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Extant models of health behaviour change often overlook stages in which individuals decide to partake in interventions. The current study aimed to identify behavioural and psychological factors that could capture a person's readiness to change a health behaviour and whether these could predict progression through stages of commitment. Rather than explicitly advertising a health behaviour intervention, we invited individuals to partake in a general health behaviour survey using a paid advertising campaign on Facebook (Phase 1).

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Purpose: Prior work estimating sound exposure dose from earphone use has typically measured earphone use time with retrospective questionnaires or device-based tracking, both of which have limitations. This research note presents an exploratory analysis of sound exposure dose from earphone use among college-aged adults using real-ear measures to estimate exposure level and ecological momentary assessment (EMA) to estimate use time.

Method: Earphone levels were measured at the ear drum of 53 college students using their own devices, earphones, and preferred music and speech stimuli at their normal listening volume.

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According to the Projective Consciousness Model (PCM), in human spatial awareness, 3-dimensional projective geometry structures information integration and action planning through perspective taking within an internal representation space. The way different perspectives are related to and transform a world model defines a specific perception and imagination scheme. In mathematics, such a collection of transformations corresponds to a 'group', whose 'actions' characterize the geometry of a space.

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Introduction: Artificial Intelligence (AI) is increasingly being integrated into healthcare, particularly through predictive analytics that can enhance patient care and operational efficiency. Nursing leaders play a crucial role in the successful adoption of these technologies.

Aim: This study aims to assess the readiness of nursing leaders for AI integration and evaluate their perceptions of the benefits of AI-driven predictive analytics in healthcare.

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To evaluate the feasibility of using the National Patient-Centered Clinical Research Network (PCORnet) as a source of electronic health record (EHR) data for cleft outcomes research. Exploratory retrospective analysis of multi-year, administrative and clinical, structured data stored in PCORnet. Academic institution with an ACPA-approved cleft and craniofacial team.

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