Publications by authors named "Valerie Shalin"

The lack of explainability in using relevant clinical knowledge hinders the adoption of artificial intelligence-powered analysis of unstructured clinical dialogue. A wealth of relevant, untapped Mental Health (MH) data is available in online communities, providing the opportunity to address the explainability problem with substantial potential impact as a screening tool for both online and offline applications. Inspired by how clinicians rely on their expertise when interacting with patients, we leverage relevant clinical knowledge to classify and explain depression-related data, reducing manual review time and engendering trust.

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Background: In clinical diagnostic interviews, mental health professionals (MHPs) implement a care practice that involves asking open questions (eg, "What do you want from your life?" "What have you tried before to bring change in your life?") while listening empathetically to patients. During these interviews, MHPs attempted to build a trusting human-centered relationship while collecting data necessary for professional medical and psychiatric care. Often, because of the social stigma of mental health disorders, patient discomfort in discussing their presenting problem may add additional complexities and nuances to the language they use, that is, hidden signals among noisy content.

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Background: Hand motion analysis by video recording during surgery has potential for evaluation of surgical performance. The aim was to identify how technical skill during open surgery can be measured unobtrusively by video recording during a surgical procedure. We hypothesized that procedural-step timing, hand movements, instrument use and Shannon entropy differ with expertise and training and are concordant with a performance-based validated individual procedure score.

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THIS ARTICLE USES WORDS OR LANGUAGE THAT IS CONSIDERED PROFANE, VULGAR, OR OFFENSIVE BY SOME READERS. The presence of a significant amount of harassment in user-generated content and its negative impact calls for robust automatic detection approaches. This requires the identification of different types of harassment.

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Background: Long-term retention of trauma procedural core-competency skills and need for re-training after a 1-day cadaver-based course remains unknown. We measured and compared technical skills for trauma core competencies at mean 14 months (38 residents), 30 months (35 practicing surgeons), and 46 months (10 experts) after training to determine if skill degradation occurs with time. Technical performance during extremity vascular exposures and lower-extremity fasciotomy in fresh cadavers measured by validated individual procedure score (IPS) was the primary outcome.

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Objectives: Surgical residents express confidence in performing specific vascular exposures before training, but such self-reported confidence did not correlate with co-located evaluator ratings. This study reports residents' self-confidence evaluated before and after Advanced Surgical Skills for Exposure in Trauma (ASSET) cadaver-based training, and 12-18 mo later. We hypothesize that residents will better judge their own skill after ASSET than before when compared with evaluator ratings.

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Background: Work-hour restrictions have reduced operative experience for residents. The Advanced Surgical Skills for Exposure in Trauma (ASSET) course fills this training gap. Cadaver use has limitations including cost and availability.

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Objective This paper identifies general properties of language style in social media to help identify areas of need in disasters. Background In the search for metrics of need in social media data, much of the existing literature ignores processes of language usage. Psychological concepts, such as narrative breach, Gricean maxims, and lexical marking in cognition, may assist the recovery of disaster-relevant metrics from altered patterns of word prevalence.

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Despite increasing prominence, little is known about the cognitive processes underlying shared decision making. To investigate these processes, we conceptualize shared decision making as a form of distributed cognition. We introduce a Decision Space Model to identify physical and social influences on decision making.

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Objective: Test with an individual procedure score (IPS) to assess whether an unpreserved cadaver trauma training course, including upper and lower limb vascular exposure, improves correct identification of surgical landmarks, underlying anatomy, and shortens time to vascular control.

Design: Prospective study of performance of 3 vascular exposure and control procedures (axillary, brachial, and femoral arteries) using IPS metrics by 2 colocated and trained evaluators before and after training with the Advanced Surgical Skills Exposure for Trauma (ASSET) course. IPS, including identification of anatomical landmarks, incisions, underlying structures, and time to completion of each procedure was compared before and after training using repeated measurement models.

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Background: Maintaining trauma-specific surgical skills is an ongoing challenge for surgical training programs. An objective assessment of surgical skills is needed. We hypothesized that a validated surgical performance assessment tool could detect differences following a training intervention.

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Purpose: Electronic medical records (EMR) promise potential benefits for the practice of medical care. However, individual technologies such as EMR must interact with the work system as a whole - including people, technology and work practices - to enable or hinder the coordination of dynamic work demands. Based on this extended perspective, we address in this paper how support technologies (should) impact the coordination of work across multiple agents, controlling a dynamic domain with multiple, interacting processes.

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Objective: To assess the relationship between decision making and successful diabetes self-management.

Background: Patients with type II diabetes make routine but critical self-management decisions.

Method: We conducted cognitive task analysis interviews with 18 patients to examine problem detection, functional relationships, problem-solving strategies, and types of knowledge used to make self-management decisions.

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Calls for an alternative conceptualization of cognition for applied concerns retain the core commitment of the basic research community to abstract cognition detached from a physical environment. The present paper attempts to break out of the dominant, narrow view of cognition and cognitive domains, with a cognitive analysis of digging ditches for the utility industry. To illustrate knowledge-based cognition in manual labour excerpts are presented from the journal entries of a moderately experienced student working a summer job, organized with a representation that distinguishes between the goals and methods of work.

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