mHealth intervention to improve quality of life in patients with chronic diseases during the COVID-19 crisis in Paraguay: A study protocol for a randomized controlled trial

Background Patients with chronic disease represent an at-risk group in the face of the COVID-19 crisis as they need to regularly monitor their lifestyle and emotional management. Coping with the illness becomes a challenge due to supply problems and lack of access to health care facilities. It is expected these limitations, along with lockdown and social distancing measures, have affected the routine disease management of these patients, being more pronounced in low- and middle-income countries with a flawed health care system. Objectives The purpose of this study is to describe a protocol for a randomized controlled trial to test the efficacy of the Adhera® MejoraCare Digital Program, an mHealth intervention aimed at improving the quality of life of patients with chronic diseases during the COVID-19 outbreak in Paraguay. Method A two-arm randomized controlled trial will be carried out, with repeated measures (baseline, 1-month, 3-month, 6-month, and 12-month) under two conditions: Adhera® MejoraCare Digital Program or waiting list. The primary outcome is a change in the quality of life on the EuroQol 5-Dimensions 3-Levels Questionnaire (EQ-5D-3L). Other secondary outcomes, as the effect on anxiety and health empowerment, will be considered. All participants must be 18 years of age or older and meet the criteria for chronic disease. A total of 96 participants will be recruited (48 per arm). Conclusions It is expected that the Adhera® MejoraCare Digital Program will show significant improvements in quality of life and emotional distress compared to the waiting list condition. Additionally, it is hypothesized that this intervention will be positively evaluated by the participants in terms of usability and satisfaction. The findings will provide new insights into the viability and efficacy of mHealth solutions for chronic disease management in developing countries and in times of pandemic

Automatic landmarks detection in breast reconstruction aesthetic assessment.

Journal Article;This paper addresses a fully automatic landmarks detection method for breast reconstruction aesthetic assessment. The set of landmarks detected are the supraesternal notch (SSN), armpits, nipples, and inframammary fold (IMF). These landmarks are commonly used in order to perform anthropometric measurements for aesthetic assessment. The methodological approach is based on both illumination and morphological analysis. The proposed method has been tested with 21 images. A good overall performance is observed, although several improvements must be achieved in order to refine the detection of nipples and SSNs.Ye

Breast Cancer Physical Activity Mobile Intervention: Early Findings From a User Experience and Acceptability Mixed Methods Study.

Physical activity (PA) is the most well-established lifestyle factor associated with breast cancer (BC) survival. Even women with advanced BC may benefit from moderate PA. However, most BC symptoms and treatment side effects are barriers to PA. Mobile health coaching systems can implement functionalities and features based on behavioral change theories to promote healthier behaviors. However, to increase its acceptability among women with BC, it is essential that these digital persuasive systems are designed considering their contextual characteristics, needs, and preferences. This study aimed to examine the potential acceptability and feasibility of a mobile-based intervention to promote PA in patients with BC; assess usability and other aspects of the user experience; and identify key considerations and aspects for future improvements, which may help increase and sustain acceptability and engagement. A mixed methods case series evaluation of usability and acceptability was conducted in this study. The study comprised 3 sessions: initial, home, and final sessions. Two standardized scales were used: the Satisfaction with Life Scale and the International Physical Activity Questionnaire-Short Form. Participants were asked to use the app at home for approximately 2 weeks. App use and PA data were collected from the app and stored on a secure server during this period. In the final session, the participants filled in 2 app evaluation scales and took part in a short individual interview. They also completed the System Usability Scale and the user version of the Mobile App Rating Scale. Participants were provided with a waist pocket, wired in-ear headphones, and a smartphone. They also received printed instructions. A content analysis of the qualitative data collected in the interviews was conducted iteratively, ensuring that no critical information was overlooked. The International Physical Activity Questionnaire-Short Form found that all participants (n=4) were moderately active; however, half of them did not reach the recommended levels in the guidelines. System Usability Scale scores were all >70 out of 100 (72.5, 77.5, 95, and 80), whereas the overall user version of the Mobile App Rating Scale scores were 4, 4.3, 4.4, and 3.6 out of 5. The app was perceived to be nice, user-friendly, straightforward, and easy to understand. Recognition of achievements, the possibility of checking activity history, and the rescheduling option were positively highlighted. Technical difficulties with system data collection, particularly with the miscount of steps, could make users feel frustrated. The participants suggested improvements and indicated that the app has the potential to work well for survivors of BC. Early results presented in this study point to the potential of this tool concept to provide a friendly and satisfying coaching experience to users, which may help improve PA adherence in survivors of BC

