Electronic health intervention to manage symptoms of immunotherapy in patients with cancer (SOFIA): Results from a randomized controlled pilot trial.

BACKGROUND: For patients receiving immune checkpoint inhibitors, early detection of immune-related adverse events (irAEs) is critical for one's safety. To this end, a smartphone app (SOFIA) was developed that featured the assessment of electronic patient-reported outcomes (ePROs) focusing on irAEs as well as a set of comprehensive supportive information. Its feasibility and preliminary efficacy were evaluated in a randomized controlled trial (RCT). METHODS: Patients who received immune checkpoint inhibition therapy were randomly assigned to an intervention group (IG) or a control group (CG; care as usual). During the 12-week intervention period, IG patients used SOFIA to report twice weekly ePROs and receive cancer- and immunotherapy-relevant contents. Before a patient's next clinical visit, the physician in charge was given the ePRO reports. The primary objective was to test the feasibility of SOFIA. Furthermore, the preliminary efficacy of SOFIA for health-related quality of life (HRQOL), psychosocial outcomes, and medical data was examined. Clinical outcomes were assessed at baseline (T0), post-intervention (T1), and a 3-month follow-up (T2). RESULTS: Seventy-one patients were randomized to the IG (n = 34) or the CG (n = 37). SOFIA showed high feasibility and acceptance. At T1, patients in the IG reported significantly better HRQOL and role functioning and less depression, distress, and appetite loss. No significant differences were revealed regarding medical data, the utilization of supportive care services, or survival. CONCLUSIONS: SOFIA showed high feasibility and acceptance and improved HRQOL and psychosocial outcomes. These results suggest further evaluation of efficacy in a large-scale confirmatory multicenter RCT.

Similarity-based multimodal regression.

To better understand complex human phenotypes, large-scale studies have increasingly collected multiple data modalities across domains such as imaging, mobile health, and physical activity. The properties of each data type often differ substantially and require either separate analyses or extensive processing to obtain comparable features for a combined analysis. Multimodal data fusion enables certain analyses on matrix-valued and vector-valued data, but it generally cannot integrate modalities of different dimensions and data structures. For a single data modality, multivariate distance matrix regression provides a distance-based framework for regression accommodating a wide range of data types. However, no distance-based method exists to handle multiple complementary types of data. We propose a novel distance-based regression model, which we refer to as Similarity-based Multimodal Regression (SiMMR), that enables simultaneous regression of multiple modalities through their distance profiles. We demonstrate through simulation, imaging studies, and longitudinal mobile health analyses that our proposed method can detect associations between clinical variables and multimodal data of differing properties and dimensionalities, even with modest sample sizes. We perform experiments to evaluate several different test statistics and provide recommendations for applying our method across a broad range of scenarios.

Feasibility, Acceptability, and Outcomes of a Mobile Health Tool for Radical Cystectomy Recovery.

PURPOSE: Postoperative education and symptom tracking are essential following cystectomy to reduce readmission rates and information overload. To address these issues, an internet-based tool was developed to provide education, alerts, and symptom tracking. We aimed to evaluate the tool's feasibility, acceptability, and impact on complication and readmission rates. MATERIALS AND METHODS: Thirty-three eligible patients over 18 years old scheduled for cystectomy were enrolled. Patients were asked to use the mobile health (mHealth) tool daily for the first 2 weeks, then less frequently up to 90 days after discharge. Descriptive statistics were used to summarize study variables. Feasibility was defined as at least 50% of patients using the tool once a week, and acceptability as patient satisfaction of > 75%. RESULTS: Use of the mHealth tool was feasible, with 90% of patients using it 1 week after discharge, but engagement declined over time to 50%, with technological difficulties being the main reason for nonengagement. Patient and provider acceptability was high, with satisfaction > 90%. Within 90 days, 36% experienced complications after discharge and 30% were readmitted. Engagement with the mHealth application varied but was not statistically associated with readmission (P = .21). CONCLUSIONS: The study showed that the electronic mobile health intervention for patients undergoing cystectomy was feasible, acceptable, and provided valuable educational content and symptom management. Future larger studies are needed to determine the tool's effectiveness in improving patient outcomes and its potential implementation into routine clinical care.

