Relevance of Objective Measures in Psychiatric Disorders—Rest-Activity Rhythm and Psychophysiological Measures

Abstract Purpose of Review We present a review of recent methods of objective measurement in psychiatry and psychology with a focus on home monitoring and its utility in guiding treatment. Recent Findings For individualized diagnostics and treatment of insomnia, actigraphy can generate clinically useful graphical presentations of sleep timing and patterns. Psychophysiological measures may complement psychometrics by tracking parallel changes in physiological responses and emotional functioning, especially during therapy for trauma symptoms and emotion regulation. It seems that rather than defining universal cut-offs, an individualised range of variability could characterize treatment response. Summary Wearable actigraphy and psychophysiological sensors are promising devices to provide biofeedback and guide treatment. Use of feasible and reliable technology during experimental and clinical procedures may necessitate defining healthy and abnormal responses in different populations and pathological states. We present a “call for action” towards further collaborative work to enable large scale use of objective measures.

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Media capture in the era of megaleaks

Journalism ◽

10.1177/1464884917725166 ◽

2017 ◽

Vol 19 (8) ◽

pp. 1182-1195 ◽

Cited By ~ 2

Author(s):

Angela Woodall

Keyword(s):

Large Scale ◽

Collaborative Work ◽

Second Look ◽

Main Effect ◽

The Media ◽

Official Sources ◽

Media Capture

Much has been written about the potential of large-scale digital disclosures, or ‘megaleaks’, to transform journalistic coverage of high-value news. This analysis takes a second look at the phenomenon by analyzing three of the best-known megaleaks to date: those disclosed by Chelsea Manning, Edward Snowden, and John Doe, the source of the Panama Papers. To what extent did these large-scale disclosures disrupt the media capture that distorts or limits coverage by an autonomous press? A study of circumstances surrounding these three megaleaks suggests that their main effect was encouraging a culture of collaborative work that favors independence from official sources.

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Covidom, a Telesurveillance Solution for Home Monitoring Patients With COVID-19 (Preprint)

10.2196/preprints.20748 ◽

2020 ◽

Author(s):

Youri Yordanov ◽

Agnes Dechartres ◽

Xavier Lescure ◽

Caroline Apra ◽

Pascaline Villie ◽

...

Keyword(s):

Health Care Professionals ◽

Web Application ◽

Large Scale ◽

Home Monitoring ◽

Control Center ◽

Regional Control ◽

Global Pandemic ◽

Number Of Patients ◽

Paris Area ◽

Innovative Solution

UNSTRUCTURED In a matter of months, COVID-19 has escalated from a cluster of cases in Wuhan, China, to a global pandemic. As the number of patients with COVID-19 grew, solutions for the home monitoring of infected patients became critical. This viewpoint presents a telesurveillance solution—Covidom—deployed in the greater Paris area to monitor patients with COVID-19 in their homes. The system was rapidly developed and is being used on a large scale with more than 65,000 registered patients to date. The Covidom solution combines an easy-to-use and free web application for patients (through which patients fill out short questionnaires on their health status) with a regional control center that monitors and manages alerts (triggered by questionnaire responses) from patients whose health may be deteriorating. This innovative solution could alleviate the burden of health care professionals and systems while allowing for rapid response when patients trigger an alert.

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Architecting for Connected Healthcare

Enterprise Architecture for Connected E-Government ◽

10.4018/978-1-4666-1824-4.ch013 ◽

2012 ◽

pp. 306-325

Author(s):

Torben Tambo ◽

Nikolai Hoffmann-Petersen ◽

Karsten Bejder

Keyword(s):

Healthcare System ◽

Change Process ◽

Large Scale ◽

Enterprise Architecture ◽

Self Care ◽

Home Monitoring ◽

Technological Changes ◽

The Everyday ◽

Scale Population ◽

Hospital Stays

The healthcare system is in many countries operated by the governments, and interaction with the healthcare system is one of the most frequent interactions between citizen and government. Demographic, medical, and technological changes are likely to bring new aspects of connectedness into the everyday life of people and place healthcare and homecare professionals in new roles. A transformation is taking place where hospital best practices are constantly reducing patient’s in-hospital stays to alternative, less-costly care—notably at home. Telemedicine, telehealth, eHealth, home monitoring, and self-care are essential aspects of this transformation. Many issues are influencing this transformation, and new barriers are showing up where others are removed. A broadly oriented enterprise architecture effort is presented for the underpinning of the change process. The architectural approach encompasses views of the citizen, the healthcare system, the information infrastructure, and the citizen-oriented technology. A case of telemonitoring and self-care is presented using mobile hypertension measurement on a large-scale population cohort. Evaluation of the acceptance and success of the solutions is done within a combined understanding including technology, economy, organization, and culture.

