Better alignment between circadian preference and sleep and work timings during COVID-19 did not benefit work engagement at home.

Modern society is structured around early routines which cause evening types to suffer from health and performance detriments associated with sleep times being misaligned with biological needs (circadian preference). Given that COVID-19 lockdowns were less constrained by social schedules, the current study explores whether temporal behaviours became better aligned with biological needs, and whether these changes benefited work engagement. 406 UK participants reported circadian preference and pre-lockdown and lockdown sleep times, work times, and work engagement. Results found that sleep health improved under lockdown measures in terms of increased sleep duration and reduced social jetlag, and sleep and work times became better aligned with circadian preferences. The most circadian-misaligned participants - students and young adults - exhibited the largest changes to sleep and work habits. However, work engagement decreased more in participants with improved social jetlag and delayed work habits, which is surprising given that these temporal changes reflect improved circadian alignment. We discuss potential moderators including poor sleep quality, non-engaging work-from-home environments, and mental health. These findings have implications for encouraging flexible educational and employment schedules post-COVID-19 to satisfy the common drive to improve circadian alignment, but future work must determine the moderating factors that impair work engagement during remote work.

Doctor, why does my thumb hurt?

BACKGROUND: Stable and pain-free thumb function and pinch is vital for personal care, work, domestic and leisure activities. OBJECTIVE: The aim of this article is to increase awareness of timely referral to hand therapists for three common thumb conditions. This article covers three thumb conditions: acute trauma (ulnar collateral ligament), repetitive trauma (De Quervain's tendinopathy) and chronic progression (basal thumb osteoarthritis). DISCUSSION: The Australian Hand Therapy Association awards accreditation to occupational therapists and physiotherapists with specialist knowledge of the upper limb. Understanding the role of hand therapy in clinical testing, custom orthoses and exercise prescription benefits general practitioners, as timely referrals yield optimal functional outcomes for patients.

Sleep deprivation and memory: Meta-analytic reviews of studies on sleep deprivation before and after learning.

Research suggests that sleep deprivation both before and after encoding has a detrimental effect on memory for newly learned material. However, there is as yet no quantitative analyses of the size of these effects. We conducted two meta-analyses of studies published between 1970 and 2020 that investigated effects of total, acute sleep deprivation on memory (i.e., at least one full night of sleep deprivation): one for deprivation occurring before learning and one for deprivation occurring after learning. The impact of sleep deprivation after learning on memory was associated with Hedges' g = 0.277, 95% CI [0.177, 0.377]. Whether testing took place immediately after deprivation or after recovery sleep moderated the effect, with significantly larger effects observed in immediate tests. Procedural memory tasks also showed significantly larger effects than declarative memory tasks. The impact of sleep deprivation before learning was associated with Hedges' g = 0.621, 95% CI [0.473, 0.769]. Egger's tests for funnel plot asymmetry suggested significant publication bias in both meta-analyses. Statistical power was very low in most of the analyzed studies. Highly powered, preregistered replications are needed to estimate the underlying effect sizes more precisely. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Generalisation in language learning can withstand total sleep deprivation.

Research suggests that sleep plays a vital role in memory. We tested the impact of total sleep deprivation on adults' memory for a newly learned writing system and on their ability to generalise this knowledge to read untrained novel words. We trained participants to read fictitious words printed in a novel artificial orthography, while depriving them of sleep the night after learning (Experiment 1) or the night before learning (Experiment 2). Following two nights of recovery sleep, and again 10 days later, participants were tested on trained words and untrained words, and performance was compared to control groups who had not undergone sleep deprivation. Participants showed a high degree of accuracy in learning the trained words and in generalising their knowledge to untrained words. There was little evidence of impact of sleep deprivation on memory or generalisation. These data support emerging theories which suggest sleep-associated memory consolidation can be accelerated or entirely bypassed under certain conditions, and that such conditions also facilitate generalisation.

A review of neurobiological factors underlying the selective enhancement of memory at encoding, consolidation, and retrieval.

How is the strength of a memory determined? This review discusses three main factors that contribute to memory enhancement - 1) emotion, 2) targeted memory reactivation, and 3) neural reinstatement. Whilst the mechanisms through which memories become enhanced vary, this review demonstrates that activation of the basolateral amygdala and hippocampal formation are crucial for facilitating encoding, consolidation, and retrieval. Here we suggest methodological factors to consider in future studies, and discuss several unanswered questions that should be pursued in order to clarify selective memory enhancement.

