Near-infrared fluorescent probe visual detection of Hg2+ and its application in biological system and ecological system.

Mercury ion (Hg2+), a heavy metal cation with greater toxicity, is widely present in the ecological environment and has become a serious threat to human health and environmental safety. Currently, developing a solution to simultaneously visualize and monitor Hg2+ in environmental samples, including water, soil, and plants, remains a great challenge. In this work, we created and synthesized a near-infrared fluorescent probe, BBN-Hg, and utilized Hg2+ to trigger the partial cleavage of the carbon sulfate ester in BBN-Hg as a sensing mechanism, and the fluorescence intensity of BBN-Hg was significantly enhanced at 650 nm, thus realizing the visualization of Hg2+ with good selectivity (detection limit, 53 nM). In live cells and zebrafish, the probe BBN-Hg enhances the red fluorescence signal in the presence of Hg2+, and successfully performs 3D imaging on zebrafish, making it a powerful tool for detecting Hg2+ in living systems. More importantly, with BBN-Hg, we are able to detect Hg2+ in actual water samples, soil and plant seedling roots. Furthermore, the probe was prepared as a test strip for on-site determination of Hg2+ with the assistance of a smartphone. Therefore, this study offers an easy-to-use and useful method for tracking Hg2+ levels in living organisms and their surroundings.

Smartphone video imaging: A versatile, low-cost technology for food authentication.

This study presents a low-cost smartphone-based imaging technique called smartphone video imaging (SVI) to capture short videos of samples that are illuminated by a colour-changing screen. Assisted by artificial intelligence, the study develops new capabilities to make SVI a versatile imaging technique such as the hyperspectral imaging (HSI). SVI enables classification of samples with heterogeneous contents, spatial representation of analyte contents and reconstruction of hyperspectral images from videos. When integrated with a residual neural network, SVI outperforms traditional computer vision methods for ginseng classification. Moreover, the technique effectively maps the spatial distribution of saffron purity in powder mixtures with predictive performance that is comparable to that of HSI. In addition, SVI combined with the U-Net deep learning module can produce high-quality images that closely resemble the target images acquired by HSI. These results suggest that SVI can serve as a consumer-oriented solution for food authentication.

Sensitive visual detection of norfloxacin in water by smartphone assisted colorimetric method based on peroxidase-like active cobalt-doped Fe3O4 nanozyme.

Norfloxacin is widely used owing to its strong bactericidal effect on Gram-negative bacteria. However, the residual norfloxacin in the environment can be biomagnified via food chain and may damage the human liver and delay the bone development of minors. Present work described a reliable and sensitive smartphone colorimetric sensing system based on cobalt-doped Fe3O4 magnetic nanoparticles (Co-Fe3O4 MNPs) for the visual detection of norfloxacin. Compared with Fe3O4, Co-Fe3O4 MNPs earned more remarkably peroxidase-like activity and TMB (colorless) was rapidly oxidized to oxTMB (blue) with the presence of H2O2. Interestingly, the addition of low concentration of norfloxacin can accelerate the color reaction process of TMB, and blue deepening of the solution can be observed with the naked eye. However, after adding high concentration of norfloxacin, the activity of nanozyme was inhibited, resulting in the gradual fading of the solution. Based on this principle, a colorimetric sensor integrated with smartphone RGB mode was established. The visual sensor exhibited good linearity for norfloxacin monitoring in the range of 0.13-2.51 µmol/L and 17.5-100 µmol/L. The limit of visual detection was 0.08 µmol/L. In the actual water sample analysis, the spiked recoveries of norfloxacin were over the range of 95.7%-104.7 %. These results demonstrated that the visual sensor was a convenient and fast method for the efficient and accurate detection of norfloxacin in water, which may have broad application prospect.