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Understanding Loan Aversion in Education

AERA Open ◽

10.1177/2332858416683649 ◽

2017 ◽

Vol 3 (1) ◽

pp. 233285841668364 ◽

Cited By ~ 20

Author(s):

Angela Boatman ◽

Brent J. Evans ◽

Adela Soliz

Keyword(s):

United States ◽

College Students ◽

High School ◽

Community College ◽

College Women ◽

Large Scale ◽

College Education ◽

The United States ◽

Quantitative Evidence ◽

Different Populations

Although prior research has suggested that some students may be averse to taking out loans to finance their college education, there is little empirical evidence showing the extent to which loan aversion exists or how it affects different populations of students. This study provides the first large-scale quantitative evidence of levels of loan aversion in the United States. Using survey data collected on more than 6,000 individuals, we examine the frequency of loan aversion in three distinct populations. Depending on the measure, between 20 and 40% of high school seniors exhibit loan aversion with lower rates among community college students and adults not in college. Women are less likely to express loan-averse attitudes than men, and Hispanic respondents are more likely to be loan averse than White respondents.

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The JGrass-NewAge system for forecasting and managing the hydrological budgets at the basin scale: models of flow generation and propagation/routing

Geoscientific Model Development ◽

10.5194/gmd-4-943-2011 ◽

2011 ◽

Vol 4 (4) ◽

pp. 943-955 ◽

Cited By ~ 30

Author(s):

G. Formetta ◽

R. Mantilla ◽

S. Franceschi ◽

A. Antonello ◽

R. Rigon

Keyword(s):

Large Scale ◽

Goodness Of Fit ◽

Hydrological Modeling ◽

Collaborative Work ◽

Flow Equation ◽

River Network ◽

Predictive Capacity ◽

Flow Generation ◽

Basin Scale ◽

Runoff Production

Abstract. This paper presents a discussion of the predictive capacity of the implementation of the semi-distributed hydrological modeling system JGrass-NewAge. This model focuses on the hydrological budgets of medium scale to large scale basins as the product of the processes at the hillslope scale with the interplay of the river network. The part of the modeling system presented here deals with the: (i) estimation of the space-time structure of precipitation, (ii) estimation of runoff production; (iii) aggregation and propagation of flows in channel; (v) estimation of evapotranspiration; (vi) automatic calibration of the discharge with the method of particle swarming. The system is based on a hillslope-link geometrical partition of the landscape, combining raster and vectorial treatment of hillslope data with vector based tracking of flow in channels. Measured precipitation are spatially interpolated with the use of kriging. Runoff production at each channel link is estimated through a peculiar application of the Hymod model. Routing in channels uses an integrated flow equation and produces discharges at any link end, for any link in the river network. Evapotranspiration is estimated with an implementation of the Priestley-Taylor equation. The model system assembly is calibrated using the particle swarming algorithm. A two year simulation of hourly discharge of the Little Washita (OK, USA) basin is presented and discussed with the support of some classical indices of goodness of fit, and analysis of the residuals. A novelty with respect to traditional hydrological modeling is that each of the elements above, including the preprocessing and the analysis tools, is implemented as a software component, built upon Object Modelling System v3 and jgrasstools prescriptions, that can be cleanly switched in and out at run-time, rather than at compiling time. The possibility of creating different modeling products by the connection of modules with or without the calibration tool, as for instance the case of the present modeling chain, reduces redundancy in programming, promotes collaborative work, enhances the productivity of researchers, and facilitates the search for the optimal modeling solution.