When can I go home? A prospective case control study to improve communication with patients regarding their diagnosis, treatment plan and likely discharge date.

AIM: This study aimed to improve our ability to communicate with patients with regard to four key issues. Their diagnosis, treatment plan, clinical criteria for discharge and estimated discharge date. METHODS: This was a prospective case control study. It involved 200 general medical patients admitted to Christchurch Public Hospital. Each day there were two general medical admitting teams. One team formed the control group and the other team the intervention group. The 100 patients in the control group had their consultant ward round as normal. The 100 patients in the intervention group had a consultant ward round and were provided with additional written information answering the following four points: (1) their diagnosis (2) management plan for the day (3) clinical criteria for discharge and (4) estimated date of discharge. This was a laminated sheet that remained attached to their bedside locker. At four or more hours after the ward round every new patient would undergo a questionnaire based interview addressing their ability to correctly answer the points listed above. A comparison was then made between the intervention and control groups. A subgroup (n=30) were selected to obtain feedback on the initiative. RESULTS: 90% of respondents from the intervention group knew their diagnosis versus 59% of the control group (p<0.01). 76% knew their treatment plan for the day versus 41% (p<0.01). 76% knew some of the clinical criteria for safe discharge versus 25% (p<0.01) and 83% of the intervention group knew their estimated discharge date versus 52% of the control group (p<0.01). The median age of the patients in the intervention group was 78 years of age and 74 for the control group (p>0.05). Of those that gave feedback 70% believed the intervention was helpful in helping them understand their diagnosis and 70% believed knowing their likely discharge date was useful. CONCLUSION: The use of a card with written information for the patient regarding their diagnosis, treatment plan, clinical criteria for safe discharge and estimated discharge date at the bedside helped improve the patients understanding of their care and aided effective communication.

Targeting Staphylococcus aureus quorum sensing with nonpeptidic small molecule inhibitors.

A series of 3-oxo-C12-HSL, tetramic acid, and tetronic acid analogues were synthesized to gain insights into the structural requirements for quorum sensing inhibition in Staphylococcus aureus. Compounds active against agr were noncompetitive inhibitors of the autoinducing peptide (AIP) activated AgrC receptor, by altering the activation efficacy of the cognate AIP-1. They appeared to act as negative allosteric modulators and are exemplified by 3-tetradecanoyltetronic acid 17, which reduced nasal cell colonization and arthritis in a murine infection model.

METACOGNITIVE SCAFFOLDS IMPROVE SELF-JUDGMENTS OF ACCURACY IN A MEDICAL INTELLIGENT TUTORING SYSTEM.

In this study, we examined the effect of two metacognitive scaffolds on the accuracy of confidence judgments made while diagnosing dermatopathology slides in SlideTutor. Thirty-one (N = 31) first- to fourth-year pathology and dermatology residents were randomly assigned to one of the two scaffolding conditions. The cases used in this study were selected from the domain of Nodular and Diffuse Dermatitides. Both groups worked with a version of SlideTutor that provided immediate feedback on their actions for two hours before proceeding to solve cases in either the Considering Alternatives or Playback condition. No immediate feedback was provided on actions performed by participants in the scaffolding mode. Measurements included learning gains (pre-test and post-test), as well as metacognitive performance, including Goodman-Kruskal Gamma correlation, bias, and discrimination. Results showed that participants in both conditions improved significantly in terms of their diagnostic scores from pre-test to post-test. More importantly, participants in the Considering Alternatives condition outperformed those in the Playback condition in the accuracy of their confidence judgments and the discrimination of the correctness of their assertions while solving cases. The results suggested that presenting participants with their diagnostic decision paths and highlighting correct and incorrect paths helps them to become more metacognitively accurate in their confidence judgments.

Design of electronic medical record user interfaces: a matrix-based method for improving usability.

This study examines a new approach of using the Design Structure Matrix (DSM) modeling technique to improve the design of Electronic Medical Record (EMR) user interfaces. The usability of an EMR medication dosage calculator used for placing orders in an academic hospital setting was investigated. The proposed method captures and analyzes the interactions between user interface elements of the EMR system and groups elements based on information exchange, spatial adjacency, and similarity to improve screen density and time-on-task. Medication dose adjustment task time was recorded for the existing and new designs using a cognitive simulation model that predicts user performance. We estimate that the design improvement could reduce time-on-task by saving an average of 21 hours of hospital physicians' time over the course of a month. The study suggests that the application of DSM can improve the usability of an EMR user interface.