Adicción al uso del teléfono móvil inteligente en estudiantes de enfermería / Addiction to the use of smartphones among nursing students / Dependência do uso de smartphones em alunos de enfermagem

Resumen Marco contextual: Los teléfonos móviles inteligentes permiten acceder a información de manera inmediata. La adicción al uso de estos dispositivos es cada vez mayor, los teléfonos móviles inteligentes se han convertido en un elemento importante para los estudiantes de enfermería. Objetivo: Identificar la adicción al uso del teléfono móvil inteligente en estudiantes de enfermería. Metodología: Estudio descriptivo correlacional, el muestreo fue aleatorio, la muestra se calculó considerando un nivel de confianza de 0,05, una potencia de 90%, un tamaño de efecto mediano de 0,09, la muestra se conformó por 149 estudiantes de enfermería. Resultados: El componente de uso, abuso y adicción al teléfono móvil inteligente se relacionó negativamente con el componente rasgo de personalidad (r s = -0,228; p = 0,005), el uso, abuso y adicción al teléfono móvil inteligente se relacionó positivamente con el gasto monetario (r s = 0,376; p = 0,001). Conclusión: Se identificó que existe un alto uso de los teléfonos móviles inteligentes, comprender el alcance de dicho fenómeno puede ayudar a plantear estrategias eficaces para prevenir la adicción al teléfono móvil inteligente.

Abstract Background: Smartphones provide immediate access to information, and nursing students consider them essential tools. However, the addiction to these devices is increasing. Objective: To identify smartphone addiction among nursing students. Methodology: A descriptive correlational study was conducted using the stratified random sampling method. The sample size was calculated based on a confidence level of 0.05, with 90% power, and a median effect size of 0.09. The study included 149 nursing students. Results: The component "Smartphone use, abuse, and addiction" correlated negatively with the component "Personality traits" (r s = -0.228; p = 0.005); the component "Smartphone use, abuse, and addiction" correlated positively with the component "Financial spending" (r s = 0.376; p = 0.001). Conclusion: Smartphone use is high. Understanding the extent of this phenomenon can aid in developing effective strategies to prevent smartphone addiction.

Resumo Enquadramento: Os telemóveis inteligentes estão permitem acesso imediato à informação. O vício no uso desses dispositivos é cada vez maior, os celulares inteligentes tornaram-se um elemento importante para os estudantes de enfermagem. Objetivo: Identificar a dependência do uso do smartphone em estudantes de enfermagem. Metodologia: Estudo correlacional descritivo, a amostragem foi aleatória, a amostra foi calculada considerando nível de confiança de 0,05, poder de 90%, tamanho de efeito médio de 0,09, a amostra foi composta por 149 estudantes de enfermagem. Resultados: O componente de uso, abuso e dependência de smartphone foi negativamente relacionado ao componente de traço de personalidade (r s = -0,228; p = 0,005), o uso, abuso e dependência de smartphone foi relacionado positivamente com gastos monetários (r s = 0,376; p = 0,001). Conclusão: Identificou-se que existe um alto uso de telefones móveis inteligentes, compreender a abrangência desse fenômeno pode ajudar a propor estratégias eficazes para prevenir o vício em celulares.

Smartphone use by children in fast food restaurants in Barcelona (Spain): a direct observation study.

OBJECTIVE: To explore the use of smartphones at mealtimes by children in fast food restaurants in the city of Barcelona and to assess the variables associated with this use. METHOD: A cross-sectional study was carried out. Data from 1616 children of estimated ages between 4 to 10 years were collected in fast-food restaurants in the ten districts of Barcelona between October 2021 and July 2022. The percentage of smartphone use, overall and according to covariates, were calculated. Chi-squared and Fisher's exact tests, and crude and adjusted Poisson regression models with robust variance, were carried out to assess the association between use and covariates. RESULTS: Direct observation revealed that in 28.1% of meals with children at fast food restaurants, children used smartphones. Smartphone use was significantly higher in older children if their caregivers were younger than 30 years and when there was no caregiver-child interaction. In the adjusted model, higher patterns of smartphone use were associated with older children (aPR [95% CI]: 1.36[1.20-1.55]) and younger parents (aPR [95% CI]: 1.38[1.09-1.73]). CONCLUSIONS: Almost one in three meals with children at fast-food restaurants in Barcelona involves smartphone use. This finding underlines the importance of raising awareness of responsible screen use and promoting healthier environments for children at mealtimes.