Implementation and Evaluation of a mHealth-Based Community Health Worker Feedback Loop for Hispanics with and at Risk for Diabetes.

BACKGROUND: Gaps in accessibility and communication hinder diabetes care in poor communities. Combining mobile health (mHealth) and community health workers (CHWs) into models to bridge these gaps has great potential but needs evaluation. OBJECTIVE: To evaluate a mHealth-based, Participant-CHW-Clinician feedback loop in a real-world setting. DESIGN: Quasi-experimental feasibility study with intervention and usual care (UC) groups. PARTICIPANTS: A total of 134 participants (n = 67/group) who were all low-income, uninsured Hispanics with or at-risk for type 2 diabetes. INTERVENTION: A 15-month study with a weekly to semimonthly mHealth Participant-CHW-Clinician feedback loop to identify participant issues and provide participants monthly diabetes education via YouTube. MAIN MEASURES: We used pre-defined feasibility measures to evaluate our intervention: (a) implementation, the execution of feedback loops to identify and resolve participant issues, and (b) efficacy, intended effects of the program on clinical outcomes (baseline to 15-month HbA1c, systolic blood pressure (SBP), diastolic blood pressure (DBP), and weight changes) for each group and their subgroups (at-risk; with diabetes, including uncontrolled (HbA1c ≥ 7%)). KEY RESULTS: CHWs identified 433 participant issues (mean = 6.5 ± 5.3) and resolved 91.9% of these. Most issues were related to supplies, 26.3% (n = 114); physical health, 23.1% (n = 100); and medication access, 20.8% (n = 90). Intervention participants significantly improved HbA1c (- 0.51%, p = 0.03); UC did not (- 0.10%, p = 0.76). UC DBP worsened (1.91 mmHg, p < 0.01). Subgroup analyses revealed HbA1c improvements for uncontrolled diabetes (intervention: - 1.59%, p < 0.01; controlled: - 0.72, p = 0.03). Several variables for UC at-risk participants worsened: HbA1c (0.25%, p < 0.01), SBP (4.05 mmHg, p < 0.01), DBP (3.21 mmHg, p = 0.01). There were no other significant changes for either group. CONCLUSIONS: A novel mHealth-based, Participant-CHW-Clinician feedback loop was associated with improved HbA1c levels and identification and resolution of participant issues. UC individuals had several areas of clinical deterioration, particularly those at-risk for diabetes, which is concerning for progression to diabetes and disease-related complications. CLINICAL TRIAL: NCT03394456, accessed at https://clinicaltrials.gov/ct2/show/NCT03394456.

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.

Feasibility and Accuracy of Wrist-Worn Sensors for Perioperative Monitoring During and After Major Abdominal Surgery: An Observational Study.

INTRODUCTION: Continuous, ambulatory perioperative monitoring using wearable devices has shown promise for earlier detection of physiological deterioration and postoperative complications, preventing 'failure-to-rescue'. This study aimed to compare the accuracy of vital signs measured by wrist-based wearables with gold standard measurements from vital signs monitors or nurse assessments in major abdominal surgery. METHODS: Adult patients were eligible for inclusion in this prospective observational study validating the Empatica E4 wrist sensor intraoperatively and postoperatively. The primary outcomes were the 95% limits of agreement (LoA) between manual and device recordings of heart rate (HR) and temperature evaluated via Bland-Altman analysis. Secondary analysis was conducted using Clarke-Error grid analysis. RESULTS: Overall, 31 patients were recruited, and 27 patients completed the study. The median duration of recording per patient was 70.3 h, and a total of 2112 h of data recording were completed. Wrist-based HR measurement was accurate and moderately precise (bias: 0.3 bpm; 95% LoA -15.5 to 17.1), but temperature measurement was neither accurate nor precise (bias -2.2°C; 95% LoA -6.0 to 1.6). On Clarke-Error grid analysis, 74.5% and 29.6% of HR and temperature measurements, respectively, fell within the acceptable range of reference standards. CONCLUSIONS: Continuous perioperative monitoring of HR and temperature after major abdominal surgery using wrist-based sensors is feasible but was limited in this study by low precision. While wrist-based devices offer promise for the continuous monitoring of high-risk surgical patients, current technology is inadequate. Ongoing device hardware and software innovation with robust validation is required before such technologies can be routinely adopted in clinical practice.

