Discourse types and (re)distribution of responsibility in simulated emergency team encounters

Successful teamwork, constitutive of team talk, depends largely on shared responsibility in the coordination of tasks in a goal-oriented way. This paper examines how specific modes of talk or ‘discourse types’ are utilised by a healthcare team in simulated emergency care. The data corpus comprises six video-recorded simulation training sessions in an emergency department at a large Norwegian hospital. Our analysis focuses on the critical moment when the original healthcare team is joined by other specialists in an ad hoc manner, which necessitates the (re)distribution of expert responsibility in the management of the patient’s condition. We examine the interactional trajectories and, in particular, the discourse types surrounding the critical moment which marks the incorporation of the new team members. The analysis centres on three discourse types (online commentary, offline commentary and metacommentary) that are utilised in accomplishing the multiple tasks in a collaborative and coordinated fashion. We suggest that team talk overlays and overlaps with distributed medical work in highly charged decision-making contexts such as emergency care. The findings have relevance for how healthcare professionals and students are trained in multidisciplinary team talk and teamwork.</jats:p

Team talk and team activity in simulated medical emergencies: a discourse analytical approach

Background: Communication errors can reduce patient safety, especially in emergency situations that require rapid responses by experts in a number of medical specialties. Talking to each other is crucial for utilizing the collective expertise of the team. Here we explored the functions of “team talk” (talking between team members) with an emphasis on the talk-work relationship in interdisciplinary emergency teams. Methods: Five interdisciplinary medical emergency teams were observed and videotaped during in situ simulations at an emergency department at a university hospital in Norway. Team talk and simultaneous actions were transcribed and analysed. We used qualitative discourse analysis to perform structural mapping of the team talk and to analyse the function of online commentaries (real-time observations and assessments of observations based on relevant cues in the clinical situation). Results: Structural mapping revealed recurring and diverse patterns. Team expansion stood out as a critical phase in the teamwork. Online commentaries that occurred during the critical phase served several functions and demonstrated the inextricable interconnections between team talk and actions. Discussion: Discourse analysis allowed us to capture the dynamics and complexity of team talk during a simulated emergency situation. Even though the team talk did not follow a predefined structure, the team members managed to manoeuvre safely within the complex situation. Our results support that online commentaries contributes to shared team situation awareness. Conclusions: Discourse analysis reveals naturally occurring communication strategies that trigger actions relevant for safe practice and thus provides supplemental insights into what comprises “good” team communication in medical emergencies

Interaksjon med brukere i Nav: Analyse av samtaledata som grunnlag for fagutvikling

publishedVersio

Interaksjon med brukere i Nav: Analyse av samtaledata som grunnlag for fagutvikling

Møter mellom Nav-veileder og bruker er viktige både for samfunnets mål om flest mulig i arbeid, og for den enkelte bruker som har behov for veiledning, økonomisk eller praktisk hjelp. Gjennom FOU-satsingen «Interaksjon med brukere» legger Nav vekt på brukermøtene og hvordan kvaliteten i disse henger sammen med målene om aktivisering og brukermedvirkning. Denne metodologiske artikkelen bruker norsk og internasjonal forskning om samtaler i arbeids- og velferdssektoren som empirisk grunnlag for å diskutere hvordan ulike metoder er egna til å belyse ulike problemstillinger. Detaljert analyse av samarbeidet og samspillet i faktiske brukermøter er en lite brukt metode i forskning om Nav. I denne artikkelen diskuterer vi derfor hva som kan oppnås gjennom å gjøre nærstudier av interaksjonen i brukermøter med utgangspunkt i lyd-/bildeopptak og med verktøy fra samtaleforskning. Vi gir eksempler på hvordan analyse av samtaledata kan gi grunnlag for å nyansere standardiserte råd om kommunikasjon og belyse hvordan brukermøtets interaksjonelle forløp skaper vilkår for deltakelse i samtalen. Å være samtaleleder i brukermøter er en viktig del av Nav-veilederes jobb. Denne artikkelen bidrar med en forskningsbasert begrunnelse for hvorfor bevisstgjøring om samtalens dynamikk i brukermøtene bør være del av fagutviklingen i Nav.publishedVersionThis article is downloaded from www.idunn.no. © 2018 Author(s). This is an open access article distributed under the terms of the Creative Commons CC-BY-NC 4.0 License (http://creativecommons.org/licenses/by-nc/4.0/)

Students’ top 10 priorities of research uncertainties on students’ sleep: a pragmatic James Lind Alliance approach