A Longitudinal Investigation on the Reciprocal Relationship of Problematic Smartphone Use with Bedtime Procrastination, Sleep Quality, and Mental Health Among University Students.

Background: Problematic smartphone use (PSU) is linked to various mental health issues, but the relationship between PSU, bedtime procrastination, and mental health symptoms is unclear. Sleep factors related to PSU and its mental health effects have been understudied. This study explores the longitudinal associations between PSU, bedtime procrastination, sleep quality, and mental health in university students. Methods: In this study, a total of 683 university students participated by completing questionnaires on Smart Phone Addiction (SAS) scale, Bedtime Procrastination Scale (BPS), Pittsburgh Sleep Quality Index (PSQI), and Depression, Anxiety Stress Scales 21 (DASS-21) across two different time points with six-months interval between them. The participants were selected using a cluster sampling technique from Quaid-e-Azam University, Islamabad, Pakistan. A cross-lagged model was utilized to assess the longitudinal association between these variables. Results: Statistically significant reciprocal associations were found between PSU, bedtime procrastination, and mental health symptoms. PSU at Time 1 significantly predicted PSU at Time 2, bedtime procrastination at Time 2, sleep quality at Time 2, and mental health symptoms at Time 2. Bedtime procrastination at Time 1 predicted PSU at Time 2, sleep quality at Time 2, and mental health symptoms at Time 2. Sleep quality at Time 1 predicted bedtime procrastination at Time 2 and mental health symptoms at Time 2. Mental health symptoms at Time 1 predicted PSU at Time 2 and sleep quality at Time 2. Conclusion: The research findings have significantly advanced understanding of the longitudinal connections between PSU, bedtime procrastination, sleep quality, and mental health indicators. This enhanced comprehension is instrumental for psychological practitioners in devising targeted interventions to mitigate such issues among the university student demographic.

Smartphone-Related Neck Pain: A Study Among Saudi Residents in the Eastern Province.

BACKGROUND: The pervasive use of mobile phones has raised concerns about their impact on musculoskeletal health, particularly neck pain. This issue is notably relevant in the Eastern Province of Saudi Arabia, where high mobile phone usage intersects with demographic diversity. While extensive phone use has been linked to neck pain and other musculoskeletal disorders globally, specific data on this issue in the Eastern Province are limited. This study addresses this gap by examining phone use patterns, neck positions, and associated symptoms in the region. METHODS: Using an online, self-administered survey, this cross-sectional study investigated the relationship between phone use and neck pain in the Eastern Province of Saudi Arabia. Participants aged 18 years and older were recruited via social media, community groups, and university networks. The survey collected data on demographics, phone use patterns, neck positions, awareness of health risks, and pain symptoms. It was pre-tested, administered through Google Forms (Google, Mountain View, CA), and available for four weeks. Data were analyzed using descriptive statistics and cross-tabulations with SPSS 26.0 (IBM Corp., Armonk, NY). RESULTS: The study included 400 participants, with 273 females (68.3%) and 127 males (31.8%). Most participants were single (245, 61.3%) and held a university degree (301, 75.3%). Daily phone use varied: 228 participants (57.0%) used their phones for less than five hours daily, while 43 (10.8%) used them for 10-15 hours or more. Neck positions ranged from 0° to 60°, with 168 participants (42.0%) maintaining a 30° angle. Awareness of health risks associated with phone use was high, with 364 participants (91.0%) aware of these risks. Neck pain was reported by 244 participants (61.0%), with additional symptoms including headache (22 participants, 5.5%) and upper back pain (five participants, 1.3%). CONCLUSION: This study found a significant link between prolonged phone use and neck pain in the Eastern Province of Saudi Arabia. Despite high awareness of the risks, many individuals report discomfort. These findings underscore the need for public health interventions and ergonomic education to improve phone use practices and musculoskeletal health.

On-site burn severity assessment using smartphone-captured color burn wound images.

