Investigating change in network structure of eating disorder symptoms after delivery of a smartphone app-based intervention.

BACKGROUND: Eating disorder (ED) research has embraced a network perspective of psychopathology, which proposes that psychiatric disorders can be conceptualized as a complex system of interacting symptoms. However, existing intervention studies using the network perspective have failed to find that symptom reductions coincide with reductions in strength of associations among these symptoms. We propose that this may reflect failure of alignment between network theory and study design and analysis. We offer hypotheses for specific symptom associations expected to be disrupted by an app-based intervention, and test sensitivity of a range of statistical metrics for identifying this intervention-induced disruption. METHODS: Data were analyzed from individuals with recurrent binge eating who participated in a randomized controlled trial of a cognitive-behavioral smartphone application. Participants were categorized into one of three groups: waitlist (n = 155), intervention responder (n = 49), and intervention non-responder (n = 77). Several statistical tests (bivariate associations, network-derived strength statistics, network invariance tests) were compared in ability to identify change in network structure. RESULTS: Hypothesized disruption to specific symptom associations was observed through change in bivariate correlations from baseline to post-intervention among the responder group but were not evident from symptom and whole-of-network based network analysis statistics. Effects were masked when the intervention group was assessed together, ignoring heterogeneity in treatment responsiveness. CONCLUSION: Findings are consistent with our contention that study design and analytic approach influence the ability to test network theory predictions with fidelity. We conclude by offering key recommendations for future network theory-driven interventional studies.

The effect of digital health interventions on postpartum depression or anxiety: a systematic review and meta-analysis of randomized controlled trials.

OBJECTIVE: This study aimed to examine the effect of digital health interventions compared with treatment as usual on preventing and treating postpartum depression and postpartum anxiety. DATA SOURCES: Searches were conducted in Ovid MEDLINE, Embase, Scopus, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov. STUDY ELIGIBILITY REQUIREMENTS: The systematic review included full-text randomized controlled trials comparing digital health interventions with treatment as usual for preventing or treating postpartum depression and postpartum anxiety. STUDY APPRAISAL AND SYNTHESIS METHODS: Two authors independently screened all abstracts for eligibility and independently reviewed all potentially eligible full-text articles for inclusion. A third author screened abstracts and full-text articles as needed to determine eligibility in cases of discrepancy. The primary outcome was the score on the first ascertainment of postpartum depression or postpartum anxiety symptoms after the intervention. Secondary outcomes included screening positive for postpartum depression or postpartum anxiety --as defined in the primary study --and loss to follow-up, defined as the proportion of participants who completed the final study assessment compared with the number of initially randomized participants. For continuous outcomes, the Hedges method was used to obtain standardized mean differences when the studies used different psychometric scales, and weighted mean differences were calculated when studies used the same psychometric scales. For categorical outcomes, pooled relative risks were estimated. RESULTS: Of 921 studies originally identified, 31 randomized controlled trials-corresponding to 5532 participants randomized to digital health intervention and 5492 participants randomized to treatment as usual-were included. Compared with treatment as usual, digital health interventions significantly reduced mean scores ascertaining postpartum depression symptoms (29 studies: standardized mean difference, -0.64 [95% confidence interval, -0.88 to -0.40]; I2=94.4%) and postpartum anxiety symptoms (17 studies: standardized mean difference, -0.49 [95% confidence interval, -0.72 to -0.25]; I2=84.6%). In the few studies that assessed screen-positive rates for postpartum depression (n=4) or postpartum anxiety (n=1), there were no significant differences between those randomized to digital health intervention and treatment as usual. Overall, those randomized to digital health intervention had 38% increased risk of not completing the final study assessment compared with those randomized to treatment as usual (pooled relative risk, 1.38 [95% confidence interval, 1.18-1.62]), but those randomized to app-based digital health intervention had similar loss-to-follow-up rates as those randomized to treatment as usual (relative risk, 1.04 [95% confidence interval, 0.91-1.19]). CONCLUSION: Digital health interventions modestly, but significantly, reduced scores assessing postpartum depression and postpartum anxiety symptoms. More research is needed to identify digital health interventions that effectively prevent or treat postpartum depression and postpartum anxiety but encourage ongoing engagement throughout the study period.

