Is a smartphone application (BlueIce) acceptable and safe for university students who self-harm: an open study.

BACKGROUND: Many university students self-harm but few receive support. Smartphone apps have been identified as acceptable sources of support for students who self-harm, but the use of supportive self-harm apps is yet to be explored in this population. OBJECTIVE: This study sought to explore the acceptability and safety of a specific app (BlueIce) for university students who self-harm. METHODS: This was an exploratory, mixed methods study with 15 university students attending university well-being services with self-harming thoughts and/or behaviours. BlueIce was offered alongside the face-to-face support provided by the well-being service. Self-harming thoughts and behaviours, coping self-efficacy, and symptoms of anxiety and depression were measured before and after using BlueIce for 6 weeks. Follow-up interviews were also undertaken to explore how students perceived BlueIce in more depth. RESULTS: Following app use, there were statistically significant reductions in symptoms of anxiety (baseline M 12.47, SD 4.42; follow-up M 10, SD 4.16) t(14)=2.26, p=0.040, d=0.58 and depression (baseline M 16.5, SD 5.17, follow-up M 12.27, SD 3.66) t(13)=5.50, p<0.001, d=1.47. Qualitative findings showed participants found BlueIce to be acceptable, safe and helpful, and reported that they were more able to cope with difficult feelings and better understand their self-harm triggers following use of the app. CONCLUSION: BlueIce was an acceptable, safe and helpful source of support for university students struggling with self-harm thoughts and/or behaviours. This builds on previous findings with adolescents and suggests that BlueIce could be a particularly acceptable and helpful resource for university students.

The mediating effect of attentional impulsivity between mindfulness and problematic smartphone use.

OBJECTIVE: Problematic smartphone use has been linked to lower levels of mindfulness, impaired attentional function, and higher impulsivity. This study aimed to identify the psychological mechanisms of problematic smartphone use by exploring the relationship between addictive smartphone use, mindfulness, attentional function and impulsivity. METHODS: Ninety participants were evaluated with the smartphone addiction proneness scale and classified into the problematic smartphone use group (n = 42; 24 women; mean age: 27.6 ± 7.2 years) or normal use group (n = 48; 22 women; mean age: 30.1 ± 5.7 years). All participants completed self-report questionnaires evaluating their trait impulsivity and mindfulness and attention tests that assessed selective, sustained and divided attention. We compared the variables between the groups and explored the relationship between mindfulness, attentional function, impulsivity and addictive smartphone use through mediation analysis. RESULTS: The problematic smartphone use group showed higher trait impulsivity and lower mindfulness than the normal use group. There were no significant group differences in performance on attention tests. Levels of addictive smartphone use were significantly correlated with higher levels of trait impulsivity and lower levels of mindfulness, but not with performance on attention tests. Mediation analysis showed that acting with awareness, an aspect of mindfulness, reduces the degree of addictive smartphone use through attentional impulsivity, one of the trait impulsivity. CONCLUSION: Acting without sufficient awareness could influence addictive smartphone use by mediating attentional impulsivity. This supports that executive control deficits, reflected in high attentional impulsivity, contribute to problematic smartphone use. Our findings imply that mindfulness-based interventions can enhance executive control over smartphone use by promoting awareness.

Nucleic Acid Plate Culture: Label-Free and Naked-Eye-Based Digital Loop-Mediated Isothermal Amplification in Hydrogel with Machine Learning.

Digital nucleic acid amplification enables the absolute quantification of single molecules. However, due to the ultrasmall reaction volume in the digital system (i.e., short light path), most digital systems are limited to fluorescence signals, while label-free and naked-eye readout remain challenging. In this work, we report a digital nucleic acid plate culture method for label-free, ultrasimple, and naked-eye nucleic acid analysis. As simple as the bacteria culture, the nanoconfined digital loop-mediated isothermal amplification was performed by using polyacrylamide (PAM) hydrogel as the amplification matrix. The nanoconfinement of PAM hydrogel with an ionic polymer chain can remarkably accelerate the amplification of target nucleic acids and the growth of inorganic byproducts, namely, magnesium pyrophosphate particles (MPPs). Compared to that in aqueous solutions, MPPs trapped in the hydrogel with enhanced light scattering characteristics are clearly visible to the naked eye, forming white "colony" spots that can be simply counted in a label-free and instrument-free manner. The MPPs can also be photographed by a smartphone and automatically counted by a machine-learning algorithm to realize the absolute quantification of antibiotic-resistant pathogens in diverse real samples.

