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Workplaces in the oil and gas (O&G) industry have evolved to become part of the modern complex sociotechnical system that characterises onshore and offshore facilities today. The intense interactions between workers, systems, equipment and processes have made companies in this sector more productive. However, significant and complex risks have also emerged. Managing them requires a methodology capable of understanding and recognising how this entire sociotechnical system works. This research uses the FRAM to model the activities performed by drillers, from the perspective of their workplace, inside the drilling unit of an offshore oil rig—a complex sociotechnical system. The interviews, on-board observations and data gathering performed as part of this study provided information that was used to build a FRAM model capable of representing the real work done by drillers inside the doghouses on offshore oil rigs. Through this model, the variability of human behaviour could be analysed in the context of the different situations that may happen, enabling researchers to understand the specific demands of the work and the correlation between WAI and WAD that naturally emerges. This FRAM-based analysis acknowledges that human factors and non-technical skills are responsible for the productive and safe execution of the work in both normal and critical operations situations, and identifies the impact of this variability—positive or negative—in the execution of daily tasks. It shows that workers’ varied responses can properly deal with complex system demands both in normal situations and in emergencies.

•Decontextualized simulation offers an innovative method for enhancing non technical skills (NTS) training in healthcare.•Harness the gaming environnement to encourage sustained attention, engagement, knowledge retention and feedback.•Integrate decontextualized simulation within educational programs and training to enhanced team performance.•Versatility and easy implementation make decontextualized simulation a valuable tool for perioperative quality and safety.

Aim The aim of this study was to explore how operating room nurses (ORNs) experience operating room (OR) team communication concerning non‐technical skills. Design Based on the Scrub Practitioners List of Intraoperative Non‐Technical Skill (SPLINTS), qualitative individual in‐depth semi‐structured interviews were conducted with 11 ORNs in a Norwegian university hospital. Braun and Clarke's six analytic phases for thematic data analysis were used. Results Surgeons being unprepared or demanding different instruments than the preoperative information indicates, cause stress and frustration. So does noise and brusquely or poor communication. Ensuring good information flow within the entire team is important. When silence is required, the ORNs communicate with gestures, looks and nods. Creating a positive and secure team culture facilitates discussions, questions and information sharing. Conclusion Inappropriate dynamics, inaccurate and/or disrespectful communication and noise may reduce patient safety. Interdisciplinary team training may bring attention to the value of communication as a non‐technical skill.

AbstractObjectivesPit crew models are designed to improve teamwork in critical medical situations, like advanced life support (ALS). We investigated if a pit crew model training improves performance assessment and ALS skills retention when compared to standard ALS education. MethodsThis was a prospective, blinded, randomized, and controlled, parallel‐group trial. We recruited students to 4‐person resuscitation teams. We video recorded simulated ALS‐situations after the ALS education and after 6‐month follow‐up. We analyzed technical skills (TS) and non‐technical skills (NTS) demonstrated in them with an instrument measuring TS and NTS, and used a linear mixed model to model the difference between the groups in the TS and NTS. Another linear model was used to explore the difference between the groups in hands‐on ratio and hands‐free time. The difference in the total assessment score was analyzed with the Mann‐Whitney U‐test. The primary outcome was the difference in the total assessment score between the groups at follow‐up. ALS skills were considered to be a secondary outcome. ResultsTwenty‐six teams underwent randomization. Twenty‐two teams received the allocated education. Fifteen teams were evaluated at 6‐month follow‐up: 7 in the intervention group and 8 in the control group. At 6‐month follow‐up, the median (Q 1–Q 3) total assessment score for the control group was 6.5 (6–8) and 7 (6.25–8) for the intervention group but the difference was not significant (U = 133, P = 0.373). The intervention group performed better in terms of chest compression quality (interaction term, β3 = 0.23; 95% confidence interval, 0.01–0.50; P = 0.043) at follow‐up. ConclusionWe found no difference in overall performance between the study arms. However, trends indicate that the pit crew model may help to retain ALS skills in different areas like chest compression quality.

