Does the PedsQL reflect the real-time quality of life in autistic adolescents? A comparison with the experience sampling methodology.

BACKGROUND: The PedsQL is widely used to retrospectively evaluate quality of life (QoL) in autistic adolescents. However, concerns have arisen regarding its ability to reflect real-time QoL, considering their challenges in recollecting past experiences. OBJECTIVE: We examined the overall and social QoLs of autistic adolescents compared to neurotypical peers using the PedsQL and the experience sampling method (ESM), an ecological momentary assessment of QoL in real-time. Additionally, we explored the relationship between these measures in each group. METHODS: A total of 175 participants, including 117 autistic and 58 neurotypical adolescents aged 10-16, completed the PedsQL and an ESM protocol with a mobile device to record their real-time experiences seven times a day for seven days. We performed multiple linear regression and multilevel analyses to compare QoLs between groups and the association between the two measures. RESULTS: Autistic adolescents scored significantly lower than neurotypical peers on PedsQL overall and social QoL but not on the real-time experiences collected with ESM. Among neurotypical adolescents, we found significant associations between the Social Functioning score of the PedsQL and various aspects of real-time social experiences recorded with ESM. For autistic adolescents, only the real-time experience of 'loneliness' during social engagement was associated with Social Functioning on the PedsQL. CONCLUSIONS: The retrospective PedsQL does not entirely capture the real-time QoL via ESM. However, relying solely on ESM may overlook situations where participants opt out or could not complete surveys. Thus, using both retrospective and real-time assessments to examine QoL among autistic adolescents is recommended.

Incorporation of water quality index models with machine learning-based techniques for real-time assessment of aquatic ecosystems.

Water quality index (WQI) is a well-established tool for assessing the overall quality of fresh inland-waters. However, the effectiveness of real-time assessment of aquatic ecosystems using the WQI is usually impacted by the absence of some water quality parameters in which their accurately in-situ measurements are impossible and face difficulties. Using a rich water quality dataset spanned from 1980 to 2023, we employed four machine learning-based models to estimate the British Colombia WQI (BCWQI) in the Lake Päijänne, Finland, without parameters like chemical oxygen demand (COD) and total phosphorus (TP). Measurement of both COD and TP is time-consuming, needs laboratory equipment and labor costs, and faces sampling-related difficulties. Our results suggest the machine learning-based models successfully estimate the BCWQI in Lake Päijänne when TP and COD are omitted from the dataset. The long-short term memory model is the least sensitive model to exclusion of COD and TP from inputs. This model with the coefficient of determination and root-mean squared error of 0.91 and 0.11, respectively, outperforms the support vector regression, random forest, and neural network models in real-time estimation of the BCWQI in Lake Päijänne. Incorporation of BCWQI with the machine learning-based models could enhance assessment of overall quality of inland-waters with a limited database in a more economical and time-saving way. Our proposed method is an effort to replace the traditional offline water quality assessment tools with a real-time model and improve understanding of decision-makers on the effectiveness of management practices on the changes in lake water quality.

Acceptability and Feasibility of a Smartphone-Based Real-Time Assessment of Suicide Among Black Men: Mixed Methods Pilot Study.

BACKGROUND: Suicide rates in the United States have increased recently among Black men. To address this public health crisis, smartphone-based ecological momentary assessment (EMA) platforms are a promising way to collect dynamic, real-time data that can help improve suicide prevention efforts. Despite the promise of this methodology, little is known about its suitability in detecting experiences related to suicidal thoughts and behavior (STB) among Black men. OBJECTIVE: This study aims to clarify the acceptability and feasibility of using smartphone-based EMA through a pilot study that assesses the user experience among Black men. METHODS: We recruited Black men aged 18 years and older using the MyChart patient portal messaging (the patient-facing side of the Epic electronic medical record system) or outpatient provider referrals. Eligible participants self-identified as Black men with a previous history of STB and ownership of an Android or iOS smartphone. Eligible participants completed a 7-day smartphone-based EMA study. They received a prompt 4 times per day to complete a brief survey detailing their STB, as well as proximal risk factors, such as depression, social isolation, and feeling like a burden to others. At the conclusion of each day, participants also received a daily diary survey detailing their sleep quality and their daily experiences of everyday discrimination. Participants completed a semistructured exit interview of 60-90 minutes at the study's conclusion. RESULTS: In total, 10 participants completed 166 EMA surveys and 39 daily diary entries. A total of 4 of the 10 participants completed 75% (21/28) or more of the EMA surveys, while 9 (90%) out of 10 completed 25% (7/28) or more. The average completion rate of all surveys was 58% (20.3/35), with a minimum of 17% (6/35) and maximum of 100% (35/35). A total of 4 (40%) out of 10 participants completed daily diary entries for the full pilot study. No safety-related incidents were reported. On average, participants took 2.08 minutes to complete EMA prompts and 2.72 minutes for daily diary surveys. Our qualitative results generally affirm the acceptability and feasibility of the study procedures, but the participants noted difficulties with the technology and the redundancy of the survey questions. Emerging themes also addressed issues such as reduced EMA survey compliance and diminished mood related to deficit-framed questions related to suicide. CONCLUSIONS: Findings from this study will be used to clarify the suitability of EMA for Black men. Overall, our EMA pilot study demonstrated mixed feasibility and acceptability when delivered through smartphone-based apps to Black men. Specific recommendations are provided for managing safety within these study designs and for refinements in future intervention and implementation science research. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/31241.