Accurate assessment of burn severity is crucial for the management of burn injuries. Currently, clinicians mainly rely on visual inspection to assess burns, characterized by notable inter-observer discrepancies. In this study, we introduce an innovative analysis platform using color burn wound images for automatic burn severity assessment. To do this, we propose a novel joint-task deep learning model, which is capable of simultaneously segmenting both burn regions and body parts, the two crucial components in calculating the percentage of total body surface area (%TBSA). Asymmetric attention mechanism is introduced, allowing attention guidance from the body part segmentation task to the burn region segmentation task. A user-friendly mobile application is developed to facilitate a fast assessment of burn severity at clinical settings. The proposed framework was evaluated on a dataset comprising 1340 color burn wound images captured on-site at clinical settings. The average Dice coefficients for burn depth segmentation and body part segmentation are 85.12 % and 85.36 %, respectively. The R2 for %TBSA assessment is 0.9136. The source codes for the joint-task framework and the application are released on Github (https://github.com/xjtu-mia/BurnAnalysis). The proposed platform holds the potential to be widely used at clinical settings to facilitate a fast and precise burn assessment.

Socio-demographic and other factors contributing to excessive leisure screen time in preadolescent children.

OBJECTIVES: Excessive screen use in early school age is associated with worsened health habits and negative child development in later age. We aimed to assess the time spent on modern and traditional screen-based devices and examine its associations with socio-demographic characteristics. METHODS: This population-based cross-sectional observation study was conducted in Czechia, Slovakia and Finland between April and June 2021. Participants (N = 1,915) were parents/caregivers of children attending elementary school grades 1 to 3, selected by stratified random sampling. Children's daily leisure screen time (LST) based on parental reports was the main outcome. Descriptive statistics, mean comparison and linear regression analysis were used for the analysis. RESULTS: The average daily LST was found to be as high as 3.5 hours and significantly associated with most socio-demographic variables. Eighty percent of children exceeded the threshold of two hours of LST per day, which was formerly introduced by the American Academy of Pediatrics. The most important predictor of LST in children was having their screen-based device(s) for their exclusive personal use (EPU). Linear regression with all predictors assessed together confirmed the significant effect of the screen-based devices' EPU, the child's sex and grade, the child's birth order and the parent's education, even when controlled for media parenting practices. CONCLUSIONS: Given the widespread availability of smartphones for exclusive personal use among young children, the regulation of EPU and the reinforcement of effective media parenting practices, particularly in families with lower education and income, are critical public health strategies to mitigate the negative impact of excessive screen time on child development and overall well-being.

Point-of-Care Testing for Cardiovascular Disease: A Narrative Review.

Cardiovascular disease is a major global public health challenge. Point-of-- care testing (POCT) technologies are crucial for the prevention, early diagnosis, and treatment of cardiovascular conditions. Numerous POCT technologies for cardiovascular disease are currently available, which include but are not limited to conventional methods, paper-based microfluidic technology, microfluidic chip technology, electrochemical detection technology, ultrasonic detection technology, and smartphone-based detection technology. Each method has a broad range of applications and performs differently across various detection scenarios. This article offers a comprehensive analysis of current POCT technologies for cardiovascular disease, assessing their effectiveness, limitations, and future development directions. The aim is to provide insights and theoretical references for innovative research and clinical applications in POCT methods for cardiovascular disease.

Effectiveness and cost-effectiveness of an integrated digital psychological intervention (EmoEase) in Chinese chronic obstructive pulmonary disease patients: Study protocol of a randomized controlled trial.

Background: Mental health problems in patients with chronic obstructive pulmonary disease (COPD) are common and frequently neglected. Digital psychological interventions may reduce mental health problems, but their effectiveness has not been evaluated in the Chinese COPD population. In this study, we will develop an integrated digital psychological intervention (EmoEase) and evaluate its effectiveness and cost-effectiveness in enhancing the mental wellbeing of patients with COPD in China. Methods: This study is a multicenter, two-arm, randomized controlled trial (RCT) with a parallel-group design to enroll at least 420 patients with COPD with age over 35 years. Participants will be assigned to receive either usual care (control group) or usual care + EmoEase (intervention group). Assessments will take place at baseline (T0) and 4 weeks (T1), 8 weeks (T2), and 16 weeks (T3) after baseline, and participants will be asked to complete questionnaires and physical measurements. The primary outcome measure will assess mental wellbeing using the Warwick Edinburgh Mental Wellbeing Scale (WEMWBS). Secondary outcome measures will assess mental health, physical health, COPD symptoms, health risk behaviors, socioeconomic indicators, and healthcare utilization and expenditure. Analyses will utilize an intention-to-treat approach. Discussion: This is the first RCT to examine the value of EmoEase, a novel digital psychological intervention for patients with COPD. If this intervention is effective and cost-effective, it could be rapidly scaled up to provide mental healthcare for patients with COPD in China. Trial registration: ClinicalTrials.gov Identifier: NCT06026709. Date of first submission: 30 August 2023. https://clinicaltrials.gov/study/NCT06026709.

