Coding the negative emotions of family members and patients among the high-risk preoperative conversations with the Chinese version of VR-CoDES

Abstract Background Little is known about family members' and patients' expression of negative emotions among high‐risk preoperative conversations. Objectives This study aimed to identify the occurrence and patterns of the negative emotions of family members and patients in preoperative conversations, to investigate the conversation themes and to explore the correlation between the negative emotions and the conversation themes. Methods A retrospective study was conducted using the Chinese version of Verona Coding Definitions of Emotional Sequences (VR‐CoDES‐C) to code 297 conversations on high‐risk procedures. Inductive content analysis was used to analyse the topics in which negative emotions nested. The χ2 Test was used to test the association between the cues and the conversation themes. Results The occurrence rate of family members' and patients' negative emotions was very high (85.9%), much higher when compared to most conversations under other medical settings. The negative emotions were mainly expressed by cues (96.4%), and cue‐b (67.4%) was the most frequent category. Cues and concerns were mostly elicited by family members and patients (71.6%). Negative emotions were observed among seven themes, in which ‘Psychological stress relating to illness severity, family's care and financial burden’ (30.3%) ranked the top. Cue‐b, cue‐c and cue‐d had a significant correlation (p < .001) with certain themes. Conclusions Family members and patients conveyed significantly more negative emotions in the high‐risk preoperative conversations than in other medical communications. Certain categories of cues were induced by specific emotional conversation contents. Patient Contribution Family members and patients contributed to data

How physicians respond to negative emotions in high-risk preoperative conversations

This work was supported by the China Medical Board, CMB 14-200.Objective To investigate physicians’ responses to negative emotions in high-risk preoperative conversations; and to explore the influencing factors of these responses. Methods One hundred and sixty-two audio recordings were coded using the Chinese Verona Coding Definition of Emotional Sequences (VR-CoDES). Big Five Personality Inventory Brief Version and Emotional Intelligence Scale were administered to explore the influencing factors of physicians’ responses. SPSS 24.0 and R 3.6.3 LME4 Package were used for data analysis. Results Reduce Space (83%), referring to physicians’ responses reducing the opportunities of patients to disclose emotions, was physicians’ most frequent response to patients or families’ emotions. The main responses were Information-advice (ERIa) and Ignoring (NRIa). Younger age, female, Agreeableness and Openness were factors positively associated with Explicit Provide Space (EP); Neuroticism was negatively correlated with EP. Extroversion was negatively correlated with Explicit Reduce Space (ER); Conscientiousness was negatively correlated with both EP and ER responses. Emotional intelligence had no significant influence on physicians’ responses. Conclusion The majority of physicians were inclined to reduce space by providing information advice or ignoring. Physicians’ responses were correlated with their gender, age and personality traits. Practice Implications The trainees’ gender, age and personality should be considered when conducting doctor-patient communication skills training.Publisher PDFPeer reviewe

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Alternating Direction Method of Multipliers for Generalized Low-Rank Tensor Recovery

Low-Rank Tensor Recovery (LRTR), the higher order generalization of Low-Rank Matrix Recovery (LRMR), is especially suitable for analyzing multi-linear data with gross corruptions, outliers and missing values, and it attracts broad attention in the fields of computer vision, machine learning and data mining. This paper considers a generalized model of LRTR and attempts to recover simultaneously the low-rank, the sparse, and the small disturbance components from partial entries of a given data tensor. Specifically, we first describe generalized LRTR as a tensor nuclear norm optimization problem that minimizes a weighted combination of the tensor nuclear norm, the l1-norm and the Frobenius norm under linear constraints. Then, the technique of Alternating Direction Method of Multipliers (ADMM) is employed to solve the proposed minimization problem. Next, we discuss the weak convergence of the proposed iterative algorithm. Finally, experimental results on synthetic and real-world datasets validate the efficiency and effectiveness of the proposed method