Real-Time Real-World Digital Monitoring of Adolescent Suicide Risk During the Six Months Following Emergency Department Discharge: Protocol for an Intensive Longitudinal Study.

BACKGROUND: Suicide is the second leading cause of death in adolescents, and self-harm is one of the strongest predictors of death by suicide. The rates of adolescents presenting to emergency departments (EDs) for suicidal thoughts and behaviors (STBs) have increased. Still, existing follow-up after ED discharge is inadequate, leaving a high-risk period for reattempts and suicide. There is a need for innovative evaluation of imminent suicide risk factors in these patients, focusing on continuous real-time evaluations with low assessment burden and minimal reliance on patient disclosure of suicidal intent. OBJECTIVE: This study examines prospective longitudinal associations between observed real-time mobile passive sensing, including communication and activity patterns, and clinical and self-reported assessments of STB over 6 months. METHODS: This study will include 90 adolescents recruited on their first outpatient clinic visit following their discharge from the ED due to a recent STB. Participants will complete brief weekly assessments and be monitored continuously for their mobile app usage, including mobility, activity, and communication patterns, over 6 months using the iFeel research app. Participants will complete 4 in-person visits for clinical assessment at baseline and at the 1-, 3-, and 6-month follow-ups. The digital data will be processed, involving feature extraction, scaling, selection, and dimensionality reduction. Passive monitoring data will be analyzed using both classical machine learning models and deep learning models to identify proximal associations between real-time observed communication, activity patterns, and STB. The data will be split into a training and validation data set, and predictions will be matched against the clinical evaluations and self-reported STB events (ie, labels). To use both labeled and unlabeled digital data (ie, passively collected), we will use semisupervised methods in conjunction with a novel method that is based on anomaly detection notions. RESULTS: Participant recruitment and follow-up started in February 2021 and are expected to be completed by 2024. We expect to find prospective proximal associations between mobile sensor communication, activity data, and STB outcomes. We will test predictive models for suicidal behaviors among high-risk adolescents. CONCLUSIONS: Developing digital markers of STB in a real-world sample of high-risk adolescents presenting to ED can inform different interventions and provide an objective means to assess the risk of suicidal behaviors. The results of this study will be the first step toward large-scale validation that may lead to suicide risk measures that aid psychiatric follow-up, decision-making, and targeted treatments. This novel assessment could facilitate timely identification and intervention to save young people's lives. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46464.

Real-time site safety risk assessment and intervention method using the RFID-based multi-sensor intelligent system.