Comparative effectiveness research designs: an analysis of terms and coverage in Medical Subject Headings (MeSH) and Emtree.

OBJECTIVES: We analyzed the extent to which comparative effectiveness research (CER) organizations share terms for designs, analyzed coverage of CER designs in Medical Subject Headings (MeSH) and Emtree, and explored whether scientists use CER design terms. METHODS: We developed local terminologies (LTs) and a CER design terminology by extracting terms in documents from five organizations. We defined coverage as the distribution over match type in MeSH and Emtree. We created a crosswalk by recording terms to which design terms mapped in both controlled vocabularies. We analyzed the hits for queries restricted to titles and abstracts to explore scientists' language. RESULTS: Pairwise LT overlap ranged from 22.64% (12/53) to 75.61% (31/41). The CER design terminology (n = 78 terms) consisted of terms for primary study designs and a few terms useful for evaluating evidence, such as opinion paper and systematic review. Patterns of coverage were similar in MeSH and Emtree (gamma = 0.581, P = 0.002). CONCLUSIONS: Stakeholder terminologies vary, and terms are inconsistently covered in MeSH and Emtree. The CER design terminology and crosswalk may be useful for expert searchers. For partially mapped terms, queries could consist of free text for modifiers such as nonrandomized or interrupted added to broad or related controlled terms.

Automated detection of heuristics and biases among pathologists in a computer-based system.

The purpose of this study is threefold: (1) to develop an automated, computer-based method to detect heuristics and biases as pathologists examine virtual slide cases, (2) to measure the frequency and distribution of heuristics and errors across three levels of training, and (3) to examine relationships of heuristics to biases, and biases to diagnostic errors. The authors conducted the study using a computer-based system to view and diagnose virtual slide cases. The software recorded participant responses throughout the diagnostic process, and automatically classified participant actions based on definitions of eight common heuristics and/or biases. The authors measured frequency of heuristic use and bias across three levels of training. Biases studied were detected at varying frequencies, with availability and search satisficing observed most frequently. There were few significant differences by level of training. For representativeness and anchoring, the heuristic was used appropriately as often or more often than it was used in biased judgment. Approximately half of the diagnostic errors were associated with one or more biases. We conclude that heuristic use and biases were observed among physicians at all levels of training using the virtual slide system, although their frequencies varied. The system can be employed to detect heuristic use and to test methods for decreasing diagnostic errors resulting from cognitive biases.

Perceptual analysis of the reading of dermatopathology virtual slides by pathology residents.

CONTEXT: The process by which pathologists arrive at a given diagnosis-a combination of their slide exploration strategy, perceptual information gathering, and cognitive decision making-has not been thoroughly explored, and many questions remain unanswered. OBJECTIVE: To determine how pathology residents learn to diagnose inflammatory skin dermatoses, we contrasted the slide exploration strategy, perceptual capture of relevant histopathologic findings, and cognitive integration of identified features between 2 groups of residents, those who had and those who had not undergone their dermatopathology rotation. DESIGN: Residents read a case set of 20 virtual slides (10 depicting nodular and diffuse dermatitis and 10 depicting subepidermal vesicular dermatitis), using an in-house-developed interface. We recorded residents' reports of diagnostic findings, conjectured diagnostic hypotheses, and final (or differential) diagnosis for each case, and time stamped each interaction with the interface. We created search maps of residents' slide exploration strategy. RESULTS: No statistically significant differences were observed between the resident groups in the number of correctly or incorrectly reported diagnostic findings, but residents with dermatopathology training generated significantly more correct hypotheses (mean improvement of 88.5%) and correct diagnoses (70% of all correct diagnoses). CONCLUSIONS: Two types of slide exploration strategy were identified for both groups: (1) a focused and efficient search, observed when the final diagnosis was correct; and (2) a more dispersed, time-consuming strategy, observed when the final diagnosis was incorrect. This difference was statistically significant, and it suggests that initial interpretation of a slide may bias further slide exploration.

Anaphoric reference in clinical reports: characteristics of an annotated corpus.

