From Jeddah, Saudi Arabia

Background Telemedicine has expanded significantly, driven by technology and the necessity for accessible healthcare. However, users' knowledge, attitudes, and perceived barriers determine its application. This study aimed to assess these factors among patients in Jeddah, Saudi Arabia. Methodology We conducted a cross-sectional study on 403 participants from Ministry of Health centers in Jeddah from February to May 2023. A structured questionnaire was used for data collection, and subsequent analysis was performed using SPSS version 28.0 (IBM Corp., Armonk, NY, USA). Results Most participants (93.1%) agreed that telehealth services have improved healthcare accessibility and expressed willingness to participate in future telemedicine consultations. However, 73.7% felt potential embarrassment or discomfort due to camera and equipment presence. Remarkably, 76.2% of participants believed telemedicine suits all medical conditions, and 95% recommended its use. Barriers to telemedicine use were identified, including the need to travel to access healthcare services in the absence of telemedicine and the associated inconvenience and cost. The overall satisfaction score was 4.56 ± 0.78, with the highest satisfaction reported for the ability to talk freely over telemedicine (4.64 ± 0.76) and the ease of registration/scheduling (4.63 ± 0.82). Significant differences (p < 0.001) in satisfaction scores were found across various age groups, gender, nationality, employment status, and education level. Patients aged >55 years and those who used telemedicine services for the first time were associated with a significantly increased risk of poor satisfaction (odds ratio (OR) = 8.068, p = 0.011 and OR = 8.919, p = 0.005, respectively). Conclusions The findings suggest high satisfaction and positive attitudes toward telemedicine services in Jeddah, Saudi Arabia, despite identifiable barriers such as potential discomfort from camera presence. Patient age and familiarity with telemedicine services significantly influenced satisfaction levels, indicating areas that require attention for the successful implementation and expansion of telemedicine in Saudi Arabia.

Effectiveness and implementation of a text messaging intervention to reduce depression and anxiety symptoms among Latinx and Non-Latinx white users during the COVID-19 pandemic

Text messaging interventions are increasingly used to help people manage depression and anxiety. However, little is known about the effectiveness and implementation of these interventions among U.S. Latinxs, who often face barriers to using mental health tools. The StayWell at Home (StayWell) intervention, a 60-day text messaging program based on cognitive behavioral therapy (CBT), was developed to help adults cope with depressive and anxiety symptoms during the COVID-19 pandemic. StayWell users (n = 398) received daily mood inquiries and automated skills-based text messages delivering CBT-informed coping strategies from an investigator-generated message bank. We conduct a Hybrid Type 1 mixed-methods study to compare the effectiveness and implementation of StayWell for Latinx and Non-Latinx White (NLW) adults using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. Effectiveness was measured using the PHQ-8 depression and GAD-7 anxiety scales, assessed before starting and after completing StayWell. Guided by RE-AIM, we conducted a thematic text analysis of responses to an open-ended question about user experiences to help contextualize quantitative findings. Approximately 65.8% (n = 262) of StayWell users completed pre-and-post surveys. On average, depressive (-1.48, p = 0.001) and anxiety (-1.38, p = 0.001) symptoms decreased from pre-to-post StayWell. Compared to NLW users (n = 192), Latinx users (n = 70) reported an additional -1.45 point (p < 0.05) decline in depressive symptoms, adjusting for demographics. Although Latinxs reported StayWell as relatively less useable (76.8 vs. 83.9, p = 0.001) than NLWs, they were more interested in continuing the program (7.5 vs. 6.2 out of 10, p = 0.001) and recommending it to a family member/friend (7.8 vs. 7.0 out of 10, p = 0.01). Based on the thematic analysis, both Latinx and NLW users enjoyed responding to mood inquiries and sought bi-directional, personalized text messages and texts with links to more information to resources. Only NLW users stated that StayWell provided no new information than they already knew from therapy or other sources. In contrast, Latinx users suggested that engagement with a behavioral provider through text or support groups would be beneficial, highlighting this group's unmet need for behavioral health care. mHealth interventions like StayWell are well-positioned to address population-level disparities by serving those with the greatest unmet needs if they are culturally adapted and actively disseminated to marginalized groups. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04473599.