BACKGROUND: One of the main problems that may put people's safety in danger is the lack of real-time detection, evaluation, and recognition of predictable safety risks. Current real-time risk identification solutions are limited to proximity sensing, which lack providing the exposed person with risk-specific information in real-time. Combined values of concurrently presented risks are either unrecognized or underestimated. OBJECTIVE: This study goes beyond the proximity sensing state-of-the-art by envisioning, planning, designing, developing, assembling, and examining an automated intelligent real-time risk (AIR) assessment system. METHODS: A holistic safety assessment approach is followed to include identification, prioritization, detection, evaluation, and control at risk exposure time. Multi-sensor technologies based on RFID are integrated with a risk assessment intelligent system. System prototype is developed and examined to prove the concept for on-foot building construction workers. RESULTS: The evaluation of AIR assessment system's performance proved its validity, significance, simplicity, representation, accuracy, precision, and timeliness. The reliability of providing quantitative proximity values of risk can be limited due to the signal attenuation; however, it can be reliable in providing risk proximity in a subjective linguistic fashion (Near/Far). CONCLUSION: The main contributions of the AIR assessment system are that the mobile wearable device can provide a linguistic meaningful risk assessment resultant value, the value represents the combined evaluation of concurrently presented risks, and can be sound delivered to the exposed person in real-time of exposure. Therefore, AIR system can be used as an effective prognostic risk assessment tool that can empower workers with real-time recognition and measurability of risk exposure.

An exploration of "real time" assessments as a means to better understand preceptors' judgments of student performance.

Clinical supervisors are known to assess trainee performance idiosyncratically, causing concern about the validity of their ratings. The literature on this issue relies heavily on retrospective collection of decisions, resulting in the risk of inaccurate information regarding what actually drives raters' perceptions. Capturing in-the-moment information about supervisors' impressions could yield better insight into how to intervene. The purpose of this study, therefore, was to gather "real-time" judgments to explore what drives preceptors' judgments of student performance. We performed a prospective study in which physicians were asked to adjust a rating scale in real-time while watching two video-recordings of trainee clinical performances. Scores were captured in 1-s increments, examined for frequency, direction, and magnitude of adjustments, and compared to assessors' final entrustability judgment as measured by the modified Ottawa Clinic Assessment Tool. The standard deviation in raters' judgment was examined as a function of time to determine how long it takes impressions to begin to vary. 20 participants viewed 2 clinical vignettes. Considerable variability in ratings was observed with different behaviours triggering scale adjustments for different raters. That idiosyncrasy occurred very quickly, with the standard deviation in raters' judgments rapidly increasing within 30 s of case onset. Particular moments appeared to generally be influential, but their degree of influence still varied. Correlations between the final assessment and (a) score assigned upon first adjustment of the scale, (b) upon last adjustment, and (c) the mean score, were r = 0.13, 0.32, and 0.57 for one video and r = 0.30, 0.50, and 0.52 for the other, indicating the degree to which overall impressions reflected accumulation of raters' idiosyncratic moment-by-moment observations. Our results demonstrated that variability in raters' impressions begins very early in a case presentation and is associated with different behaviours having different influence on different raters. More generally, this study outlines a novel methodology that offers a new path for gaining insight into factors influencing assessor judgments.

Real-time assessment of kidney allografts during HOPE using flavin mononucleotide (FMN) - a preclinical study.

Introduction: The gap between available donor grafts and patients on the waiting lists is constantly growing. This leads to an increased utilization of high-risk and therefore more vulnerable kidney grafts. The use of high-risk organs requires further optimization of machine preservation and assessment strategies before transplantation. Hypothermic machine perfusion (HMP) is the standard of care for kidneys originating from donation after circulatory death (DCD), whereas the evidence of HMP with additional oxygen (HOPE) is still very limited. Furthermore, an objective quality assessment of HMP-perfused kidneys is lacking. Recently, the release of mitochondria derived fragments, i.e., flavin mononucleotide (FMN) of complex I during machine liver perfusion was shown to be predictive for liver graft function before implantation. Therefore, the aim of this study was to evaluate, if FMN is useful also for assessment of kidney injury before use. Methods: A porcine perfusion model was used to investigate the feasibility of assessment of kidney grafts during hypothermic oxygenated perfusion (HOPE) with either 0, 30 or 60 minutes of warm ischemia. The model with warm ischemia times (WIT) of 30 min and 60 min, was used to mimic a clinically relevant scenario. A group with no warm ischemia time (0' WIT) served as control group. The groups underwent minimal static cold storage (SCS) of 2 h followed by 2 h of end-ischemic HOPE with repeated real-time FMN measurements. In a further step, these values were related to the release of damage-associated molecular patterns (DAMPs) and to the functionality of the respiratory chain, represented by the capacity of ATP production. Results: We demonstrate, first, feasibility of perfusate FMN measurements in perfused kidneys, and secondly its correlation with donor warm ischemia time. Accordingly, FMN measurement showed significantly higher release in the 60-minute WIT group (n = 4) compared to the 30-minute WIT (n = 4) and the control group (n = 4). FMN release correlated also with DAMP signaling, such as the release of 8-OHdG and HMGB1. Finally, ATP replenishment proved to be best in control kidneys, followed by kidneys with 30 min and then by kidneys with 60 min of WIT. Discussion: This study demonstrates the feasibility of FMN measurement in kidneys during HOPE. In addition, we show a correlation between FMN quantification and pre-existing kidney graft injury. Based on this, real-time FMN measurement during HOPE may be an objective assessment tool to accept high-risk kidneys for transplantation while minimizing post-transplant dysfunction, moving away from former "gut feeling" towards objective criteria in accepting marginal kidney grafts for transplantation. Graft evaluation based on these results may close the gap between available grafts and patients on the waiting lists by increasing utilization rates without significant impact for the recipients.