Stricker Learning Span criterion validity: a remote self-administered multi-device compatible digital word list memory measure shows similar ability to differentiate amyloid and tau PET-defined biomarker groups as in-person Auditory Verbal Learning Test.

OBJECTIVE: The Stricker Learning Span (SLS) is a computer-adaptive digital word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). We aimed to establish criterion validity of the SLS by comparing its ability to differentiate biomarker-defined groups to the person-administered Rey's Auditory Verbal Learning Test (AVLT). METHOD: Participants (N = 353; mean age = 71, SD = 11; 93% cognitively unimpaired [CU]) completed the AVLT during an in-person visit, the SLS remotely (within 3 months) and had brain amyloid and tau PET scans available (within 3 years). Overlapping groups were formed for 1) those on the Alzheimer's disease (AD) continuum (amyloid PET positive, A+, n = 125) or not (A-, n = 228), and those with biological AD (amyloid and tau PET positive, A+T+, n = 55) vs no evidence of AD pathology (A-T-, n = 195). Analyses were repeated among CU participants only. RESULTS: The SLS and AVLT showed similar ability to differentiate biomarker-defined groups when comparing AUROCs (p's > .05). In logistic regression models, SLS contributed significantly to predicting biomarker group beyond age, education, and sex, including when limited to CU participants. Medium (A- vs A+) to large (A-T- vs A+T+) unadjusted effect sizes were observed for both SLS and AVLT. Learning and delay variables were similar in terms of ability to separate biomarker groups. CONCLUSIONS: Remotely administered SLS performed similarly to in-person-administered AVLT in its ability to separate biomarker-defined groups, providing evidence of criterion validity. Results suggest the SLS may be sensitive to detecting subtle objective cognitive decline in preclinical AD.

Implementation of free-draft text messaging to enhance care retention and satisfaction for persons living with HIV infection.

Eligible persons with HIV infection can receive client-centered case management to coordinate medical and social services. Novel mobile health interventions could improve effective case management and retention in care, an important goal to help end the HIV epidemic. Using a hybrid type I effectiveness-implementation design, we assessed whether access to bidirectional, free-draft secure text messaging with a case manager and clinic pharmacist could improve client satisfaction and care retention in a Southern academic HIV clinic. Sixty-four clients enrolled between November 2019 and March 2020, had a median age of 39 years, and were mostly male, single, and African-American. Heavy app users texted over 100 times (n = 6) over the course of the 12-month intervention while others never texted (n = 12). App usage peaked during months of clinic closure due to COVID-19. Most participants reported high satisfaction with the app and planned continued usage after study completion. Changes in clinic retention and virologic suppression rates were not observed, a result confounded by practice changes due to COVID-19. High usage and satisfaction of free-draft text messaging in case-managed HIV clients supports inclusion of this communication option in routine HIV clinical care.

Real-world validation of smartphone-based photoplethysmography for rate and rhythm monitoring in atrial fibrillation.

