Journal articles on the topic 'Phone duration modeling'

e18068 Background: Wearable activity trackers and frequent interrogation of remote patient reported outcomes (PROs) have the potential to revolutionize oncology clinical trial design, therapeutic sequencing and patient (pt) safety. Established feasibility and novel systems of data processing are necessary to substantiate value for these methods. Methods: Expanding upon our clinical research data platform, Prometheus, we have developed a HIPPA compliant, remote pt monitoring system capable of collecting minute-by-minute step count and heart rate (via Fitbit) in addition to smart phone derived symptom surveys. To pilot this program, a cohort of metastatic castration resistant prostate cancer (mCRPC) pts participated in continuous Fitbit monitoring and thrice weekly NCI-PRO-CTCAE survey for 26 weeks. Pre-specified interim feasibility results were examined with a focus on pt characteristics, treatment and compliance. Qualitative assessment of barriers to pt enrollment and device use was performed. Results: 15 mCRPC pts completed our pilot program: mean age 63.1 years (range 48-79), pre-treatment PSA 33.2 ng/mL (range 0.3 – 499.9), 80.0% stage M1b, ECOG 0 or 1. All pts were treated per protocol NCT02703623: abiraterone/prednisone/apalutamide for 8 weeks followed by continuation of therapy (5 pts), cabazitaxel/carboplatin (6 pts) or addition of ipilimumab (2 pts). 33.3% of pts reported grade 3 clinician interpreted adverse events. 14 pts had data available for compliance analysis. Mean Fitbit compliance was 62.6% (STD 35.5%) with rates trending down over the study duration (week 1 vs 26 = 86.7% vs 33.3%; p= 0.002; R2= 0.716). Mean smart phone derived NCI-PRO-CTCAE survey completion rate was 37.1%. Barriers to pt enrollment included slow Fitbit app download times, incompatible smart phones and the need for extensive device use education/counseling. Barriers to data collection were missed survey text prompts and inconsistent use of Bluetooth. Conclusions: MD Anderson’s novel, home-grown, remote pt monitoring platform, utilizing Fitbit and smart phone derived PROs, is feasible in function and pt use. Automated compliance checks, streamlined enrollment and pt education are critical to future application. This foundational work will facilitate longitudinal signal variation benchmarked against standard monitoring methods, ultimately aiming to improve outcomes and support of discovery through enriched access to pt experience.

Historically, travel surveys have been conducted face-to-face, by mail, or by phone. With the increasing share of households having access to the Internet, other survey modes have been deployed. This paper focuses on web surveys. Among other advantages, using the web to conduct surveys reduces costs and helps mitigate poor response rates among young households. Very few studies have been conducted on interview duration and its determinant using paradata from web travel surveys. Such knowledge is necessary to validate the context in which travel data are gathered and can be used to understand sample and data quality. Interview duration modeling is also essential for allocating survey servers and monitoring interviews during the data collection phase. This paper models interview duration using paradata from nine web surveys conducted in the Quebec province from 2010 to 2014. The main objectives of the model are to assist the monitoring of interviews by detecting outliers, provide a better estimate of the interview duration to respondents and survey managers during the interview, and allow a more precise evaluation of the server performance needed before conducting web travel surveys. Using a multiple regression model, we observed that the most important variables in explaining interview duration were number of car and transit trips as well as number of unique places visited during a day. Conducting the interview on a small-screen device also increased interview duration. The model also provides a baseline estimate of interview duration on the basis of demographic features and questionnaire design.

