Effects of the "AI-TA" Mobile App With Intelligent Design on Psychological and Related Symptoms of Young Survivors of Breast Cancer: Randomized Controlled Trial.

BACKGROUND: Young women often face substantial psychological challenges in the initial years following cancer diagnosis, leading to a comparatively lower quality of life than older survivors. While mobile apps have emerged as potential interventions, their effectiveness remains inconclusive due to the diversity in intervention types and variation in follow-up periods. Furthermore, there is a particular dearth of evidence regarding the efficacy of these apps' intelligent features in addressing psychological distress with these apps. OBJECTIVE: This study aims to evaluate the effectiveness of a mobile app with intelligent design called "AI-TA" on cancer-related psychological health and ongoing symptoms with a randomized controlled design. METHODS: Women aged 18 to 45 years diagnosed with breast cancer were randomly assigned to the intervention or control group. The intervention was AI-TA, which included 2-way web-based follow-up every 2 weeks. Both intention-to-treat (ITT) and per-protocol (PP) analyses employed repeated measurement analysis of variance. The participants' background features, primary outcomes (psychological distress and frequency, self-efficacy, and social support), and secondary outcomes (quality of life) were measured using multiple instruments at 3 time points (baseline, 1-month intervention, and 3-month intervention). RESULTS: A total of 124 participants were randomly allocated to the control group (n=62, 50%) or intervention group (n=62, 50%). In total, 92.7% (115/124) of the participants completed the intervention. Significant improvements in psychological symptoms (Memorial Symptom Assessment Scale-Short Form) were observed in the ITT group from baseline to 1-month intervention relative to the control group (ITT vs control: 1.17 vs 1.23; P<.001), which persisted at 3-month follow-up (ITT vs control: 0.68 vs 0.91; P<.001). Both the ITT and PP groups exhibited greater improvements in self-efficacy (Cancer Behavior Inventory-Brief Version) than the control group at 1-month (ITT vs PP vs control: 82.83 vs 77.12 vs 65.35; P<.001) and 3-month intervention (ITT vs PP vs control: 92.83 vs 89.30 vs 85.65; P<.001). However, the change in social support (Social Support Rating Scale) did not increase significantly until 3-month intervention (ITT vs control: 50.09 vs 45.10; P=.002) (PP vs control: 49.78 vs 45.10; P<.001). All groups also experienced beneficial effects on quality of life (Functional Assessment of Cancer Therapy-Breast), which persisted at 3-month follow-up (P<.001). CONCLUSIONS: The intelligent mobile app AI-TA incorporating intelligent design shows promise for reducing psychological and cancer-related symptoms among young survivors of breast cancer. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2200058823; https://www.chictr.org.cn/showproj.html?proj=151195.

Draft genome sequence of Bacillus thuringiensis strain V-AB8.18, a novel isolate with potential nematicidal activity.

We report the draft genome of Bacillus thuringiensis strain V-AB8.18, comprising 308 contigs totaling 6,182,614 bp, with 35% G + C content. It contains 6,151 putative protein-coding genes, including App6 and Cry5-like crystal proteins, exhibiting 99% pairwise identity to nematicidal proteins App6Aa2 and Cry5Ba2, active against Meloidogyne incognita and Meloidogyne hapla.

Telemedicine With Wearable Technologies in Patients Undergoing Hematopoietic Cell Transplantation and Chimeric Antigen Receptor T-Cell Therapy (TEL-HEMATO Study): Prospective Noninterventional Single-Center Study.

BACKGROUND: Patients with hematological malignancies receiving hematopoietic cell transplantation (HCT) or chimeric antigen receptor (CAR) T-cell therapy are at risk of developing serious clinical complications after discharge. OBJECTIVE: The aim of the TEL-HEMATO study was to improve our telehealth platform for the follow-up of patients undergoing HCT or CAR T-cell therapy during the first 3 months after discharge with the addition of wearable devices. METHODS: Eleven patients who received autologous (n=2) or allogeneic (n=5) HCT or CAR T-cell therapy (n=4) for hematological malignancies were screened from November 2022 to July 2023. Two patients discontinued the study after enrollment. The telehealth platform consisted of the daily collection of vital signs, physical symptoms, and quality of life assessment up to 3 months after hospital discharge. Each patient received a clinically validated smartwatch (ScanWatch) and a digital thermometer, and a dedicated smartphone app was used to collect these data. Daily revision of the data was performed through a web-based platform by a hematologist or a nurse specialized in HCT and CAR T-cell therapy. RESULTS: Vital signs measured through ScanWatch were successfully collected with medium/high adherence: heart rate was recorded in 8/9 (89%) patients, oxygen saturation and daily steps were recorded in 9/9 (100%) patients, and sleeping hours were recorded in 7/9 (78%) patients. However, temperature recorded manually by the patients was associated with lower compliance, which was recorded in 5/9 (55%) patients. Overall, 5/9 (55%) patients reported clinical symptoms in the app. Quality of life assessment was completed by 8/9 (89%) patients at study enrollment, which decreased to 3/9 (33%) at the end of the third month. Usability was considered acceptable through ratings provided on the System Usability Scale. However, technological issues were reported by the patients. CONCLUSIONS: While the addition of wearable devices to a telehealth clinical platform could have potentially synergic benefits for HCT and CAR T-cell therapy patient monitoring, noncomplete automation of the platform and the absence of a dedicated telemedicine team still represent major limitations to be overcome. This is especially true in our real-life setting where the target population generally comprises patients of older age with a low digital education level.