Red filter meibography by smartphones in patients with meibomian gland dysfunction: a validity and reliability study.

OBJECTIVE: The objective of this study is to determine the validity and reliability of the red filter meibography by smartphone compared with infrared in assessing meibomian gland drop-out. METHODS AND ANALYSIS: An analytical cross-sectional study was done with a total of 35 subjects (68 eyes) with suspected MGD based on symptoms and lid morphological abnormalities. Meibomian glands were photographed using two smartphones (Samsung S9 and iPhone XR) on a slit-lamp with added red filter. Images were assessed subjectively using meiboscore by the two raters and drop-out percentages were assessed by ImageJ. RESULTS: There was no agreement in meiboscore and a minimal level of agreement in drop-out percentages between red filter meibography and infrared. Inter-rater reliability showed no agreement between two raters. Intra-rater reliability demonstrated weak agreement in rater 1 and no agreement in rater 2. CONCLUSION: Validity of the red filter meibography technique by smartphones is not yet satisfactory in evaluating drop-out. Further improvement on qualities of images must be done and research on subjective assessment was deemed necessary due to poor results of intrarater and inter-rater reliability.

Dual-mode detection of 2,6-pyridinedicarboxylic acid based on the enhanced peroxidase-like activity and fluorescence property of novel Eu-MOFs.

2,6-Pyridinedicarboxylic acid (DPA) is a significant biomarker of anthrax, which is a deadly infectious disease for human beings. However, the development of a convenient anthrax detection method is still a challenge. Herein, we report a novel europium metal-organic framework (Eu-MOF) with an enhanced peroxidase-like activity and fluorescence property for DPA detection. The Eu-MOF was one-step synthesized using Eu3+ ions and 2-methylimidazole. In the presence of DPA, the intrinsic fluorescence of Eu3+ ions is sensitized, the fluorescence intensity linearly increases with an increase in DPA concentration, and the fluorescence color changes from blue to purple. Simultaneously, the peroxide-like activity of the Eu-MOF is enhanced by DPA, which can promote the oxidation of TMB to oxTMB. The absorbance values increase linearly with DPA concentrations, and the colorimetric images change from colorless to blue. The dual-mode detection of DPA has good sensitivity with a colorimetric detection limit of 0.67 µM and a fluorescent detection limit of 16.67 nM. Moreover, a simple detection method for DPA was developed using a smartphone with the RGB analysis system. A portable kit with standard color cards was developed using paper test strips. The proposed methods have good practicability for DPA detection in real samples. In conclusion, the developed Eu-MOF biosensor offers a valuable and general platform for anthrax diagnosis.

The roles of health literacy and social support in the association between smartphone ownership and frailty in older adults: a moderated mediation model.

BACKGROUND: Understanding the role of smartphones to promote the health status of older adults is important in the digital society. Little is known about the effects of having smartphones on physical frailty despite its positive effect on the well-being of older adults. This study aimed to explore the association between smartphone ownership and frailty in community-dwelling older adults and its underlying mechanism. METHODS: We used data from the Korean Frailty and Aging Cohort Study and analyzed 2,469 older adults aged 72-86 years. Frailty, health literacy, and social support were assessed by Fried's frailty phenotype, the Behavioral Risk Factor Surveillance System health literacy module, and the Enhancing Recovery in Coronary Heart Disease (ENRICHD) Social Support Instrument, respectively. The mediation model and moderated mediation model were estimated, where the mediator was health literacy and the moderator was social support, to explore the relationship between smartphone ownership and frailty. RESULTS: Of our study participants, 58.9% owned smartphones, and 10.9% were classified as frail. Smartphone ownership was negatively associated with frailty (ß = -0.623, p < 0.001). Health literacy mediated the relationship between smartphone ownership and frailty (ß = -0.154, boot confidence interval [CI] = - 0.222, - 0.096), and social support moderated the mediation effect (ß = -0.010, Boot CI = - 0.016, - 0.004). CONCLUSIONS: Owning smartphones among older adults could reduce the risk of frailty. Promoting health literacy and social support among older adults with smartphones would be effective to prevent frailty.

Mobile monitoring system detects the disease activity pattern and shows the association with clinical outcomes in patients with newly diagnosed Crohn's disease.