Artificial Intelligence in Education (AIED) has witnessed significant growth over the last twenty-five years, providing a wide range of technologies to support academic, institutional, and administrative services. More recently, AIED applications have been developed to prepare students for the workforce, providing career guidance services for higher education. However, this remains challenging, especially concerning the rapidly changing labour market in the IT sector. In this paper, we introduce an AI-based solution named C3-IoC ( https://c3-ioc.co.uk ), which intends to help students explore career paths in IT according to their level of education, skills and prior experience. The C3-IoC presents a novel similarity metric method for relating existing job roles to a range of technical and non-technical skills. This also allows the visualisation of a job role network, placing the student within communities of job roles. Using a unique knowledge base, user skill profiling, job role matching, and visualisation modules, the C3-IoC supports students in self-evaluating their skills and understanding how they relate to emerging IT jobs.

In spite of a large body of research in the field of emotion regulation, this subject has not yet been studied vigorously in naturalistic settings, especially not in the context of task performance. Therefore, it remains uncertain whether predominant theoretical conceptualizations of emotion regulation (e.g., Gross, 1998) can be applied to this sort of situation. In this qualitative study, we aimed to identify emotion regulation strategies of paramedic crew leaders (n = 30) in a simulated task with a sudden onset of a stressful incident. For this purpose, we analyzed their emotional behavior (i.e., facial expression, voice volume, body posture and movements etc.) on video recorded performance, and their affective states and emotion regulation strategies based on interviews conducted right after the task. Verbal reports were analyzed via phenomenologically-laden template analysis. We classified emergent strategies into two basic categories: task-related (e.g., attention narrowing, mobilization to action, monitoring) and self-supportive (e.g., emotional distancing, behavioral withdrawal, detachment and selective attention). Results of our analysis suggest that regulatory strategies are largely implemented on an implicit level of processing and their function might be a better criterion for their distinction than a type of mental process.

ObjectivesTo investigate the relationship between teamwork and clinical performance and potential moderating variables of this relationship.DesignSystematic review and meta-analysis.Data sourcePubMed was searched in June 2018 without a limit on the date of publication. Additional literature was selected through a manual backward search of relevant reviews, manual backward and forward search of studies included in the meta-analysis and contacting of selected authors via email.Eligibility criteriaStudies were included if they reported a relationship between a teamwork process (eg, coordination, non-technical skills) and a performance measure (eg, checklist based expert rating, errors) in an acute care setting.Data extraction and synthesisModerator variables (ie, professional composition, team familiarity, average team size, task type, patient realism and type of performance measure) were coded and random-effect models were estimated. Two investigators independently extracted information on study characteristics in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.ResultsThe review identified 2002 articles of which 31 were included in the meta-analysis comprising 1390 teams. The sample-sized weighted mean correlation was r =0.28 (corresponding to an OR of 2.8), indicating that teamwork is positively related to performance. The test of moderators was not significant, suggesting that the examined factors did not influence the average effect of teamwork on performance.ConclusionTeamwork has a medium-sized effect on performance. The analysis of moderators illustrated that teamwork relates to performance regardless of characteristics of the team or task. Therefore, healthcare organisations should recognise the value of teamwork and emphasise approaches that maintain and improve teamwork for the benefit of their patients.

BackgroundEvidence for surgical coaching has yet to demonstrate an impact on surgeons’ practice. We evaluated a surgical coaching program by analyzing quantitative and qualitative data on surgeons’ intraoperative performance.MethodsIn the 2018–2019 Surgical Coaching for Operative Performance Enhancement (SCOPE) program, 46 practicing surgeons in multiple specialties at four academic medical centers were recruited to complete three peer coaching sessions, each comprising preoperative goal-setting, intraoperative observation, and postoperative debriefing. Coach and coachee rated the coachee’s performance using modified Objective Structured Assessment of Technical Skills (OSATS, range 1–5) and Non-Technical Skills for Surgeons (NOTSS, range 4–16). We used generalized estimating equations to evaluate trends in skill ratings over time, adjusting for case difficulty, clinical experience, and coaching role. Upon program completion, we analyzed semi-structured interviews with individual participants regarding the perceived impact of coaching on their practice.ResultsEleven of 23 coachees (48%) completed three coaching sessions, three (13%) completed two sessions, and six (26%) completed one session. Adjusted mean OSATS ratings did not vary over three coaching sessions (4.39 vs 4.52 vs 4.44, respectively; P = 0.655). Adjusted mean total NOTSS ratings also did not vary over three coaching sessions (15.05 vs 15.50 vs 15.08, respectively; P = 0.529). Regarding patient care, participants self-reported improved teamwork skills, communication skills, and awareness in and outside the operating room. Participants acknowledged the potential for coaching to improve burnout due to reduced intraoperative stress and enhanced peer support but also the potential to worsen burnout by adding to chronic work overload.ConclusionsSurgeons reported high perceived impact of peer coaching on patient care and surgeon well-being, although changes in coachees’ technical and non-technical skills were not detected over three coaching sessions. While quantitative skill measurement warrants further study, longitudinal peer surgical coaching should be considered a meaningful strategy for surgeons’ professional development.

