Gamified Mobile App (MobERAS) for Telemonitoring Patients in the Postoperative Period Based on the Enhanced Recovery after Surgery Program: Development and Validation Study.

BACKGROUND: Digital technology and gamified apps can be useful in the health care context. Gamification uses technology to influence users' actions and motivations through experiences that resemble games. Patient adherence to the enhanced recovery after surgery (ERAS) program is crucial for achieving early recovery after surgery and continuous monitoring is essential for obtaining good results. OBJECTIVE: This study aimed to describe the development and validation of a mobile app for enhanced recovery after surgery (MobERAS), a gamified mobile health app for telemonitoring patients in the postoperative period based on the ERAS program, and to evaluate its functionality and usability and the experience of patients, health care professionals, and computer professionals with its use. METHODS: We developed MobERAS for postoperative telemonitoring, with active participation of patients in the process, and offering availability of real-time information for the health team. The app development process included idealization, interdisciplinary team formation, potential needs assessment, and product deployment. Usability tests were conducted throughout the development process with improvements, technical adjustments, and updates. After finalization, comprehensive verification tests were performed. The parameters evaluated are those that can influence the length of hospital stay, such as nausea, vomiting, pain scales, return to normal gastrointestinal function, and thromboembolic events. MobERAS was designed to be downloaded by users on their phones, tablets, or other mobile devices and to provide postoperative data. The app has a GPS that monitors the patient's walking time and distance and is connected to a virtual database that stores the collected data. RESULTS: Women undergoing medium and major gynecologic oncologic surgeries were included. We included 65 patients with an average age of 53.2 (SD 7.4, range 18-85) years. The time of use ranged from 23.4 to 70 hours (mean 45.1, SD 19.2 hours). Regarding adherence to the use of MobERAS, the mean fill rate was 56.3% (SD 12.1%, range 41.7%-100%), and ambulation data were obtained for 60 (92.3%) of the 65 patients. The researcher had access to the data filled out by the patients in real time. There was good acceptance of the use of MobERAS by the patients, with good evaluation of the app's usability. MobERAS was easy to use and considered attractive because of its gamified design. The app was rated as good or very good in all items by health care professionals (n=20) and professionals specializing in technological innovation (n=10). CONCLUSIONS: MobERAS is easy to use, safe, well accepted by patients, and well evaluated by experts. It can be of great use in clinical surgical practice and an important tool for greater engagement of patients and health care professionals with the ERAS program.

Developing a Guided Web App for Postpartum Depression Symptoms: User-Centered Design Approach.

BACKGROUND: Psychological internet-based interventions have shown promise in preventing and treating perinatal depression, but their effectiveness can be hindered by low user engagement. This challenge often arises from a misalignment between technology attributes, user needs, and context. A user-centered, iterative approach involving all stakeholders is recommended. OBJECTIVE: In this paper, we aimed to develop a user-friendly psychological internet-based intervention aimed at addressing the symptoms of perinatal depression through an iterative, user-centered approach. METHODS: The development process followed the Center for eHealth Research and Disease Management Roadmap phases of contextual inquiry, value specification, and design. It involved a comprehensive literature review, 2 surveys, 10 focus groups, 5 usability interviews, and 1 technical pilot. RESULTS: The contextual inquiry revealed a demand for accessible interventions for perinatal mental health, with internet-based solutions seen as viable options. Insights from the literature influenced intervention content and features. Stakeholders' openness to the intervention became evident during this phase, along with the integration of the first set of values. Initially, we assessed the broader perinatal context to identify the optimal period for the intervention. On the basis of the findings and practical considerations, we decided to specifically target postpartum depression symptoms. The value specification phase further defined the central values and translated them into requirements. In the design phase, feedback was obtained on the user experience of an early digital prototype and on the prototype's final version. The resulting intervention, named Mamá, te entiendo ("Mom, I get you"), is a guided web app based on cognitive behavioral therapy principles, integrating elements from attachment and mentalization theories. It aims to reduce depressive symptoms in women during the first months postpartum and consists of 6 core sequential modules, along with 3 additional modules, including 5 case examples illustrating depressive symptoms and therapeutic techniques. The intervention provides homework exercises and offers users the opportunity to receive feedback from an e-coach through the web app. CONCLUSIONS: This study emphasizes the importance of a user-centered and iterative development process for psychological internet-based interventions. This process helps clarify user needs and provides valuable feedback on service design and quality, ultimately having the potential to enhance the utility and, presumably, the effectiveness of the intervention. The Discussion section shares valuable insights from the project, such as the value of the requirement sessions.

WhatsApp-based intervention in urban Colombia to support the prevention of arboviral diseases: a feasibility study.