Use of new technologies for the promotion of physical activity in patients with mental illness: A systematic review

BACKGROUND

Physical exercise is an underutilized tool for the management of mental disorders. New technologies have made a breakthrough in health care, and one of its possible applications (apps) could be that of customizing exercise programs for special populations, such as patients with mental disorders. However, the app of the so-called e-health to mental health care is still limited.

AIM

To know the efficacy of apps to promote physical activity in patients with mental disorders.

METHODS

We conducted a systematic review of the PubMed and Embase databases with the aim of exploring the use of new technologies for the enhancement of physical exercise in patients with a psychiatric illness. Following the selection process, 10 articles were included in the review.

RESULTS

The most commonly used devices in this type of intervention are wearable devices and web platforms. Good results in terms of effectiveness and acceptability were obtained in most of the studies.

CONCLUSION

Our findings suggest that the use of new technologies in mental health represents a feasible strategy with great potential in clinical practice.

A Web-Based Stratified Stepped Care Platform for Mental Well-being (TourHeart+): User-Centered Research and Design

BACKGROUND

Internet-based mental health interventions have been demonstrated to be effective in alleviating psychological distress and promoting mental well-being. However, real-world uptake and engagement of such interventions have been low. Rather than being stand-alone interventions, situating internet-based interventions under a stratified stepped care system can support users to continue with mental health practice and monitor their mental health status for timely services that are commensurate with their needs. A user-centered approach should be used in the development of such web-based platforms to understand the facilitators and barriers in user engagement to enhance platform uptake, usability, and adherence so it can support the users' continued adoption and practice of self-care for their mental health.

OBJECTIVE

The aim of this study was to describe the design process taken to develop a web-based stratified stepped care mental health platform, TourHeart+, using a user-centered approach that gathers target users' perceptions on mental self-care and feedback on the platform design and incorporates them into the design.

METHODS

The process involved a design workshop with the interdisciplinary development team, user interviews, and 2 usability testing sessions on the flow of registration and mental health assessment and the web-based self-help interventions of the platform. The data collected were summarized as descriptive statistics if appropriate and insights are extracted inductively. Qualitative data were extracted using a thematic coding approach.

RESULTS

In the design workshop, the team generated empathy maps and point-of-view statements related to the possible mental health needs of target users. Four user personas and related processes in the mental health self-care journey were developed based on user interviews. Design considerations were derived based on the insights drawn from the personas and mental health self-care journey. Survey results from 104 users during usability testing showed that the overall experience during registration and mental health assessment was friendly, and they felt cared for, although no statistically significant differences on preference ratings were found between using a web-based questionnaire tool and through an interactive chatbot, except that chatbot format was deemed more interesting. Facilitators of and barriers to registering the platform and completing the mental health assessment were identified through user feedback during simulation with mock-ups. In the usability testing for guided self-help interventions, users expressed pain points in course adherence, and corresponding amendments were made in the flow and design of the web-based courses.

CONCLUSIONS

The design process and findings presented in the study are important in developing a user-centric platform to optimize users' acceptance and usability of a web-based stratified stepped care platform with guided self-help interventions for mental well-being. Accounting for users' perceptions and needs toward mental health self-care and their experiences in the design process can enhance the usability of an evidence-based mental health platform on the web.

The Use of Robotic Technology in the Healthcare of People above the Age of 65-A Systematic Review

AIM

The integration of robots can help provide solutions in regards to the need for an increase in resources in healthcare. The aim of this review was to identify how robots are utilized in the healthcare of people who are over the age of 65 and how this population experiences interacting with healthcare robots.

DESIGN

A systematic literature review with an integrated design was conducted.

METHODS

A literature search was performed in the electronic databases CINAHL via EBSCO, EMBASE, and Medline via Ovid. Content analysis was performed to assess the studies that were included in this review.

RESULTS

A total of 14 articles were included. Participants in the studies included 453 older people ranging from 65 to 108 years of age. Nine of the studies focused on people with dementia or cognitive impairment. Seven studies included different types of socially assistive human-like robots, six of the studies included two different types of animal-like robots, and one study focused on a robotic rollator. The robots mainly served as social assistive- or engagement robots.