MOTIVATION: Expressions that refer to a real-world entity already mentioned in a narrative are often considered anaphoric. For example, in the sentence "The pain comes and goes," the expression "the pain" is probably referring to a previous mention of pain. Interpretation of meaning involves resolving the anaphoric reference: deciding which expression in the text is the correct antecedent of the referring expression, also called an anaphor. We annotated a set of 180 clinical reports (surgical pathology, radiology, discharge summaries, and emergency department) from two institutions to indicate all anaphor-antecedent pairs. OBJECTIVE: The objective of this study is to describe the characteristics of the corpus in terms of the frequency of anaphoric relations, the syntactic and semantic nature of the members of the pairs, and the types of anaphoric relations that occur. Understanding how anaphoric reference is exhibited in clinical reports is critical to developing reference resolution algorithms and to identifying peculiarities of clinical text that may alter the features and methodologies that will be successful for automated anaphora resolution. RESULTS: We found that anaphoric reference is prevalent in all types of clinical reports, that annotations of noun phrases, semantic type, and section headings may be especially important for automated resolution of anaphoric reference, and that separate modules for reference resolution may be required for different report types, different institutions, and different types of anaphors. Accurate resolution will probably require extensive domain knowledge-especially for pathology and radiology reports with more part/whole and set/subset relations. CONCLUSION: We hope researchers will leverage the annotations in this corpus to develop automated algorithms and will add to the annotations to generate a more extensive corpus.

A system for coreference resolution for the clinical narrative.

OBJECTIVE: To research computational methods for coreference resolution in the clinical narrative and build a system implementing the best methods. METHODS: The Ontology Development and Information Extraction corpus annotated for coreference relations consists of 7214 coreferential markables, forming 5992 pairs and 1304 chains. We trained classifiers with semantic, syntactic, and surface features pruned by feature selection. For the three system components--for the resolution of relative pronouns, personal pronouns, and noun phrases--we experimented with support vector machines with linear and radial basis function (RBF) kernels, decision trees, and perceptrons. Evaluation of algorithms and varied feature sets was performed using standard metrics. RESULTS: The best performing combination is support vector machines with an RBF kernel and all features (MUC score=0.352, B(3)=0.690, CEAF=0.486, BLANC=0.596) outperforming a traditional decision tree baseline. DISCUSSION: The application showed good performance similar to performance on general English text. The main error source was sentence distances exceeding a window of 10 sentences between markables. A possible solution to this problem is hinted at by the fact that coreferent markables sometimes occurred in predictable (although distant) note sections. Another system limitation is failure to fully utilize synonymy and ontological knowledge. Future work will investigate additional ways to incorporate syntactic features into the coreference problem. CONCLUSION: We investigated computational methods for coreference resolution in the clinical narrative. The best methods are released as modules of the open source Clinical Text Analysis and Knowledge Extraction System and Ontology Development and Information Extraction platforms.

Coreference resolution: a review of general methodologies and applications in the clinical domain.

Coreference resolution is the task of determining linguistic expressions that refer to the same real-world entity in natural language. Research on coreference resolution in the general English domain dates back to 1960s and 1970s. However, research on coreference resolution in the clinical free text has not seen major development. The recent US government initiatives that promote the use of electronic health records (EHRs) provide opportunities to mine patient notes as more and more health care institutions adopt EHR. Our goal was to review recent advances in general purpose coreference resolution to lay the foundation for methodologies in the clinical domain, facilitated by the availability of a shared lexical resource of gold standard coreference annotations, the Ontology Development and Information Extraction (ODIE) corpus.

The feasibility of automating audit and feedback for ART guideline adherence in Malawi.

OBJECTIVE: To determine the feasibility of using electronic medical record (EMR) data to provide audit and feedback of antiretroviral therapy (ART) clinical guideline adherence to healthcare workers (HCWs) in Malawi. MATERIALS AND METHODS: We evaluated recommendations from Malawi's ART guidelines using GuideLine Implementability Appraisal criteria. Recommendations that passed selected criteria were converted into ratio-based performance measures. We queried representative EMR data to determine the feasibility of generating feedback for each performance measure, summed clinical encounters representing each performance measure's denominator, and then measured the distribution of encounter frequency for individual HCWs across nurse and clinical officer groups. RESULTS: We analyzed 423,831 encounters in the EMR data and generated automated feedback for 21 recommendations (12%) from Malawi's ART guidelines. We identified 11 nurse recommendations and eight clinical officer recommendations. Individual nurses and clinical officers had an average of 45 and 59 encounters per month, per recommendation, respectively. Another 37 recommendations (21%) would support audit and feedback if additional routine EMR data are captured and temporal constraints are modeled. DISCUSSION: It appears feasible to implement automated guideline adherence feedback that could potentially improve HCW performance and supervision. Feedback reports may support workplace learning by increasing HCWs' opportunities to reflect on their performance. CONCLUSION: A moderate number of recommendations from Malawi's ART guidelines can be used to generate automated guideline adherence feedback using existing EMR data. Further study is needed to determine the receptivity of HCWs to peer comparison feedback and barriers to implementation of automated audit and feedback in low-resource settings.