So-Lo-Mo Study: An mHealth Intervention to Improve the Efficacy of the Smoking Cessation Process

Introduction Social-Local-Mobile (So-Lo-Mo) is an innovative intervention based on mobile technologies: it has the capacity to trigger behavioural changes. In this sense, the So-Lo-Mo App is a complement to pharmacological therapies to quit smoking providing personalised motivational messages, physical activity monitoring, lifestyle advices and distractions (mini-games) to help pass the cravings. The purpose of this study is to analyse the efficacy of the So-Lo-Mo intervention applied to the smoking cessation process compared to usual care. Secondary study objectives are: (i) to analyse safety of pharmacological therapy; (ii) to analyse subjects’ motivation to give up smoking; (iii) to analyse subjects’ health-related quality of life; (iv) to monitor physical activity; and (v) to monitor healthy lifestyle habits. Methods So-Lo-Mo study is a 12-months randomized open-label parallel-group trial performance at the Virgen del Rocio University Hospital premises. Efficacy was considered as the abstinence rate at 1 year measured by means of exhaled Carbon Monoxide (CO) and urine cotinine tests; safety was measured as the number of adverse events related with pharmacological therapies under consideration (either bupropion or varenicline); subjects’ motivation was measured through the Richmond test; health-related quality of life was measured through the EuroQoL-5D-5L questionnaire; physical activity was measured through the International Physical Activity Questionnaire (IPAQ-27); and lifestyle habits was measured through the subjects’ weight evolution during the follow-up period. Results So far, data gathered from 59 subjects (30 women, 28 controls) has been analysed at 6 months form baseline, yielding the following results: (i) Efficacy: success rate were 53.6% and 71% for control and intervention groups respectively (p = 0.168). (ii) Safety: 12 adverse events were reported for the bupropion therapy (n = 24) while 30 adverse events were reported for the varenicline therapy (n = 35). (iii) Motivation: Richmond scores were 9.36 ± 0.83 and 9.50 ± 0.63 (p = 0.465) for control and intervention group respectively. (iv) Health-related quality of life: the average evolution on the Visual Analogic Scale (VAS) score was 6.87 ± 11.31 (p = 0.007) and 7.69 ± 16.20 (p = 0.023) for control and intervention groups respectively. (v) Physical activity: the evolution of metabolic equivalent (MET) minutes per week was 1120.42 ± 6113.12 and -10.36 ± 4188.47 (p = 0.436) for control and intervention groups respectively. (vi) Lifestyle habits: subjects’ weight evolution in kilograms was 3.51 ± 2.90 and 2.93 ± 5.77 (p = 0.202) for control and intervention groups respectively. Conclusions (i) Efficacy: the So-Lo-Mo intervention provides a consistent improvement on the efficacy compared to controls. (ii) Safety: the number and type of the reported adverse events related to the pharmacological treatment is in keeping to their expected incidence as reported by the European Medicines Agency. (iii) Motivation: a slight bias on the subjects’ motivation has been reported, showing lower motivation score in controls compared to intervention group. (iv) Health-related quality of life: Statistically significant improvements in the VAS health score were found for both groups. Furthermore, a greater average improvement has been reported for intervention subjects compared to controls, which suggest that the intervention has an added value. (v) Physical activity: physical activity evolution has been reported higher for controls compared to intervention subjects. This finding should be taken with care, since the variability reported for the increments in the IPAQ27 score is very high and, therefore, more observations are needed before drawing a conclusion from this analysis. (vi) Lifestyle habits: weight increment in control group was reported to be higher when compared to intervention group. This finding, in combination with the efficacy, could support the preliminary conclusion that the So-Lo-Mo intervention improves the efficacy of the smoking cessation process while helps to control weight increments associated to the nicotine abstinence. Preliminary analyses show a very promising trend in achieving the main objective of this study. However, stronger statistical significance is needed to endorse this statement