AIMS: Photoplethysmography- (PPG) based smartphone applications facilitate heart rate and rhythm monitoring in patients with paroxysmal and persistent atrial fibrillation (AF). Despite an endorsement from the European Heart Rhythm Association, validation studies in this setting are lacking. Therefore, we evaluated the accuracy of PPG-derived heart rate and rhythm classification in subjects with an established diagnosis of AF in unsupervised real-world conditions. METHODS AND RESULTS: Fifty consecutive patients were enrolled, 4 weeks before undergoing AF ablation. Patients used a handheld single-lead electrocardiography (ECG) device and a fingertip PPG smartphone application to record 3907 heart rhythm measurements twice daily during 8 weeks. The ECG was performed immediately before and after each PPG recording and was given a diagnosis by the majority of three blinded cardiologists. A consistent ECG diagnosis was exhibited along with PPG data of sufficient quality in 3407 measurements. A single measurement exhibited good quality more often with ECG (93.2%) compared to PPG (89.5%; P < 0.001). However, PPG signal quality improved to 96.6% with repeated measurements. Photoplethysmography-based detection of AF demonstrated excellent sensitivity [98.3%; confidence interval (CI): 96.7-99.9%], specificity (99.9%; CI: 99.8-100.0%), positive predictive value (99.6%; CI: 99.1-100.0%), and negative predictive value (99.6%; CI: 99.0-100.0%). Photoplethysmography underestimated the heart rate in AF with 6.6 b.p.m. (95% CI: 5.8 b.p.m. to 7.4 b.p.m.). Bland-Altman analysis revealed increased underestimation in high heart rates. The root mean square error was 11.8 b.p.m. CONCLUSION: Smartphone applications using PPG can be used to monitor patients with AF in unsupervised real-world conditions. The accuracy of AF detection algorithms in this setting is excellent, but PPG-derived heart rate may tend to underestimate higher heart rates.

Validation of a novel smartphone-based photoplethysmographic method for ambulatory heart rhythm diagnostics: the SMARTBEATS study.

AIMS: In the current guidelines, smartphone photoplethysmography (PPG) is not recommended for diagnosis of atrial fibrillation (AF), without a confirmatory electrocardiogram (ECG) recording. Previous validation studies have been performed under supervision in healthcare settings, with limited generalizability of the results. We aim to investigate the diagnostic performance of a smartphone-PPG method in a real-world setting, with ambulatory unsupervised smartphone-PPG recordings, compared with simultaneous ECG recordings and including patients with atrial flutter (AFL). METHODS AND RESULTS: Unselected patients undergoing direct current cardioversion for treatment of AF or AFL were asked to perform 1-min heart rhythm recordings post-treatment, at least twice daily for 30 days at home, using an iPhone 7 smartphone running the CORAI Heart Monitor PPG application simultaneously with a single-lead ECG recording (KardiaMobile). Photoplethysmography and ECG recordings were read independently by two experienced readers. In total, 280 patients recorded 18 005 simultaneous PPG and ECG recordings. Sufficient quality for diagnosis was seen in 96.9% (PPG) vs. 95.1% (ECG) of the recordings (P < 0.001). Manual reading of the PPG recordings, compared with manually interpreted ECG recordings, had a sensitivity, specificity, and overall accuracy of 97.7%, 99.4%, and 98.9% with AFL recordings included and 99.0%, 99.7%, and 99.5%, respectively, with AFL recordings excluded. CONCLUSION: A novel smartphone-PPG method can be used by patients unsupervised at home to achieve accurate heart rhythm diagnostics of AF and AFL with very high sensitivity and specificity. This smartphone-PPG device can be used as an independent heart rhythm diagnostic device following cardioversion, without the requirement of confirmation with ECG.

Validation and verification framework and data integration of biosensors and in vitro diagnostic devices: a position statement of the IFCC Committee on Mobile Health and Bioengineering in Laboratory Medicine (C-MBHLM) and the IFCC Scientific Division.

Advances in technology have transformed healthcare and laboratory medicine. Biosensors have emerged as a promising technology in healthcare, providing a way to monitor human physiological parameters in a continuous, real-time, and non-intrusive manner and offering value and benefits in a wide range of applications. This position statement aims to present the current situation around biosensors, their perspectives and importantly the need to set the framework for their validation and safe use. The development of a qualification framework for biosensors should be conceptually adopted and extended to cover digitally measured biomarkers from biosensors for advancing healthcare and achieving more individualized patient management and better patient outcome.