Conduct a scoping review to critically appraise the development and summarize the evidence on the measurement properties of T-NOTECHS including sensibility, reliability, and validity. A literature search was performed using Pubmed and Ovid databases. Studies that described the development process of T-NOTECHS and primary studies that presented evidence of reliability and validity were identified and included. Measurement properties of T-NOTECHS was assessed and summarized under the following: scale development, sensibility, reliability, and validity. The literature search yielded 245 articles with 24 studies meeting inclusion criteria. The T-NOTECHS was developed with an acceptable robust methodology. It has good sensibility with adequate content, face validity, and feasibility. It is a reliable measure of non-technical skills in the setting of trauma video review, which improves with expert raters or extensive training. The T-NOTECHS is a valid discriminative and evaluative instrument that measures non-technical skills of multidisciplinary trauma teams. T-NOTECHS provides reliable and valid measurements of non-technical skills of trauma teams, particularly when assessing trauma video review and non-technical skills training interventions by expert raters. •T-NOTECHS was developed with an acceptable robust methodology.•The tool has good sensibility with adequate content, face validity, & feasibility.•Synthesis of evidence supports T-NOTECHS′ use as a discriminative & evaluative tool.•Ideal rater has clinical expertise in trauma care & simulation-based teaching.•Ideal setting to utilize T-NOTECHS is with trauma video review.

BACKGROUND: Sensor technologies and data collection practices are changing and improving quality metrics across various domains. Surgical skill assessment in Robot-Assisted Minimally Invasive Surgery (RAMIS) is essential for training and quality assurance. The mental workload on the surgeon (such as time criticality, task complexity, distractions) and non-technical surgical skills (including situational awareness, decision making, stress resilience, communication, leadership) may directly influence the clinical outcome of the surgery. METHODS: A literature search in PubMed, Scopus and PsycNet databases was conducted for relevant scientific publications. The standard PRISMA method was followed to filter the search results, including non-technical skill assessment and mental/cognitive load and workload estimation in RAMIS. Publications related to traditional manual Minimally Invasive Surgery were excluded, and also the usability studies on the surgical tools were not assessed. RESULTS: 50 relevant publications were identified for non-technical skill assessment and mental load and workload estimation in the domain of RAMIS. The identified assessment techniques ranged from self-rating questionnaires and expert ratings to autonomous techniques, citing their most important benefits and disadvantages. CONCLUSIONS: Despite the systematic research, only a limited number of articles was found, indicating that non-technical skill and mental load assessment in RAMIS is not a well-studied area. Workload assessment and soft skill measurement do not constitute part of the regular clinical training and practice yet. Meanwhile, the importance of the research domain is clear based on the publicly available surgical error statistics. Questionnaires and expert-rating techniques are widely employed in traditional surgical skill assessment; nevertheless, recent technological development in sensors and Internet of Things-type devices show that skill assessment approaches in RAMIS can be much more profound employing automated solutions. Measurements and especially big data type analysis may introduce more objectivity and transparency to this critical domain as well. SIGNIFICANCE: Non-technical skill assessment and mental load evaluation in Robot-Assisted Minimally Invasive Surgery is not a well-studied area yet; while the importance of this domain from the clinical outcome’s point of view is clearly indicated by the available surgical error statistics.