Effectiveness of mHealth Interventions in Medication Adherence among Patients with Cardiovascular Diseases: A Systematic Review

mHealth interventions have been reported to improve adherence to long-term therapies in chronic conditions. Therefore, this study aimed at determining the effectiveness of mHealth interventions in medication adherence among patients with cardiovascular diseases (CVDs), a leading cause of mortality globally. Relying on our inclusion criteria and the PRISMA recommendations, a literature search was carried out in the PubMed, Medline, and ProQuest databases for primary studies that investigated the impact of mHealth on medication adherence for cardiovascular disease (CVD) between 2000–2021. A total of 23 randomized controlled trials with 34,915 participants matched the selection criteria. The mHealth interventions used included text messages, mobile phone applications, and voice calls, which were used either as a single intervention or combined. Additionally, studies on enhancing drug adherence had contradictory findings: most of the studies elaborated positive results; however, six studies were unable to reveal any significant effect. Finally, a risk bias analysis revealed varying outcomes across all studies. This review, as a whole, supported the notion that mHealth interventions can be effective in improving adherence to CVD medication even though they could not improve adherence to all CVD medications when compared with controls. Further trials with more refined designs integrated with comprehensive interventions are needed to produce better health outcomes.

Feasibility and Acceptability of an Internet of Things-Enabled Sedentary Behavior Intervention: Mixed Methods Study

BACKGROUND

Encouraging office workers to break up prolonged sedentary behavior (SB) at work with regular microbreaks can be beneficial yet challenging. The Internet of Things (IoT) offers great promise for delivering more subtle and hence acceptable behavior change interventions in the workplace. We previously developed an IoT-enabled SB intervention, called WorkMyWay, by applying a combination of theory-informed and human-centered design approaches. According to the Medical Research Council's framework for developing and evaluating complex interventions such as WorkMyWay, process evaluation in the feasibility phase can help establish the viability of novel modes of delivery and identify facilitators and barriers to successful delivery.

OBJECTIVE

This study aims to evaluate the feasibility and acceptability of the WorkMyWay intervention and its technological delivery system.

METHODS

A mixed methods approach was adopted. A sample of 15 office workers were recruited to use WorkMyWay during work hours for 6 weeks. Questionnaires were administered before and after the intervention period to assess self-report occupational sitting and physical activity (OSPA) and psychosocial variables theoretically aligned with prolonged occupational SB (eg, intention, perceived behavioral control, prospective memory and retrospective memory of breaks, and automaticity of regular break behaviors). Behavioral and interactional data were obtained through the system database to determine adherence, quality of delivery, compliance, and objective OSPA. Semistructured interviews were conducted at the end of the study, and a thematic analysis was performed on interview transcripts.

RESULTS

All 15 participants completed the study (attrition=0%) and on average used the system for 25 tracking days (out of a possible 30 days; adherence=83%). Although no significant change was observed in either objective or self-report OSPA, postintervention improvements were significant in the automaticity of regular break behaviors (t₁₄=2.606; P=.02), retrospective memory of breaks (t₁₄=7.926; P<.001), and prospective memory of breaks (t₁₄=-2.661; P=.02). The qualitative analysis identified 6 themes, which lent support to the high acceptability of WorkMyWay, though delivery was compromised by issues concerning Bluetooth connectivity and factors related to user behaviors. Fixing technical issues, tailoring to individual differences, soliciting organizational supports, and harnessing interpersonal influences could facilitate delivery and enhance acceptance.

CONCLUSIONS

It is acceptable and feasible to deliver an SB intervention with an IoT system that involves a wearable activity tracking device, an app, and a digitally augmented everyday object (eg, cup). More industrial design and technological development work on WorkMyWay is warranted to improve delivery. Future research should seek to establish the broad acceptability of similar IoT-enabled interventions while expanding the range of digitally augmented objects as the modes of delivery to meet diverse needs.