Background: An economic evaluation of Sun Safe Schools intervention designed to aid California elementary schools with implementing sun safety practices consistent with local board–approved policy. Design: Program cost analysis: intervention delivery and practice implementation. Setting: California elementary schools (58 interventions and 60 controls). Principals at 52 intervention and 53 control schools provided complete implementation data. Participants: Principals completing pre-/postintervention surveys assessing practice implementation. Intervention: Phone-based 45-minute session with a project coach on practice implementation, follow-up e-mails/phone contacts, $500 mini-grant. Schools chose from a list of 10 practices for implementation: ultraviolet monitoring, clothing, hats, and/or sunscreen recommendations, outdoor shade, class education, staff training and/or modeling, parent outreach, and resource allocation. The duration of intervention was 20 months. Rolling recruitment/intervention: February 2014 to December 2017. Measures: Intervention delivery and practice implementation costs. Correlations of school demographics and administrator beliefs with costs. Analysis: Intervention delivery activities micro-costed. Implemented practices assessed using costing template. Results: Intervention schools: 234 implemented practices, control schools: 157. Twenty-month delivery costs: $29 310; $16 653 (per school: $320) for project staff, mostly mini-grants and coaching time. Administrator costs: $12 657 (per school: $243). Per-student delivery costs: $1.01. Costs of implemented practices: $641 843 for intervention schools (per-school mean: $12 343, median: $6 969); $496 365 for controls (per-school mean: $9365, median: $3123). Delivery costs correlated with implemented practices (0.37, P < .01) and total practice costs (0.37, P < .05). Implemented practices correlated with principal beliefs about the importance of skin cancer prevention to student health (0.46, P < .001) and parents (0.45, P < .001). Conclusion: Coaching of elementary school personnel can stimulate sun safety practice implementation at a reasonable cost. Findings can assist schools in implementing appropriate sun safety practices.

Purpose – This paper aims to develop an estimation tool for warpage behavior of slim printed circuit board (PCB) array while soldering with electronic components by using finite element method. One of the essential requirements for handheld devices, such as smart phone, digital camera, and Note-PC, is the slim design to satisfy the customers’ desires. Accordingly, the printed circuit board (PCB) should be also thinner for a slim appearance, which would result in decreasing the PCB’s bending stiffness. This means that PCB deforms severely during the reflow (soldering) process where the peak temperature goes up to 250°C. Therefore, it is important to estimate PCB deformation at a high temperature for thermo-mechanical quality/reliability after reflow process. Design/methodology/approach – A numerical simulation technique was devised and customized to accurately estimate the behavior of a thin printed board assembly (PBA) during reflow by considering all components, including PCB, microelectronic packages and solder interconnects. Findings – By applying appropriate constraints and boundary conditions, it was found that PBA’s warpage can be accurately predicted during the reflow process. The results were also validated by warpage measurement, which showed a fairly good agreement with one and another. Research limitations/implications – For research limitations, there are many assumptions regarding numerical modeling. That is, the viscoplastic material property of solder ball is ignored, the reflow profile is simplified and the accurate heat capacity is not considered. Furthermore, the residual stress within the PCB, generated at PCB manufacturing process, is not included in this paper. Practical implications – This paper shows how to calculate PBA warpage during the reflow process as accurately as possible. This methodology helps a PCB designer and surface-mount technology (SMT) process manager to predict a PBA warpage issue and modify PCB design before PCB real fabrication. Practically, this modeling and simulation process can be easily performed by using a graphical user interface (GUI) module, so that the engineer can handle an issue by inputting some numbers and clicking some buttons. Social implications – In a common sense manner, a numerical simulation method can decrease time and cost in manufacturing real samples. This PCB warpage method can also decrease product development duration and produce a new product earlier. Furthermore, PCB is a common component in all the electronic devices. So, this PCB warpage method can have various applications. Originality/value – Because of an economic advantage, the development of a numerical simulation tool for estimating the thin PBA warpage behaviour during reflow process was attempted. The developed tool contains the features of detailed modeling for electronic components and contact boundary conditions of the supporting rails in the reflow oven.

Energy consumption in a mobile device becomes a great interest as limited battery source restricts the power to activate the device. Current battery capacity displayed on a mobile phone screen is based on current state. A more precise prediction method is important as the connected application critically depends on the power availability. This paper reports the 802.16 energy assessment and modelling. A state and duration based energy consumption prediction is proposed and compared to simulated energy measurement. The evaluation showed state trend results 0.18% deviation for training data, 0.187% for test data 1 and 0.191% for test data 2. While state and duration trends result 0.194% deviation for training data, 0.211% for test data 1 and 0.215% for test data 2.