Arboviral diseases remain a significant health concern worldwide, with over half the world's population at risk for dengue alone. Without a vaccine or targeted treatment, the most effective strategy of prevention is vector management with community involvement. mHealth interventions, like WhatsApp, offer promising results for engaging communities and promoting healthier behaviors. This study explores the feasibility of integrating WhatsApp in vector control activities to improve arbovirus prevention in Colombia. A mixed-methods approach was employed to assess the WhatsApp-based intervention. WhatsApp messages were sent to 45 community women for 5 weeks to increase their knowledge and practices about dengue, Zika, and chikungunya. Pre-and-post surveys and focus group discussions were conducted in community settings to measure the feasibility and acceptability of this intervention. Chat reviews were done to assess the usability of users. A total of 1566 messages were exchanged in 45 WhatsApp chats. High acceptance and good usability (82% of users used the app for replying) were reported in this study. WhatsApp messages were perceived as short, clear, and enjoyable. Users liked the frequency, and design of messages. Pre- and post-surveys demonstrated improvements in the knowledge and practices of arboviral diseases. The intention to apply this knowledge in practice was reflected in a significant improvement, particularly in cleaning the laundry tank once a week (pre 62.1% to post 89.6%, p < 0.008). This study suggests that using WhatsApp as an additional tool could be a feasible, acceptable, and affordable strategy for improving the adoption of better practices in the prevention of arboviral diseases.

Transdisciplinary research before, during and after COVID-19 vaccination in Chile: a virtuoso collaboration with future perspectives.

The COVID-19 pandemic presented numerous challenges that required immediate attention to mitigate its devastating consequences on a local and global scale. In March 2020, the Chilean government, along with health and science authorities, implemented a strategy aimed at generating relevant evidence to inform effective public health decisions. One of the key strengths of this strategy was the active involvement of the scientific community, employing transdisciplinary approaches to address critical questions and support political decision-making. The strategy promoted collaborations between the government, public and private institutions, and transdisciplinary academic groups throughout each phase of the pandemic. By focusing on pressing problems and questions, this approach formed the foundation of this report which reflects the collaborative effort throughout the pandemic of individuals from the Instituto de Sistemas Complejos de Ingeniería (ISCI), the Faculty of Medicine of the University of Chile, government authorities and industry. Early in the pandemic, it became crucial to gather evidence on how to minimize the impact of infection and disease while awaiting the availability of vaccines. This included studying the dynamics of SARS-CoV-2 infection in children, assessing the impact of quarantines on people's mobility, implementing strategies for widespread SARS-CoV-2 polymerase chain reaction (PCR) testing, and exploring pool testing for large populations. The urgent need to reduce disease severity and transmission posed a significant challenge, as it was essential to prevent overwhelming healthcare systems. Studies were conducted to predict ICU bed requirements at the local level using mathematical models. Additionally, novel approaches, such as using cellphone mobility-based technology to actively identify infected individuals, and to optimize population sampling, were explored following the first wave of the pandemic. Chile took early action in addressing vaccination through a high-level scientific board, before vaccines became available. Studies conducted during this period included population-based immunologic evaluations of different vaccines, which helped build confidence in the population and supported the need for booster doses and potential vaccination of children. These studies and collaborations, which will be discussed here, have provided valuable insights and will inform future approaches in a post-pandemic world. Importantly, highly conservative estimates indicate that 3,000 lives and more than 300 million USD were saved by this academic-public-private collaborative effort.

Developing a Multiprofessional Mobile App to Enhance Health Habits in Older Adults: User-Centered Approach.

BACKGROUND: Although comprehensive lifestyle habits are crucial for healthy aging, their adherence tends to decline as individuals grow older. Sustaining a healthy life over time poses a motivational challenge. Some digital tools, such as smartphone apps aimed at promoting healthy habits, have been used to counteract this decline. However, a more profound investigation is necessary into the diverse experiences of users, particularly when it concerns older adults or those who are unfamiliar with information and communications technologies. OBJECTIVE: We aimed to develop a mobile app focused on promoting the health of older adults based on the principles of software engineering and a user-centered design. The project respected all ethical guidelines and involved the participation of older adults at various stages of the development of the app. METHODS: This study used a mixed methods approach, combining both quantitative and qualitative methodologies for data collection. The study was conducted in Ribeirão Prêto, São Paulo, Brazil, and involved 20 older adults of both genders who were aged ≥60 years and enrolled in the Physical Education Program for the Elderly at the University of São Paulo. The research unfolded in multiple phases, encompassing the development and refinement of the app with active engagement from the participants. RESULTS: A total of 20 participants used a mobile health app with an average age of 64.8 (SD 2.7) years. Most participants had a high school education, middle-class status, and varying health literacy (mean score 73.55, SD 26.70). Overall, 90% (18/20) of the participants owned smartphones. However, 20% (4/20) of the participants faced installation challenges and 30% (6/20) struggled with web-based searches. The focus groups assessed app usability and satisfaction. Adjustments increased satisfaction scores significantly (Suitability Assessment of Materials: 34.89% to 70.65%; System Usability Scale: 71.23 to 87.14). Participant feedback emphasized font size, navigation, visual feedback, and personalization, and suggestions included health device integration, social interaction, and in-app communication support. CONCLUSIONS: This study contributes to the development of health care technologies tailored to the older adult population, considering their specific needs. It is anticipated that the resulting app will serve as a valuable tool for promoting healthy habits and enhancing the quality of life for older adults.