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.

Efficacy-based comparison between adults and children regarding using advanced counseling for asthma.

BACKGROUND: Asthma advanced counseling using smartphone applications has recently become one of the most effective and commonly used methods among adults and children with asthma. OBJECTIVES: We aimed to compare the advanced counseling effectiveness between adults and children with asthma. METHODS: A cohort prospective parallel study was performed on a group of adults and children nonsmoking patients with asthma, using a pressurized metered dose inhaler (pMDI). The patients were divided into two groups namely adults with asthma with ages ranging from 19 to 60 years and Children with asthma with ages ranging from 11 to 18 years, the two groups received a 2-month course of advanced counseling using "Asthma software" and "Asthma Dodge" smartphone applications, during which the two groups were monitored using the forced expiratory volume in the first second to the forced vital capacity (FEV1/FVC) ratio and asthma control test (ACT). The study has obtained ethical approval with the serial number REC-H-PhBSU-23002, adhering to the principles outlined in The Declaration of Helsinki, from the Ethical Approval Committee of Beni-Suef University Faculty of Pharmacy. RESULTS: With a total of 60 patients with asthma (N = 60), 31 adults (N = 31), and 29 children (N = 29), We found that starting from the first-month visit of counseling the children group showed superiority over the adult group in terms of the pulmonary function improvement p = .006. Also, regarding ACT scores the children group showed a superiority over the adult group this significance started from the first-month visit and continued to the second-month visit with p values = .032 and .011, respectively. CONCLUSION: The advanced counseling achieved better asthma control and pulmonary function improvement in children and adults; however, the improvement was much better in children with asthma than adults with asthma.

Smartphone-based digital phenotyping for genome-wide association study of intramuscular fat traits in longissimus dorsi muscle of pigs.

Intramuscular fat (IMF) content and distribution significantly contribute to the eating quality of pork. However, the current methods used for measuring these traits are complex, time-consuming and costly. To simplify the measurement process, this study developed a smartphone application (App) called Pork IMF. This App serves as a rapid and portable phenotyping tool for acquiring pork images and extracting the image-based IMF traits through embedded deep-learning algorithms. Utilizing this App, we collected the IMF traits of the longissimus dorsi muscle in a crossbred population of Large White × Tongcheng pigs. Genome-wide association studies detected 13 and 16 SNPs that were significantly associated with IMF content and distribution, respectively, highlighting NR2F2, MCTP2, MTLN, ST3GAL5, NDUFAB1 and PID1 as candidate genes. Our research introduces a user-friendly digital phenotyping technology for quantifying IMF traits and suggests candidate genes and SNPs for genetic improvement of IMF traits in pigs.

A smartphone application for personalized facial aesthetic monitoring.

BACKGROUND: Methods available at home for capturing facial images to track changes in skin quality and evaluate skincare treatments are limited. In this study, we developed a smartphone camera application (app) for personalized facial aesthetic monitoring. MATERIALS AND METHODS: A face alignment indicators (FAIN) system utilizing facial landmark detection, an artificial intelligence technique, to estimate key facial parts, was implemented into the app to maintain a consistent facial appearance during image capture. The FAIN system is composed of a fixed target indicator and an alignment indicator that dynamically changes its shape according to the user's face position, size, and orientation. Users align their faces to match the alignment indicator with the fixed target indicator, and the image is automatically captured when alignment is achieved. RESULTS: We investigated the app's effectiveness in ensuring a consistent facial appearance by analyzing both geometric and colorimetric data. Geometric information from captured faces and colorimetric data from stickers applied to the faces were utilized. The coefficients of variation (CVs) for the L*, a*, and b* values of the stickers were higher compared to those measured by a colorimeter, with CVs of 14.9 times, 8.14 times, and 4.41 times for L*, a*, and b*, respectively. To assess the feasibility of the app for facial aesthetic monitoring, we tracked changes in pseudo-skin color on the cheek of a participant using skin-colored stickers. As a result, we observed the smallest color difference ∆Eab of 1.901, which can be considered as the experimentally validated detection limit using images acquired by the app. CONCLUSION: While the current monitoring method is a relative quantification approach, it contributes to evidence-based evaluations of skincare treatments.