Deep learning to capture leaf shape in plant images: Validation by geometric morphometrics.

Plant leaves play a pivotal role in automated species identification using deep learning (DL). However, achieving reproducible capture of leaf variation remains challenging due to the inherent "black box" problem of DL models. To evaluate the effectiveness of DL in capturing leaf shape, we used geometric morphometrics (GM), an emerging component of eXplainable Artificial Intelligence (XAI) toolkits. We photographed Ranunculus auricomus leaves directly in situ and after herbarization. From these corresponding leaf images, we automatically extracted DL features using a neural network and digitized leaf shapes using GM. The association between the extracted DL features and GM shapes was then evaluated using dimension reduction and covariation models. DL features facilitated the clustering of leaf images by source populations in both in situ and herbarized leaf image datasets, and certain DL features were significantly associated with biological leaf shape variation as inferred by GM. DL features also enabled leaf classification into morpho-phylogenomic groups within the intricate R. auricomus species complex. We demonstrated that simple in situ leaf imaging and DL reproducibly captured leaf shape variation at the population level, while combining this approach with GM provided key insights into the shape information extracted from images by computer vision, a necessary prerequisite for reliable automated plant phenotyping.

Digital Interventions for Managing Medication and Health Care Service Delivery in West Africa: Systematic Review.

BACKGROUND: As a result of the recent advancements in technology, the incorporation of digital interventions into the health care system has gained a lot of attention and adoption globally. However, these interventions have not been fully adopted, thereby limiting their impact on health care delivery in West Africa. OBJECTIVE: This review primarily aims at evaluating the current digital interventions for medication and health care delivery in West Africa. Its secondary aim is to assess the impacts of digital interventions in managing medication and health care service delivery with the intent of providing vital recommendations that would contribute to an excellent adoption of digital intervention tools in the health care space in West Africa. METHODS: In line with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), a comprehensive search through various databases yielded 529 results. After a rigorous screening, 29 articles that provided information on 3 broad digital health intervention tools were found eligible for this review. RESULTS: Out of 29 studies, 16 (55%) studies examined phone-based interventions, 9 (31%) studies focused on tele- and e-based interventions, and 4 (14%) studies evaluated digital interventions. These interventions were used for diverse purposes, some of which are monitoring adverse drug reactions, general health, sexual and reproductive health, and training of health care practitioners. The phone-based intervention appears to be the most known and impactful of all the interventions, followed by tele- and e-based, while digital interventions were scarcely used. CONCLUSIONS: Digital interventions have had a considerable level of impact on medication and health care delivery across West Africa. However, the overall impact is limited. Therefore, strategies must be developed to address the challenges limiting the use of digital intervention tools so that these tools can be fully incorporated into the health care space in West Africa.

Measuring Environmental and Behavioral Drivers of Chronic Diseases Using Smartphone-Based Digital Phenotyping: Intensive Longitudinal Observational mHealth Substudy Embedded in 2 Prospective Cohorts of Adults.