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Covidom, a Telesurveillance Solution for Home Monitoring Patients With COVID-19

Journal of Medical Internet Research ◽

10.2196/20748 ◽

2020 ◽

Vol 22 (10) ◽

pp. e20748

Author(s):

Youri Yordanov ◽

Agnes Dechartres ◽

Xavier Lescure ◽

Caroline Apra ◽

Pascaline Villie ◽

...

Keyword(s):

Health Care Professionals ◽

Web Application ◽

Large Scale ◽

Home Monitoring ◽

Control Center ◽

Regional Control ◽

Global Pandemic ◽

Number Of Patients ◽

Paris Area ◽

Innovative Solution

In a matter of months, COVID-19 has escalated from a cluster of cases in Wuhan, China, to a global pandemic. As the number of patients with COVID-19 grew, solutions for the home monitoring of infected patients became critical. This viewpoint presents a telesurveillance solution—Covidom—deployed in the greater Paris area to monitor patients with COVID-19 in their homes. The system was rapidly developed and is being used on a large scale with more than 65,000 registered patients to date. The Covidom solution combines an easy-to-use and free web application for patients (through which patients fill out short questionnaires on their health status) with a regional control center that monitors and manages alerts (triggered by questionnaire responses) from patients whose health may be deteriorating. This innovative solution could alleviate the burden of health care professionals and systems while allowing for rapid response when patients trigger an alert.

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Trialling the use of Google Apps together with online marking to enhance collaborative learning and provide effective feedback

F1000Research ◽

10.12688/f1000research.6520.2 ◽

2017 ◽

Vol 4 ◽

pp. 177

Author(s):

Nicky J. D. Slee ◽

Marty H. Jacobs

Keyword(s):

Large Scale ◽

Peer Assessment ◽

Collaborative Work ◽

Virtual Learning Environment ◽

Data Sets ◽

Ecological Data ◽

Data Set ◽

Assessment Task ◽

Google Drive ◽

Google Apps

This paper describes a new approach to an ecology practical in which 76 Level 4 students were divided into four groups (n = 20 +/-2) to collect data. Each group studied a different habitat and was further divided into seven subgroups (n = 2 or 3) to collect field data. Each of the four groups collaborated through Google Drive on descriptions and images of the habitat site, and also collaborated at the subgroup level on their own habitat data. The four groups then shared habitat descriptions with the aim to provide enough information to enable everyone to understand the entire data set. The three-stage assignment was assessed and feedback issued at group and individual level via the University’s online submission service (FASER), with some additional feedback given via Moodle, the University’s Virtual Learning Environment. Two separate submissions were made to FASER, the first was the group and subgroup work (stage 1), and the second included the peer assessment task (stage 2) and the individual evaluation of the habitats (stage 3). Feedback was given after the second submission had been uploaded to FASER and again when the assessment for the second submission was complete. The group and subgroup data sets were provided to all students via Moodle, so that individuals could carry out their own analysis of all four habitats. The use of Google Drive and Google Apps helped to improve the digital literacy of the staff and students involved. All three stages of the assignment were successful; over 85% of students passed the first two stages, and 82.9% passed stage 3. The collaborative work enabled students to produce high quality descriptive ecology documents valuable for the subsequent stages of the assignment. The peer assessment encouraged students to gain information on expected Undergraduate Minimum Standards, and gave students the opportunity to study multiple habitats. The final stage was open ended and challenged students to make sense of large ecological data sets. There was a positive correlation between levels of success at stages 1 and 3 for students who achieved less than 65% for the independent work, i.e. they benefited from carrying out group work. This collaborative, three-stage approach is recommended especially as it helps lower ability students gain subject knowledge and improve their presentation skills. However, some modifications are recommended: 1) simplifying the sample and data collection, and 2) providing more guidance for the peer assessment task and individual analysis. Learner autonomy enabled self-directed learning to take place and enriched large scale teaching as it encouraged student-student interaction. Significant differences between gender and ability are discussed.