Objective: To investigate dietary habits, sleep and psychological well-being of adolescents and medical students during COVID-19 lockdown in Split, Croatia. Methods: We surveyed 1326 students during 2018 and 2019, and compared their responses with 531 students enrolled in May 2020. Perceived stress, quality of life (QoL), happiness, anxiety, and optimism were assessed as proxies of psychological well-being, using general linear modelling. Results: We found no substantial differences in dietary pattern between pre-lockdown and lockdown periods, including the overall Mediterranean diet (MD) adherence. However, the MD pattern changed, showing increased adherence to the MD pyramid for fruit, legumes, fish, and sweets, while cereals, nuts, and dairy intake decreased during COVID-19 lockdown. A third of students reported weight loss during lockdown, 19% reported weight gain, while physical activity remained rather stable. The most prominent change was feeling refreshed after a night’s sleep, reported by 31.5% of students during lockdown vs. 8.5% before; median length of sleep duration increased by 1.5 h. Lockdown significantly affected QoL, happiness, optimism (all p < 0.001), and perceived stress in students (p = 0.005). MD adherence was positively correlated with QoL and study time, and negatively with TV and mobile phone use in pre-lockdown period (all p < 0.001). Interestingly, higher MD adherence was correlated with less perceived hardship and greater happiness and QoL during lockdown. Conclusion: These insights provide valuable information for tailored interventions aimed at maintaining healthy lifestyle in young population. Given the numerous beneficial effects associated with MD adherence, modification of lifestyle through application of lifestyle medicine deserves a priority approach.

Abstract In this study, we propose to diagnose facial nerve palsy using Support Vector Machines (SVMs) and Emergent Self-Organizing Map (ESOM). This research seeks to analyze facial palsy domain using facial features and grade the degree of nerve damage based on the House-Brackmann score. Traditional diagnostic approaches involve a medical doctor recording a thorough history of a patient and determining the onset of paralysis, rate of progression and so on. The most important step is to assess the degree of voluntary movement of the facial nerves and document the grade of facial paralysis using House- Brackmann score. The significance of the work is the attempt to understand the diagnosis and grading processes using semi-supervised learning with the aim of automating the process. The value of the research is in identifying and documenting the limited literature seen in this area. The use of automated diagnosis and grading greatly reduces the duration of medical examination and increases the consistency, because many palsy images are stored to provide benchmark references for comparative purposes. The proposed automated diagnosis and grading are computationally efficient. This automated process makes it ideal for remote diagnosis and examination of facial palsy. The profiling of a large number of facial images are captured using mobile phones and digital cameras.