BACKGROUND: Previous studies investigating environmental and behavioral drivers of chronic disease have often had limited temporal and spatial data coverage. Smartphone-based digital phenotyping mitigates the limitations of these studies by using intensive data collection schemes that take advantage of the widespread use of smartphones while allowing for less burdensome data collection and longer follow-up periods. In addition, smartphone apps can be programmed to conduct daily or intraday surveys on health behaviors and psychological well-being. OBJECTIVE: The aim of this study was to investigate the feasibility and scalability of embedding smartphone-based digital phenotyping in large epidemiological cohorts by examining participant adherence to a smartphone-based data collection protocol in 2 ongoing nationwide prospective cohort studies. METHODS: Participants (N=2394) of the Beiwe Substudy of the Nurses' Health Study 3 and Growing Up Today Study were followed over 1 year. During this time, they completed questionnaires every 10 days delivered via the Beiwe smartphone app covering topics such as emotions, stress and enjoyment, physical activity, access to green spaces, pets, diet (vegetables, meats, beverages, nuts and dairy, and fruits), sleep, and sitting. These questionnaires aimed to measure participants' key health behaviors to combine them with objectively assessed high-resolution GPS and accelerometer data provided by participants during the same period. RESULTS: Between July 2021 and June 2023, we received 11.1 TB of GPS and accelerometer data from 2394 participants and 23,682 survey responses. The average follow-up time for each participant was 214 (SD 148) days. During this period, participants provided an average of 14.8 (SD 5.9) valid hours of GPS data and 13.2 (SD 4.8) valid hours of accelerometer data. Using a 10-hour cutoff, we found that 51.46% (1232/2394) and 53.23% (1274/2394) of participants had >50% of valid data collection days for GPS and accelerometer data, respectively. In addition, each participant submitted an average of 10 (SD 11) surveys during the same period, with a mean response rate of 36% across all surveys (SD 17%; median 41%). After initial processing of GPS and accelerometer data, we also found that participants spent an average of 14.6 (SD 7.5) hours per day at home and 1.6 (SD 1.6) hours per day on trips. We also recorded an average of 1046 (SD 1029) steps per day. CONCLUSIONS: In this study, smartphone-based digital phenotyping was used to collect intensive longitudinal data on lifestyle and behavioral factors in 2 well-established prospective cohorts. Our assessment of adherence to smartphone-based data collection protocols over 1 year suggests that adherence in our study was either higher or similar to most previous studies with shorter follow-up periods and smaller sample sizes. Our efforts resulted in a large dataset on health behaviors that can be linked to spatial datasets to examine environmental and behavioral drivers of chronic disease.

Smartphone-deployable and all-in-one machine vision for visual quantification analysis based on distance readout of electrophoresis titration biosensor.

As a class of point-of-care (POC) assays with visible distance readout (thermometer style), the electrophoresis titration (ET) biosensor affords high robustness, versatility, and simplicity for point-of-care quantification. However, naked-eye observation of the distance readout is unreliable in POC settings and manual processing of distance readout is time-consuming. Herein, we developed a smartphone-deployable and all-in-one machine vision for four ET biosensors (bovine serum albumin, melamine, uric acid, glutathione) to classify and quantify the samples simultaneously. To ensure accurate and rapid quantification on the smartphone, we customized the decolorization methods and edge detection operators to balance the region of interest (ROI) extraction performance and processing speed. We then established a dataset of 180 distance readout images to endow our machine vision with the ability to classify four sample types. Consequently, our machine vision demonstrated high accuracy in determining the sample type (>97.2%) and concentration (>97.3%). Moreover, expanding its applications to other targets was readily achieved by including distance readout images of other ET biosensors (e.g., hemoglobin A1c) in the dataset. Therefore, our strategy of constructing machine vision is compatible with the versatile ET biosensor technique, suggesting that the same strategy can be used for other thermometer-style POC assays.

Enhancing the Chain of Survival: The Role of Smartphone Applications in Cardiopulmonary Resuscitation.

This review explores the role of smartphone applications in providing real-time guidance for cardiopulmonary resuscitation (CPR) practices and highlights their potential to improve CPR quality among laypersons. A narrative literature review was conducted on the effectiveness of mobile CPR applications for smartphones. Studies published between 2014 and 2024 were included to ensure that new technological advances were examined. Our findings revealed that guided CPR applications significantly improve most critical parameters for efficacious resuscitation. Application users demonstrated that they achieved performance comparable to or even better than CPR-certified individuals. However, these tools have limitations, mostly related to familiarity, which may result in a delay in activating the application and, therefore, in initiating CPR. While smartphone applications are promising tools for enhancing bystander CPR, their integration into emergency medical response requires careful consideration. To fully take advantage of these applications, they should be incorporated into public health campaigns and standard CPR training. This would be even more successful if the application's functionality were standardized across different regions. Our research indicates that a combination of education and technology will likely play a major role in CPR training in the future, improving the efficacy and accessibility of life-saving measures. Smartphone applications could greatly improve the chain of survival in out-of-hospital cardiac arrest (OHCA) events. The design and accessibility of these applications as well as the integration of these applications with current emergency response frameworks should be the main areas of future research.