Supporting parents with acutely ill children: Environment scan and user evaluation of mobile applications (the SuPa kids project).

BACKGROUND: Children are one of the biggest users of emergency departments in the UK, sometimes utilising services when experiencing acute illnesses that can be managed at home. mHealth can be an efficacious way for parents/guardians to manage acute illnesses. It has also become a ubiquitous resource to promote public health interests within a resource constrained health system. However, to be effective, co-design is necessary with concepts such as usefulness, ease of use, trustworthiness and security underpinning the utility of mHealth interventions for acute childhood illness. OBJECTIVE: The objective of this study was to conduct an environmental scan of mHealth apps for parental assessment and management of acute childhood illnesses in 0- to 5-year-olds, review the content and functionality of each identified app against the list of desired attributes identified in previous research and synthesise publicly available reviews from end users to demonstrate the quality of current apps in the marketplace and identify areas for improvement. METHOD: App characteristics were mapped to an a priori defined list of desirable attributes. End user reviews were mapped to a modified Technology Acceptance Model framework that included overarching themes of: Perceived Usefulness (PU), Perceived Ease of Use (PEU), Perceived Trustworthiness (PT) and Perceived Security (PS) using reflexive thematic analysis. RESULTS: Overall, 15 apps were included in the analysis (Table 2). Fourteen of the 15 apps were available on both the iOS and Android platforms. 'Baby Illness, Prevention, Cure' was only available on the Android store. All apps were free to download and did not restrict access to information or features via in-app purchases. Baby and child first aid (British Red Cross) was the earliest app to be released (2014). This app was updated annually, with the most recent update being 2022. The most recent apps to be released (2018) were 'AskFirst' (formerly Ask NHS), 'Essex Child Health' and 'The Lullaby Trust Baby Check', updated in 2022, 2020 and 2019, respectively. No individual app met all the desirable attributes highlighted by parents in previous research. Both 'Healthier Together', and 'The Lullaby Trust Baby Check' included all but one desirable attributes (video), as did the ''CATCH (Common Approach to Children's Health), which did not utilise a traffic light system. Apps that were locality specific were not rated by users (Berkshire Child Health, Cheshire Child Health, Child Health Guide Newham, Child Health HMR, Oldham Child Illness and Walsall Healthy Child). All other apps were rated from 2/5 to 5/5 stars. When considering localities, the 'CATCH' app was only supported in Halton, Cheshire, Knowsley, Liverpool, St Helens and Vale Royal. Further investigation evidenced no correlation between inclusion of the desirable attributes and app rating. CONCLUSION: Overall, this research has highlighted several aspects of best practise when developing mHealth apps for the management of acute childhood illnesses, for increasing PU, PEU, PT and PS; and also, places importance on co-design.

Does an App a Day Keep the Doctor Away? AI Symptom Checker Applications, Entrenched Bias, and Professional Responsibility.

The growing prominence of artificial intelligence (AI) in mobile health (mHealth) has given rise to a distinct subset of apps that provide users with diagnostic information using their inputted health status and symptom information-AI-powered symptom checker apps (AISympCheck). While these apps may potentially increase access to health care, they raise consequential ethical and legal questions. This paper will highlight notable concerns with AI usage in the health care system, further entrenchment of preexisting biases in the health care system and issues with professional accountability. To provide an in-depth analysis of the issues of bias and complications of professional obligations and liability, we focus on 2 mHealth apps as examples-Babylon and Ada. We selected these 2 apps as they were both widely distributed during the COVID-19 pandemic and make prominent claims about their use of AI for the purpose of assessing user symptoms. First, bias entrenchment often originates from the data used to train AI systems, causing the AI to replicate these inequalities through a "garbage in, garbage out" phenomenon. Users of these apps are also unlikely to be demographically representative of the larger population, leading to distorted results. Second, professional accountability poses a substantial challenge given the vast diversity and lack of regulation surrounding the reliability of AISympCheck apps. It is unclear whether these apps should be subject to safety reviews, who is responsible for app-mediated misdiagnosis, and whether these apps ought to be recommended by physicians. With the rapidly increasing number of apps, there remains little guidance available for health professionals. Professional bodies and advocacy organizations have a particularly important role to play in addressing these ethical and legal gaps. Implementing technical safeguards within these apps could mitigate bias, AIs could be trained with primarily neutral data, and apps could be subject to a system of regulation to allow users to make informed decisions. In our view, it is critical that these legal concerns are considered throughout the design and implementation of these potentially disruptive technologies. Entrenched bias and professional responsibility, while operating in different ways, are ultimately exacerbated by the unregulated nature of mHealth.