Benchmarking machine learning approaches to predict radiation-induced toxicities in lung cancer patients

Background and purpose: Radiation-induced toxicities are common adverse events in lung cancer (LC) patients undergoing radiotherapy (RT). An accurate prediction of these adverse events might facilitate an informed and shared decision-making process between patient and radiation oncologist with a clearer view of life-balance implications in treatment choices. This work provides a benchmark of machine learning (ML) approaches to predict radiation-induced toxicities in LC patients built upon a real-world health dataset based on a generalizable methodology for their implementation and external validation. Materials and Methods: Ten feature selection (FS) methods were combined with five ML-based classifiers to predict six RT-induced toxicities (acute esophagitis, acute cough, acute dyspnea, acute pneumonitis, chronic dyspnea, and chronic pneumonitis). A real-world health dataset (RWHD) built from 875 consecutive LC patients was used to train and validate the resulting 300 predictive models. Internal and external accuracy was calculated in terms of AUC per clinical endpoint, FS method, and ML-based classifier under analysis. Results: Best performing predictive models obtained per clinical endpoint achieved comparable performances to methods from state-of-the-art at internal validation (AUC ≥ 0.81 in all cases) and at external validation (AUC ≥ 0.73 in 5 out of 6 cases). Conclusion: A benchmark of 300 different ML-based approaches has been tested against a RWHD achieving satisfactory results following a generalizable methodology. The outcomes suggest potential relationships between underrecognized clinical factors and the onset of acute esophagitis or chronic dyspnea, thus demonstrating the potential that ML-based approaches have to generate novel data-driven hypotheses in the field

Monitoring chronic inflammatory musculoskeletal diseases mixing virtual and face-to-face assessments—Results of the digireuma study

Mobile health technology holds great promise for the clinical management of patients with chronic disease. However, evidence on the implementation of projects involving digital health solutions in rheumatology is scarce. We aimed to study the feasibility of a hybrid (virtual and face-to-face) monitoring strategy for personalized care in rheumatoid arthritis (RA) and spondyloarthritis (SpA). This project included the development of a remote monitoring model and its assessment. After a focus group with patients and rheumatologists, relevant concerns regarding the management of RA and SpA were raised, leading to the development of the Mixed Attention Model (MAM), which combined hybrid (virtual and face-to-face) monitoring. Then, a prospective study using the mobile solution Adhera for Rheumatology was conducted. Over a 3-month follow-up period, patients were given the opportunity to complete disease-specific electronic patient reported outcomes (ePROs) for RA and SpA with a pre-established frequency, as well as flares and changes in medication at any time. Number of interactions and alerts were assessed. The usability of the mobile solution was measured by the Net-Promoter Score (NPS) and through a 5-star Likert scale. Following the MAM development, forty-six patients were recruited to utilize the mobile solution, of whom 22 had RA and 24 SpA. There were 4,019 total interactions in the RA group, and 3,160 in the SpA group. Fifteen patients generated a total of 26 alerts, of which 24 were flares and 2 were medication-related problems; most (69%) were managed remotely. Regarding patient satisfaction, 65% of the respondents were considered to have endorsed Adhera for Rheumatology, yielding a NPS of 57 and an overall rating was 4.3 out of 5 stars. We concluded that the use of the digital health solution is feasible in clinical practice to monitor ePROs for RA and SpA. Next steps involve the implementation of this telemonitoring method in a multicentric setting. Author summary There has been an exponential growth in the use of communication technologies to support diagnosis, monitoring or treatment in recent years. In rheumatology, the use of mobile applications, provides an opportunity to improve disease management through the collection of large amounts of data. This can be done using electronic patient-reported-outcomes (ePROs). Here, we present the development and implementation of a mobile solution and a hybrid care model. We found the use of ePROs feasible to monitor disease activity, flares and problems with the medication in patients with rheumatoid arthritis (RA) and spondyloarthritis (SpA). Our study provides new insights into the use of digital health technology in rheumatology, highlighting the importance of the involvement of both healthcare professionals and patients the implementation of mobile health in clinical practic

Monitoring chronic inflammatory musculoskeletal diseases mixing virtual and face-to-face assessments-Results of the digireuma study.