Developing Culturally Tailored Mobile Web App Education to Promote Breast Cancer Screening: Knowledge, Barriers, and Needs Among American Indian Women

American Indian (AI) women face disproportionate rates of breast cancer mortality and cancer disparities. This study conducted qualitative research to assess perspectives of AI women towards breast cancer screening, knowledge, barriers, and needs about mobile web app-based education to promote breast cancer screening. This study, in collaboration with the Yankton Sioux Tribe (YST), followed a community-based participatory research approach and conducted two focus groups with a total of 22 YST women aged 40-70 years living on reservation in rural South Dakota. Each group consisted of 11 local professionals working in healthcare and social services and community members. A grounded theory was used for the qualitative analysis. A large portion of participants reported having prior knowledge about breast cancer and screening methods, yet lacked awareness of the detailed procedure and recommended guidelines. Competing priorities and cost of mammograms were noted as major barriers to screening. Participants wanted to learn-in a convenient and easy-to-understand manner-more about breast cancer and prevention from a credible source. Both groups were favorable toward novel educational tools, such as the mobile web app education, and cited potential health benefits, particularly for women aged 40s to 60s. Our findings highlighted the importance of creating effective, culturally tailored educational interventions built into programs specific to AIs to increase understanding about breast cancer screening and promote screening behaviors among AI women. Particular attention to how AIs' culture, beliefs, and barriers are implicated in screening behaviors could help with developing culturally tailored health education tools for this population.

Assessment and Disruption of Ruminative Episodes to Enhance Mobile Cognitive Behavioral Therapy Just-in-Time Adaptive Interventions in Clinical Depression: Pilot Randomized Controlled Trial

BACKGROUND

A just-in-time adaptive intervention (JITAI) is "designed to address the dynamically changing needs of individuals via the provision of the type or amount of support needed, at the right time when needed." If and how rumination-focused cognitive behavioral therapy (RFCBT), the gold standard, blocks emotional cascades underlying rumination is unclear. Furthermore, cognitive behavioral therapy has been successfully used as a mobile variant, but RFCBT has not been adapted for a mobile variant (mobile RFCBT [MRFCBT]) or for a JITAI variant.

OBJECTIVE

This study aimed to pilot-test a fully automated JITAI leveraging RFCBT and ways to identify and block cascading depressive rumination.

METHODS

Patients in therapy for clinical depression were recruited for a randomized controlled trial (RCT). After consenting to be part of the RCT, they were randomly assigned to either of the 2 mobile versions of the RFCBT conditions personalized to the individual's rumination timing patterns (JITAI-MRFCBT) or a no-treatment control condition through a double-blind procedure. Although the initial design was to have a 3-armed trial with 2 JITAI conditions (a JITAI and a narrative JITAI condition), we later opted to collapse those 2 conditions into 1 JITAI condition because of the low number of participants. All participants were recruited and participated through their smartphones, receiving 5 SMS text message reminders on each of the 35 days to self-report their rumination-related symptoms (eg, rumination episodes and duration). In the JITAI-MRFCBT condition, they also received treatment materials. The first 7 days provided a rumination baseline, and the last 7 days provided a postintervention rumination value. In total, 42% (25/59) of volunteers were eligible and provided their phone numbers, 20% (5/25) of whom never replied to the SMS text message reminding them to start the RCT. A total of 90% (18/20) of volunteers completed it (ie, finishing, as prespecified, 80% of the questionnaires and training tasks) and, therefore, were included in the analysis.

RESULTS

Using independent 2-tailed t tests with bootstrapping, results showed that participants in the JITAI-MRFCBT condition, compared with those in the control condition, reported a greater reduction in counts of rumination episodes (mean -25.28, SD 14.50 vs mean 1.44, SD 4.12, P<.001) and greater reduced average time (minutes) spent in rumination (mean -21.53, SD 17.6 vs mean 1.47, SD 1.5; P=.04). Results also suggest that, compared with those in the control group, those in treatment reduced ruminative carryover from one episode to the next.

CONCLUSIONS

The results suggest that JITAI-MRFCBT may reduce negative rumination by providing RFCBT just in time following rumination, thereby blocking the next rumination episode using the same trigger. This study supports a subsequent, full-scale JITAI and the importance of leveraging mobile smartphone technology with MRFCBT to curb depressive symptoms.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04554706; https://clinicaltrials.gov/ct2/show/NCT04554706.