Effectiveness of a supportive care program via a smartphone application on the quality of life and care burden among family caregivers of patients with major depressive disorder: a randomized controlled trial.

BACKGROUND: The majority of patients with major depressive disorder require care that has generally affected caregivers' lives. Providing care could cause negative experiences as a care burden and deteriorate quality of life. However, there is a lack of evidence about caregiver training-based informatics and its impact on the caregiver's life. METHODS: This experimental study was carried out in Mashhad, Iran. A total of 60 primary family caregivers of patients with major depressive disorder were included in the study between February and July 2021. The quadruple block randomization method was used to allocate the participants into control and intervention groups. In the intervention group, family caregivers used the application with weekly phone calls for one month. The app contains the most important points of patient care and has the possibility of communicating with the nurse. The Novak and Guest Care Burden Inventory and the short form of the World Health Organization Quality of Life Questionnaire were completed before and after the intervention. Data analysis was performed using chi-squared tests, independent sample t tests, and analysis of covariance. RESULTS: At baseline, the mean scores of care burden and quality of life were homogeneous between the two groups. After the intervention, the mean scores of care burden and quality of life were significantly reduced and improved in the intervention group compared with the control group (p < 0.001). CONCLUSIONS: Using the application with the ability to communicate with the caregiver, along with educational support, helps to strengthen the relationship between the family caregiver and the nurse. Despite the effectiveness of the present intervention, before including this form of implementation of support in care programs, it is necessary to evaluate its other positive aspects in future studies. TRIAL REGISTRATION: Iranian Registry of Clinical Trials (IRCT), IRCT20210202050222N1. Registered on 05/02/2022.

Boosts for walking: how humorous messages increase brisk walking among cognitively fatigued individuals.

BACKGROUND: A well-studied internal barrier to regular physical activity, and more specifically brisk walking, is cognitive fatigue. However, thus far little research examined how cognitively fatigued individuals can be motivated to exercise, more specifically to engage in brisk walking. This study investigates whether humorous intervention messages might be an effective strategy to motivate cognitively fatigued individuals to brisk walk, and through which underlying processes. METHODS: An online experiment was performed in which variation in cognitive fatigue was induced through mental arithmetic questions. Afterwards, participants (n = 250) recruited through Prolific, randomly received either humorous or non-humorous intervention messages related to brisk walking. Potential mediators of the relations between physical activity, humour and cognitive fatigue were measured, were self-efficacy, self-control, and motivation. RESULTS: First, regression analyses confirmed that cognitive fatigue negatively influences brisk walking intentions and that the perceived humour of the intervention messages moderated this relationship. Second, results showed that self-control and self-efficacy are mediators explaining the relationship between cognitive fatigue and brisk walking intentions. Lastly, this study found that perceived humour of the intervention messages moderated the relationship between cognitive fatigue and self-control, indicating that perceptions of self-control were positively changed after receiving messages that were perceived as humorous compared to messages that were not perceived as humorous, subsequently increasing brisk walking intentions. CONCLUSIONS: This study is the first to unravel the underlying relationship between humorous intervention messages and brisk walking intentions through positive changes in perceptions of self-control within a cognitively fatigued sample. Results of this study suggest that existing smartphone applications monitoring and promoting brisk walking should integrate tailored message strategies within their cues to brisk walk by implementing humour as a strategy to motivate users when they are cognitively fatigued.

Combining anchoring with financial incentives to increase physical activity: a randomized controlled trial among college students.

The purpose of this study was to: (1) compare the relative efficacy of different combinations of three behavioral intervention strategies (i.e., personalized reminders, financial incentives, and anchoring) for establishing physical activity habits using an mHealth app and (2) to examine the effects of these different combined interventions on intrinsic motivation for physical activity and daily walking habit strength. A four-arm randomized controlled trial was conducted in a sample of college students (N = 161) who had a self-reported personal wellness goal of increasing their physical activity. Receiving cue-contingent financial incentives (i.e., incentives conditional on performing physical activity within ± one hour of a prespecified physical activity cue) combined with anchoring resulted in the highest daily step counts and greatest odds of temporally consistent walking during both the four-week intervention and the full eight-week study period. Cue-contingent financial incentives were also more successful at increasing physical activity and maintaining these effects post-intervention than traditional non-cue-contingent incentives. There were no differences in intrinsic motivation or habit strength between study groups at any time point. Financial incentives, particularly cue-contingent incentives, can be effectively used to support the anchoring intervention strategy for establishing physical activity habits. Moreover, mHealth apps are a feasible method for delivering the combined intervention technique of financial incentives with anchoring.