Real-time detection of imidacloprid residues in water using f-MWCNT/EDTA as energetically suitable electrode interface.

Real-time assessment of an active ingredient imidacloprid in the water matrix is critically momentous in monitoring the levels of pesticide contaminants in water bodies. Conventional approaches predominantly deal with the detection of imidacloprid, relying on the purified analytical grade compound. Herein, we report an organic/inorganic composite (f-MWCNT/EDTA) integrated electrochemical sensor for the real-time analysis of analytical grade imidacloprid and extended the performance evaluation in agriculture-purpose imidacloprid compound used commercially by farmers. The choice of the electrode interface significantly supports the electrocatalytic activity towards imidacloprid due to the presence of appropriate energy levels, which are favourable for charge transfer processes validated with Density Functional Theory (DFT) calculations. Further, the performance of the sensor was evaluated in the aquatic environment using river water samples procured from seven different sampling sites and in tap water. The organic/inorganic composite-based electrochemical sensor shows a detection limit of 3.1 × 10-3 pM and three significant wide linear concentration ranges of 0.001-0.05 nM, 0.001-0.04 µM, and 0.001-0.004 mM with apparent interferent resistance. This work paves the way for the real-time environmental monitoring and quantification of imidacloprid by utilizing the highly effective f-MWCNT/EDTA composite catalytic layer.

Real-time determination of water status upon simultaneous zebrafish exposure to sublethal concentrations of CuSO4.

Water pollution from commonly occurring contaminants (metals, xenobiotics, etc.) is a serious global problem. Copper is a commonly occurring water contaminant. A variety of physiological and biological methods have been developed to monitor water quality. The assessment of biological responses is an effective method for identifying the harmful effects of contaminants on ecosystems. Fish is a highly recommended animal model in water quality monitoring. Swimming consistency (firmness) and respiratory metabolism (oxygen consumption rate, carbon dioxide excretion rate and respiratory quotient) are essential for fish to maintain body homeostasis toward coping with environmental stress. We exposed zebrafish to different concentrations (Treatment I-0.1 mg/L and Treatment II-1.58 mg/L) of CuSO4. We have continuously quantified the strength of behavior (swimming consistency) and physiological (respiratory rates) biomarkers for ten days using an online monitoring system of swimming behavior and external respiration. Swimming consistency and respiratory rates of zebrafish (p<0.05) decreased in the CuSO4-treated groups compared to the control group. Avoidance behavior has led to an endpoint behavior at copperiedus. The time-delayed toxic effect has resulted in CuSO4 treatment groups. We checked for swimming consistency aberration on the artificial neural array, Self-organizing map (SOM). Circadian rhythms were influenced by prolonged exposure to CuSO4 toxicity. A concentration- and duration-dependent behavior anomaly was noted in this study. Swimming behavior and respiratory metabolism patterns are sensitive non-invasive stress biomarkers for water quality monitoring studies.

A descriptive assessment of a broad range of food-related parenting practices in a diverse cohort of parents of preschoolers using the novel Real-Time Parent Feeding Practices Survey.