We aimed to determine whether Crohn's disease (CD) activity patterns assessed via a web-based symptom diary can help predict clinical outcomes in patients with newly diagnosed CD. Patients diagnosed with CD within the preceding 3 months were prospectively enrolled at four tertiary centers. All patients recorded their symptoms on a website using a smartphone at least once a week. The index outcomes were disease-related admission and surgery during follow-up. The disease activity from enrollment to outcome or last follow-up was reviewed for pattern analysis. Cox regression analysis was used to identify the predictors of disease outcomes. A total of 102 patients were enrolled. During a median follow-up period of 42 months, 25 (24.5%) and 6 (5.9%) patients required admission and surgery, respectively. Poor activity pattern was an independent predictor of disease-related hospitalization (adjusted hazard ratio [aHR], 3.96; 95% confidence interval [CI] 1.5-10.45; p = 0.005). A poor activity pattern (aHR, 19.48; 95% CI 1.86-203.95; p = 0.013) and female sex (aHR, 11.28; 95% CI 1.49-85.01; p = 0.018) were found to be independent predictors of bowel resection. CD disease activity patterns monitored through the mobile monitoring system may help predict clinical outcomes, such as disease-related hospitalization and surgery, in patients with newly diagnosed CD.

Experiences of a Community-Based Digital Intervention Among Older People Living in a Low-Income Neighborhood: Qualitative Study.

BACKGROUND: Older adults worldwide experienced heightened risks of depression, anxiety, loneliness, and poor mental well-being during the COVID-19 pandemic. During this period, digital technology emerged as a means to mitigate social isolation and enhance social connectedness among older adults. However, older adults' behaviors and attitudes toward the adoption and use of digital technology are heterogeneous and shaped by factors such as age, income, and education. Few empirical studies have examined how older adults experiencing social and economic disadvantages perceive the learning of digital tools. OBJECTIVE: This study aims to examine the motivations, experiences, and perceptions toward a community-based digital intervention among older adults residing in public rental flats in a low-income neighborhood. Specifically, we explored how their attitudes and behaviors toward learning the use of smartphones are shaped by their experiences related to age and socioeconomic challenges. METHODS: This study adopted a qualitative methodology. Between December 2020 and March 2021, we conducted semistructured in-depth interviews with 19 participants aged ≥60 years who had completed the community-based digital intervention. We asked participants questions about the challenges encountered amid the pandemic, their perceived benefits of and difficulties with smartphone use, and their experiences with participating in the intervention. All interviews were audio recorded and analyzed using a reflexive thematic approach. RESULTS: Although older learners stated varying levels of motivation to learn, most expressed ambivalence about the perceived utility and relevance of the smartphone to their current needs and priorities. While participants valued the social interaction with volunteers and the personalized learning model of the digital intervention, they also articulated barriers such as age-related cognitive and physical limitations and language and illiteracy that hindered their sustained use of these digital devices. Most importantly, the internalization of ageist stereotypes of being less worthy learners and the perception of smartphone use as being in the realm of the privileged other further reduced self-efficacy and interest in learning. CONCLUSIONS: To improve learning and sustained use of smartphones for older adults with low income, it is essential to explore avenues that render digital tools pertinent to their daily lives, such as creating opportunities for social connections and relationship building. Future studies should investigate the relationships between older adults' social, economic, and health marginality and their ability to access digital technologies. We recommend that the design and implementation of digital interventions should prioritize catering to the needs and preferences of various segments of older adults, while working to bridge rather than perpetuate the digital divide.

CoMnOx Nanoflower-Based Smartphone Sensing Platform and Virtual Reality Display for Colorimetric Detection of Ziram and Cu2.

Transition metal doping is an ideal strategy to construct multifunctional and efficient nanozymes for biosensing. In this work, a metal-doped CoMnOx nanozyme was designed and synthesized by hydrothermal reaction and high-temperature calcination. Based on its oxidase activity, an "on-off-on" smartphone sensing platform was established to detect ziram and Cu2+. The obtained flower-shaped CoMnOx could exhibit oxidase-, catalase-, and laccase-like activities. The oxidase activity mechanism of CoMnOx was deeply explored. O2 molecules adsorbed on the surface of CoMnOx were activated to produce a large amount of O2·-, and then, O2·- could extract acidic hydrogen from TMB to produce blue oxTMB. Meanwhile, TMB was oxidized directly to the blue product oxTMB via the high redox ability of Co species. According to the excellent oxidase-like activity of CoMnOx, a versatile colorimetric detection platform for ziram and Cu2+ was successfully constructed. The linear detection ranges for ziram and Cu2+ were 5~280 µM and 80~360 µM, and the detection limits were 1.475 µM and 3.906 µM, respectively. In addition, a portable smartphone platform for ziram and Cu2+ sensing was established for instant analysis, showing great application promise in the detection of real samples including environmental soil and water.