The results of following type 2 diabetes patients with mobile health services during the COVID-19 pandemic

OBJECTIVE

The aim of this study is to determine the level of compliance with treatment and achieving metabolic goals in type 2 diabetes mellitus (T2DM) patients who are remotely monitored with mobile health (mHealth) technologies during the pandemic.

METHODS

A total number of 86 patients were included in the study. Data from two periods were used: from 1 month before the date when the first COVID-19 case in Turkiye was reported on March 11, 2020 (Febraury 10, 2020-March 31, 2020) and from the pandemic was severe between April 01, 2020 and May 31, 2020. Participants' mean blood glucose, step count, blood pressure, body weight, and diet compliance levels were evaluated.

RESULTS

When the blood sugar, blood pressure, and weight averages of the patients were compared between the pre-pandemic period and the pandemic months separately, no significant difference was observed. However, it was observed that the number of steps decreased significantly compared to the period before the pandemic (p<0.05). It was determined that 88% of the participants were able to access health services without applying to the hospital.

CONCLUSION

In this study, we showed that patients with T2DM who were followed up with mHealth technologies provided the necessary metabolic control and compliance with the treatment during the pandemic.

Changes in patient perceptions regarding ChatGPT-written explanations on lifestyle modifications for preventing urolithiasis recurrence

Purpose

Artificial Intelligence (AI) imitating human-like language, such as ChatGPT, has impacted lives throughout various multidisciplinary fields. However, despite these innovations, it is unclear how well its implementation will assist patients in clinical situations. We evaluated changes in patient perceptions regarding AI before and after reading a ChatGPT-written explanation.

Materials and methods

In total, 24 South Korean patients receiving urolithiasis treatment were surveyed through questionnaires. The ChatGPT explanatory note was provided between the first and second questionnaires, detailing lifestyle modifications for preventing urolithiasis recurrence. The study questionnaire was the Korean version of the General Attitudes toward Artificial Intelligence Scale, including positive and negative attitude items. Wilcoxon signed-rank tests were accomplished to compare questionnaire scores before and after receiving the explanatory note. A linear regression analysis with stepwise elimination was used to assess variable (demographic data) accuracy in predicting outcomes.

Results

There were significant differences between total negative questionnaire scores pre- and post-surveys of ChatGPT, but not in the positive scores. Among variables, only education level significantly influenced mean score differences in the negative questionnaires.

Conclusions

The negative perception change among urolithiasis patients after receiving the explanatory note provided by the AI chatbot program was observed, evidencing that patients with lower education levels expressed a more negative response. The explanatory note provided by the AI chatbot program could provoke an adverse change in AI perception. Negative human responses must be considered to improve and adapt new technology in health care. Only through changing patient perspectives will upgraded AI technology integrate into medical healthcare.

Testing the Mystic School Mobile Application to Promote Active Commuting to School in Spanish Adolescents: The PACO Study

Active commuting to and/or from school (ACS) is an opportunity to increase daily physical activity (PA) levels in young people. Mobile-device interventions focused on promoting the practice of health-related PA can be more cost-effective than traditional interventions in this population.

OBJECTIVE

To analyze the adolescents' opinion of the mobile application (app) Mystic School, which was designed to promote ACS in Spanish adolescents.

METHODS

A total of 44 students (14-15 years old) from Granada and Jaén participated in the test of the Mystic School app during two phases: phase 1 (n = 10) for 2 weeks and phase 2 (n = 34) for 1 month. Each phase included an app presentation, a follow-up, and focus group sessions. The qualitative analysis was carried out through NVivo software.

RESULTS

In phase 1, adolescents reported improvements in the design and functioning, such as the avatar movement, virtual steps utilities, and multiplayer function. These suggestions were included in phase 2. After phase 2, adolescents reported that it is important to add the possibility of playing without an Internet connection to the game, to include more competitive options, prizes, and to increase the difficulty of the levels. In both phases, problems with the step number counting remained.

CONCLUSION

The Mystic School app can be a useful tool for the physical education teacher to integrate the content from this curriculum related to the promotion of PA, such as ACS.