BACKGROUND: Much of the research to-date on food parenting has evaluated typical use of various parent feeding practices via questionnaire. The Real-Time Parent Feeding Practices Measurement survey was developed for use within an Ecological Momentary Assessment (EMA) protocol to capture momentary use of parent feeding practices in real-time. METHODS: This manuscript describes the development of the EMA-based Real-Time Parent Feeding Practices survey and highlights initial descriptive data on the real-time use of 22 individual parent feeding practices (e.g., pressure-to-eat, guided choices, etc.) as reported via EMA by parents of preschool-aged children (n = 116) over a 10-day data collection time period. A total of 3382 eating occasions were reported, with an average of 29.2 reported eating occasions per participant. RESULTS: Results revealed that most participants used a variety of food-related parenting practices day-to-day that span four higher-order domains: structure, autonomy support, coercive control and indulgence. Supportive feeding practices, defined as those from the structure and autonomy support domains, were reported most frequently, with one or more structure behavior (e.g., specific mealtime rules/routines) was used at 88.9% of reported eating occasions and one or more autonomy support behavior (e.g., involvement of the child in meal preparation) was used at 87.3% of eating occasions. While unsupportive feeding practices, defined as practices from within the coercive control (e.g., pressure-to-eat) and indulgent (e.g., anticipatory catering) feeding domains, were reported less frequently, one or more behaviors from each of these domains were still reported at over 25% of all eating occasions. CONCLUSIONS: Results of the current study take a next step towards deepening our understanding of the use of a broad range of food-related parenting practices in real-time. Findings revealed that the vast majority of practices used by parents fall within the structure and autonomy support domains. However, most parents did not exclusively use supportive or unsupportive practices, rather they used a combination of food-related parenting practices across all domains. Future research should continue to explore a broad range of food-related parenting practices and seek to understand how parent approaches to feeding are associated with long-term child outcomes, including dietary intake, food preferences, and eating patterns.

Assessment of eco-toxic effects of commonly used water disinfectant on zebrafish (Danio rerio) swimming behaviour and recovery responses: an early-warning biomarker approach.

Eco-toxicity profiles for commonly used disinfectants were lacking. Available traditional toxicity techniques have some limitations (assessments and ethical issues). Behaviour toxicology is a promising research area towards early warning and non-invasive approaches. We studied the potential eco-toxic effects of sodium hypochlorite (NaOCl) on the swimming behaviour of zebrafish. Zebrafish were exposed to different concentrations (Treatment I, Treatment II, Treatment III, and Treatment IV) of NaOCl for 360 h. Recovery study (144 h) was conducted for NaOCl treatment groups. The swimming behaviour of zebrafish was quantified efficiently using an online monitoring system (OMS). OMS dataset was processed for determination of behavioural differences by MATLAB and SPSS. Compared to the control group, the swimming strength of zebrafish under NaOCl treatments declined significantly (p < 0.001). Avoidance behaviour has occurred on zebrafish under NaOCl exposure periods. Furthermore, NaOCl toxicity also adjusted circadian rhythms on zebrafish. Zebrafish swimming strength was significantly (p < 0.001) improved under-recovery periods. Moreover, normal diurnal patterns have occurred. NaOCl could cause behavioural abnormalities in non-target organisms. Continuous exposure to common disinfectants could cause external and internal stress on non-target organisms, resulting in behavioural changes and circadian rhythm adjustments. Continuous changes in behavioural and circadian rhythms might reduce organisms' fitness and adaptation capacity. This study highlights (1) the importance of computer-based toxicity assessments, and (2) swimming behaviour is an early warning biomarker for eco-toxicity studies.

Quality of Sarcoma Care: Longitudinal Real-Time Assessment and Evidence Analytics of Quality Indicators.

Sarcomas represent a large group of rare to very rare diseases, requiring complex management with a transdisciplinary approach. Overall progress has been hampered because of discipline, institution and network fragmentation, and there is no global data harmonization or quality standards. To report on and improve quality, a common definition of quality indicators (QIs) of sarcoma care as well as the capacity to assess longitudinal real-time data is required. An international advisory board of world-renowned sarcoma experts defined six categories of QIs, totaling more than 80 quality indicators. An interoperable (web-based) digital platform was then created combining the management of the weekly sarcoma board meeting with the sarcoma registry and incorporating patient-reported outcome measures (PROMs) into the routine follow-up care to assess the entire care cycle of the patient. The QIs were then programmed into the digital platform for real-time analysis and visualization. The definition of standardized QIs covering all physician- (diagnostics and therapeutics), patient- (PROMS/PREMS), and cost-based aspects in combination with their real-time assessment over the entire sarcoma care cycle can be realized. Standardized QIs as well as their real-time assessment and data visualization are critical to improving the quality of sarcoma care. By enabling predictive modelling and introducing VBHC, precision health care for a complex disease is on the horizon.