Behavioral Activation mHealth Application for Smoking Cessation: A Randomized Controlled Pilot Trial.

BACKGROUND: Behavioral activation (BA) is an effective intervention for both depression and substance use disorders. Combining BA with a standard smoking cessation intervention may improve quit rates by addressing depressive symptoms, a key barrier to quitting. This study preliminarily evaluated the acceptability and efficacy of the BA-based Actify! mobile health application (mHealth app) for smoking cessation. METHODS: We conducted a pilot randomized controlled trial (n=242) comparing Actify! with the National Cancer Institute's (NCI) app for smoking cessation (QuitGuide) on acceptability (user satisfaction, app openings), smoking abstinence, and mechanisms of change (behavioral activation and depressive symptoms) at 8 weeks and 6 months post-randomization. Participants were US adults recruited online who smoked daily. RESULTS: Treatment satisfaction was uniformly higher in the Actify! arm. Number of app openings was similar across arms (M=34.3 openings over 8 weeks in both arms). Self-reported 30-day point prevalence abstinence (PPA) at 8 weeks was 12.6% for Actify! vs. 7.3% for QuitGuide. Differences in 30-day PPA continued through 6 months (18.5% for Actify! vs. 12.2% for QuitGuide). Changes between baseline and 8 weeks in depressive symptoms and behavioral activation favored Actify!. Planned subgroup analyses suggested greater benefit of Actify! among participants with pre-treatment mild to moderate depression symptom severity compared to those with no depression symptoms. CONCLUSIONS: Actify! showed considerable promise as a novel mHealth treatment, as evidenced by high usage and higher user satisfaction and quit rates than QuitGuide at both short- and long-term follow-up. The next step is to evaluate Actify! in a fully-powered efficacy trial. IMPLICATIONS: Study findings demonstrate the promise of a behavioral activation (BA)-based mobile health app (Actify!) for smoking cessation as a population-level intervention that can effectively address depressive symptoms as a risk factor for worse smoking treatment outcomes. The Actify! app is the first standalone BA-based app to demonstrate potential for improved acceptability and efficacy relative to a standard care comparison app, with user satisfaction and smoking quit rates descriptively exceeding those of the National Cancer Institute's QuitGuide app.

Epilepsy self-management mobile health application: A needs assessment in people with epilepsy and caregivers in Viet Nam.

OBJECTIVES: This study aimed to determine (1) the needsof Vietnamese people with epilepsy (PWE) and their caregivers for self-management mobile health applications and (2) the self-management features expected to be included in an application. METHODS: The survey consisted of an anonymous self-administered questionnaire that was distributed to PWE and caregivers from the age of 18 in Vietnam through online platforms and onsite at Nguyen Tri Phuong Hospital and University Medical Center, Ho Chi Minh City, from February 2022 to May 2022. The questionnaire assessed the participants' attitudes toward epilepsy self-management mobile applications, their willingness to use applications, and their expectations of the contents of an application. RESULTS: Responses from 103 participants were submitted. Eighty-one participants (78.6%) reported using a smartphone, but only 50.6% of those claimed to know about self-management applications. Most respondents (70.9%) thought the applications would be useful for disease self-management, and 68.9% were willing to use epilepsy self-management applications. In addition, the most expected features to be included in self-management applications were epilepsy information, seizure first aid, connecting with medical professionals, and a seizure diary. CONCLUSION: Most Vietnamese PWE and caregivers had a willingness to use epilepsy self-management applications.The expected features are related to all aspects of self-management, including information, seizure, medication, and safety management.

Chat-ePRO: Development and pilot study of an electronic patient-reported outcomes system based on ChatGPT.