Using artificial intelligence to improve COVID-19 rapid diagnostic test result interpretation.

Serological rapid diagnostic tests (RDTs) are widely used across pathologies, often providing users a simple, binary result (positive or negative) in as little as 5 to 20 min. Since the beginning of the COVID-19 pandemic, new RDTs for identifying SARS-CoV-2 have rapidly proliferated. However, these seemingly easy-to-read tests can be highly subjective, and interpretations of the visible "bands" of color that appear (or not) in a test window may vary between users, test models, and brands. We developed and evaluated the accuracy/performance of a smartphone application (xRCovid) that uses machine learning to classify SARS-CoV-2 serological RDT results and reduce reading ambiguities. Across 11 COVID-19 RDT models, the app yielded 99.3% precision compared to reading by eye. Using the app replaces the uncertainty from visual RDT interpretation with a smaller uncertainty of the image classifier, thereby increasing confidence of clinicians and laboratory staff when using RDTs, and creating opportunities for patient self-testing.

Navigating the calvaria with mobile mixed reality-based neurosurgical planning: how feasible are smartphone applications as a craniotomy guide?

OBJECTIVE: Virtual simulation and imaging systems have evolved as advanced products of computing technology over the years. With advancements in mobile technology, smartphones, and tablets, the quality of display and processing speed have gradually improved, thanks to faster central processing units with higher capacity. Integrating these two technologies into the fields of healthcare and medical education has had a positive impact on surgical training. However, contemporary neurosurgical planning units are expensive and integrated neuronavigation systems in operating rooms require additional accessories. The aim of this study was to investigate the compatibility of smartphone applications in augmented reality (AR)-based craniotomy planning, which can be available even in disadvantaged workplaces with insufficient facilities. METHODS: Thirty patients diagnosed with supratentorial glial tumor and who underwent operations between January 2022 and March 2023 were included in the study. The entire stages of the surgical procedures and the surgical plans were executed with neuronavigation systems. The patient CT scans were reconstructed using software and exported as a 3D figure to an AR-enhanced smartphone application. The evaluation of the application's success was based on the spatial relationship of the AR-based artificial craniotomy to the neuronavigation-based craniotomy, with each AR-based craniotomy scaled from 0 to 3. RESULTS: In the comparison between neuronavigation-based and AR fusion-based craniotomies, 8 of 30 (26.6%) patients scored 0 and were considered failed, 6 (20%) scored 1 and were considered ineffective, 7 (23.3%) scored 2 and were considered acceptable, and 9 (30%) scored 3 and were considered favorable. CONCLUSIONS: AR technology has great potential to be a revolutionary milestone of neurosurgical planning, training, and education in the near future. In the authors' opinion, with the necessary legal permissions, there is no obstacle to the integration of surgical technological systems with mobile technology devices such as smartphones and tablets that benefit from their low-budget requirements, wide-range availability, and built-in operating systems.

A Novel Smartphone-Based Intervention Aimed at Increasing Future Orientation via the Future Self: a Pilot Randomized Controlled Trial of a Prototype Application.

We developed and tested a smartphone-based intervention, FutureU, that aims to stimulate future-oriented thinking and behavior by strengthening the degree to which people identify with their future self. In order to examine the potential of this intervention prototype and opportunities for further optimization, we evaluated 1) the immediate and long-term efficacy of the intervention, and 2) intervention effects after each of three intervention modules. To this end, we conducted a randomized controlled pilot study among first-year university students (N = 176). Results showed a decrease in goal commitment immediately after the intervention. At 3-months follow-up, trends showed an increase in future orientation and in self-efficacy. During the intervention, there was a positive effect on vividness of the future self after the first module. Although there is scope for improvement, the findings highlight the potential of the intervention to increase people's future-oriented thinking and behavior.