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Gender and Racial/Ethnic Disparities in Undergraduate and Graduate Students’ Mental Health and Treatment Use amid the COVID-19 Pandemic

10.31234/osf.io/qhy5j ◽

2021 ◽

Author(s):

Sin-Ying Lin ◽

Jessica L. Schleider ◽

Brady Nelson ◽

Lauren Richmond ◽

Nicholas R Eaton

Keyword(s):

Mental Health ◽

Graduate Students ◽

Large Scale ◽

Online Survey ◽

Service Use ◽

Ethnic Disparities ◽

Problem Severity ◽

Treatment Use ◽

Internalizing Problem ◽

Racial Ethnic

Objective: To investigate gender and racial/ethnic disparities in mental health and treatment use in college and graduate students amid the COVID-19 pandemic.Method: Based on a large-scale online survey (N = 1,415) administered during the weeks following a pandemic-related university-wide campus closure in March 2020, we examined gender and racial disparities in current internalizing severity and treatment use with t-tests and logistic regression models.Results: Specifically, we found that students with marginalized gender (e.g., woman [p < .001], non-binary gender [p < .001]) or Hispanic/Latinx identity (p = .002) reported higher levels of internalizing problem severity compared to their privileged counterparts (e.g., man, non- Hispanic/Latinx White). Regarding treatment use, Asian (p < .001) and multiracial students (p = .002) reported lower treatment use after controlling for internalizing problem severity. Internalizing severity was generally associated with higher treatment use (logit = 0.53, p = .001), indicating a match of objective needs with service use. However, this relationship was offset by a negative interaction between internalizing problem severity and Asian (logit = -0.49, p < .001) or Black identity (logit = -0.57, p = .03) in predicting treatment use.Conclusion: The findings revealed unique mental health challenges faced by different demographic groups and served as a call that specific actions to enhance mental health equity, such as continued mental health support for students with marginalized gender identities, additional COVID-related mental and practical support for Hispanic/Latinx students, and promotion of mental health awareness and trust in Asian/Black students, are desperately needed.

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The iconicity toolbox: empirical approaches to measuring iconicity

Language and Cognition ◽

10.1017/langcog.2019.14 ◽

2019 ◽

Vol 11 (02) ◽

pp. 188-207 ◽

Cited By ~ 4

Author(s):

YASAMIN MOTAMEDI ◽

HANNAH LITTLE ◽

ALAN NIELSEN ◽

JUSTIN SULIK

Keyword(s):

Large Scale ◽

Empirical Work ◽

Objective Measures ◽

Empirical Methods ◽

Testing Methods ◽

Cognitive Sciences ◽

Empirical Approaches

abstractGrowing evidence from across the cognitive sciences indicates that iconicity plays an important role in a number of fundamental language processes, spanning learning, comprehension, and online use. One benefit of this recent upsurge in empirical work is the diversification of methods available for measuring iconicity. In this paper, we provide an overview of methods in the form of a ‘toolbox’. We lay out empirical methods for measuring iconicity at a behavioural level, in the perception, production, and comprehension of iconic forms. We also discuss large-scale studies that look at iconicity on a system-wide level, based on objective measures of similarity between signals and meanings. We give a detailed overview of how different measures of iconicity can better address specific hypotheses, providing greater clarity when choosing testing methods.

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Self-Concept Predicts Academic Achievement across Levels of the Achievement Distribution: Domain-Specificity for Math and Reading

10.31234/osf.io/zsq39 ◽

2018 ◽

Author(s):

Maria Ines Susperreguy ◽

Pamela Davis-Kean ◽

Kathryn Duckworth ◽

Meichu Chen

Keyword(s):

Large Scale ◽

Demographic Variables ◽

Self Concept ◽

Data Sets ◽

Regression Analyses ◽

Achievement Data ◽

Different Populations ◽

Robust Evidence ◽

Different Levels

This study examines whether self-concept of ability in math and reading predicts later math and reading attainment across different levels of achievement. Data from three large-scale longitudinal data sets, the ALSPAC, NICHD-SECCYD, and PSID-CDS, were used to answer this question by employing quantile regression analyses. After controlling for demographic variables, child characteristics, and early ability, the findings indicate that self-concept of ability in math and reading predicts later achievement in each respective domain across all quantile levels of achievement. These results were replicated across the three data sets representing different populations and provide robust evidence for the role of self-concept of ability in understanding achievement from early childhood to adolescence across the spectrum of performance (low to high).

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