A Smartphone-Based M-Health Monitoring System for Arrhythmia Diagnosis.

Deep learning technology has been widely adopted in the research of automatic arrhythmia detection. However, there are several limitations in existing diagnostic models, e.g., difficulties in extracting temporal information from long-term ECG signals, a plethora of parameters, and sluggish operation speed. Additionally, the diagnosis performance of arrhythmia is prone to mistakes from signal noise. This paper proposes a smartphone-based m-health system for arrhythmia diagnosis. First, we design a cycle-GAN-based ECG denoising model which takes real-world noise signals as input and aims to produce clean ECG signals. In order to train its two generators and two discriminators simultaneously, we explore an unsupervised pre-training strategy to initialize the generator and accelerate the convergence speed during training. Second, we propose an arrhythmia diagnosis model based on the time convolution network (TCN). This model can identify 34 common arrhythmia events using eight-lead ECG signals, and we deploy such a model on the Android platform to develop an at-home ECG monitoring system. Experimental results have demonstrated that our approach outperforms the existing noise reduction methods and arrhythmia diagnosis models in terms of denoising effect, recognition accuracy, model size, and operation speed, making it more suitable for deployment on mobile devices for m-health monitoring services.

Evaluating the User Experience of a Smartphone-Delivered Sexual Health Promotion Program for Older Adults in the Netherlands: Single-Arm Pilot Study.

BACKGROUND: Sexual health is an important component of quality of life in older adults. However, older adults often face barriers to attaining a fulfilling sexual life because of issues such as stigma, lack of information, or difficult access to adequate support. OBJECTIVE: We aimed to evaluate the user experience of a self-guided, smartphone-delivered program to promote sexual health among older adults. METHODS: The mobile app was made available to community-dwelling older adults in the Netherlands, who freely used the app for 8 weeks. User experience and its respective components were assessed using self-developed questionnaires, the System Usability Scale, and semistructured interviews. Quantitative and qualitative data were descriptively and thematically analyzed, respectively. RESULTS: In total, 15 participants (mean age 71.7, SD 9.5 years) completed the trial. Participants showed a neutral to positive stance regarding the mobile app's usefulness and ease of use. Usability was assessed as "Ok/Fair." The participants felt confident about using the mobile app. To increase user experience, participants offered suggestions to improve content and interaction, including access to specialized sexual health services. CONCLUSIONS: The sexual health promotion program delivered through a smartphone in a self-guided mode was usable. Participants' perception is that improvements to user experience, namely in content and interaction, as well as connection to external services, will likely improve usefulness and acceptance.

A fusion architecture to deliver multipurpose mobile health services.

Mobile Health (mHealth) services typically make use of customized software architectures, leading to development-dependent fragmentation. Nevertheless, irrespective of their specific purpose, most mHealth services share common functionalities, where standard pieces could be reused or adapted to expedite service deployment and even extend the follow-up of appearing conditions under the same service. To harness compatibility and reuse, this article presents a data fusion architecture proposing a common design framework for mHealth services. An exhaustive mapping of mHealth functionalities identified in the literature serves as starting point. The architecture is then conceptualized making use of the Joint Directors of Laboratories (JDL) data fusion model. The aim of the architecture is to exploit the multi-source data acquisition capabilities supported by smartphones and Internet of Things devices, and artificial intelligence-enabled feature fusion. A series of interconnected fusion layers ensure streamlined data management; each layer is composed of microservices which may be implemented or omitted depending on the specific goals of the healthcare service. Moreover, the architecture considers essential features related to authentication mechanisms, data sharing protocols, practitioner-patient communication, context-based notifications and tailored visualization interfaces. The effectiveness of the architecture is underscored by its instantiation for four real cases, encompassing risk assessment for youth with mental health issues, remote monitoring for SARS-CoV-2 patients, liquid intake control for kidney disease patients, and peritoneal dialysis treatment support. This breadth of applications exemplifies how the architecture can effectively serve as a guidance framework to accelerate the design of mHealth services.