A real-time 31P-NMR-based approach for the assessment of glycerol kinase catalyzed monophosphorylations.

Phosphorous-NMR is scarcely employed to evaluate enzyme kinetics of kinase driven monophosphorylations, despite of being a powerful and reliable tool to undoubtedly detect the actual phosphoryl transfer to the targeted substrate. Another advantage is that an external supplementation source of the NMR active isotope is not required, since 31P is highly abundant in nature. Glycerol kinase (GlpK) from E. coli is an exemplary ATP-dependent kinase/phosphotransferase model to illustrate the value and usefulness of a 31P-NMR-based approach to assess the enzymatically driven monophosphorylation of glycerol. Moreover, the described approach offers an alternative to the indirect coupled glycerol kinase enzyme assays. Herein, we provided a real time 31P-NMR-based method customized for the direct assessment of the glycerol kinase enzyme activity.•Real-time detection for phosphoryl group dynamics in the GlpK driven reaction•Direct assessment of product formation (glycerol-monophosphate)•Parallel determination of cosubstrate (ATP) consumption and coproduct (ADP) generation•Method validation was performed via 31P-NMR for each phosphorylated molecule involved in the reaction in order to assist in the molecular assignments.

The after-effects of momentary suicidal ideation: A preliminary examination of emotion intensity changes following suicidal thoughts.

Research using ecological momentary assessments has highlighted the importance of negative emotions as predictors of day-to-day suicidal thoughts. Yet only one study has examined the real-time consequences of these thoughts. This preliminary investigation examined changes in emotion intensity following suicidal thoughts. It also explored associations between these changes and endorsement of suicide functions as an escape and/or as a solution, examined both as momentary thoughts and intractable beliefs about suicide. Thirty-nine community participants endorsing suicidal ideation were followed for two-weeks and completed multiple daily surveys related to suicidal thoughts, functions of suicide, and emotion intensity. Participants reported heightened emotion intensity immediately following a suicidal thought across six emotions, with delayed reductions in stress and anxiety following ideation onset. When assessed in the moment, suicide as a solution to a problem predicted increases in hopelessness, sadness, stress and general negative affect immediately following a thought, while suicide as an escape predicted increases in anger immediately after a thought. When measured as intractable beliefs, only stronger belief in suicide as a solution to a problem predicted delayed reductions in stress following ideation. Increased intensity of negative emotions immediately following suicidal ideation suggests a potential vicious cycle of heightened emotion intensity and suicidality.

Usability of a Mobile App for Real-Time Assessment of Fatigue and Related Symptoms in Patients With Multiple Sclerosis: Observational Study.

BACKGROUND: Although fatigue is one of the most debilitating symptoms in patients with multiple sclerosis (MS), its pathogenesis is not well understood. Neurogenic, inflammatory, endocrine, and metabolic mechanisms have been proposed. Taking into account the temporal dynamics and comorbid mood symptoms of fatigue may help differentiate fatigue phenotypes. These phenotypes may reflect different pathogeneses and may respond to different mechanism-specific treatments. Although several tools have been developed to assess various symptoms (including fatigue), monitor clinical status, or improve the perceived level of fatigue in patients with MS, options for a detailed, real-time assessment of MS-related fatigue and relevant comorbidities are still limited. OBJECTIVE: This study aims to present a novel mobile app specifically designed to differentiate fatigue phenotypes using circadian symptom monitoring and state-of-the-art characterization of MS-related fatigue and its related symptoms. We also aim to report the first findings regarding patient compliance and the relationship between compliance and patient characteristics, including MS disease severity. METHODS: After developing the app, we used it in a prospective study designed to investigate the brain magnetic resonance imaging correlates of MS-related fatigue. In total, 64 patients with MS were recruited into this study and asked to use the app over a 2-week period. The app features the following modules: Visual Analogue Scales (VASs) to assess circadian changes in fatigue, depression, anxiety, and pain; daily sleep diaries (SLDs) to assess sleep habits and quality; and 10 one-time questionnaires to assess fatigue, depression, anxiety, sleepiness, physical activity, and motivation, as well as several other one-time questionnaires that were created to assess those relevant aspects of fatigue that were not captured by existing fatigue questionnaires. The app prompts subjects to assess their symptoms multiple times a day and enables real-time symptom monitoring through a web-accessible portal. RESULTS: Of 64 patients, 56 (88%) used the app, of which 51 (91%) completed all one-time questionnaires and 47 (84%) completed all one-time questionnaires, VASs, and SLDs. Patients reported no issues with the usage of the app, and there were no technical issues with our web-based data collection system. The relapsing-remitting MS to secondary-progressive MS ratio was significantly higher in patients who completed all one-time questionnaires, VASs, and SLDs than in those who completed all one-time questionnaires but not all VASs and SLDs (P=.01). No other significant differences in demographics, fatigue, or disease severity were observed between the degrees of compliance. CONCLUSIONS: The app can be used with reasonable compliance across patients with relapsing-remitting and secondary-progressive MS irrespective of demographics, fatigue, or disease severity.

