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.

'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.

Acceptability and experience of a smartphone symptom monitoring app for people with psychosis in China (YouXin): a qualitative study.

BACKGROUND: Access to high-quality mental healthcare remains challenging for people with psychosis globally, including China. Smartphone-based symptom monitoring has the potential to support scalable mental healthcare. However, no such tool, until now, has been developed and evaluated for people with psychosis in China. This study investigated the acceptability and the experience of using a symptom self-monitoring smartphone app (YouXin) specifically developed for people with psychosis in China. METHODS: Semi-structured interviews were conducted with 10 participants with psychosis to explore the acceptability of YouXin. Participants were recruited from the non-randomised feasibility study that tested the validity, feasibility, acceptability and safety of the YouXin app. Data analysis was guided by the theoretical framework of acceptability. RESULTS: Most participants felt the app was acceptable and easy to use, and no unbearable burdens or opportunity costs were reported. Participants found completing the self-monitoring app rewarding and experienced a sense of achievement. Privacy and data security were not major concerns for participants, largely due to trust in their treating hospital around data protection. Participants found the app easy to use and attributed this to the training provided at the beginning of the study. A few participants said they had built some form of relationship with the app and would miss the app when the study finished. CONCLUSIONS: The YouXin app is acceptable for symptom self-monitoring in people with experience of psychosis in China. Participants gained greater insights about their symptoms by using the YouXin app. As we only collected retrospective acceptability in this study, future studies are warranted to assess hypothetical acceptability before the commencement of study to provide a more comprehensive understanding of implementation.

The effects of mindfulness training for emergency department and intermediate care unit nurses.

AIM: The aim of this study was to determine the effects of mindfulness and self-compassion skills on the experienced stress and work satisfaction of emergency department (ED) and intermediate care unit employees. METHODS: All ED and intermediate care unit employees in the study hospital were invited to participate in an introductory lecture about mindfulness, compassion, and the intervention in January 2020. After the lecture, it was possible to enroll in training. This training was postponed due to Covid-19 and started in October 2020. RESULTS: The most important findings of this study are that instructor-led mindfulness training, and the regular use of a smartphone mindfulness application can significantly reduce stress and burnout and promote mindfulness and well-being of ED and intermediate care unit personnel. CONCLUSIONS: This study shows that compact mindfulness training via innovative digital technology has a positive effect in reducing ED and intermediate care unit employees stress and burnout, while improving mindfulness and well-being, and this is consistent with the wider literature. KEY FINDINGS: The regular practice of smartphone-guided mindfulness can reduce stress and burnout, as well as promote mindfulness and well-being among ED and intermediate care unit employees.

Reliability and Validity of Smartphone Cognitive Testing for Frontotemporal Lobar Degeneration.