Technology-Supported Guidance Models to Stimulate Nursing Students' Self-Efficacy in Clinical Practice: Scoping Review.

BACKGROUND: In nursing education, bridging the gap between theoretical knowledge and practical skills is crucial for developing competence in clinical practice. Nursing students encounter challenges in acquiring these essential skills, making self-efficacy a critical component in their professional development. Self-efficacy pertains to individual's belief in their ability to perform tasks and overcome challenges, with significant implications for clinical skills acquisition and academic success. Previous research has underscored the strong link between nursing students' self-efficacy and their clinical competence. Technology has emerged as a promising tool to enhance self-efficacy by enabling personalized learning experiences and in-depth discussions. However, there is a need for a comprehensive literature review to assess the existing body of knowledge and identify research gaps. OBJECTIVE: The aim of this study is to systematically map and identify gaps in published studies on the use of technology-supported guidance models to stimulate nursing students' self-efficacy in clinical practice. METHODS: This scoping review followed the framework of Arksey and O'Malley and was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR). A systematic, comprehensive literature search was conducted in ERIC, CINAHL, MEDLINE, Embase, PsycINFO, and Web of Science for studies published between January 2011 and April 2023. The reference lists of the included papers were manually searched to identify additional studies. Pairs of authors screened the papers, assessed eligibility, and extracted the data. The data were thematically organized. RESULTS: A total of 8 studies were included and four thematic groups were identified: (1) technological solutions for learning support, (2) learning focus in clinical practice, (3) teaching strategies and theoretical approaches for self-efficacy, and (4) assessment of self-efficacy and complementary outcomes. CONCLUSIONS: Various technological solutions were adopted in the guidance models to stimulate the self-efficacy of nursing students in clinical practice, leading to positive findings. A total of 7 out of 8 studies presented results that were not statistically significant, highlighting the need for further refinement of the applied interventions. Nurse educators play a pivotal role in applying learning strategies and theoretical approaches to enhance nursing students' self-efficacy, but the contributions of nurse preceptors and peers should not be overlooked. Future studies should consider involving users in the intervention process and using validated instruments tailored to the studies' intervention objectives, ensuring relevance and enabling comparisons across studies.

Recruiting hard-to-reach populations via respondent driven sampling for mobile phone surveys in Colombia: a qualitative study.

BACKGROUND: Uptake of mobile phone surveys (MPS) is increasing in many low- and middle-income countries, particularly within the context of data collection on non-communicable diseases (NCDs) behavioural risk factors. One barrier to collecting representative data through MPS is capturing data from older participants.Respondent driven sampling (RDS) consists of chain-referral strategies where existing study subjects recruit follow-up participants purposively based on predefined eligibility criteria. Adapting RDS strategies to MPS efforts could, theoretically, yield higher rates of participation for that age group. OBJECTIVE: To investigate factors that influence the perceived acceptability of a RDS recruitment method for MPS involving people over 45 years of age living in Colombia. METHODS: An MPS recruitment strategy deploying RDS techniques was piloted to increase participation of older populations. We conducted a qualitative study that drew from surveys with open and closed-ended items, semi-structured interviews for feedback, and focus group discussions to explore perceptions of the strategy and barriers to its application amongst MPS participants. RESULTS: The strategy's success is affected by factors such as cultural adaptation, institutional credibility and public trust, data protection, and challenges with mobile phone technology. These factors are relevant to individuals' willingness to facilitate RDS efforts targeting hard-to-reach people. Recruitment strategies are valuable in part because hard-to-reach populations are often most accessible through their contacts within their social network who can serve as trust liaisons and drive engagement. CONCLUSIONS: These findings may inform future studies where similar interventions are being considered to improve access to mobile phone-based data collection amongst hard-to-reach groups.

Embodied Conversational Agents Providing Motivational Interviewing to Improve Health-Related Behaviors: Scoping Review.