Effects of stomach content on the breath alcohol concentration-transdermal alcohol concentration relationship.

INTRODUCTION: Wearable devices that obtain transdermal alcohol concentration (TAC) could become valuable research tools for monitoring alcohol consumption levels in naturalistic environments if the TAC they produce could be converted into quantitatively-meaningful estimates of breath alcohol concentration (eBrAC). Our team has developed mathematical models to produce eBrAC from TAC, but it is not yet clear how a variety of factors affect the accuracy of the models. Stomach content is one factor that is known to affect breath alcohol concentration (BrAC), but its effect on the BrAC-TAC relationship has not yet been studied. METHODS: We examine the BrAC-TAC relationship by having two investigators participate in four laboratory drinking sessions with varied stomach content conditions: (i) no meal, (ii) half and (iii) full meal before drinking, and (iv) full meal after drinking. BrAC and TAC were obtained every 10 min over the BrAC curve. RESULTS: Eating before drinking lowered BrAC and TAC levels, with greater variability in TAC across person-device pairings, but the BrAC-TAC relationship was not consistently altered by stomach content. The mathematical model calibration parameters, fit indices, and eBrAC curves and summary score outputs did not consistently vary based on stomach content, indicating that our models were able to produce eBrAC from TAC with similar accuracy despite variations in the shape and magnitude of the BrAC curves under different conditions. DISCUSSION AND CONCLUSIONS: This study represents the first examination of how stomach content affects our ability to model estimates of BrAC from TAC and indicates it is not a major factor.

Real-Time Quantitative Assessment of Accuracy and Precision of Blood Volume Derived from DCE-MRI in Individual Patients During a Clinical Trial.

Accuracy and precision of quantitative imaging (QI) metrics should be assessed in real time in each patient during a clinical trial to support QI-based decision-making. We developed a framework for real-time quantitative assessment of QI metrics and evaluated accuracy and precision of dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI)-derived blood volume (BV) in a clinical trial for head and neck cancers. Patients underwent DCE-MRI before and after 2 weeks of radiation therapy (2wkRT). A mean as a reference value and a repeatability coefficient (RC) of BV values established from n patients in cerebellum volumes of interest (VOIs), which were normal and affected little by therapy, served as accuracy and precision measurements. The BV maps of a new patient were called accurate and precise if the values in cerebellum VOIs and the difference between the 2 scans agreed with the respective mean and RC with 95% confidence. The new data could be used to update reference values. Otherwise, the data were flagged for further evaluation before use in the trial. BV maps from 62 patients enrolled on the trial were evaluated. Mean BV values were 2.21 (±0.14) mL/100 g pre-RT and 2.22 (±0.17) mL/100 g at 2wkRT; relative RC was 15.9%. The BV maps from 3 patients were identified to be inaccurate and imprecise before use in the clinical trial. Our framework of real-time quantitative assessment of QI metrics during a clinical trial can be translated to different QI metrics and organ-sites for supporting QI-based decision-making that warrants success of a clinical trial.

Developing a smartphone-based ecological momentary assessment protocol to collect biopsychosocial data with community-dwelling late-middle-aged and older adults.