Feasibility of app-based home monitoring after abdominal surgery: A systematic review.

BACKGROUND: Abdominal surgery presents great challenges postoperatively. Considering financial healthcare constraints, the use of mobile applications has received increased interest. This systematic review was conducted to assess and report the feasibility of app-based home monitoring after abdominal surgery. METHODS: MEDLINE, EMBASE, and The Cochrane Library were searched on the October 17, 2023. This systematic review was conducted in accordance with the PRISMA guidelines. RESULTS: Thirty-six articles were included, 17 of these originating from USA or Canada. The response rate varied between 11.9 â€‹% and 100 â€‹%. Bariatric, upper gastrointestinal, and colorectal surgery reported the highest response rates. All included studies had a degree of bias. CONCLUSION: This study found varying response rates. The data indicated that the response rates were high within bariatric surgery, with additional factors potentially affecting this. The degree of bias was generally high, and the quality of the included studies limits the conclusions.

Restoring Brain Pathways Involved in Diabetes-Associated Neurocognitive Disorders: The Potential of Dipeptidyl Peptidase 4 Inhibitors as a Therapeutic Strategy.

Diabetes, a widespread chronic metabolic disease, is projected to affect 783 million people globally by 2045. Recent studies emphasize the neuroprotective potential of dipeptidyl peptidase 4 (DPP4i) inhibitors, pointing toward a promising avenue for intervention in addressing cognitive challenges associated with diabetes. Due to limited data on the effect of DPP4i on brain pathways involved in diabetes-related neurocognitive disorders, the decision was made to conduct this study to fill existing knowledge gaps on this topic. The primary aim of our study was to evaluate the potential of DPP4 inhibitors (DPP4i) in preventing cognitive decline in mice with type 2 diabetes (T2D), placing special emphasis on gaining insight into the complex molecular mechanisms underlying this action. We examined drug efficacy in modulating neurotrophic factors, calcium levels, and the expression of key genes (HIF1α, APP, Arc) crucial for neural plasticity. Conducting cognitive assessments with the hole board and passive avoidance tests, we discerned a remarkable influence of short-term gliptin usage on the limiting progress of cognitive dysfunction in diabetic mice. The administration of DPP4 inhibitors led to heightened neurotrophin levels, increased HIF1α in the prefrontal cortex, and a significant elevation in Arc mRNA levels. Our findings reveal that DPP4 inhibitors effectively limit the progression of diabetes-related cognitive disorders. This breakthrough discovery not only opens new research avenues but also constitutes a potential starting point for creating innovative strategies for the treatment of central nervous system disorders focused on improving cognitive abilities.

High Throughput Phosphoglycolate Phosphatase Activity Assay Using Crude Leaf Extract and Recombinant Enzyme to Determine Kinetic Parameters Km and Vmax Using a Microplate Reader.

Determining enzyme activities involved in photorespiration, either in a crude plant tissue extract or in a preparation of a recombinant enzyme, is time-consuming, especially when large number of samples need to be processed. This chapter presents a phosphoglycolate phosphatase (PGLP) activity assay that is adapted for use in a 96-well microplate format. The microplate format for the assay requires fewer enzymes and reagents and allows rapid and less expensive measurement of PGLP enzyme activity. The small volume of reaction mix in a 96-well microplate format enables the determination of PGLP enzyme activity for screening many plant samples, multiple enzyme activities using the same protein extract, and/or identifying kinetic parameters for a recombinant enzyme. To assist in preparing assay reagents, we also present an R Shiny buffer preparation app for PGLP and other photorespiratory enzyme activities and a Km and Vmax calculation app.

An App-Based Physical Activity Intervention in Community-Dwelling Chinese-, Tagalog-, and Vietnamese-Speaking Americans: Single-Arm Intervention Study.