Needs and views on healthy lifestyles for the prevention of dementia and the potential role for mobile health (mHealth) interventions in China: a qualitative study

OBJECTIVES

Over the coming decades, China is expected to face the largest worldwide increase in dementia incidence. Mobile health (mHealth) may improve the accessibility of dementia prevention strategies, targeting lifestyle-related risk factors. Our aim is to explore the needs and views of Chinese older adults regarding healthy lifestyles to prevent cardiovascular disease (CVD) and dementia through mHealth, supporting the Prevention of Dementia using Mobile Phone Applications (PRODEMOS) study.

DESIGN

Qualitative semi-structured interview study, using thematic analysis.

SETTING

Primary and secondary care in Beijing and Tai'an, China.

PARTICIPANTS

Older adults aged 55 and over without dementia with an increased dementia risk, possessing a smartphone. Participants were recruited through seven hospitals participating in the PRODEMOS study, purposively sampled on age, sex, living area and history of CVD and diabetes.

RESULTS

We performed 26 interviews with participants aged 55-86 years. Three main themes were identified: valuing a healthy lifestyle, sociocultural expectations and need for guidance. First, following a healthy lifestyle was generally deemed important. In addition to generic healthy behaviours, participants regarded certain specific Chinese lifestyle practices as important to prevent disease. Second, the sociocultural context played a crucial role, as an important motive to avoid disease was to limit the care burden put on family members. However, time-consuming family obligations and other social values could also impede healthy behaviours such as regular physical activity. Finally, there seemed to be a need for reliable and personalised lifestyle advice and for guidance from a health professional.

CONCLUSIONS

The Chinese older adults included in this study highly value a healthy lifestyle. They express a need for personalised lifestyle support in order to adopt healthy behaviours. Potentially, the PRODEMOS mHealth intervention can meet these needs through blended lifestyle support to improve risk factors for dementia and CVD.

TRIAL REGISTRATION NUMBER

ISRCTN15986016; Pre-results.

Advancing digital health Equity: Directions for behavioral and social science research

The field of digital health is evolving rapidly and encompasses a wide range of complex and changing technologies used to support individual and population health. The COVID-19 pandemic has augmented digital health expansion and significantly changed how digital health technologies are used. To ensure that these technologies do not create or exacerbate existing health disparities, a multi-pronged and comprehensive research approach is needed. In this commentary, we outline five recommendations for behavioral and social science researchers that are critical to promoting digital health equity. These recommendations include: (i) centering equity in research teams and theoretical approaches, (ii) focusing on issues of digital health literacy and engagement, (iii) using methods that elevate perspectives and needs of underserved populations, (iv) ensuring ethical approaches for collecting and using digital health data, and (v) developing strategies for integrating digital health tools within and across systems and settings. Taken together, these recommendations can help advance the science of digital health equity and justice.

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.

Eliciting Information Needs of Child Patients: Adapting the Kano Model to the Design of mHealth Applications

BACKGROUND

 Health care services are increasingly being digitized, but extant literature shows that digital technologies and applications are often developed without careful consideration of user needs. Research is needed to identify and investigate best-in-class methods to support user-centered design of mHealth applications.

OBJECTIVES

 The article investigates how the Kano model can be adapted and used for the purpose of eliciting child patients' information needs during the design phase of mHealth application development. The aim is to demonstrate its applicability for collecting and analyzing patient-centered data that are key to designing technology-supported solutions for health management.

METHODS

 The article is based on a mixed-methods case study, which includes interviews with 21 patients aged 6 to 18. Structured interviews are analyzed based on prescriptions of the Kano model. Semi-structured interviews about child patients' information needs are analyzed thematically.

RESULTS

 The results demonstrate several improvements to the Kano model that take into account the difficulties of effectively communicating with child patients. The combination of two types of interviews offers unique insights into the what, how, and why of patients' needs. Adaptation of the Kano model, simplification of response options, and participation of child patients' parents in interviews facilitate data collection.

CONCLUSIONS

 The article shows how the Kano model can be adapted to provide an effective means of eliciting child patients' needs. Adapting the model by combining structured and semi-structured interviews makes it a powerful tool in designing mHealth applications.