BACKGROUND: Embodied conversational agents (ECAs) are advanced human-like interfaces that engage users in natural face-to-face conversations and interactions. These traits position ECAs as innovative tools for delivering interventions for promoting health-related behavior adoption. This includes motivational interviewing (MI), a therapeutic approach that combines brief interventions with motivational techniques to encourage the adoption of healthier behaviors. OBJECTIVE: This study aims to identify the health issues addressed by ECAs delivering MI interventions, explore the key characteristics of these ECAs (eg, appearance, dialogue mechanism, emotional model), analyze the implementation of MI principles and techniques within ECAs, and examine the evaluation methods and primary outcomes of studies that use ECAs providing MI interventions. METHODS: We conducted a scoping review following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) methodology. Our systematic search covered the PubMed, Scopus, IEEE Xplore, ACM Digital, and PsycINFO databases for papers published between January 2008 and December 2022. We included papers describing ECAs developed for delivering MI interventions targeting health-related behaviors and excluded articles that did not describe ECAs with human appearances and without the necessary evaluation or MI explanation. In a multistage process, 3 independent reviewers performed screening and data extraction, and the collected data were synthesized using a narrative approach. RESULTS: The initial search identified 404 articles, of which 3.5% (n=14) were included in the review. ECAs primarily focused on reducing alcohol use (n=5, 36%), took on female representations (n=9, 64%), and gave limited consideration to user ethnicity (n=9, 64%). Most of them used rules-driven dialogue mechanisms (n=13, 93%), include emotional behavior to convey empathy (n=8, 57%) but without an automatic recognition of user emotions (n=12, 86%). Regarding MI implementation, of 14 studies, 3 (21%) covered all MI principles, 4 (29%) included all processes, and none covered all techniques. Most studies (8/14, 57%) conducted acceptability, usability, and user experience assessments, whereas a smaller proportion (4/14, 29%) used randomized controlled trials to evaluate behavior changes. Overall, the studies reported positive results regarding acceptability, usability, and user experience and showed promising outcomes in changes in attitudes, beliefs, motivation, and behavior. CONCLUSIONS: This study revealed significant advancements in the use of ECAs for delivering MI interventions aimed at promoting healthier behaviors over the past 15 years. However, this review emphasizes the need for a more in-depth exploration of ECA characteristics. In addition, there is a need for the enhanced integration of MI principles, processes, and techniques into ECAs. Although acceptability and usability have received considerable attention, there is a compelling argument for placing a stronger emphasis on assessing changes in attitudes, beliefs, motivation, and behavior. Consequently, inclusion of more randomized controlled trials is essential for comprehensive intervention evaluations.

Human mobility and socioeconomic datasets of the Rio de Janeiro metropolitan area.

This data descriptor presents two main datasets and a set of auxiliary files. The mobility dataset presents a long-term study of human mobility in the Rio de Janeiro Metropolitan Area (RJMA) performed in the entire year of 2014 based on mobile phone data. The socioeconomic dataset presents selected socioeconomic variables of the Brazilian 2010 census. A set of auxiliary files is included to present georeferenced information and geographic features (shapefiles) and data used to validate the mobility estimates. The human mobility estimation was carried out using a methodology that allows direct integration with census data, based on an approximation of the geographic boundaries of census units by an aggregation of Voronoi polygons of the mobile phone antennas. The study area is the Brazilian local area 21, which includes the entire RJMA and four other municipalities. The mobility dataset is divided into two files: one is an estimation of the origin-destination (OD) matrix per day, and the other is a visitors' dataset where the number of visitors of each location is estimated in four shifts each day. The socioeconomic dataset presents information of 55 variables for each location, which have been used in different studies and present the longest human mobility dataset available for public use.

Development and Implementation of DIALOG+S in the School Setting as a Tool for Promoting Adolescent Mental Well-Being and Resilience in a Post-Armed Conflict Area in Colombia: Exploratory Cluster Randomized Controlled Trial.

BACKGROUND: Educational settings are ideal for promoting mental well-being and resilience in children. The challenges of the COVID-19 pandemic made evident the important role that teachers and school counselors play in the mental health of their students. Therefore, it is imperative to develop and implement cost-effective interventions that allow them to identify and address mental health problems early, especially in post-armed conflict areas, to reduce the burden of mental disorders in this population. OBJECTIVE: This study aimed to adapt an existing patient-focused digital intervention called DIALOG+ from an adult clinical setting to an adolescent educational setting and to assess the feasibility, acceptability, and estimated effect of implementing this intervention as a tool for promoting quality of life, mental well-being, and resilience. METHODS: We conducted an exploratory mixed methods study in 2 public schools in postconflict areas in Tolima, Colombia. This study was conducted in 3 phases. In the adaptation phase, focus groups were conducted with students and teachers to identify changes required in DIALOG+ for it to be used in the school setting. The exploration phase consisted of an exploratory cluster randomized controlled trial. A total of 14 clusters, each with 1 teacher and 5 students, were randomly allocated to either the experimental (DIALOG+S) group or to an active control group (counseling as usual). Teachers in both groups delivered the intervention once a month for 6 months. Through screening scales, information was collected on mental health symptoms, quality of life, self-esteem, resilience, and family functionality before and after the intervention. Finally, the consolidation phase explored the experiences of teachers and students with DIALOG+S using focus group discussions. RESULTS: The changes suggested by participants in the adaptation phase highlighted the central importance of the school setting in the mental health of adolescents. In the exploratory phase, 70 participants with a mean age of 14.69 (SD 2.13) years were included. Changes observed in the screening scale scores of the intervention group suggest that the DIALOG+S intervention has the potential to improve aspects of mental health, especially quality of life, resilience, and emotional symptoms. The consolidation phase showed that stakeholders felt that using this intervention in the school setting was feasible, acceptable, and an enriching experience that generated changes in the perceived mental health and behavior of participants. CONCLUSIONS: Our results are encouraging and show that the DIALOG+S intervention is feasible and acceptable as a promising opportunity to promote well-being and prevent and identify mental health problems in the school context in a postconflict area in Colombia. Larger, fully powered studies are warranted to properly assess the efficacy and potential impact of the intervention and to refine implementation plans. TRIAL REGISTRATION: International Standard Randomised Controlled Trial Number (ISRCTN) registry ISRCTN14396374; https://www.isrctn.com/ISRCTN14396374. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/40286.