Climate change induced sea-level rise (SLR) is on its increase globally. Regionally the lowlands of China, Vietnam, Bangladesh, and islands of the Malaysian, Indonesian and Philippine archipelagos are among the world’s most threatened regions. Sea-level rise has major impacts on the ecosystems and society. It threatens coastal populations, economic activities, and fragile ecosystems as mangroves, coastal salt-marches and wetlands. This paper provides a summary of the current state of knowledge of sea level-rise and its effects on both human and natural ecosystems. The focus is on coastal urban areas and low lying deltas in South-East Asia and Vietnam, as one of the most threatened areas in the world. About 3 mm per year reflects the growing consensus on the average SLR worldwide. The trend speeds up during recent decades. The figures are subject to local, temporal and methodological variation. In Vietnam the average values of 3.3 mm per year during the 1993-2014 period are above the worldwide average. Although a basic conceptual understanding exists that the increasing global frequency of the strongest tropical cyclones is related with the increasing temperature and SLR, this relationship is insufficiently understood. Moreover the precise, complex environmental, economic, social, and health impacts are currently unclear. SLR, storms and changing precipitation patterns increase flood risks, in particular in urban areas. Part of the current scientific debate is on how urban agglomeration can be made more resilient to flood risks. Where originally mainly technical interventions dominated this discussion, it becomes increasingly clear that proactive special planning, flood defense, flood risk mitigation, flood preparation, and flood recovery are important, but costly instruments. Next to the main focus on SLR and its effects on resilience, the paper reviews main SLR associated impacts: Floods and inundation, salinization, shoreline change, and effects on mangroves and wetlands. The hazards of SLR related floods increase fastest in urban areas. This is related with both the increasing surface major cities are expected to occupy during the decades to come and the increasing coastal population. In particular Asia and its megacities in the southern part of the continent are increasingly at risk. The discussion points to complexity, inter-disciplinarity, and the related uncertainty, as core characteristics. An integrated combination of mitigation, adaptation and resilience measures is currently considered as the most indicated way to resist SLR today and in the near future.References Aerts J.C.J.H., Hassan A., Savenije H.H.G., Khan M.F., 2000. Using GIS tools and rapid assessment techniques for determining salt intrusion: Stream a river basin management instrument. 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This study elucidate ‘Nomophobia' by developing a research model that identifies various determinants of the Smartphone taking apart of usage among students it leads to addiction and self-control, cyber addiction and positive aspects of using the Smartphone. Structural equation modeling of the proposed model indicates that students were using for long duration and its analysis the purpose of using the Smartphone positive and negative aspects, poor self-control, cyber addiction and problem using Smartphone, they are more fond of to the Smartphone devices, which, in go-round, lead to the Smartphone addiction "Nomophobia".

AbstractWe describe the multi-layer temporal network which connects a population of more than 700 university students over a period of four weeks. The dataset was collected via smartphones as part of the Copenhagen Networks Study. We include the network of physical proximity among the participants (estimated via Bluetooth signal strength), the network of phone calls (start time, duration, no content), the network of text messages (time of message, no content), and information about Facebook friendships. Thus, we provide multiple types of communication networks expressed in a single, large population with high temporal resolution, and over a period of multiple weeks, a fact which makes the dataset shared here unique. We expect that reuse of this dataset will allow researchers to make progress on the analysis and modeling of human social networks.

Understanding human mobility within urban settings is fundamental for urban and transport planning. Travel demand modeling and planning typically rely on data that are collected from large-scale household travel surveys (i.e., origin–destination surveys) and compiled into single- or multiple-day travel diaries. The laborious task of collecting these data has left traditional methods with numerous limitations, resulting in significant trade-offs in regard to accuracy, sample size, and study duration, while also being vulnerable to reporting and transcription error. Rising mobile phone ownership has provided opportunities to acquire expansive cellular network data from service providers and location-based service data through smartphone applications. At the same time, the Google Maps smartphone application provides built-in infrastructure that can passively collect detailed location information from user smartphone devices. The resulting data are known as Google location history (GLH). To better understand the potential of these data offerings in transportation modeling and planning, GLH data passively collected from five different smartphones following prescribed itineraries over 12 days was evaluated. As 51% of 934 locations and 32% of 888 trips were matched to the pre-determined travel diary data, it was determined that GLH data does not currently appear to be an adequate tool for travel diary data collection. On average, locations that were missed by GLH were shorter (mean of 355 s), whereas locations that were identified were longer (mean of 762 s).

The purpose of this study is to examine the effects of audio imagery with video modelling on participants’ self-efficacy during resistance exercise. Forty five individuals volunteered as research participant and were divided homogenously into imagery with modelling end instruction (EIM) or initial instruction (IIM) groups and a modelling only (M) as control group. During the pre-test all participants employed self-efficacy (SE) of lunges exercise. All participants were provided with the interventions (EIM, IIM, & M) during 10 minutes rest before the first post-test which, all measurements were conducted to look at the acute effects of interventions employed. Participants’ android phones were downloaded with specific intervention according to their group and they were advised to employ the intervention once a day for seven days. The second post-test was conducted consist of all measurements after seven days of intervention duration. For self-efficacy, significant results were recorded on pre-test and post-test within participants in EIM and IIM (p < 0.05), moreover, results for post-test comparing data between groups indicates significant between EIM and M groups, IIM and M groups (p < 0.05). No significant different results found comparing EIM with IIM groups. Results from this study indicate that there are psychological performances improvement among participant who employed imagery and modelling comparing to modelling alone.