What's in a name? A systematic review and meta-analysis to assess the effectiveness of non-medical amplification devices in adults with mild and moderate hearing losses.

OBJECTIVE: To assess non-medical amplification devices in adults with mild-to-moderate hearing loss, and the impact of device features on outcomes. DESIGN: A prospectively registered systematic review. STUDY SAMPLE: Ten studies evaluating personal sound amplification products (PSAPs), and four evaluating smartphone amplification applications (or apps). Devices were classified as "premium" or "basic" based on the number of compression channels (≥16 or <16, respectively). RESULTS: Meta-analyses showed that premium PSAPs improved speech intelligibility in noise performance compared to unaided, whereas basic PSAPs and smartphone apps did not. Premium PSAPs performed better than basic hearing aids. Premium hearing aids performed better than premium and basic PSAPs, smartphone apps, and basic hearing aids. Although data could not be pooled, similar findings were also found for quality of life, listening ability, cognition, feasibility, and adverse effects. CONCLUSIONS: Premium PSAPs appear to be an effective non-medical amplification device for adults with mild-to-moderate hearing loss. Given the overlap in features available, it may be that this is a key consideration when drawing comparisons between devices, rather than the device being named a PSAP or hearing aid. Nevertheless, the extent to which PSAPs are effective without audiological input remains to be determined.

Point-of-care blood tests using a smartphone-based colorimetric analyzer for health check-up.

A microscale colorimetric assay was designed and implemented for the simultaneous determination of clinical chemistry tests measuring six parameters, including glucose (GLU), total protein (TP), human serum albumin (HSA), uric acid (UA), total cholesterol (TC), and triglycerides (TGs) in plasma samples. The test kit was fabricated using chromogenic reagents, comprising specific enzymes and binding dyes. Multiple colors that appeared on the reaction well when it was exposed to each analyte were captured by a smartphone and processed by the homemade Check6 application, which was designed as a colorimetric analyzer and simultaneously generated a report that assessed test results against gender-dependent reference ranges. Six blood checkup parameters for four plasma samples were conducted within 12 min on one capture picture. The assay achieved wide working concentration ranges of 10.45-600 mg dL-1 GLU, 1.39-10.0 g dL-1 TP, 1.85-8.0 g dL-1 HSA, 0.86-40.0 mg dL-1 UA, 11.28-600 mg dL-1 TC, and 11.93-400 mg dL-1 TGs. The smartphone-based assay was accurate with recoveries of 93-108% GLU, 93-107% TP, 92-107% HSA, 93-107% UA, 92-107% TC, and 99-113% TGs. The coefficient of variation for intra-assay and inter-assay precision ranged from 3.2-5.2% GLU, 4.6-5.3% TP, 4.3-5.3% HSA, 2.8-6.6% UA, 2.7-6.5% TC, and 1.1-3.9% TGs. This assay demonstrated remarkable accuracy in quantifying the concentration-dependent color intensity of the plasma, even in the presence of other suspected interferences commonly present in serum. The results of the proposed method correlated well with results determined by the microplate spectrophotometer (R2 > 0.95). Measurement of these six clinical chemistry parameters in plasma using a microscale colorimetric test kit coupled with the Check6 smartphone application showed potential for real-time point-of-care analysis, providing cost-effective and rapid assays for health checkup testing.

The Reliability and Validity of the OneStep Smartphone Application for Gait Analysis among Patients Undergoing Rehabilitation for Unilateral Lower Limb Disability.