BACKGROUND: Physical inactivity is associated with adverse health outcomes among Asian Americans, who exhibit the least adherence to physical activity guidelines compared with other racial and ethnic groups. Mobile app-based interventions are a promising approach to promote healthy behaviors. However, there is a lack of app-based interventions focused on improving physical activity among Asian Americans whose primary language is not English. OBJECTIVE: This pilot study aimed to assess the feasibility and acceptability of a 5-week intervention using a culturally and linguistically adapted, evidence-based mobile phone app with an accelerometer program, to promote physical activity among Chinese-, Tagalog-, or Vietnamese-speaking Americans. METHODS: Participants were recruited through collaborations with community-based organizations. The intervention was adapted from a 12-month physical activity randomized controlled trial involving the app and accelerometer for English-speaking adults. Sociodemographic characteristics, lifestyle factors, and physical measurements were collected at the baseline visit. A 7-day run-in period was conducted to screen for the participants who could wear a Fitbit One (Fitbit LLC) accelerometer and complete the app's daily step diary. During the 4-week intervention period, participants wore the accelerometer and reported their daily steps in the app. Participants also received daily messages to reinforce key contents taught during an in-person educational session, remind them to input steps, and provide tailored feedback. Feasibility measures were the percentage of eligible participants completing the run-in period and the percentage of participants who used the app diary for at least 5 out of 7 days during the intervention period. We conducted poststudy participant interviews to explore overall intervention acceptability. RESULTS: A total of 19 participants were enrolled at the beginning of the study with a mean age of 47 (SD 13.3; range 29-70) years, and 58% (n=11) of them were female. Of the participants, 26% (n=5) were Chinese, 32% (n=6) were Vietnamese, and 42% (n=8) were Filipino. All participants met the run-in criteria to proceed with the intervention. Adherence to the app diary ranged from 74% (n=14) in week 2 to 95% (n=18) in week 4. The daily average steps per week from accelerometers increased each week from 8451 (SD 3378) steps during the run-in period to 10,930 (SD 4213) steps in week 4. Participants reported positive experiences including an increased motivation to walk and the enjoyment of being able to monitor their physical activity. CONCLUSIONS: This is the first pilot study of a multicomponent intervention and evidence-based mobile phone app to promote physical activity among Asian Americans who use apps in traditional Chinese, Tagalog, or Vietnamese, which demonstrated high feasibility and acceptability. Future work focused on multilingual mobile apps to address disparities in physical inactivity among Asian Americans should be considered.

Behavioral Weight Loss Programs for Cancer Survivors Throughout Maryland: Protocol for a Pragmatic Trial and Participant Characteristics.

BACKGROUND: Clinical trials examining lifestyle interventions for weight loss in cancer survivors have been demonstrated to be safe, feasible, and effective. However, scalable weight loss programs are needed to support their widespread implementation. The ASPIRE trial was designed to evaluate real-world, lifestyle-based, weight loss programs for cancer survivors throughout Maryland. OBJECTIVE: The objectives of this protocol paper are to describe the design of a nonrandomized pragmatic trial, study recruitment, and baseline characteristics of participants. METHODS: Participants were aged ≥18 years, residing in Maryland, with a BMI ≥25 kg/m2, who reported a diagnosis of a malignant solid tumor, completed curative treatment, and had no ongoing or planned cancer treatment. Enrollment criteria were minimized to increase generalizability. The primary recruitment source was the Johns Hopkins Health System electronic health records (EHRs). Participants selected 1 of 3 remotely delivered weight loss programs: self-directed, app-supported, or coach-supported program. RESULTS: Participants were recruited across all 5 geographic regions of Maryland. Targeted invitations using EHRs accounted for 287 (84.4%) of the 340 participants enrolled. Of the 5644 patients invited through EHR, 5.1% (287/5644) enrolled. Participants had a mean age of 60.7 (SD 10.8) years, 74.7% (254/340) were female, 55.9% (190/340) identified as non-Hispanic Black, 58.5% (199/340) had a bachelor's degree, and the average BMI was 34.1 kg/m2 (SD 5.9 kg/m2). The most common types of cancers were breast (168/340, 49.4%), prostate (72/340, 21.2%), and thyroid (39/340, 8.5%). The self-directed weight loss program (n=91) included 25 participants who agreed to provide weights through a study scale; the app-supported program (n=142) included 108 individuals who agreed to provide their weight measurements; and the coach-supported weight loss program included 107 participants. We anticipate final analysis will take place in the fall of 2024. CONCLUSIONS: Using EHR-based recruitment efforts, this study took a pragmatic approach to reach and enroll cancer survivors into remotely delivered weight loss programs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04534309; https://clinicaltrials.gov/study/NCT04534309. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/54126.

