Nurses' Decisions in Error Reporting and Disclosing Based on Error Scenarios: A Mixed-method Study

Background: It is ensured that nurses’ error reporting and disclosing improve services to patients and are considered a movement toward creating a culture of transparency in the healthcare system. Objectives: This study aimed to investigate the nurses' decisions on reporting and disclosing Medical Errors (MEs). Methods: This research followed a mixed-method embedded design that was performed in five hospitals in Iran in 2018. A total of 491 nurses participated in the quantitative phase of the study with stratified sampling, followed by a simple random sampling technique. Also, 22 nurses joined the qualitative phase. Data were collected using a researcher-made questionnaire and semi-structured interviews through a scenario-based method. Quantitative data analysis was performed using descriptive and analytical statistics by SPSS 21.0 and Expert Choice 10.0 software. The qualitative data were analyzed based on the content analysis approach. Results: The most important perceived barriers with the highest impact coincided with educational (57.17%) and motivational (56.77%) factors based on SEM analysis (ES: 1.33, SE: 0.16). Regression analysis showed that error-reporting mechanisms, educational factors, and reporting consequences were significantly associated with age, sex, and work experience (P-Value ≤0.05). Error scenarios were thematized into three categories: Error perception (including ambiguity and weakness in error definition, the severity of the error, unawareness of guidelines, deviation from standards, and untrained staff), error reporting (including ineffective reporting system, hesitation in reporting to a formal system, increased workload, improper reaction, punitive responses, and concerns about consequences), and error disclosure (including no disclosure, partial disclosure, and full disclosure). Conclusions: The obtained results contributed to a better understanding of the barriers to error reporting and disclosing. In addition, these results can help hospitals encourage error reporting and ultimately make organizational changes, which reduce the incidence of errors.

Effects of Trait Anxiety on Error Processing and Post-error Adjustments: An Event-Related Potential Study With Stop-Signal Task

The present study aimed to use event-related potentials with the stop-signal task to investigate the effects of trait anxiety on inhibitory control, error monitoring, and post-error adjustments. The stop-signal reaction time (SSRT) was used to evaluate the behavioral competence of inhibitory control. Electrophysiological signals of error-related negativity (ERN) and error positivity (Pe) were used to study error perception and error awareness, respectively. Post-error slowing (PES) was applied to examine the behavioral adjustments after making errors. The results showed that SSRT and PES did not differ significantly between individuals with high trait anxiety (HTA) and those with low trait anxiety (LTA). However, individuals with HTA demonstrated reduced ERN amplitudes and prolonged Pe latencies than those with LTA. Prolonged Pe latencies were also significantly associated with poorer post-error adjustments. In conclusion, HTA led to reduced cortical responses to error monitoring. Furthermore, inefficient conscious awareness of errors might lead to maladaptive post-error adjustments.

Experience of After-Effect of Memory Update Reduces Sensitivity to Errors During Sensory-Motor Adaptation Task

Motor learning is the process of updating motor commands in response to a trajectory error induced by a perturbation to the body or vision. The brain has a great capability to accelerate learning by increasing the sensitivity of the memory update to the perceived trajectory errors. Conventional theory suggests that the statistics of perturbations or the statistics of the experienced errors induced by the external perturbations determine the learning speeds. However, the potential effect of another type of error perception, a self-generated error as a result of motor command updates (i.e., an aftereffect), on the learning speeds has not been examined yet. In this study, we dissociated the two kinds of errors by controlling the perception of the aftereffect using a channel-force environment. One group experienced errors due to the aftereffect of the learning process, while the other did not. We found that the participants who perceived the aftereffect of the memory updates exhibited a significant decrease in error-sensitivity, whereas the participants who did not perceive the aftereffect did not show an increase or decrease in error-sensitivity. This suggests that the perception of the aftereffect of learning attenuated updating the motor commands from the perceived errors. Thus, both self-generated and externally induced errors may modulate learning speeds.