Smartphone application-delivered cognitive behavioural therapy for insomnia with telephone support for insomnia disorder compared to a waitlist control: a randomised clinical trial.

Although there have been promising findings for smartphone application (app)-delivered cognitive behavioural therapy for insomnia (CBT-I), previous trials have not screened participants rigorously for insomnia disorder and used therapist support. Based on the above, we aimed to examine the effects of smartphone app-delivered CBT-I with telephone support against a waitlist (WL) in a sample with insomnia disorder. A total of 64 participants with insomnia disorder were randomised to smartphone app-delivered CBT-I (n = 32) or a WL (n = 32). Smartphone app-delivered CBT-I consisted of six weekly smartphone app modules with 15 min of telephone support per week. At pre- and post-treatment, and the 3-month follow-up, we assessed insomnia symptoms and associated correlates and consequences. At post-treatment, we also assessed measures related to adherence (therapist support, exercise/module completion), self-rated perception of treatment content, activity, and adverse events. CBT-I significantly outperformed the WL with large effects on the primary outcome (d = 2.26) and was significantly different on most of the secondary outcomes with medium to large effects. CBT-I also resulted in a significantly larger proportion of treatment remitters (CBT-I: 64.5-77.4%, WL: 6.5-6.9%) and responders (CBT-I: 77.4-90.3%, WL: 19.4-24.1%) at post-treatment and follow-up, compared to the WL. Treatment was associated with high satisfaction, high adherence, low attrition, and few treatment-impeding adverse events. Based on the medium to large effects of smartphone app-delivered CBT-I with telephone support, this trial highlights the potential of delivering CBT-I exclusively through an app with therapist telephone support for high efficacy, satisfaction, and adherence.

Moderators of the Effects of a Digital Parenting Intervention on Child Conduct and Emotional Problems Implemented During the COVID-19 Pandemic: Results From a Secondary Analysis of Data From the Supporting Parents and Kids Through Lockdown Experiences (SPARKLE) Randomized Controlled Trial.

BACKGROUND: A smartphone app, Parent Positive, was developed to help parents manage their children's conduct and emotional problems during the COVID-19 pandemic. A randomized controlled trial, Supporting Parents and Kids Through Lockdown Experiences (SPARKLE), found Parent Positive to be effective in reducing children's emotional problems. However, app effectiveness may be influenced by a range of child, family, socioeconomic, and pandemic-related factors. OBJECTIVE: This study examined whether baseline factors related to the child, family, and socioeconomic status, as well as pandemic-related disruption circumstances, moderated Parent Positive's effects on child conduct and emotional problems at 1- and 2-month follow-up. METHODS: This study was a secondary exploratory analysis of SPARKLE data. The data set included 646 children (4-10 years of age) with parents randomized to either Parent Positive (n=320) or follow-up as usual (n=326). Candidate baseline moderators included child age, gender, attention-deficit/hyperactivity disorder symptoms, parental psychological distress, family conflict, household income, employment status, household overcrowding, and pandemic-related disruption risk (ie, homeschooling, lockdown status, and isolation status). Child conduct and emotional problem outcomes measured at 1- (T2) and 2-months (T3) post randomization were analyzed using linear mixed-effects analysis of covariance models adjusting for baseline (T1) measure of outcome and including intervention and intervention by time point interaction terms allowing for different effects at the 2 time points. Moderation of intervention effects by baseline factors was assessed by replacing the intervention by time interaction terms with intervention by time point by baseline moderator interaction terms. RESULTS: Child gender was a significant moderator of the Parent Positive versus follow-up as usual effect on emotional problems (B=0.72, 95% CI 0.12-1.33; P=.02). Specifically, the effect of Parent Positive was close to significant (T2: B=-0.41, 95% CI -0.82 to 0.0004; P=.05) or significant (T3: B=-0.76, 95% CI -1.22 to -0.30; P<.001) in males only when compared with females, and males experienced a significantly larger reduction in emotional problems than females in the Parent Positive arm at the 2-month post randomization time point. None of the other investigated baseline factors moderated effects on emotional problems, and no factors moderated effects on conduct problems. CONCLUSIONS: This study highlights Parent Positive's potential for effectively reducing emotional problems in primary school-aged male children across a wide range of families. However, due to limited variability in the demographic background of the families, cautious interpretation is required, and replications are necessary in diverse samples with longer follow-up times. TRIAL REGISTRATION: ClinicalTrials.gov NCT04786080; https://clinicaltrials.gov/ct2/show/NCT04786080.