App-based Therapy of Erectile Dysfunction Using a Digital Health Application (EDDIG Study): A Randomized, Single-blind, Controlled Trial.

BACKGROUND AND OBJECTIVE: While international guidelines advocate for a multifaceted approach to treating erectile dysfunction (ED) involving physical activities, psychological support, and education, structured programs are infrequent. To address this gap, an app-based therapy was developed, offering a systematic approach. This randomized, single-blind controlled trial aimed to assess the effectiveness of an app-based therapeutic in improving ED. METHODS: A total of 241 patients (49.74, standard deviation 12.73 yr) with ED (International Index of Erectile Function [IIEF]-5 <22) were randomized to the 12-wk app-based therapy (treatment group [TG], n = 122) or a waiting list for the app with continuation of their current management protocol (control group [CG], n = 119). Patients on long-term medication for ED were included, but subsequent exclusion occurred for those starting new medication. Coprimary endpoints were improvements from baseline to 12 wk in erectile function (IIEF-5), disease-related quality of life (QOL-Med-15), and patient activation (Patient Activation Measure [PAM-13]). KEY FINDINGS AND LIMITATIONS: Erectile function (IIEF-5) improved by 4.5 points in the TG versus 0.2 points in the CG (p < 0.0001, 95% confidence interval [CI] 3.4-5.0) group. Quality of life (QOL-Med) improved by 20.5 points in the TG versus -0.0 points in the CG (p < 0.0001, 95% CI 19.2-26.0) group. Patient activation (PAM-13) improved by 11.2 points in the TG versus 0.6 points in the CG (p < 0.0001, 95% CI 9.1-13.6) group. Phosphodiesterase type 5 inhibitor intake had no influence on all observed treatment effects. CONCLUSIONS AND CLINICAL IMPLICATIONS: App-based therapy of patients with ED provided a significant, clinically meaningful improvement. Quality of life and patient activation were also enhanced significantly. This program has the potential to change clinical practice in the treatment of ED. PATIENT SUMMARY: A therapy app improved sexual function and overall well-being for men experiencing erectile dysfunction, leading to better quality of life.

mHealth Intervention for Elevated Blood Pressure Among College Students: Single-Arm Intervention Study.

BACKGROUND: Current evidence reveals a growing pattern of hypertension among young adults, significantly increasing their risk for cardiovascular disease later in life. Young adults, particularly those of college age, often develop risk factors related to lifestyle choices in diet, exercise, and alcohol consumption. Developing useful interventions that can assist with screening and possible behavioral modifications that are suitable and appealing to college-aged young adults could help with early identification and intervention for hypertension. Recent studies indicate mobile health (mHealth) apps are acceptable and effective for communication and message delivery among this population. OBJECTIVE: The purpose of this study was to examine the feasibility of using a mobile smartphone delivery system that provides tailored messages based on participant self-measured blood pressure (BP) with college-aged young adults. METHODS: Using a single-arm intervention, pilot study design, the mHealth to Optimize BP Improvement (MOBILE) intervention was implemented with college students aged 18 years to 39 years who had systolic BP >120 mm Hg and diastolic BP ≥80 mm Hg. Participants were required to measure their BP daily for 28 days, submit the readings to the app, and receive preset educational text messages tailored to their BP value and related to encouraging healthy lifestyle modifications. Changes in a participant's BP was evaluated using a mixed regression model, and a postintervention survey evaluated their perspectives on the mHealth intervention. RESULTS: The participants' (N=9) mean age was 22.64 (SD 4.54) years; 56% (5/9) were overweight, and 11% (1/9) were obese. The average daily participation rate was 86%. Of the 9 participants, 8 completed the survey, and all indicated the intervention was easy to use, found it increased awareness of their individual BP levels, indicated the text messages were helpful, and reported making lifestyle changes based on the study intervention. They also provided suggestions for future implementation of the intervention and program. Overall, no significant changes were noted in BP over the 28 days. CONCLUSIONS: The mHealth-supported MOBILE intervention for BP monitoring and tailored text messaging was feasible to implement, as our study indicated high rates of participation and acceptability. These encouraging findings support further development and testing in a larger sample over a longer time frame and hold the potential for early identification and intervention among college-aged adults, filling a gap in current research.

App Engagement as a Predictor of Weight Loss in Blended-Care Interventions: Retrospective Observational Study Using Large-Scale Real-World Data.