Although ecological momentary assessment (EMA) has been used in youth and adult populations, very few of the studies provided evidence of the feasibility and utility of smartphone-based EMA protocols to collect biopsychosocial data from aging populations. This study aimed to describe the design and implementation of a smartphone-based EMA protocol, and to evaluate the feasibility and utility of this EMA protocol among community-dwelling late-middle-aged and older Chinese. A sample of 78 community-dwelling Chinese aged between 50 and 70 years was trained to participate in a 1-week EMA data collection, during which each participant carried an Android smartphone loaded with a researcher-developed EMA application and a smartphone-based electrocardiogram (ECG) monitor to provide psychosocial (e.g., daily activities, social interaction, affect) data and ECG recordings six times daily. Adherence was demonstrated with a total response rate of 91.5% of all scheduled assessments (n = 3,822) and a moderately high level of perceived feasibility. Female participants reported higher compliance to the study and rated the overall experience as more pleasant and interesting than male participants. Our study provided the first evidence of the feasibility and utility of smartphone-based EMA protocols among late-middle-aged and older Chinese. Key areas for improvement in future design and implementation of mobile-based EMA include the incorporation of usable technology, adequate and training, and timely assistance.

Applying a novel population-based model approach to estimating breath alcohol concentration (BrAC) from transdermal alcohol concentration (TAC) biosensor data.

Alcohol biosensor devices have been developed to unobtrusively measure transdermal alcohol concentration (TAC), the amount of ethanol diffusing through the skin, in nearly continuous fashion in naturalistic settings. Because TAC data are affected by physiological and environmental factors that vary across individuals and drinking episodes, there is not an elementary formula to convert TAC into easily interpretable metrics such as blood and breath alcohol concentrations (BAC/BrAC). In our prior work, we addressed this conversion problem in a deterministic way by developing physics/physiological-based models to convert TAC to estimated BrAC (eBrAC), in which the model parameter values were individually determined for each person wearing a specific transdermal sensor using simultaneously collected TAC (via a biosensor) and BrAC (via a breath analyzer) during a calibration episode. We found these individualized parameter values produced relatively good eBrAC curves for subsequent drinking episodes, but our results also indicated the models were not fully capturing the dynamics of the system and variations across drinking episodes. Here, we report on a novel mathematical framework to improve our ability to model eBrAC from TAC data that uses aggregate population data instead of individualized calibration data to determine model parameter values via a random diffusion equation. We first provide the theoretical mathematical basis for our approach, and then test the efficacy of this method using datasets of contemporaneous BrAC/TAC measurements obtained by a) a single subject during multiple drinking episodes and b) multiple subjects during single drinking episodes. For each dataset, we used a set of drinking episodes to construct the population model, and then ran the model with another set of randomly selected test episodes. We compared raw TAC data to model-simulated TAC curve, breath analyzer BrAC data to model eBrAC curve with 75% credible bands, episode summary scores of peak BrAC, times of peak BrAC, and area under the drinking curve also with 75% credible intervals, and report the percent of the raw BrAC captured within the eBrAC curve credible bands. We also display results when stratifying the data based on the relationship between the raw BrAC and TAC data. Results indicate the population-based model is promising, with better fit within a single participant when stratifying episodes. This study provides initial proof-of-concept for constructing, fitting, and using a population-based model to obtain estimates and error bands for BrAC from TAC. The advancements in this study, including new applications of math, the development of a population-based model with error bars, and the production of corresponding MATLAB codes, represent a major step forward in our ability to produce quantitatively- and temporally-accurate estimates of BrAC from TAC biosensor data.

Procrastination, Flow, and Academic Performance in Real Time Using the Experience Sampling Method.

The authors' aim was to first provide an alternative methodology in the assessment of procrastination and flow that would not reply on retrospective or prospective self-reports. Using real-time assessment of both procrastination and flow, the authors investigated how these factors impact academic performance by using the Experience Sampling Method. They assessed flow by measuring student self-reported skill versus challenge, and procrastination by measuring the days to completion of an assignment. Procrastination and flow were measured for six days before a writing assignment due date while students (n = 14) were enrolled in a research methods course. Regardless of status of flow, both the nonflow and flow groups showed high levels of procrastination. Students who experienced flow as they worked on their paper, in real time, earned significantly higher grades (M = 3.05 ± 0.30: an average grade of B) as compared with the nonflow group (M = 1.16 ± 0.33: an average grade of D; p = .007). Additionally, students experiencing flow were more accurate in predicting their grade (difference scores, flow M = 0.12 ± 0.33 vs. nonflow M = 1.39 ± 0.29; p = .015). Students in the nonflow group were nearly a grade and a half off in their prediction of their grade on the paper. To the authors' knowledge, the study is the first to provide experimental evidence showing differences in academic performance between students experiencing flow and nonflow students.