Mobile health technology holds great promise for the clinical management of patients with chronic disease. However, evidence on the implementation of projects involving digital health solutions in rheumatology is scarce. We aimed to study the feasibility of a hybrid (virtual and face-to-face) monitoring strategy for personalized care in rheumatoid arthritis (RA) and spondyloarthritis (SpA). This project included the development of a remote monitoring model and its assessment. After a focus group with patients and rheumatologists, relevant concerns regarding the management of RA and SpA were raised, leading to the development of the Mixed Attention Model (MAM), which combined hybrid (virtual and face-to-face) monitoring. Then, a prospective study using the mobile solution Adhera for Rheumatology was conducted. Over a 3-month follow-up period, patients were given the opportunity to complete disease-specific electronic patient reported outcomes (ePROs) for RA and SpA with a pre-established frequency, as well as flares and changes in medication at any time. Number of interactions and alerts were assessed. The usability of the mobile solution was measured by the Net-Promoter Score (NPS) and through a 5-star Likert scale. Following the MAM development, forty-six patients were recruited to utilize the mobile solution, of whom 22 had RA and 24 SpA. There were 4,019 total interactions in the RA group, and 3,160 in the SpA group. Fifteen patients generated a total of 26 alerts, of which 24 were flares and 2 were medication-related problems; most (69%) were managed remotely. Regarding patient satisfaction, 65% of the respondents were considered to have endorsed Adhera for Rheumatology, yielding a NPS of 57 and an overall rating was 4.3 out of 5 stars. We concluded that the use of the digital health solution is feasible in clinical practice to monitor ePROs for RA and SpA. Next steps involve the implementation of this telemonitoring method in a multicentric setting

A Digital Health Intervention for Stress and Anxiety Relief in Perioperative Care: Protocol for a Feasibility Randomized Controlled Trial

BackgroundStress and anxiety are psychophysiological responses commonly experienced by patients during the perioperative process that can increase presurgical and postsurgical complications to a comprehensive and positive recovery. Preventing and intervening in stress and anxiety can help patients achieve positive health and well-being outcomes. Similarly, the provision of education about surgery can be a crucial component and is inversely correlated with preoperative anxiety levels. However, few patients receive stress and anxiety relief support before surgery, and resource constraints make face-to-face education sessions untenable. Digital health interventions can be helpful in empowering patients and enhancing a more positive experience. Digital health interventions have been shown to help patients feel informed about the possible benefits and risks of available treatment options. However, they currently focus only on providing informative content, neglecting the importance of personalization and patient empowerment. ObjectiveThis study aimed to explore the feasibility of a digital health intervention called the Adhera CARINAE Digital Health Program, designed to provide evidence-based, personalized stress- and anxiety-management methods enabled by a comprehensive digital ecosystem that incorporates wearable, mobile, and virtual reality technologies. The intervention program includes the use of advanced data-driven techniques for tailored patient education and lifestyle support. MethodsThe trial will include 5 hospitals across 3 European countries and will use a randomized controlled design including 30 intervention participants and 30 control group participants. The involved surgeries are cardiopulmonary and coronary artery bypass surgeries, cardiac valve replacement, prostate or bladder cancer surgeries, hip and knee replacement, maxillofacial surgery, or scoliosis. The control group will receive standard care, and the intervention group will additionally be exposed to the digital health intervention program. ResultsThe recruitment process started in January 2022 and has been completed. The primary impact analysis is currently ongoing. The expected results will be published in early 2023. ConclusionsThis manuscript details a comprehensive protocol for a study that will provide valuable information about the intervention program, such as the measurement of comparative intervention effects on stress; anxiety and pain management; and usability by patients, caregivers, and health care professionals. This will contribute to the evidence planning process for the future adoption of diverse digital health solutions in the field of surgery. Trial RegistrationClinicalTrials.gov NCT05184725; https://www.clinicaltrials.gov/ct2/show/NCT05184725 International Registered Report Identifier (IRRID)DERR1-10.2196/3853

Functionalities of the Adhera MejoraCare solution.

Left: Symptom’s monitoring. Center: Patient empowerment categories in the educational section. Right: Educational units included in the ‘‘How to protect from coronavirus” category.</p

SPIRIT checklist.

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