Importance: Frontotemporal lobar degeneration (FTLD) is relatively rare, behavioral and motor symptoms increase travel burden, and standard neuropsychological tests are not sensitive to early-stage disease. Remote smartphone-based cognitive assessments could mitigate these barriers to trial recruitment and success, but no such tools are validated for FTLD. Objective: To evaluate the reliability and validity of smartphone-based cognitive measures for remote FTLD evaluations. Design, Setting, and Participants: In this cohort study conducted from January 10, 2019, to July 31, 2023, controls and participants with FTLD performed smartphone application (app)-based executive functioning tasks and an associative memory task 3 times over 2 weeks. Observational research participants were enrolled through 18 centers of a North American FTLD research consortium (ALLFTD) and were asked to complete the tests remotely using their own smartphones. Of 1163 eligible individuals (enrolled in parent studies), 360 were enrolled in the present study; 364 refused and 439 were excluded. Participants were divided into discovery (n = 258) and validation (n = 102) cohorts. Among 329 participants with data available on disease stage, 195 were asymptomatic or had preclinical FTLD (59.3%), 66 had prodromal FTLD (20.1%), and 68 had symptomatic FTLD (20.7%) with a range of clinical syndromes. Exposure: Participants completed standard in-clinic measures and remotely administered ALLFTD mobile app (app) smartphone tests. Main Outcomes and Measures: Internal consistency, test-retest reliability, association of smartphone tests with criterion standard clinical measures, and diagnostic accuracy. Results: In the 360 participants (mean [SD] age, 54.0 [15.4] years; 209 [58.1%] women), smartphone tests showed moderate-to-excellent reliability (intraclass correlation coefficients, 0.77-0.95). Validity was supported by association of smartphones tests with disease severity (r range, 0.38-0.59), criterion-standard neuropsychological tests (r range, 0.40-0.66), and brain volume (standardized ß range, 0.34-0.50). Smartphone tests accurately differentiated individuals with dementia from controls (area under the curve [AUC], 0.93 [95% CI, 0.90-0.96]) and were more sensitive to early symptoms (AUC, 0.82 [95% CI, 0.76-0.88]) than the Montreal Cognitive Assessment (AUC, 0.68 [95% CI, 0.59-0.78]) (z of comparison, -2.49 [95% CI, -0.19 to -0.02]; P = .01). Reliability and validity findings were highly similar in the discovery and validation cohorts. Preclinical participants who carried pathogenic variants performed significantly worse than noncarrier family controls on 3 app tasks (eg, 2-back ß = -0.49 [95% CI, -0.72 to -0.25]; P < .001) but not a composite of traditional neuropsychological measures (ß = -0.14 [95% CI, -0.42 to 0.14]; P = .32). Conclusions and Relevance: The findings of this cohort study suggest that smartphones could offer a feasible, reliable, valid, and scalable solution for remote evaluations of FTLD and may improve early detection. Smartphone assessments should be considered as a complementary approach to traditional in-person trial designs. Future research should validate these results in diverse populations and evaluate the utility of these tests for longitudinal monitoring.

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.

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.

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.

Smartphone app-based interventions on physical activity behaviors and psychological correlates in healthy young adults: A systematic review.

BACKGROUND: The issue of low physical activity (PA) levels among the youth is a longstanding concern. Smartphone applications offer a promising avenue for delivering interventions that are both accessible and engaging. Up to now, there appears to be a gap in the literature, with no systematic reviews assessing the efficacy of smartphone apps in encouraging increased physical activity among healthy young adults. OBJECTIVE: To synthesize the effects of a smartphone app-based intervention on PA and PA-related psychological correlates in healthy young adults (18-35 years old). METHODS: A search was conducted on eighteen databases: PubMed, Medline, Web of Science, SPORTDiscus, Scopus, Academic Search Premier, Communication and Mass Media Complete, Article First, Biomed Central, BioOne, EBSCOHost, JSTOR, ProQuest, SAGE Reference Online, ScienceDirect, SpringerLink, Taylor&Francis, and Wiley Online. The search covered the period up until December 2023. This research included all randomized controlled trials (RCTs) that evaluated the effectiveness of smartphone app-based interventions on PA and PA related psychological outcomes in healthy young adults. The overall impact was determined by vote counting based on the direction of effect and aggregating p values. The quality of the evidence was evaluated using an 8-item scale. This study has been registered in the PROSPERO database with the identification number CRD42023390033. RESULTS: A total of 8403 articles were retrieved, and based on the predefined inclusion and exclusion criteria, seven articles were selected for inclusion. Among these articles, four high-quality RCTs were identified, and the results of vote counting and combining p values methods suggested that smartphone-based app interventions did not demonstrate significant effectiveness in improving PA and PA-related psychological outcomes. However, some improvements were observed. The analysis results, which were categorized into fitness apps and health apps based on the characteristics of the interventions, also failed to demonstrate significant intervention effects. CONCLUSION: The findings indicate that, currently, there are no significant effects of smartphone app interventions on improving PA and PA-related psychological outcomes in healthy young adults aged 18-35 years. It is important to note that these findings should be interpreted with caution due to the limited number of included studies. Future research should focus on employing high-quality study designs to determine the true effects of interventions and analyze various smartphone app interventions. These analyses should encompass different app characteristics (e.g., fitness app and health app), various combinations (e.g., fitness app alone and fitness app in combination with other interventions), diverse intervention goals (e.g., PA and PA along with other outcomes), and multiple intervention characteristics (e.g., frequency and duration).