Explainable prediction of problematic smartphone use among South Korea's children and adolescents using a Machine learning approach.

BACKGROUND: Korea is known for its technological prowess, has the highest smartphone ownership rate in the world at 95%, and the smallest gap in smartphone ownership between generations. Since the onset of the COVID-19 pandemic, problematic smartphone use is becoming more prevalent among Korean children and adolescent owing to limited school attendance and outdoor activities, resulting in increased reliance on smartphones. 40.1% of adolescents are classified as high-risk, with only the adolescent group showing a persistent rise year after year. OBJECTIVE: The study purpose is to present data-driven analysis results for predicting and preventing smartphone addiction in Korea, where problematic smartphone use is severe. PARTICIPANTS AND METHODS: To predict the risk of problematic smartphone use in Korean children and adolescents at an early stage, we used data collected from the Smartphone Overdependence Survey conducted by the National Information Society Agency between 2017 and 2021. Eight representative machine and deep learning algorithms were used to predict groups at high risk for smartphone addiction: Logistic Regression, Random Forest, Gradient Boosting Machine (GBM), extreme Gradient Boosting (XGBoost), Light GBM, Categorical Boosting, Multilayer Perceptron, and Convolutional Neural Network. RESULTS: The XGBoost ensemble algorithm predicted 87.60% of participants at risk of future problematic smartphone usebased on precision. Our results showed that prolonged use of games, webtoons/web novels, and e-books, which have not been found in previous studies, further increased the risk of problematic smartphone use. CONCLUSIONS: Artificial intelligence algorithms have potential predictive and explanatory capabilities for identifying early signs of problematic smartphone use in adolescents and young children. We recommend that a variety of healthy, beneficial, and face-to-face activities be offered as alternatives to smartphones for leisure and play culture.

A smartphone-based diagnostic analyzer for point-of-care milk somatic cell counting.

BACKGROUND: Mastitis, a pervasive and detrimental disease in dairy farming, poses a significant challenge to the global dairy industry. Monitoring the milk somatic cell count (SCC) is vital for assessing the incidence of mastitis and the quality of raw cow's milk. However, existing SCC detection methods typically require large-scale instruments and specialized operators, limiting their application in resource-constrained settings such as dairy farms and small-scale labs. To address these limitations, this study introduces a novel, smartphone-based, on-site SCC testing method that leverages smartphone capabilities for milk somatic cell identification and enumeration, offering a portable and user-friendly testing platform. RESULTS: The central findings of our study demonstrate the effectiveness of the proposed method for counting milk somatic cells. Its on-site applicability, facilitated by the microfluidic chip, optical system, and smartphone integration, heralds a paradigm shift in point-of-care testing (POCT) for dairy farms and smaller laboratories. This approach bypasses complex processing and presents a user-friendly solution for real-time SCC monitoring in resource-limited settings. This device boasts several unique features: small size, low cost (<$1,000 total manufacturing cost and <$1 per test), and high accuracy. Remarkably, it delivers test results within just 2 min. Actual-sample testing confirmed its consistency with results from the commercial Bentley FTS/FCM cytometer, affirming the reliability of the proposed method. Overall, these results underscore the potential for transformative change in dairy farm management and laboratory testing practices. SIGNIFICANCE: In summary, this study concludes that the proposed smartphone-based method significantly contributes to the accessibility and ease of SCC testing in resource-limited environments. By fostering the use of POCT technology in food safety control, particularly in the dairy industry, this innovative approach has the potential to revolutionize the monitoring and management of mastitis, ultimately benefiting the global dairy sector.

'The way to obtain freedom and equality': Experiences and needs of Thai adolescent mothers in terms of the use smartphone applications for breastfeeding support.