BACKGROUND: Early weight loss is an established predictor for treatment outcomes in weight management interventions for people with obesity. However, there is a paucity of additional, reliable, and clinically actionable early predictors in weight management interventions. Novel blended-care weight management interventions combine coach and app support and afford new means of structured, continuous data collection, informing research on treatment adherence and outcome prediction. OBJECTIVE: Against this backdrop, this study analyzes app engagement as a predictor for weight loss in large-scale, real-world, blended-care interventions. We hypothesize that patients who engage more frequently in app usage in blended-care treatment (eg, higher logging activity) lose more weight than patients who engage comparably less frequently at 3 and 6 months of intervention. METHODS: Real-world data from 19,211 patients in obesity treatment were analyzed retrospectively. Patients were treated with 3 different blended-care weight management interventions, offered in Switzerland, the United Kingdom, and Germany by a digital behavior change provider. The principal component analysis identified an overarching metric for app engagement based on app usage. A median split informed a distinction in higher and lower engagers among the patients. Both groups were matched through optimal propensity score matching for relevant characteristics (eg, gender, age, and start weight). A linear regression model, combining patient characteristics and app-derived data, was applied to identify predictors for weight loss outcomes. RESULTS: For the entire sample (N=19,211), mean weight loss was -3.24% (SD 4.58%) at 3 months and -5.22% (SD 6.29%) at 6 months. Across countries, higher app engagement yielded more weight loss than lower engagement after 3 but not after 6 months of intervention (P3 months<.001 and P6 months=.59). Early app engagement within the first 3 months predicted percentage weight loss in Switzerland and Germany, but not in the United Kingdom (PSwitzerland<.001, PUnited Kingdom=.12, and PGermany=.005). Higher age was associated with stronger weight loss in the 3-month period (PSwitzerland=.001, PUnited Kingdom=.002, and PGermany<.001) and, for Germany, also in the 6-month period (PSwitzerland=.09, PUnited Kingdom=.46, and PGermany=.03). In Switzerland, higher numbers of patients' messages to coaches were associated with higher weight loss (P3 months<.001 and P6 months<.001). Messages from coaches were not significantly associated with weight loss (all P>.05). CONCLUSIONS: Early app engagement is a predictor of weight loss, with higher engagement yielding more weight loss than lower engagement in this analysis. This new predictor lends itself to automated monitoring and as a digital indicator for needed or adapted clinical action. Further research needs to establish the reliability of early app engagement as a predictor for treatment adherence and outcomes. In general, the obtained results testify to the potential of app-derived data to inform clinical monitoring practices and intervention design.

Correlates of Problematic Gambling in Emerging Adult University Students in Ireland.

INTRODUCTION: Understanding the correlates of problematic gambling among emerging adult university students is crucial for developing effective approaches to minimise harm. METHODS: This cross-sectional survey study reports on 397 18-25 year old emerging adults studying at Irish universities who completed an online survey about problematic gambling and a range of biopsychosocial variables. Chi-square and binary logistic regression analyses explored the relationships between problematic gambling and the biopsychosocial variables measured. RESULTS: Chi-square analyses showed that being male, having an online gambling account, having a mobile gambling app, novelty seeking (impulsivity), harm avoidance (fear of uncertainty), and high alcohol volume consumption were significantly associated with problematic gambling. Regression analyses showed that individuals were more likely to report problematic gambling if they were male (OR = 9.57 times), had an online gambling account (OR = 17.05 times), had a mobile gambling app (OR = 20.37 times), scored high in impulsivity (OR = 7.79 times), and reported high alcohol volume consumption (OR = 4.66 times). Individuals were less likely to report problematic gambling if they scored high in fear of uncertainty (OR = 0.26 times). CONCLUSIONS: A high rate of problematic gambling was observed among the current study sample. Participants were more likely to reported problematic gambling if they were male, had online gambling accounts, mobile gambling apps, scored high in impulsivity, scored low in fear of uncertainty, or consumed high volumes of alcohol in typical drinking sessions. These findings have implications for Irish legislation and policy-makers, Irish higher education institutions, and young adult Irish university students.

Gait characterization in rare bone diseases in a real-world environment - A comparative controlled study.

BACKGROUND: Rare bone diseases (RBD) cause physical and sensory disability that affects quality of life. Mobility challenges are common for people with RBDs, and travelling to gait analysis labs can be very complex. Smartphone sensors could provide remote monitoring. RESEARCH QUESTION: This study aimed to search for and identify variables that can be used to discriminate between people with RBD and healthy people by using built-in smartphone sensors in a real-world setting. METHODS: In total, 18 participants (healthy: n=9; RBD: n=9), controlled by age and sex, were included in this cross-sectional study. A freely available App (Phyphox) was used to gather data from built-in smartphone sensors (accelerometer & gyroscope) at 60 Hz during a 15-min walk on a level surface without turns or stops. Temporal gait parameters like cadence, mean stride time and, coefficient variance (CoVSt) and nonlinear analyses, as the largest Lyapunov exponent (LLE) & sample entropy (SE) in the three accelerometer axes were used to distinguish between the groups and describe gait patterns. RESULTS: The LLE (p=0.04) and the SE of the z-axis (p=0.01), which are correlated with balance control during walking and regularity of the gait, are sufficiently sensitive to distinguish between RBD and controls. SIGNIFICANCE: The use of smartphone sensors to monitor gait in people with RBD allows for the identification of subtle changes in gait patterns, which can be used to inform assessment and management strategies in larger cohorts.