Smartphone-Derived Seismocardiography: Robust Approach for Accurate Cardiac Energy Assessment in Patients with Various Cardiovascular Conditions.

Seismocardiography (SCG), a method for measuring heart-induced chest vibrations, is gaining attention as a non-invasive, accessible, and cost-effective approach for cardiac pathologies, diagnosis, and monitoring. This study explores the integration of SCG acquired through smartphone technology by assessing the accuracy of metrics derived from smartphone recordings and their consistency when performed by patients. Therefore, we assessed smartphone-derived SCG's reliability in computing median kinetic energy parameters per record in 220 patients with various cardiovascular conditions. The study involved three key procedures: (1) simultaneous measurements of a validated hardware device and a commercial smartphone; (2) consecutive smartphone recordings performed by both clinicians and patients; (3) patients' self-conducted home recordings over three months. Our findings indicate a moderate-to-high reliability of smartphone-acquired SCG metrics compared to those obtained from a validated device, with intraclass correlation (ICC) > 0.77. The reliability of patient-acquired SCG metrics was high (ICC > 0.83). Within the cohort, 138 patients had smartphones that met the compatibility criteria for the study, with an observed at-home compliance rate of 41.4%. This research validates the potential of smartphone-derived SCG acquisition in providing repeatable SCG metrics in telemedicine, thus laying a foundation for future studies to enhance the precision of at-home cardiac data acquisition.

An integrated wearable differential microneedle array for continuous glucose monitoring in interstitial fluids.

Monitoring biomarkers in human interstitial fluids (ISF) using microneedle sensors has been extensively studied. However, most of the previous studies were limited to simple in vitro demonstrations and lacked system integration and analytical performance. Here we report a miniaturized, high-precision, fully integrated wearable electrochemical microneedle sensing device that works with a customized smartphone application to wirelessly and in real-time monitor glucose in human ISF. A microneedle array fabrication method is proposed which enables multiple individually addressable, regionally separated sensing electrodes on a single microneedle system. As a demonstration, a glucose sensor and a differential sensor are integrated in a single sensing patch. The differential sensing electrodes can eliminate common-mode interference signals, thus significantly improving the detection accuracy. The basic mechanism of microneedle penetration into the skin was analyzed using the finite element method (FEM). By optimizing the structure of the microneedle, the puncture efficiency was improved while the puncture force was reduced. The electrochemical properties, biocompatibility, and system stability of the microneedle sensing device were characterized before human application. The test results were closely correlated with the gold standard (blood). The platform can be used not only for glucose detection, but also for various ISF biomarkers, and it expands the potential of microneedle technology in wearable sensing.

Smartphone-based ecological momentary assessment reveals an incremental association between natural diversity and mental wellbeing.

Using smartphone-based ecological momentary assessment, this study investigated an association between natural diversity on mental wellbeing. A sample of 1,998 participants completed 41,448 assessments between April 2018 and September 2023. Environments which included a larger range of natural features, such as trees, plants and birdlife (high natural diversity) were associated with greater mental wellbeing than environments including a smaller range of natural features (low natural diversity). There was evidence of a mediating effect of natural diversity on the association between natural environments and mental wellbeing. These results highlight the importance of policies and practices that support richness of biodiversity for public mental health.

Development of a smartphone screening test for preclinical Alzheimer's disease and validation across the dementia continuum.