Wearable Devices to Diagnose and Monitor the Progression of COVID-19 Through Heart Rate Variability Measurement: Systematic Review and Meta-Analysis.

BACKGROUND: Recent studies have linked low heart rate variability (HRV) with COVID-19, indicating that this parameter can be a marker of the onset of the disease and its severity and a predictor of mortality in infected people. Given the large number of wearable devices that capture physiological signals of the human body easily and noninvasively, several studies have used this equipment to measure the HRV of individuals and related these measures to COVID-19. OBJECTIVE: The objective of this study was to assess the utility of HRV measurements obtained from wearable devices as predictive indicators of COVID-19, as well as the onset and worsening of symptoms in affected individuals. METHODS: A systematic review was conducted searching the following databases up to the end of January 2023: Embase, PubMed, Web of Science, Scopus, and IEEE Xplore. Studies had to include (1) measures of HRV in patients with COVID-19 and (2) measurements involving the use of wearable devices. We also conducted a meta-analysis of these measures to reduce possible biases and increase the statistical power of the primary research. RESULTS: The main finding was the association between low HRV and the onset and worsening of COVID-19 symptoms. In some cases, it was possible to predict the onset of COVID-19 before a positive clinical test. The meta-analysis of studies reported that a reduction in HRV parameters is associated with COVID-19. Individuals with COVID-19 presented a reduction in the SD of the normal-to-normal interbeat intervals and root mean square of the successive differences compared with healthy individuals. The decrease in the SD of the normal-to-normal interbeat intervals was 3.25 ms (95% CI -5.34 to -1.16 ms), and the decrease in the root mean square of the successive differences was 1.24 ms (95% CI -3.71 to 1.23 ms). CONCLUSIONS: Wearable devices that measure changes in HRV, such as smartwatches, rings, and bracelets, provide information that allows for the identification of COVID-19 during the presymptomatic period as well as its worsening through an indirect and noninvasive self-diagnosis.

An Automated Electronic System in a Motorized Wheelchair for Telemonitoring: Mixed Methods Study Based on Internet of Things.

BACKGROUND: Wheelchair positioning systems can prevent postural deficits and pressure injuries. However, a more effective professional follow-up is needed to assess and monitor positioning according to the specificities and clinical conditions of each user. OBJECTIVE: This study aims to present the concept of an electronic system embedded in a motorized wheelchair, based on the Internet of Things (IoT), for automated positioning as part of a study on wheelchairs and telemonitoring. METHODS: We conducted a mixed methods study with a user-centered design approach, interviews with 16 wheelchair users and 66 professionals for the development of system functions, and a formative assessment of 5 participants with descriptive analysis to design system concepts. RESULTS: We presented a new wheelchair system with hardware and software components developed based on coparticipation with singular components in an IoT architecture. In an IoT solution, the incorporation of sensors from the inertial measurement unit was crucial. These sensors were vital for offering alternative methods to monitor and control the tilt and recline functions of a wheelchair. This monitoring and control could be achieved autonomously through a smartphone app. In addition, this capability addressed the requirements of real users. CONCLUSIONS: The technologies presented in this system can benefit telemonitoring and favor real feedback, allowing quality provision of health services to wheelchair users. User-centered development favored development with specific functions to meet the real demands of users. We emphasize the importance of future studies on the correlation between diagnoses and the use of the system in a real environment to help professionals in treatment.

Digital Platform for Continuous Monitoring of Patients Using a Smartwatch: Longitudinal Prospective Cohort Study.