Mobile-UI-Repair: a deep learning based UI smell detection technique for mobile user interface.

The graphical user interface (GUI) in mobile applications plays a crucial role in connecting users with mobile applications. GUIs often receive many UI design smells, bugs, or feature enhancement requests. The design smells include text overlap, component occlusion, blur screens, null values, and missing images. It also provides for the behavior of mobile applications during their usage. Manual testing of mobile applications (app as short in the rest of the document) is essential to ensuring app quality, especially for identifying usability and accessibility that may be missed during automated testing. However, it is time-consuming and inefficient due to the need for testers to perform actions repeatedly and the possibility of missing some functionalities. Although several approaches have been proposed, they require significant performance improvement. In addition, the key challenges of these approaches are incorporating the design guidelines and rules necessary to follow during app development and combine the syntactical and semantic information available on the development forums. In this study, we proposed a UI bug identification and localization approach called Mobile-UI-Repair (M-UI-R). M-UI-R is capable of recognizing graphical user interfaces (GUIs) display issues and accurately identifying the specific location of the bug within the GUI. M-UI-R is trained and tested on the history data and also validated on real-time data. The evaluation shows that the average precision is 87.7% and the average recall is 86.5% achieved in the detection of UI display issues. M-UI-R also achieved an average precision of 71.5% and an average recall of 70.7% in the localization of UI design smell. Moreover, a survey involving eight developers demonstrates that the proposed approach provides valuable support for enhancing the user interface of mobile applications. This aids developers in their efforts to fix bugs.

Effectiveness of mHealth apps on adherence and symptoms to oral anticancer medications: a systematic review and meta-analysis.

PURPOSE: Despite the rapid expansion of mHealth apps, their adoption has not always been based on evidence of effectiveness on patient outcomes. This systematic review aimed to determine the effect of mHealth apps on adherence and symptom to oral anticancer medications (OAMs) and identify the app design that led to such effects. METHODS: Pubmed, Cochrane Central, PsycINFO, EMBASE, and WoS were searched from inception to April 2023. Randomised controlled trials (RCTs) that evaluated effects of mHealth apps on primary outcomes OAM adherence and symptom burden were included. Two reviewers independently assessed risk-of-bias using Cochrane Risk-of-Bias version 2 and extracted the data. Quality of evidence was assessed using GRADE. The protocol was registered in PROSPERO (CRD42023406024). RESULTS: Four RCTs involving 806 patients with cancer met the eligibility criteria. mHealth apps features included a combinations of symptom reporting, medication reminder, automated alert to care team, OAM and side effect information, one study implemented structured follow-up by a nurse. The intervention group showed no significant difference in OAM adherence (relative ratio 1.20; 95% CI 1.00 to 1.43), but significantly improved symptoms to OAMs with a lower standardised mean symptom burden score of 0.49 (SMD - 0.49; 95% CI - 0.93 to - 0.06), and a 25% lower risk of grade 3 or 4 toxicity (risk ratio 0.75; 95% CI 0.58 to 0.95) compared to usual care. CONCLUSION: These findings suggest a potential role for mHealth app in managing OAM side effect. Further research should explore the role of AI-guided algorithmic pathways on the interactive features of mHealth apps.

Protocol for the Support Application for Food PAntrieS trial: design, implementation, and evaluation plan for a digital application to promote healthy food access and support food pantry operations.