BACKGROUND: Breastfeeding brings about a positive impact on both child and maternal health in the short and long terms. However, adolescent mothers have a lower breastfeeding initiation rate and a shorter breastfeeding duration than adult mothers. Although mobile applications have been found to be the most widely used platform for breastfeeding support, there is still a lack of design specific for adolescents. AIM: To explore the experiences, perspectives and needs of adolescent mothers and professional nurses using smartphone applications for breastfeeding support and the influence of this technology on healthcare in Thailand. METHODS: This formative qualitative research of the 'Development of smartphone application for promoting breastfeeding and learning of infant responsiveness for Thai teenage pregnant women' study intends to design a smartphone application and develop an implementation plan. A purposive sample was used to elicit experiences from adolescent mothers and nurses. Data were collected from 48 adolescent mothers through in-depth interviews with six focus group discussions and 12 nurses, following the data saturation principle. Thematic analysis was conducted, and potential factors and needs were mapped to the capability, opportunity, and motivation model of behaviour change (COM-B). RESULTS: Most adolescent mothers perceived the usefulness of smartphone apps as breastfeeding support resources. The qualitative findings of adolescent mothers were grouped into the following three themes: a friendly breastfeeding tool; allows them to manage their breastfeeding activities; and enhances the accessibility and equality of breastfeeding support. The professional nurses perceived the benefits of using smartphone applications in their work, which included the following three themes: reducing workload and making their work easier; preparation is always better; and increasing the standards of breastfeeding support. CONCLUSION: Adolescent mothers and professional nurses showed favourable attitudes toward smartphone apps for breastfeeding support. These smartphone apps should be tailored to these groups to achieve optimal BF outcomes.

Association between smartphone addiction and myofascial trigger points.

BACKGROUND: The purpose of this study was to clarify the relationship between smartphone addiction and miyafascial trigger points in university students. METHODS: A cross-sectional study of university students was conducted for the purpose of this study. The participants were assessed based on age, gender, dominant side, the amount of time they spent on their smartphones, the purpose of their use, and their posture. The Smartphone Addiction Scale Short Form (SAS-SF) was used to determine addictes and non-addicts. The cut-off value of SAS-SF is 31 and above for male and 33 and above for female. RESULTS: There were 136 participants in the study. The posture score for addicts and non-addicts ones was not significantly different (p > 0,05), but the number of trigger points, maximal bending posture and trigger points in the right levator scapula and right cervical erector muscles were significantly higher in the smartphone addict participants (p < 0,05). CONCLUSIONS: Smartphone addiction in university students is associated with postural changes and trigger points in the bilateral levator scapula and right cervical erector muscles. Public health programs should be developed to raise awareness about smartphone addiction, encourage screen breaks, and emphasize physical activity and exercise regularly.

Factors influencing smartphone overdependence among adolescents.

Adolescents are particularly vulnerable to smartphone overdependence. Therefore, we identified the factors influencing smartphone overdependence and risk subgroups among adolescents. The current study is a secondary analysis of nationally representative data from the 2020 Korea Youth Risk Behavior Survey. The survey targeted middle- and high-school students in South Korea aged 12-18 using stratified, clustered, multistage probability sampling, and 53,457 students from 793 schools participated in this study. Complex sample data were analyzed considering the strata, clusters, and weights. Multiple logistic regression analysis revealed age, gender, household economic status, anxiety, loneliness, depressive symptoms, and experience of violent treatment as significant predictors of smartphone overdependence. Adolescents with severe anxiety were at a 3.326 times higher risk of smartphone overdependence than adolescents with minimal anxiety. Decision tree analysis showed that anxiety, gender, loneliness, and depressive symptoms were important in differentiating risk subgroups, with anxiety being the most significant factor. Group 13, comprising girls with severe anxiety, had the highest risk at 52.9%. Thus, early detection and prevention of issues such as anxiety, loneliness, and depressive symptoms, as well as treatment for violence, can prevent smartphone overdependence among adolescents. Additionally, more thorough interventions for anxiety are warranted to prevent smartphone overdependence.

Protocol for a construct and clinical validation study of MyCog Mobile: a remote smartphone-based cognitive screener for older adults.