OBJECTIVE: Chatbots have the potential to improve user compliance in electronic Patient-Reported Outcome (ePRO) system. Compared to rule-based chatbots, Large Language Model (LLM) offers advantages such as simplifying the development process and increasing conversational flexibility. However, there is currently a lack of practical applications of LLMs in ePRO systems. Therefore, this study utilized ChatGPT to develop the Chat-ePRO system and designed a pilot study to explore the feasibility of building an ePRO system based on LLM. MATERIALS AND METHODS: This study employed prompt engineering and offline knowledge distillation to design a dialogue algorithm and built the Chat-ePRO system on the WeChat Mini Program platform. In order to compare Chat-ePRO with the form-based ePRO and rule-based chatbot ePRO used in previous studies, we conducted a pilot study applying the three ePRO systems sequentially at the Sir Run Run Shaw Hospital to collect patients' PRO data. RESULT: Chat-ePRO is capable of correctly generating conversation based on PRO forms (success rate: 95.7 %) and accurately extracting the PRO data instantaneously from conversation (Macro-F1: 0.95). The majority of subjective evaluations from doctors (>70 %) suggest that Chat-ePRO is able to comprehend questions and consistently generate responses. Pilot study shows that Chat-ePRO demonstrates higher response rate (9/10, 90 %) and longer interaction time (10.86 s/turn) compared to the other two methods. CONCLUSION: Our study demonstrated the feasibility of utilizing algorithms such as prompt engineering to drive LLM in completing ePRO data collection tasks, and validated that the Chat-ePRO system can effectively enhance patient compliance.

The effect of personalized mobile health (mHealth) in cardiac rehabilitation for discharged elderly patients after acute myocardial infarction on their inner strength and resilience.

INTRODUCTION: Given the importance of promoting self-care and quality of life for discharged elderly patients after acute Myocardial Infarction(MI), It is necessitated we conduct interventions to promote these items. This study was conducted to determine the effect of mHealth-Cardiac rehabilitation (CR) on the inner Strength and resilience of elderly patients with MI after discharge from the hospital. METHODS: The present study was a randomized controlled trial that was conducted on 56 Elderly patients with myocardial infarction were discharged from the heart departments. In the intervention group after the patient's discharge, the patients were contacted twice a week for one month and the necessary training and support were given online. To gather data, the Mini-Mental State Examination (MMSE), the demographic and clinical characteristics questionnaire, the inner strength scale (ISS), and the Connor-Davidson Resilience Scale (CD-RISC) were completed pre- and post-intervention. The data analysis was done by SPSS16. RESULTS: This study showed the mean resilience and inner strength scores before and after the intervention in the control group had no statistically significant difference(P˃0.05). There was a significant increase in the mean resilience and inner strength scores in the intervention group after the intervention (P ≤ 0.001). CONCLUSION: The results of this study showed that mHealth as a kind of telenursing nursing has a significant effect on both variables of inner strength and resilience of post-discharge elderly patients after acute myocardial infarction. This means that using mHealth for these patients could increase the inner strength and resilience of the elderly discharged after myocardial infarction. Therefore, through using this method, elderly patients' self-care ability and quality of life could be increased.

Enhancing asthma research and improving health equity through decentralized clinical trials (DCTs) and mHealth technology.

The COVID-19 pandemic led to widespread disruption and termination of clinical research and a prompt adoption of mobile health (mHealth) technologies in the healthcare space. As the United States' healthcare system has rapidly become reliant on remotely conducted activities, the implementation of decentralized methods using mHealth technology in research investigation has become a necessary alternative to traditional in-person cohort studies. The aim of this article is to: report successful and unsuccessful examples of remote asthma clinical studies, explore the benefits and potential drawbacks of virtual clinical investigation, discuss the potential impact on equity and representation in asthma research, and provide suggestions through which investigators can implement decentralized clinical trials. Enhanced study accessibility, participant diversity, safety measures, and research efficacy are some of the benefits identified with a focused discussion on the impact on equity that decentralized clinical trials renders. Furthermore, potential concerns regarding regulatory compliance, data privacy, and effective mHealth design and solutions are discussed. Despite the setbacks and interruptions faced by the study participants and investigators due to the pandemic, the transition to decentralized clinical studies using mHealth technology is a positive, feasible step toward innovation and equity in the allergy and immunology field.