An easy-to-use and reliable tool is essential for gait assessment of people with gait pathologies. This study aimed to assess the reliability and validity of the OneStep smartphone application compared to the C-Mill-VR+ treadmill (Motek, Nederlands), among patients undergoing rehabilitation for unilateral lower extremity disability. Spatiotemporal gait parameters were extracted from the treadmill and from two smartphones, one on each leg. Inter-device reliability was evaluated using Pearson correlation, intra-cluster correlation coefficient (ICC), and Cohen's d, comparing the application's readings from the two phones. Validity was assessed by comparing readings from each phone to the treadmill. Twenty-eight patients completed the study; the median age was 45.5 years, and 61% were males. The ICC between the phones showed a high correlation (r = 0.89-1) and good-to-excellent reliability (ICC range, 0.77-1) for all the gait parameters examined. The correlations between the phones and the treadmill were mostly above 0.8. The ICC between each phone and the treadmill demonstrated moderate-to-excellent validity for all the gait parameters (range, 0.58-1). Only 'step length of the impaired leg' showed poor-to-good validity (range, 0.37-0.84). Cohen's d effect size was small (d < 0.5) for all the parameters. The studied application demonstrated good reliability and validity for spatiotemporal gait assessment in patients with unilateral lower limb disability.

Blind Calibration of Environmental Acoustics Measurements Using Smartphones.

Environmental noise control is a major health and social issue. Numerous environmental policies require local authorities to draw up noise maps to establish an inventory of the noise environment and then propose action plans to improve its quality. In general, these maps are produced using numerical simulations, which may not be sufficiently representative, for example, concerning the temporal dynamics of noise levels. Acoustic sensor measurements are also insufficient in terms of spatial coverage. More recently, an alternative approach has been proposed, consisting of using citizens as data producers by using smartphones as tools of geo-localized acoustic measurement. However, a lack of calibration of smartphones can generate a significant bias in the results obtained. Against the classical metrological principle that would aim to calibrate any sensor beforehand for physical measurement, some have proposed mass calibration procedures called "blind calibration". The method is based on the crossing of sensors in the same area at the same time, which are therefore supposed to observe the same phenomenon (i.e., measure the same value). The multiple crossings of a large number of sensors at the scale of a territory and the analysis of the relationships between sensors allow for the calibration of the set of sensors. In this article, we propose to adapt a blind calibration method to data from the NoiseCapture smartphone application. The method's behavior is then tested on NoiseCapture datasets for which information on the calibration values of some smartphones is already available.

Parental Ability to Assess Pediatric Vital Signs.

OBJECTIVE: To evaluate parents' ability to accurately assess their child's heart and respiratory rates (RRs) in the context of potential utility for telehealth visits. STUDY DESIGN: In this controlled study of 203 child-parent pairs, parents measured their child's heart rate (HR) using 4 methods: palpation, auscultation, and 2 photoplethysmographic smartphone applications. Parents measured RR by inspecting the child and tapping the smartphone application. The gold standards were electrocardiogram for the HR and the child's breaths measured by a health care professional for 60 seconds for the RR. We plotted the measurements using a Bland-Altman plot with 95% limits of agreement. RESULTS: Parents underestimated HR by palpation with a calculated bias of -18 beats per minute (bpm) (SD, 19), with limits of agreement ranging from -56 to 19 bpm. Parents overestimated and underestimated HR by auscultation with limits of agreement ranging from -53 to 46 bpm. Smartphone applications did not improve the accuracy of measurements. The accuracy of parental RR measurements was low. For young children, bias was -0.8 breaths per minute (brpm) (SD, 9.8) with limits of agreement from -20 to 19 brpm, and for older children, bias was 0.9 brpm (SD 7.4) with limits of agreement from 6 to 15 brpm. The sensitivity of parental subjective opinion to recognize accelerated RR was 37% (95% CI, 25%-51%). CONCLUSION: Parents were not able to assess their child's RR or HR accurately. Digital remote assessment of children should not rely on parental measurements of vital signs.

Automated mobile virtual reality cognitive behavior therapy for aviophobia in a natural setting: a randomized controlled trial.