BACKGROUND: Since the COVID-19 pandemic, there has been a boost in the digital transformation of the human society, where wearable devices such as a smartwatch can already measure vital signs in a continuous and naturalistic way; however, the security and privacy of personal data is a challenge to expanding the use of these data by health professionals in clinical follow-up for decision-making. Similar to the European General Data Protection Regulation, in Brazil, the Lei Geral de Proteção de Dados established rules and guidelines for the processing of personal data, including those used for patient care, such as those captured by smartwatches. Thus, in any telemonitoring scenario, there is a need to comply with rules and regulations, making this issue a challenge to overcome. OBJECTIVE: This study aimed to build a digital solution model for capturing data from wearable devices and making them available in a safe and agile manner for clinical and research use, following current laws. METHODS: A functional model was built following the Brazilian Lei Geral de Proteção de Dados (2018), where data captured by smartwatches can be transmitted anonymously over the Internet of Things and be identified later within the hospital. A total of 80 volunteers were selected for a 24-week follow-up clinical trial divided into 2 groups, one group with a previous diagnosis of COVID-19 and a control group without a previous diagnosis of COVID-19, to measure the synchronization rate of the platform with the devices and the accuracy and precision of the smartwatch in out-of-hospital conditions to simulate remote monitoring at home. RESULTS: In a 35-week clinical trial, >11.2 million records were collected with no system downtime; 66% of continuous beats per minute were synchronized within 24 hours (79% within 2 days and 91% within a week). In the limit of agreement analysis, the mean differences in oxygen saturation, diastolic blood pressure, systolic blood pressure, and heart rate were -1.280% (SD 5.679%), -1.399 (SD 19.112) mm Hg, -1.536 (SD 24.244) mm Hg, and 0.566 (SD 3.114) beats per minute, respectively. Furthermore, there was no difference in the 2 study groups in terms of data analysis (neither using the smartwatch nor the gold-standard devices), but it is worth mentioning that all volunteers in the COVID-19 group were already cured of the infection and were highly functional in their daily work life. CONCLUSIONS: On the basis of the results obtained, considering the validation conditions of accuracy and precision and simulating an extrahospital use environment, the functional model built in this study is capable of capturing data from the smartwatch and anonymously providing it to health care services, where they can be treated according to the legislation and be used to support clinical decisions during remote monitoring.

Assessing Mood With the Identifying Depression Early in Adolescence Chatbot (IDEABot): Development and Implementation Study.

BACKGROUND: Mental health status assessment is mostly limited to clinical or research settings, but recent technological advances provide new opportunities for measurement using more ecological approaches. Leveraging apps already in use by individuals on their smartphones, such as chatbots, could be a useful approach to capture subjective reports of mood in the moment. OBJECTIVE: This study aimed to describe the development and implementation of the Identifying Depression Early in Adolescence Chatbot (IDEABot), a WhatsApp-based tool designed for collecting intensive longitudinal data on adolescents' mood. METHODS: The IDEABot was developed to collect data from Brazilian adolescents via WhatsApp as part of the Identifying Depression Early in Adolescence Risk Stratified Cohort (IDEA-RiSCo) study. It supports the administration and collection of self-reported structured items or questionnaires and audio responses. The development explored WhatsApp's default features, such as emojis and recorded audio messages, and focused on scripting relevant and acceptable conversations. The IDEABot supports 5 types of interactions: textual and audio questions, administration of a version of the Short Mood and Feelings Questionnaire, unprompted interactions, and a snooze function. Six adolescents (n=4, 67% male participants and n=2, 33% female participants) aged 16 to 18 years tested the initial version of the IDEABot and were engaged to codevelop the final version of the app. The IDEABot was subsequently used for data collection in the second- and third-year follow-ups of the IDEA-RiSCo study. RESULTS: The adolescents assessed the initial version of the IDEABot as enjoyable and made suggestions for improvements that were subsequently implemented. The IDEABot's final version follows a structured script with the choice of answer based on exact text matches throughout 15 days. The implementation of the IDEABot in 2 waves of the IDEA-RiSCo sample (140 and 132 eligible adolescents in the second- and third-year follow-ups, respectively) evidenced adequate engagement indicators, with good acceptance for using the tool (113/140, 80.7% and 122/132, 92.4% for second- and third-year follow-up use, respectively), low attrition (only 1/113, 0.9% and 1/122, 0.8%, respectively, failed to engage in the protocol after initial interaction), and high compliance in terms of the proportion of responses in relation to the total number of elicited prompts (12.8, SD 3.5; 91% out of 14 possible interactions and 10.57, SD 3.4; 76% out of 14 possible interactions, respectively). CONCLUSIONS: The IDEABot is a frugal app that leverages an existing app already in daily use by our target population. It follows a simple rule-based approach that can be easily tested and implemented in diverse settings and possibly diminishes the burden of intensive data collection for participants by repurposing WhatsApp. In this context, the IDEABot appears as an acceptable and potentially scalable tool for gathering momentary information that can enhance our understanding of mood fluctuations and development.

The relationship between physical activity and interpersonal distress in college students: the chain mediating role of self-control and mobile phone addiction.