ASTHMAXcel PRO patient satisfaction and usability field testing.

Background: ASTHMAXcel PRO, an enhanced version of the ASTHMAXcel mobile application, has been developed to deliver comprehensive, guideline-based asthma education while also facilitating the collection of patient-reported outcomes (PROs) and enhancing user experience.Objective: To perform field testing and conduct formative and summative evaluation of the ASTHMAXcel PRO application to assess its impact on patient satisfaction, usability, and usage.Methods: Twenty-eight adult patients completed a baseline visit during which ASTHMAXcel PRO was introduced, health literacy was assessed, and demographic data were collected. They were instructed to use the app for 4 weeks. The Questionnaire for User Interface Satisfaction (QUIS) and the Unified Theory of Acceptance and Use of Technology (UTAUT) questionnaire were administered at baseline and 4 weeks to assess user satisfaction and technology acceptance, respectively. Semi-structured interviews were conducted to gather feedback regarding the application from patients.Results: The baseline total scores were high for both UTAUT and QUIS (mean (SD): 64.2 (10.1), 6.8 (2.2) respectively) indicating that user satisfaction and acceptance began at high levels. UTAUT total score, as well as all domain scores, improved significantly from baseline to 4 weeks (p < 0.02). QUIS total score along with several domain scores (screen, system capabilities, usability) also increased from baseline to 4-weeks (p = 0.03, 0.01, 0.03, 0.01, respectively). These improvements remained significant when adjusting for age, gender, education, and health literacy. Patients reported that the application was helpful, informative, and easy to understand and use.Conclusion: The significant increases in satisfaction and technology adoption observed among ASTHMAXcel PRO users demonstrate that the application is viable and has the potential to improve upon usability challenges faced by existing mobile health applications.

Are populations of postpartum women differentially served by community health worker programs: an observational cohort study from Zanzibar, Tanzania.

BACKGROUND: Although community health worker (CHW) programs focus on improving access to healthcare, some individuals may not receive the intended quality or quantity of an intervention. The objective of this research was to examine if certain populations of pregnant women differentially experience the implementation of a community health worker-led maternal health intervention in Zanzibar. METHODS: We included pregnant women enrolled in the Safer Deliveries (Uzazi Salama) program, which operated in 10 of 11 districts in Zanzibar, Tanzania between January 1, 2017, and June 19, 2019 (N = 33,914). The outcomes of interest were receipt of the entire postpartum intervention (three CHW visits) and time to first postpartum CHW visit (days). Visits by CHWs were done at the women's home, however, a telehealth option existed for women who were unable to be reached in-person. We conducted statistical tests to investigate the bivariate associations between our outcomes and each demographic and health characteristic. We used multivariate logistic regression to estimate the relationships between covariates and the outcomes and multivariate linear regression to estimate the association between covariates and the average time until first postpartum visit. RESULTS: Higher parity (OR = 0.85; P = 0.014; 95%CI: 0.75-0.97), unknown or unreported HIV status (OR = 0.64; p < 0.001; 95%CI: 0.53-0.78), and receipt of phone consultations (OR = 0.77; p < 0.001; 95%CI: 0.69-0.87) were associated with a lower odds of receiving all postpartum visits. Similarly, women with an unknown or unreported HIV status (estimated mean difference of 1.81 days; p < 0.001; 95%CI: 1.03-2.59) and those who received a phone consultation (estimated mean difference of 0.83 days; p < 0.001; 95%CI: 0.43-1.23), on average, experienced delays to first visit. In addition, current delivery at a referral hospital was associated with lower odds of receiving a postpartum visit and longer time to first visit compared to delivery at home, cottage hospital, PHCU + , or district hospital. Women from all other districts received their first visit earlier than women from Kaskazini B. There were no differences in the odds of receiving the entire postpartum intervention by sociodemographic variables, including age, education, and poverty assessment indicators. CONCLUSION: The results indicate no differences in intervention contact across wealth and education levels, suggesting that the program is effectively reaching women regardless of SES. However, women with other characteristics (e.g., higher parity, unknown or unreported HIV status) had lower odds of receiving the complete intervention. Overall, this work generates knowledge on existing disparities in intervention coverage and enables future programs to develop approaches to achieve equity in health care utilization and outcomes.