BACKGROUND: Dementia prevalence is predicted to triple to 152 million globally by 2050. Alzheimer's disease (AD) constitutes 70% of cases. There is an urgent need to identify individuals with preclinical AD, a 10-20-year period of progressive brain pathology without noticeable cognitive symptoms, for targeted risk reduction. Current tests of AD pathology are either too invasive, specialised or expensive for population-level assessments. Cognitive tests are normal in preclinical AD. Emerging evidence demonstrates that movement analysis is sensitive to AD across the disease continuum, including preclinical AD. Our new smartphone test, TapTalk, combines analysis of hand and speech-like movements to detect AD risk. This study aims to [1] determine which combinations of hand-speech movement data most accurately predict preclinical AD [2], determine usability, reliability, and validity of TapTalk in cognitively asymptomatic older adults and [3], prospectively validate TapTalk in older adults who have cognitive symptoms against cognitive tests and clinical diagnoses of Mild Cognitive Impairment and AD dementia. METHODS: Aim 1 will be addressed in a cross-sectional study of at least 500 cognitively asymptomatic older adults who will complete computerised tests comprising measures of hand motor control (finger tapping) and oro-motor control (syllabic diadochokinesis). So far, 1382 adults, mean (SD) age 66.20 (7.65) years, range 50-92 (72.07% female) have been recruited. Motor measures will be compared to a blood-based AD biomarker, phosphorylated tau 181 to develop an algorithm that classifies preclinical AD risk. Aim 2 comprises three sub-studies in cognitively asymptomatic adults: (i) a cross-sectional study of 30-40 adults to determine the validity of data collection from different types of smartphones, (ii) a prospective cohort study of 50-100 adults ≥ 50 years old to determine usability and test-retest reliability, and (iii) a prospective cohort study of ~1,000 adults ≥ 50 years old to validate against cognitive measures. Aim 3 will be addressed in a cross-sectional study of ~200 participants with cognitive symptoms to validate TapTalk against Montreal Cognitive Assessment and interdisciplinary consensus diagnosis. DISCUSSION: This study will establish the precision of TapTalk to identify preclinical AD and estimate risk of cognitive decline. If accurate, this innovative smartphone app will enable low-cost, accessible screening of individuals for AD risk. This will have wide applications in public health initiatives and clinical trials. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT06114914, 29 October 2023. Retrospectively registered.

Multiplexed colorimetry collaborated with smartphone-based image analysis for simultaneous and fast visualization of dyes in both environmental and food samples.

In this work, a multiplexed colorimetric strategy was initiated for simultaneous and fast visualization of dyes using low-cost and easy-to-prepare indicator papers as sorbents. Response surface methodology (RSM) was employed to model statistically and optimize the process variables for dyes extraction and colorimetric assays. Multiplexed colorimetry was realized by virtue of synchronous color alignments from different dimensions of multiple dyes co-stained colorimetric cards under RSM-optimized conditions, and smartphone-based image analysis was subsequently performed from different modes to double-check the credibility of colorimetric assays. As concept-to-proof trials, simultaneous visualization of dyes in both beverages and simulated dye effluents was experimentally proved with results highly matched to HPLC or spiked amounts at RSM-predicted staining time as short as 50 s ∼3 min, giving LODs as low as 0.97 ± 0.22/0.18 ± 0.08 µg/mL (tartrazine/brilliant blue) for multiplexed colorimetry, which much lower than those obtained by single colorimetry. Since this is the first case to propose such a RSM-guided multiplexed colorimetric concept, it will provide a reference for engineering of other all-in-one devices which can realize synchronous visualization applications within limited experimental steps.

Molecular imprinting-based triple-emission ratiometric fluorescence sensor with aggregation-induced emission effect for visual detection of doxycycline.

The development of high-performance sensors for doxycycline (DOX) detection is necessary because its residue accumulation will cause serious harm to human health and the environment. Here, a novel tri-emission ratiometric fluorescence sensor was proposed by using "post-mixing" strategy of different emissions fluorescence molecularly imprinted polymers with salicylamide as dummy template (DMIPs). BSA was chosen as assistant functional monomer, and also acted as sensitizers for the aggregation-induced emission (AIE) effect of DOX. The blue-emitting carbon dots and the red-emitting CdTe quantum dots were separately introduced into DMIPs as the response signals. Upon DOX recognition within 2 min, blue and red fluorescence of the tri-emission DMIPs sensor were quenched while green fluorescence of DOX was enhanced, resulting in a wide range of color variations observed over bluish violet-rosered-light pink-orange-yellow-green with a detection limit of 0.061 µM. The sensor possessed highly selective recognition and was successfully applied to detect DOX in complicated real samples. Moreover, with the fluorescent color collection and data processing, the smartphone-assisted visual detection of the sensors showed satisfied sensitivity with low detection limit. This work provides great potential applications for rapid and visual detection of antibiotics in complex substrates.

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.

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.

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.