INTRODUCTION: Annual cognitive screening in older adults is essential for early detection of cognitive impairment, yet primary care settings face time constraints that present barriers to routine screening. A remote cognitive screener completed on a patient's personal smartphone before a visit has the potential to save primary care clinics time, encourage broader screening practices and increase early detection of cognitive decline. MyCog Mobile is a promising new remote smartphone-based cognitive screening app for primary care settings. We propose a combined construct and clinical validation study of MyCog Mobile. METHODS AND ANALYSIS: We will recruit a total sample of 300 adult participants aged 65 years and older. A subsample of 200 healthy adult participants and a subsample of 100 adults with a cognitive impairment diagnosis (ie, dementia, mild cognitive impairment, cognitive deficits or other memory loss) will be recruited from the general population and specialty memory care centres, respectively. To evaluate the construct validity of MyCog Mobile, the healthy control sample will self-administer MyCog Mobile on study-provided smartphones and be administered a battery of gold-standard neuropsychological assessments. We will compare correlations between performance on MyCog Mobile and measures of similar and dissimilar constructs to evaluate convergent and discriminant validity. To assess clinical validity, participants in the clinical sample will self-administer MyCog Mobile on a smartphone and be administered a Mini-Cog screener and these data will be combined with the healthy control sample. We will then apply several supervised model types to determine the best predictors of cognitive impairment within the sample. Area under the receiver operating characteristic curve, accuracy, sensitivity and specificity will be the primary performance metrics for clinical validity. ETHICS AND DISSEMINATION: The Institutional Review Board at Northwestern University (STU00214921) approved this study protocol. Results will be published in peer-reviewed journals and summaries provided to the study's funders.

Generalizability of Deep Neural Networks for Vertical Cup-to-Disc Ratio Estimation in Ultra-Widefield and Smartphone-Based Fundus Images.

Purpose: To develop and validate a deep learning system (DLS) for estimation of vertical cup-to-disc ratio (vCDR) in ultra-widefield (UWF) and smartphone-based fundus images. Methods: A DLS consisting of two sequential convolutional neural networks (CNNs) to delineate optic disc (OD) and optic cup (OC) boundaries was developed using 800 standard fundus images from the public REFUGE data set. The CNNs were tested on 400 test images from the REFUGE data set and 296 UWF and 300 smartphone-based images from a teleophthalmology clinic. vCDRs derived from the delineated OD/OC boundaries were compared with optometrists' annotations using mean absolute error (MAE). Subgroup analysis was conducted to study the impact of peripapillary atrophy (PPA), and correlation study was performed to investigate potential correlations between sectoral CDR (sCDR) and retinal nerve fiber layer (RNFL) thickness. Results: The system achieved MAEs of 0.040 (95% CI, 0.037-0.043) in the REFUGE test images, 0.068 (95% CI, 0.061-0.075) in the UWF images, and 0.084 (95% CI, 0.075-0.092) in the smartphone-based images. There was no statistical significance in differences between PPA and non-PPA images. Weak correlation (r = -0.4046, P < 0.05) between sCDR and RNFL thickness was found only in the superior sector. Conclusions: We developed a deep learning system that estimates vCDR from standard, UWF, and smartphone-based images. We also described anatomic peripapillary adversarial lesion and its potential impact on OD/OC delineation. Translational Relevance: Artificial intelligence can estimate vCDR from different types of fundus images and may be used as a general and interpretable screening tool to improve community reach for diagnosis and management of glaucoma.

Anxiety and depression during post covid-19 lockdown period among medical students, and it's relation with stress and smartphone addiction in India.

OBJECTIVES: Medical profession, a competitive and ever-updating field which requires great commitment, imposes a stressful environment for students. Our study aimed to find the prevalence and factors associated with psychological illness. METHODS: A cross-sectional analytical study was done among medical students in Puducherry. A stratified random sampling strategy was incorporated to achieve a calculated sample size of 384. The presence of anxiety and depression, perceived stress and addiction to the phone were assessed using the Hospital Anxiety and Depression Scale, Perceived Stress Scale, and Smartphone Addiction Scale - short version. Prevalence of anxiety and depression was summarized as a proportion with a 95 % confidence interval (CI). The prevalence ratio (PR) for the factors associated was estimated using log-binomial regression. RESULTS: With the response from 383 students, the prevalence of anxiety and depression was 39.4 % (95 %CI: 34.5-44.3 %) and 26.6 % (22.2-31.1 %). Perceived stress was moderate in 68.2 % and high in 14 % of students. Higher age (aPR=1.49), female gender (aPR=1.22), tobacco or alcohol use (aPR=1.24), smartphone addiction (aPR=2.09) and high stress (aPR=1.93) were the predictors of anxiety among medical students in our study. Use of tobacco or alcohol (aPR=2.07), smartphone addiction (aPR=1.96) and high stress (aPR=1.72) were the predictors of depression. CONCLUSIONS: Anxiety was more prevalent than depression among the medical students. Use of tobacco or alcohol, smartphone addiction and stress increase the risk of psychological morbidity. Medical training should have a module on coping mechanisms to overcome psychological illness and have better mental well-being.