Dynamics of Perceived Social Isolation, Secondary Conditions, and Daily Activity Patterns Among Individuals With Stroke: A Network Analysis of Ecological Momentary Assessment Data.

OBJECTIVE: To assess contemporaneous and temporal dynamics of perceived social isolation (PSI), secondary conditions, and daily activity patterns in individuals post-stroke. DESIGN: Longitudinal observational study using ecological momentary assessment (EMA) as a real-time assessment of an individual's lived experiences. We conducted dynamic network analyses to examine longitudinal associations among EMA variables. SETTINGS: Home and Community. PARTICIPANTS: 202 individuals with mild-to-moderate chronic stroke (median age=60 years; 45% women; 44% black; 90% ischemic stroke; median NIHSS score=2; N=202). INTERVENTION: Not applicable. MAIN OUTCOME MEASURES: EMA questions measured PSI, secondary conditions (pain, tiredness, stress, anxiety, worthlessness, difficulty concentrating, and cheerfulness), and daily activity patterns (being at home, being alone, and participating in productive activities). RESULTS: The median EMA response rate was 84%. The contemporaneous model showed that PSI was associated with being home, alone, and all symptoms except pain. The temporal model revealed a pathway indicating that feelings of worthlessness predicted PSI (regression coefficient=0.06, P=.019), followed by stress (regression coefficient=0.06, P=.024), and then by being not at home (regression coefficient=-0.04, P=.013). CONCLUSION: Implementing dynamic network analyses on EMA data can uncover dynamic connections among PSI, secondary conditions, and daily activity patterns after stroke. This study found a significant temporal association between PSI and negative emotions. Feeling isolated was followed by feeling stressed, which was followed by a tendency to be out of home, indicating adaptive behaviors in individuals with stroke. These findings highlight the importance of engaging in out-of-home or outdoor activities to mitigate PSI and negative emotions.

Contribution of MASK-air® as a mHealth tool for digitally-enabled person-centred care in rhinitis and asthma.

In chronic diseases, mobile health apps may help to (i) improve clinical management and (ii) provide valuable real-world scientific evidence. In allergic rhinitis, a market research study has only identified four mHealth apps which were multilingual, resulted in scientific publications and displayed a comprehensive list of medications. Ot those, MASK-air® was the app with the highest number of scientific publications. MASK-air® has been launched in 2015 and is currently available in 30 countries, having collected data from more than 30,000 users. It comprises a daily monitoring questionnaire, allowing patients to register (i) their daily allergy symptoms by means of visual analogue scales, and (ii) their medication use. The achievements of MASK-air® include the development of two digital biomarkers for daily monitoring of rhinitis and asthma (combined symptom-medication score and electronic daily asthma control score). In addition, MASK-air® data have allowed to assess patients' behaviours, suggesting that patients do not follow guideline recommendations, but rather treat themselves (and often use co-medication) whenever feeling worse. Using MASK-air® data, it has also been possible to quantify the impact of allergic diseases in quality-of-life, school and work productivity. MASK-air® real-world data is being used as a source of evidence for the Allergic Rhinitis and its Impact on Asthma 2024 guidelines, in an innovative process of incorporation of mobile health data into guidelines. This review discusses the clinical and scientific contributions of MASK-air® for person-centred care of rhinitis and asthma, providing an illustrative example on the use of mobile health in chronic diseases.