Visible diffuse reflectance smartphone spectrometer with high spectral accuracy.

A smartphone-based spectrometer employing principle of diffuse reflection is reported for the surface analysis of solid samples. The instrument utilizes a thin-film grating to diffract incoming light, while a diffuse reflecting surface projects the image of this diffracted light onto the detector plane. The CMOS camera of smartphone camera directly captures the diffusely reflected photons within its limited field-of-view thus eliminating the need for collection, conditioning and converging optics. The optical setup of the instrument provides facility to calibrate the spectral response considering the nonlinear distribution of the wavelength across the diffraction direction. Additional correction in the detector response at different light intensity results a reduced spectral error with a maximum wavelength resolution of δλ=0.08 nm/pixel in the camera within the spectral range Δλ = (400 - 700) nm. As a proof of the concept, the instrument demonstrates successful detection of color pigments in food samples by absorption measurement of the samples at an average spectral error < 6 %. The distinct absorption peak associated with standard food colors are compared against the absorption profile of unknown food colors used in pastry cake. This field-functional smart analysis with internet connectivity opens opportunity of identifying food adulteration by using toxic chemical colors at the point-of-test and immediate reporting to others. The overall instrument is fabricated by utilizing low-cost and light weight plastic wood to make compact (110 mm × 105 mm × 125 mm), robust, inexpensive (∼$ 50) and suitable for field-portable (∼145 gm) hand-held operation.

Long-Term Study on the Fluctuation of Self-Reported Awake Bruxism in a Cohort of Healthy Young Adults.

BACKGROUND: The introduction of a smartphone-based ecological momentary assessment (EMA) approach has allowed achieving data on the frequency of different awake bruxism (AB) behaviours (i.e., teeth contact, teeth clenching, teeth grinding, and mandible bracing) reported by an individual in the natural environment. STUDY OBJECTIVES: The fluctuation of AB reports over time has a certain degree of variability that has never been investigated. Therefore, the aim of this investigation was to assess the long-term fluctuation of AB behaviours in a population of young adults. METHODS: A smartphone application was used to assess a real-time report on five specific oral conditions related to AB in a sample of 77 young adults, aged 24.0 ± 0.8 years. Data were recorded over three periods of 7 days, with a three-month interval for a total of 6 months. RESULTS: The average frequency of the relaxed condition was 72.9%, 78.2%, and 80.8% at the end of the first, second, and third sessions, respectively. On average, teeth contact and mandible bracing were the most frequently reported conditions, with a mean prevalence of 12.9% and 7%, respectively, whilst the frequency of teeth clenching and teeth grinding was less than 3%. The ANOVA test showed an absence of significant differences (p < 0.05) between the three recording periods, and the frequency was in general only moderately variable from day-to-day (e.g., the coefficient of variation (CV) for the condition "relaxed jaw muscles" was 0.3). No gender differences were detected either. CONCLUSIONS: Findings suggest that in a population of healthy individuals, the frequency of AB behaviours over a six-month monitoring period is quite constant. This investigation represents a standpoint for future comparisons on the study of natural fluctuations of AB behaviours as well as on AB frequency in populations with risk/associated factors and possible clinical consequences.