238455 research outputs found
Sort by
Supplements to 2015 vaccine R&D Where are they now
No full textSupplementary material for the CCDR manuscript 'Tracking Canada’s 2015 vaccine research and development (R&D) priorities: Where are we a decade later?'
Includes 2 files:
1) Word document: Appendix Table A1 and Appendix
2) Excel file: Appendix Table A2 Details on High Priority Pathogens n=1
Developing and validating a measure of parental knowledge about early math
No full textDouglas, A -A., Msall, C., Rittle-Johnson, B. (2023). Developing and validating a measure of parental knowledge about early math. Frontiers in Psychology: Developmental Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1116883
This study was a side-effect of our piloting and developing our materials for the first part of the Heising Simons grant "Helping Parents..."
Parents’ knowledge about the math skills that most preschool-aged children can develop might be an important component of the Home Math Environment (HME) as it might shape their math beliefs and efforts to support their preschoolers’ math development. This study aimed to systematically develop measures of parents’ knowledge about two critical early math topics, numeracy, and patterning, across five studies conducted with a total of 616 U.S. parents of 3- to 5-year-olds (66% mothers, 54% sons, 73% White, 60% college-educated). Parents were recruited via CloudResearch or a university database. Study 1 focused on item generation to revise a previous measure to capture a wider set of children’s early math skills and analysis of the psychometric properties of the measure after it was completed by 161 parents via a survey. Study 2 included an analysis of a new sample of parents (n = 21) who responded to the measures twice across two weeks to explore test–retest reliability. The measures were iteratively revised, administered to new samples, and analyzed in Studies 3 (n = 45), 4 (n = 46), and 5 (n = 344). The measures demonstrated adequate internal consistency and validity (construct, convergent, and discriminant) in Study 5 such as being positively related to parents’ numeracy and patterning beliefs about their children. Overall, the newly developed measures satisfy standards for the development of an adequate measure and can be used to better understand what parents know about early math development and how this relates to the HME that they facilitate.
Data and Syntax are organized by the same labelling system of studies used in the paper. However, the studies are sometimes referred to by the team as:
Study 1 ("MTR Followup 2021")
Study 2 ("Info Session 2021 Pilot")
Study 3 & 4 ("FMS Pilot 1 and 2")
Study 5 ("FMS 2022 Study"
Sound of Surveillance: Speculative Futures for Voice Data in India
No full textVoice-activated technology embodies India's ongoing negotiation between the promise of empowerment and the spectre of surveillance. Building upon the paper's dialectic, progress versus risk, and the search for ethical synthesis, this analysis offers an integrated examination of the voice interaction data lifecycle, drawing in the realities of India's socio-cultural and regulatory frameworks. Moving well beyond traditional legal compliance, it proposes contextually attuned, speculative design interventions, and situates these within broader debates about universal versus contextual privacy models in the era of AI-driven voice ecosystems.
Based on a comprehensive survey of 500 respondents across urban and semi-urban India, this study reveals profound contradictions in user behavior: while 76% remain unaware of voiceprints as biometric identifiers, they continue engaging with voice technologies that unknowingly create these digital fingerprints. The research identifies four critical tension points,the unacknowledged biometric, the convenience paradox, the lingual gap, and task-specific utility versus broad integration,that illuminate the complex relationship between technological adoption and privacy awareness in contemporary India
FP5 — A Structural Resolution of the Navier–Stokes Existence and Smoothness Problem
No full textReframes the Navier–Stokes problem through observer–field coherence dynamics, demonstrating how turbulence emerges from systemic misalignment rather than mathematical incompleteness
Hubble Tension, Dark Matter, Dark Energy
No full textThis research integrates and accounts for the **Hubble tension**, **dark matter**, and **dark energy**, which have been treated as separate mysteries in modern cosmology, not as unrelated problems of "additional particles or additional fields," but as a single continuous phenomenon arising from the **response characteristics of the spatial medium itself**. This paper redefines the vacuum not as a passive background, but as an **active impedance medium** possessing a **6π⁵ information (phase-volume) standard** and a **137-layer impedance sealing structure (α⁻¹ ≈ 137)**. In this medium, the state variables—the **unit cohesion η** and **effective impedance Z_eff**—change according to external stimuli (mass distribution, energy density, dynamic pressure, etc.), and these changes manifest as **deterministic mode switching** under critical conditions
The Impact of Temporal Landmarks on Advertising Goal Orientation
No full textWe will conduct an online experiment to verify the moderating role of product type (utilitarian vs. hedonic) on the effect of temporal landmarks on consumers' preferences for advertising goal orientations
Concise Comprehensive Assessment of Psychiatric Disorder Risks Using Machine Learning
No full textImportance. The global prevalence of mental health problems demands a short but comprehensive screening and monitoring scale of major psychiatric disorders.
Objective. To use advanced machine learning techniques to develop a concise and comprehensive screening and monitoring tool for psychiatric disorder risks and evaluate its reliability and validity.
Design, setting, and participants. We obtained three datasets of outpatient participants at a psychiatric hospital in China who completed the 567-item Minnesota Multiphasic Personality Inventory (MMPI). We used the first dataset (N=6,704) for model training, testing, and internal validation to obtain a shortened version (100 items) using the stacked generalization ensemble of several machine-learning techniques. We validated the shortened scale against two prospective pristine datasets (N=928, unpreregistered; N=484, preregistered).
Main outcomes and measures. The Area Under the Curve of the Receiver Operating Characteristic (AUC of ROC) to measure validity and Cronbach’s Alpha to measure reliability.
Results. We reduced the length of the MMPI-2 by over 82%, from 567 to 100 items. The shortened scale can measure ten target conditions with at least 85% AUC and a Cronbach’s Alpha 0.97. We implemented the shortened scaleinto a mobile-friendly web application.
Conclusions and relevance. An advanced machine-learning approach can significantly reduce a long scale to a shortened one while retaining high validity and reliability. This shortened scale can not only help alleviate pressure on healthcare systems burdened by the increased number of patients with mental health concerns but also allows for regular health monitoring or screening by individuals