Objectives Inspired by the James Lind Alliance (JLA) user involvement approach, the aim of the present study was to identify the top 10 uncertainties for sleep research raised by students in higher education, and to discuss our experiences with adapting the JLA method to a student population. Design The study design is a pragmatic JLA approach, including a priority setting partnership within the field of sleep, collection of sleep-related research uncertainties as reported by students in higher education, sorting of the uncertainties and a final identification of the top 10 uncertainties through collaborative work between researchers, students, stakeholders and experts in the field. Uncertainties were collected using a one-question online survey: ‘as a student, which question(s) do you consider to be important with regards to sleep?’. A variety of approaches were applied to promote the survey to the students, including social media, radio, the university website, stands in university cafeterias and a sleep stunt. NVivo V.12 was used to code and sort the questions. Setting A higher education institution in Norway. Participants 555 students. Results The data collection provided 608 uncertainties, and the following prioritised top 10: (1) screen time, (2) stress, (3) educational achievements, (4) social relations, (5) mental health, (6) physical activity, (7) indoor environment, (8) substance abuse, (9) shift work and (10) sleep quality. Despite successful data collection, we found sleep to be a broad topic, and defining specific questions throughout the sorting and verification process proved difficult. Conclusions We identified the prioritised top 10 research uncertainties as reported by students in higher education, ranking screen time first. However, the process was time and resource consuming. The research uncertainties addressed by the students showed great diversity, characterised by heterogeneity and a lack of specificity, making verification of the uncertainties challenging

Students’ top 10 priorities of research uncertainties on students’ sleep: a pragmatic James Lind Alliance approach

Objectives Inspired by the James Lind Alliance (JLA) user involvement approach, the aim of the present study was to identify the top 10 uncertainties for sleep research raised by students in higher education, and to discuss our experiences with adapting the JLA method to a student population. Design The study design is a pragmatic JLA approach, including a priority setting partnership within the field of sleep, collection of sleep-related research uncertainties as reported by students in higher education, sorting of the uncertainties and a final identification of the top 10 uncertainties through collaborative work between researchers, students, stakeholders and experts in the field. Uncertainties were collected using a one-question online survey: ‘as a student, which question(s) do you consider to be important with regards to sleep?’. A variety of approaches were applied to promote the survey to the students, including social media, radio, the university website, stands in university cafeterias and a sleep stunt. NVivo V.12 was used to code and sort the questions. Setting A higher education institution in Norway. Participants 555 students. Results The data collection provided 608 uncertainties, and the following prioritised top 10: (1) screen time, (2) stress, (3) educational achievements, (4) social relations, (5) mental health, (6) physical activity, (7) indoor environment, (8) substance abuse, (9) shift work and (10) sleep quality. Despite successful data collection, we found sleep to be a broad topic, and defining specific questions throughout the sorting and verification process proved difficult. Conclusions We identified the prioritised top 10 research uncertainties as reported by students in higher education, ranking screen time first. However, the process was time and resource consuming. The research uncertainties addressed by the students showed great diversity, characterised by heterogeneity and a lack of specificity, making verification of the uncertainties challenging

Students’ top 10 priorities of research uncertainties on students’ sleep: a pragmatic James Lind Alliance approach

Objectives: Inspired by the James Lind Alliance (JLA) user involvement approach, the aim of the present study was to identify the top 10 uncertainties for sleep research raised by students in higher education, and to discuss our experiences with adapting the JLA method to a student population. Design: The study design is a pragmatic JLA approach, including a priority setting partnership within the field of sleep, collection of sleep-related research uncertainties as reported by students in higher education, sorting of the uncertainties and a final identification of the top 10 uncertainties through collaborative work between researchers, students, stakeholders and experts in the field. Uncertainties were collected using a one-question online survey: ‘as a student, which question(s) do you consider to be important with regards to sleep?’. A variety of approaches were applied to promote the survey to the students, including social media, radio, the university website, stands in university cafeterias and a sleep stunt. NVivo V.12 was used to code and sort the questions. Setting: A higher education institution in Norway. Participants: 555 students. Results: The data collection provided 608 uncertainties, and the following prioritised top 10: (1) screen time, (2) stress, (3) educational achievements, (4) social relations, (5) mental health, (6) physical activity, (7) indoor environment, (8) substance abuse, (9) shift work and (10) sleep quality. Despite successful data collection, we found sleep to be a broad topic, and defining specific questions throughout the sorting and verification process proved difficult. Conclusions: We identified the prioritised top 10 research uncertainties as reported by students in higher education, ranking screen time first. However, the process was time and resource consuming. The research uncertainties addressed by the students showed great diversity, characterised by heterogeneity and a lack of specificity, making verification of the uncertainties challenging