OBJECTIVE OF THE STUDY: Interpersonal relationships, as an important variable affecting the physical and mental health and future development of individuals, were used to construct a structural equation model between physical activity and interpersonal relationships in order to help college students better adapt to society and achieve a high level of mental health. METHODS: SPSS 27.0 software was used to statistically analyze the data, and Amos 28.0 software was used to construct the model between variables. The results showed that physical activity directly predicted the interpersonal relationship status of college students (ß = - 0.108, 95% CI [- 0.210, - 0.005]), and the chain mediating effect of physical activity → self-control → mobile phone addiction tendency → interpersonal relationship distress was significant (ß = - 0.012, 95% CI [- 0.033, - 0.003]). The results of this study suggest that physical activity may be viewed as an effective intervention strategy to mitigate the interpersonal challenges that college students may face in the future.

Using Chatbot Technology to Improve Brazilian Adolescents' Body Image and Mental Health at Scale: Randomized Controlled Trial.

BACKGROUND: Accessible, cost-effective, and scalable mental health interventions are limited, particularly in low- and middle-income countries, where disparities between mental health needs and services are greatest. Microinterventions (ie, brief, stand-alone, or digital approaches) aim to provide immediate reprieve and enhancements in mental health states and offer a novel and scalable framework for embedding evidence-based mental health promotion techniques into digital environments. Body image is a global public health issue that increases young peoples' risk of developing more severe mental and physical health issues. Embedding body image microinterventions into digital environments is one avenue for providing young people with immediate and short-term reprieve and protection from the negative exposure effects associated with social media. OBJECTIVE: This 2-armed, fully remote, and preregistered randomized controlled trial assessed the impact of a body image chatbot containing microinterventions on Brazilian adolescents' state and trait body image and associated well-being outcomes. METHODS: Geographically diverse Brazilian adolescents aged 13-18 years (901/1715, 52.54% girls) were randomized into the chatbot or an assessment-only control condition and completed web-based self-assessments at baseline, immediately after the intervention time frame, and at 1-week and 1-month follow-ups. The primary outcomes were mean change in state (at chatbot entry and at the completion of a microintervention technique) and trait body image (before and after the intervention), with the secondary outcomes being mean change in affect (state and trait) and body image self-efficacy between the assessment time points. RESULTS: Most participants who entered the chatbot (258/327, 78.9%) completed ≥1 microintervention technique, with participants completing an average of 5 techniques over the 72-hour intervention period. Chatbot users experienced small significant improvements in primary (state: P<.001, Cohen d=0.30, 95% CI 0.25-0.34; and trait body image: P=.02, Cohen d range=0.10, 95% CI 0.01-0.18, to 0.26, 95% CI 0.13-0.32) and secondary outcomes across various time points (state: P<.001, Cohen d=0.28, 95% CI 0.22-0.33; trait positive affect: P=.02, Cohen d range=0.15, 95% CI 0.03-0.27, to 0.23, 95% CI 0.08-0.37; negative affect: P=.03, Cohen d range=-0.16, 95% CI -0.30 to -0.02, to -0.18, 95% CI -0.33 to -0.03; and self-efficacy: P=.02, Cohen d range=0.14, 95% CI 0.03-0.25, to 0.19, 95% CI 0.08-0.32) relative to the control condition. Intervention benefits were moderated by baseline levels of concerns but not by gender. CONCLUSIONS: This is the first large-scale randomized controlled trial assessing a body image chatbot among Brazilian adolescents. Intervention attrition was high (531/858, 61.9%) and reflected the broader digital intervention literature; barriers to engagement were discussed. Meanwhile, the findings support the emerging literature that indicates microinterventions and chatbot technology are acceptable and effective web-based service provisions. This study also offers a blueprint for accessible, cost-effective, and scalable digital approaches that address disparities between health care needs and provisions in low- and middle-income countries. TRIAL REGISTRATION: Clinicaltrials.gov NCT04825184; http://clinicaltrials.gov/ct2/show/NCT04825184. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s12889-021-12129-1.

Study Features and Response Compliance in Ecological Momentary Assessment Research in Borderline Personality Disorder: Systematic Review and Meta-analysis.