Introduction: Food-insecure households commonly rely on food pantries to supplement their nutritional needs, a challenge that was underscored during the COVID-19 pandemic. Food pantries, and the food banks that supply them, face common challenges in meeting variable client volume and dietary needs under normal and emergency (e.g., pandemic, natural disaster) conditions. A scalable digital strategy that has the capacity to streamline the emergency food distribution system, while promoting healthy food options, managing volunteer recruitment and training, and connecting to emergency management systems in times of need, is urgently required. To address this gap, we are developing a working mobile application (app) called the Support Application for Food PAntrieS (SAFPAS) and will evaluate its feasibility and impact on food pantry staff preparedness, stocking, and client uptake of healthful foods and beverages in two urban United States settings. Methods: This paper describes the protocol for a randomized controlled trial of the SAFPAS mobile application. We will conduct formative research in Baltimore, Maryland and Detroit, Michigan to develop and refine the SAFPAS app and increase scalability potential to other urban settings. Then we will test the app in 20 food pantries in Baltimore randomized to intervention or comparison. The impact of the app will be evaluated at several levels of the emergency food system, including food pantry clients (n = 360), food pantry staff and volunteers (n = 100), food pantry stock, and city agencies such as the local food bank and Office of Emergency Management. The primary outcome of the SAFPAS trial is to improve the healthfulness of the foods received by food pantry clients, measured using the Food Assessment Scoring Tool (FAST). Post-trial, we will conduct additional formative research in Detroit to prepare the app for scale-up. Discussion: We anticipate that SAFPAS will improve alignment in the supply and demand for healthy foods among food pantry clients, food pantries, and city agencies which supply food in Baltimore. Real-time, bidirectional communication between entities across the system allows for increased situational awareness at all levels during normal and emergency operations. By conducting formative research in Detroit, we hope to increase the scalability of the SAFPAS app to additional settings nationwide. Clinical trial registration: NCT87654321. https://classic.clinicaltrials.gov/ct2/show/NCT05880004.

Junior and senior students possess differential preferences towards multimodal digital anatomy resources.

Digital technologies are changing how anatomy is taught tremendously. However, little is known about the effective integration of multimodal digital resources when concurrently provided in an anatomy course. To address this question, an array of digital anatomy resources including Augmented Reality (AR) and Virtual Reality (VR) anatomy resources were concurrently trialed by a total of 326 undergraduate and postgraduate students across three undergraduate (systemic anatomy, neuroanatomy, and regional anatomy) and one postgraduate anatomy (applied musculoskeletal anatomy) curricula in 2022. A five-point Likert scale learning and teaching survey was conducted to evaluate students' experiences, preferences, and perceptions. Most undergraduate (81% systemic anatomy, 76% neuroanatomy, and 87% regional anatomy) and postgraduate (97%) participants across the four cohorts felt confident in studying anatomy using digital resources and the majority (>80% undergraduate and >90% postgraduate) found the multimodal digital anatomy resources interactive and stimulating. The response showed that undergraduate (77% systemic anatomy, 81% neuroanatomy, and 97% regional anatomy) and postgraduate students (92%) consistently enjoyed their experience of using multimodal digital anatomy resources and thought that these resources enhanced their interest in studying anatomy. However, there are significant differences in ratings of specific digital resources among the junior (first-year undergraduates) and senior (third-year undergraduates and postgraduates) students. The virtual dissection table was uniformly preferred by the four cohorts of students across the board. Interestingly, however, VR anatomy and radiographic-based digital anatomy resources received diverse ratings. VR anatomy was valued most by junior undergraduate students (84%) who studied systemic anatomy compared to their senior counterparts (73%) who studied regional anatomy, whereas radiographic-based digital anatomy resources were more valued by the postgraduate students (93%) compared to undergraduates (65% systemic anatomy, 73% neuroanatomy, and 48% regional anatomy). This study identifies that while students uniformly appreciate the value of multimodal digital anatomy teaching, there is a clear difference in their perceptions towards individual resources, likely in a course-specific manner. We conclude that the selection and adoption of digital anatomy tools must be tailored as part of course design and that digital anatomy tools should be used in combination to provide an effective learning experience for students.

Handling of outcome missing data dependent on measured or unmeasured background factors in micro-randomized trial: Simulation and application study.

Background: Micro-randomized trials (MRTs) enhance the effects of mHealth by determining the optimal components, timings, and frequency of interventions. Appropriate handling of missing values is crucial in clinical research; however, it remains insufficiently explored in the context of MRTs. Our study aimed to investigate appropriate methods for missing data in simple MRTs with uniform intervention randomization and no time-dependent covariates. We focused on outcome missing data depending on the participants' background factors. Methods: We evaluated the performance of the available data analysis (AD) and the multiple imputation in generalized estimating equations (GEE) and random effects model (RE) through simulations. The scenarios were examined based on the presence of unmeasured background factors and the presence of interaction effects. We conducted the regression and propensity score methods as multiple imputation. These missing data handling methods were also applied to actual MRT data. Results: Without the interaction effect, AD was biased for GEE, but there was almost no bias for RE. With the interaction effect, estimates were biased for both. For multiple imputation, regression methods estimated without bias when the imputation models were correct, but bias occurred when the models were incorrect. However, this bias was reduced by including the random effects in the imputation model. In the propensity score method, bias occurred even when the missing probability model was correct. Conclusions: Without the interaction effect, AD of RE was preferable. When employing GEE or anticipating interactions, we recommend the multiple imputation, especially with regression methods, including individual-level random effects.