Exploiting Machine Learning for Vision and Motion Planning of Autonomous Vehicles Navigation

The object of this paper is to create a system that can control any vehicle in any gaming environment to simulate, study, experiment and improve how self-driving vehicles operate. It is to be taken as the bases for future work on autonomous vehicles with real hardware devices. The long-term goal is to eliminate human error. Perception, localisation, planning and control subsystems were developed. LiDAR and RADAR sensors were used in addition to a normal web Camera. After getting information from the perception module, the system will be able to localise where the vehicle is, then the planning module is used to plan to which location the vehicle will move, using localisation module data to draw up the best path to use. After knowing the best path, the system will control the vehicle to move autonomously without human help. As a controller a Proportional Integral Derivative PID controller was used. Python programming language, computer vision, and machine learning were used in developing the system, where the only hardware required is a computer with a GPU and powerful graphical card that can run a game which has a vehicle, roads with lane lines and a map of the road. The developed system is intended to be a good tool in conducting experiments for achieving reliable autonomous vehicle navigation.

Neural and behavioral traces of error awareness

Monitoring for errors and behavioral adjustments after errors are essential for daily life. A question that has not been addressed systematically yet, is whether consciously perceived errors lead to different behavioral adjustments compared to unperceived errors. Our goal was to develop a task that would enable us to study different commonly observed neural correlates of error processing and post-error adjustments in their relation to error awareness and accuracy confidence in a single experiment. We assessed performance in a new number judgement error awareness task in 70 participants. We used multiple, robust, single-trial EEG regressions to investigate the link between neural correlates of error processing (e.g., error-related negativity (ERN) and error positivity (Pe)) and error awareness. We found that only aware errors had a slowing effect on reaction times in consecutive trials, but this slowing was not accompanied by post-error increases in accuracy. On a neural level, error awareness and confidence had a modulating effect on both the ERN and Pe, whereby the Pe was most predictive of participants’ error awareness. Additionally, we found partial support for a mediating role of error awareness on the coupling between the ERN and behavioral adjustments in the following trial. Our results corroborate previous findings that show both an ERN/Pe and a post-error behavioral adaptation modulation by error awareness. This suggests that conscious error perception can support meta-control processes balancing the recruitment of proactive and reactive control. Furthermore, this study strengthens the role of the Pe as a robust neural index of error awareness.

Understanding the Barriers to Nurses Error Reporting and Disclosure: A Mixed Methods Study

Background: Ensuring that nurses report errors and disclose related outcomes to patients is a movement toward creating a culture of transparency. Different factors might contribute to the tendency to under-report or to disclose. This study aim to investigate the barriers of the reporting and disclosing of medical errors via nurses’ perceptions.Methods: A mixed methods study were used to identify barriers of error reporting and disclosing. For the aim of this study, a total of 491 nurses participated in the quantitative phase and 22 nurses in the qualitative phase, Iran, 2018. The data for the quantitative phase was collected based on a questionnaire and were next analyzed by descriptive and analytical statistics. Through a scenario-based method, the qualitative data were gathered and analyzed based on content analysis approach.Results: The results showed that the most important perceived barriers with the highest impacts coincided with educational(64%), motivational(64%), and managerial factors (62%) and the univariate analysis showed a significant correlation between error-reporting mechanisms, education, and consequences of reporting errors domains and independent variables(p < 0.05). Based on SEM analysis, the most important perceived barriers were educational and motivational domains (ES:1.33, SE:0.16). Interview results were classified into three categories: error perception, error reporting, and error disclosure. In fact, 55% of the interviewed nurses identified the existence of at least one error in scenarios and 66% of participants stated that they had reported errors. Overall 83% of the participants recruited had negative attitude toward full disclosing the errors to patients.Conclusions: Our results highlight the multifactorial aspects in error reporting and disclosing. Lack of knowledge about error and its reporting, inappropriate feedback and weakness in supportive actions represent the inhibitors of reporting and disclosing errors. Actually, a guideline should be formulated on error disclosure to increase transparency and improve communication with patients.