BACKGROUND: Borderline personality disorder (BPD) is characterized by frequent and intense moment-to-moment changes in affect, behavior, identity, and interpersonal relationships, which typically result in significant and negative deterioration of the person's overall functioning and well-being. Measuring and characterizing the rapidly changing patterns of instability in BPD dysfunction as they occur in a person's daily life can be challenging. Ecological momentary assessment (EMA) is a method that can capture highly dynamic processes in psychopathology research and, thus, is well suited to study intense variability patterns across areas of dysfunction in BPD. EMA studies are characterized by frequent repeated assessments that are delivered to participants in real-life, real-time settings using handheld devices capable of registering responses to short self-report questions in daily life. Compliance in EMA research is defined as the proportion of prompts answered by the participant, considering all planned prompts sent. Low compliance with prompt schedules can compromise the relative advantages of using this method. Despite the growing EMA literature on BPD in recent years, findings regarding study design features that affect compliance with EMA protocols have not been compiled, aggregated, and estimated. OBJECTIVE: This systematic meta-analytic review aimed to investigate the relationship between study design features and participant compliance in EMA research of BPD. METHODS: A systematic review was conducted on November 12, 2021, following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and MOOSE (Meta-analyses of Observational Studies in Epidemiology) guidelines to search for articles featuring EMA studies of BPD that reported compliance rates and included sufficient data to extract relevant design features. For studies with complete data, random-effect models were used to estimate the overall compliance rate and explore its association with design features. RESULTS: In total, 28 peer-reviewed EMA studies comprising 2052 participants were included in the study. Design features (sampling strategy, average prompting frequency, number of items, response window, sampling device, financial incentive, and dropout rate) showed a large variability across studies, and many studies did not report design features. The meta-analytic synthesis was restricted to 64% (18/28) of articles and revealed a pooled compliance rate of 79% across studies. We did not find any significant relationship between design features and compliance rates. CONCLUSIONS: Our results show wide variability in the design and reporting of EMA studies assessing BPD. Compliance rates appear to be stable across varying setups, and it is likely that standard design features are not directly responsible for improving or diminishing compliance. We discuss possible nonspecific factors of study design that may have an impact on compliance. Given the promise of EMA research in BPD, we also discuss the importance of unifying standards for EMA reporting so that data stemming from this rich literature can be aggregated and interpreted jointly.

The relationship between physical activity and interpersonal distress in college students: the chain mediating role of self-control and mobile phone addiction

Objective of the study Interpersonal relationships, as an important variable afecting the physical and mental health and future development of individuals, were used to construct a structural equation model between physical activity and interpersonal relationships in order to help college students better adapt to society and achieve a high level of mental health. Methods SPSS 27.0 software was used to statistically analyze the data, and Amos 28.0 software was used to construct the model between variables. The results showed that physical activity directly predicted the interpersonal relationship status of college students (ß= −0.108, 95% CI [−0.210,−0.005]), and the chain mediating efect of physical activity→self-control→mobile phone addiction tendency→interpersonal relationship distress was signifcant (ß= −0.012, 95% CI [−0.033,−0.003]). The results of this study suggest that physical activity may be viewed as an efective intervention strategy to mitigate the interpersonal challenges that college students may face in the future.

Aplicación móvil para el análisis estadístico en Android / Mobile application for statistics analysis on Android

El uso de dispositivos móviles en la vida moderna es imprescindible debido a las ventajas que brindan al ofrecer nuevas posibilidades e implementar de manera virtual servicios ya establecidos. La mayor existencia de móviles que computadoras en los estudiantes de Cuba nos motivó a la realización de esta aplicación. El objetivo de este artículo es describir la aplicación nombrada Cálculos estadísticos y tasas en salud (Calc. Tasas versión 1.7) construida para realizar cálculos en un curso de Bioestadística, cubriendo gran parte del contenido de esta asignatura en la enseñanza de pregrado de las universidades médicas, así como otros contenidos de interés en esta materia. También incorpora una base de datos con información demográfica y sanitaria de Cuba y sus provincias en el período 2013-2020. Como resultado se logró independencia tecnológica al dejar de usar programas foráneos y se logró una mayor portabilidad pues funciona tanto en móviles como en computadoras utilizando un emulador de Android(AU)

The use of mobile devices in modern life is essential due to the advantages they provide, offering new possibilities and implementing virtual services. The existence of greater number of mobiles phones than computers in Cuban students motivated the realization of this application. The objective of the article is to describe the application Statistical calculations and rates in health (Calc. Rates version 1.7) built to perform calculations in a Biostatistics course, covering a large part of the content of this subject in the undergraduate teaching of medical universities, as well as other content related with this topic. It also incorporates a database with demographic and health information on Cuba and its provinces in the period 2013-2020. As a result, technological independence was achieved by stopping using foreign programs and a greater portability, since it works on both mobile phones and computers through an Android emulator(AU)

Determination of Population Mobility Dynamics in Popayán-Colombia during the COVID-19 Pandemic Using Open Datasets.

The COVID-19 pandemic is a catastrophic event that marked the history of humanity. The virus's transmissibility has primarily prevented the control of the pandemic, so it has become vital to determine and control the dynamics of the population mobility to reduce the epidemiological impact. Considering the above, this paper uses an exposure indicator based on the movement ranges provided by Facebook to determine the dynamics of population mobility in Popayán city for the period after the appearance of COVID-19. Using statistical analysis techniques, it then contrasts the data obtained with the public circulation reports provided by Google and Apple. The results suggest that the exposure indicator is reliable and presents moderate to strong linear relationships for the public data, which implies that it can be an additional resource for decision-making to curb the spread of the virus.