AbstractContact tracing is one of several strategies employed in many countries to curb the spread of SARS-CoV-2. Digital contact tracing (DCT) uses tools such as cell-phone applications to improve tracing speed and reach. We model the impact of DCT on the spread of the virus for a large epidemiological parameter space consistent with current literature on SARS-CoV-2. We also model DCT in combination with random testing (RT) and social distancing (SD).Modelling is done with two independently developed individual-based (stochastic) models that use the Monte Carlo technique, benchmarked against each other and against two types of deterministic models.For current best estimates of the number of asymptomatic SARS-CoV-2 carriers (approximately 40%), their contagiousness (similar to that of symptomatic carriers), the reproductive number before interventions (${R_{0}}$ R 0 at least 3) we find that DCT must be combined with other interventions such as SD and/or RT to push the reproductive number below one. At least 60% of the population would have to use the DCT system for its effect to become significant. On its own, DCT cannot bring the reproductive number below 1 unless nearly the entire population uses the DCT system and follows quarantining and testing protocols strictly. For lower uptake of the DCT system, DCT still reduces the number of people that become infected.When DCT is deployed in a population with an ongoing outbreak where $\mathcal{O}$ O (0.1%) of the population have already been infected, the gains of the DCT intervention come at the cost of requiring up to 15% of the population to be quarantined (in response to being traced) on average each day for the duration of the epidemic, even when there is sufficient testing capability to test every traced person.

Abstract Background Excessive screen time behaviors performed by children and parents at home is a major public health concern. Identifying whether child and parent screen time behaviors cluster and understanding correlates of these familial clusters can help inform interventions for the whole family. This study characterized familial typologies of screen time behaviors and identified key modifiable correlates of these typologies. Methods Parents participating in the cross-sectional Sitting in the Home (SIT) study reported the duration (mins/day) they and their child (aged 11.2 ± 2.62 years) spent in six screen time behaviors at home (computer/laptop for home/work, computer/laptop for leisure, TV/videos/DVDs, tablet/smart phone for home/work, tablet/smart phone for leisure, and electronic games) and completed items related to 21 potential correlates framed by an adapted Social Cognitive Theory, Family Perspective. Latent Class Analysis was used to identify typologies based on parent and child data for the six behaviors. Multinomial logistic regression analysis assessed the relative risk of typology membership for each potential correlate, adjusting for child and parent age and sex. Results The sample comprised 542 parent-child dyads (parents: 40.7 ± 6.3 yrs., 94% female; children: 11.2 ± 2.6 yrs., 46% female). Three typologies were identified: 1) high computer/moderate TV (n = 197); 2) high TV/tablet/smartphone, low computer (n = 135); and 3) low-screen users (n = 210). ‘Low-screen users’ spent the least amount of time in all screen time behaviors (assigned as reference category). Greater child preference for screen time behaviors, parental support for screen time behaviors and frequency of homework requiring a tablet/laptop were associated with higher odds of being in the ‘high computer/moderate TV’ typology. The odds of being in the ‘high TV/tablet/smartphone, low computer’ typology were greater amongst children with a higher preference for screen time behaviors, and lower among more active parents. Conclusions Three familial typologies of screen time behaviors were identified. The findings highlight that screen time in the home can be influenced by the home environment, parental behaviours and role modelling, child preferences as well as school policies. Findings can inform the development of family screen time interventions, however more research exploring the influence of factors outside of the home is warranted.