Anaphoric relations in the clinical narrative: corpus creation.

OBJECTIVE: The long-term goal of this work is the automated discovery of anaphoric relations from the clinical narrative. The creation of a gold standard set from a cross-institutional corpus of clinical notes and high-level characteristics of that gold standard are described. METHODS: A standard methodology for annotation guideline development, gold standard annotations, and inter-annotator agreement (IAA) was used. RESULTS: The gold standard annotations resulted in 7214 markables, 5992 pairs, and 1304 chains. Each report averaged 40 anaphoric markables, 33 pairs, and seven chains. The overall IAA is high on the Mayo dataset (0.6607), and moderate on the University of Pittsburgh Medical Center (UPMC) dataset (0.4072). The IAA between each annotator and the gold standard is high (Mayo: 0.7669, 0.7697, and 0.9021; UPMC: 0.6753 and 0.7138). These results imply a quality corpus feasible for system development. They also suggest the complementary nature of the annotations performed by the experts and the importance of an annotator team with diverse knowledge backgrounds. LIMITATIONS: Only one of the annotators had the linguistic background necessary for annotation of the linguistic attributes. The overall generalizability of the guidelines will be further strengthened by annotations of data from additional sites. This will increase the overall corpus size and the representation of each relation type. CONCLUSION: The first step toward the development of an anaphoric relation resolver as part of a comprehensive natural language processing system geared specifically for the clinical narrative in the electronic medical record is described. The deidentified annotated corpus will be available to researchers.

Ranked Levels of Influence model: selecting influence techniques to minimize IT resistance.

Implementation of electronic health records (EHR), particularly computerized physician/provider order entry systems (CPOE), is often met with resistance. Influence presented at the right time, in the right manner, may minimize resistance or at least limit the risk of complete system failure. Combining established theories on power, influence tactics, and resistance, we developed the Ranked Levels of Influence model. Applying it to documented examples of EHR/CPOE failures at Cedars-Sinai and Kaiser Permanente in Hawaii, we evaluated the influence applied, the resistance encountered, and the resulting risk to the system implementation. Using the Ranked Levels of Influence model as a guideline, we demonstrate that these system failures were associated with the use of hard influence tactics that resulted in higher levels of resistance. We suggest that when influence tactics remain at the soft tactics level, the level of resistance stabilizes or de-escalates and the system can be saved.

Natural Language Processing methods and systems for biomedical ontology learning.

While the biomedical informatics community widely acknowledges the utility of domain ontologies, there remain many barriers to their effective use. One important requirement of domain ontologies is that they must achieve a high degree of coverage of the domain concepts and concept relationships. However, the development of these ontologies is typically a manual, time-consuming, and often error-prone process. Limited resources result in missing concepts and relationships as well as difficulty in updating the ontology as knowledge changes. Methodologies developed in the fields of Natural Language Processing, information extraction, information retrieval and machine learning provide techniques for automating the enrichment of an ontology from free-text documents. In this article, we review existing methodologies and developed systems, and discuss how existing methods can benefit the development of biomedical ontologies.

Touchscreen task efficiency and learnability in an electronic medical record at the point-of-care.

The objective of this study was to determine the relative efficiency of novices compared to a prediction of skilled use when performing tasks using the touchscreen interface of an EMR developed in Malawi. We observed novice users performing touchscreen tasks and recorded timestamp data from their performances. Using a predictive human performance modeling tool, the authors predicted the skilled task performance time for each task. Efficiency and rates of error were evaluated with respect to user interface design. Nineteen participants performed 31 EMR tasks seven times for a total of 4,123 observed performances. We analyzed twelve representative tasks leaving 1,596 performances featuring six user interface designs. Mean novice performance time was significantly slower than mean predicted skilled performance time (p<0.001). However, novices performed faster than the predicted skilled level in 208 (13%) of successful task performances. These findings suggest the user interface design supports a primary design goal of the EMR--to allow novice users to perform tasks efficiently and effectively.