BACKGROUND: Access to evidence-based psychological treatment is a challenge worldwide. We assessed the effectiveness of a fully automated aviophobia smartphone app treatment delivered in combination with a $5 virtual reality (VR) viewer. METHODS: In total, 153 participants from the Dutch general population with aviophobia symptoms and smartphone access were randomized in a single-blind randomized controlled trial to either an automated VR cognitive behavior therapy (VR-CBT) app treatment condition (n = 77) or a wait-list control condition (n = 76). The VR-CBT app was delivered over a 6-week period in the participants' natural environment. Online self-report assessments were completed at baseline, post-treatment, at 3-month and at 12-month follow-up. The primary outcome measure was the Flight Anxiety Situations Questionnaire (FAS). Analyses were based on intent-to-treat. RESULTS: A significant reduction of aviophobia symptoms at post-test for the VR-CBT app compared with the control condition [p < 0.001; d = 0. 98 (95% CI 0.65-1.32)] was demonstrated. The dropout rate was 21%. Results were maintained at 3-month follow-up [within-group d = 1.14 (95% CI 0.46-1.81)] and at 12-month follow-up [within-group d = 1.12 (95% CI 0.46-1.79)]. Six participants reported adverse effects of cyber sickness symptoms. CONCLUSIONS: This study is the first to show that fully automated mobile VR-CBT therapy delivered in a natural setting can maintain long-term effectiveness in reducing aviophobia symptoms. In doing so, it offers an accessible and scalable evidence-based treatment solution that can be applied globally at a fraction of the cost of current treatment alternatives.

Randomized trial of inosine for urate elevation in amyotrophic lateral sclerosis.

INTRODUCTION/AIMS: Higher urate levels are associated with improved ALS survival in retrospective studies, however whether raising urate levels confers a survival advantage is unknown. In the Safety of Urate Elevation in Amyotrophic Lateral Sclerosis (SURE-ALS) trial, inosine raised serum urate and was safe and well-tolerated. The SURE-ALS2 trial was designed to assess longer term safety. Functional outcomes and a smartphone application were also explored. METHODS: Participants were randomized 2:1 to inosine (n = 14) or placebo (n = 9) for 20 weeks, titrated to serum urate of 7-8 mg/dL. Primary outcomes were safety and tolerability. Functional outcomes were measured with the Amyotrophic Lateral Sclerosis Functional Rating Scale Revised (ALSFRS-R). Mobility and ALSFRS-R were also assessed by a smartphone application. RESULTS: During inosine treatment, mean urate ranged 5.68-6.82 mg/dL. Treatment-emergent adverse event (TEAE) incidence was similar between groups (p > .10). Renal TEAEs occurred in three (21%) and hypertension in one (7%) of participants randomized to inosine. Inosine was tolerated in 71% of participants versus placebo 67%. Two participants (14%) in the inosine group experienced TEAEs deemed related to treatment (nephrolithiasis); one was a severe adverse event. Mean ALSFRS-R decline did not differ between groups (p = .69). Change in measured home time was similar between groups. Digital and in-clinic ALSFRS-R correlated well. DISCUSSION: Inosine met pre-specified criteria for safety and tolerability. A functional benefit was not demonstrated in this trial designed for safety and tolerability. Findings suggested potential utility for a smartphone application in ALS clinical and research settings.

Developing an artificial intelligence-based headache diagnostic model and its utility for non-specialists' diagnostic accuracy.

BACKGROUND: Misdiagnoses of headache disorders are a serious issue. Therefore, we developed an artificial intelligence-based headache diagnosis model using a large questionnaire database in a specialized headache hospital. METHODS: Phase 1: We developed an artificial intelligence model based on a retrospective investigation of 4000 patients (2800 training and 1200 test dataset) diagnosed by headache specialists. Phase 2: The model's efficacy and accuracy were validated. Five non-headache specialists first diagnosed headaches in 50 patients, who were then re-diagnosed using AI. The ground truth was the diagnosis by headache specialists. The diagnostic performance and concordance rates between headache specialists and non-specialists with or without artificial intelligence were evaluated. RESULTS: Phase 1: The model's macro-average accuracy, sensitivity (recall), specificity, precision, and F values were 76.25%, 56.26%, 92.16%, 61.24%, and 56.88%, respectively, for the test dataset. Phase 2: Five non-specialists diagnosed headaches without artificial intelligence with 46% overall accuracy and 0.212 kappa for the ground truth. The statistically improved values with artificial intelligence were 83.20% and 0.678, respectively. Other diagnostic indexes were also improved. CONCLUSIONS: Artificial intelligence improved the non-specialist diagnostic performance. Given the model's limitations based on the data from a single center and the low diagnostic accuracy for secondary headaches, further data collection and validation are needed.