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• v.9(9); 2019

How effective is teamwork really? The relationship between teamwork and performance in healthcare teams: a systematic review and meta-analysis

Jan b. schmutz.

1 Department of Communication Studies, Northwestern University, Evanston, Illinois, USA

Laurenz L. Meier

2 Department of Work and Organizational Psychology, University of Neuchâtel, Neuchâtel, Switzerland

Tanja Manser

3 FHNW School of Applied Psychology, University of Applied Sciences and Arts Northwestern Switzerland, Olten, Switzerland

Associated Data

bmjopen-2018-028280supp001.pdf

To investigate the relationship between teamwork and clinical performance and potential moderating variables of this relationship.

Systematic review and meta-analysis.

Data source

PubMed 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 criteria

Studies 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 synthesis

Moderator 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.

The 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.

Teamwork 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.

Strengths and limitations of this study

• This systematic review evaluates available studies investigating the effectiveness of teamwork processes.
• Thirty-one studies have been included resulting in a substantial sample size of 1390 teams.
• The sample size of the primary studies included is usually low.
• For some subgroup analysis, the number of studies included was small.

Introduction

May it be an emergency team in the trauma room, paramedics treating patients after an accident or a surgical team in the operating room, teams are ubiquitous in healthcare and must work across professional, disciplinary and sectorial boundaries. Although the clinical expertise of individual team members is important to ensure high performance, teams must be capable of applying and combining the unique expertise of team members to maintain safety and optimal performance. In order for a team to be effective individual team members need to collaborate and engage in teamwork. Today, experts agree that effective teamwork anchors safe and effective care at various levels of the healthcare systems 1–4 leading to a relatively recent shift towards team research and training. 5–7

Healthcare is an evidence-based field and therefore administrators and providers are seeking evidence in the literature concerning the impact of teamwork on performance outcomes like patient mortality, morbidity, infection rates or adherence to clinical treatment guidelines. Having a closer look at the literature investigating healthcare teams we find mixed and sometimes even contradicting results about the relationship between teamwork and clinical performance. 8 Some studies find a large effect of teamwork on performance outcomes (eg, Carlson et al 9 ) while others report small or no relationships. 10 11 This inconsistency arises due to several reasons. First, the conceptual and empirical literature examining teamwork is fragmented and research examining teamwork effectiveness is spread across disciplines including medicine, psychology and organisation science. Therefore, researchers and practitioners often lack a common conceptual foundation for investigating teams and teamwork in healthcare. Second, research studies on teamwork in healthcare usually exhibit small sample sizes because of the challenges of recruiting actual professional teams and carefully balancing research with patient care priorities. Small sample sizes, however, increase the likelihood of reporting results that fail to represent true effect. Third, studies investigating healthcare teams often ignore important context variables of teams (eg, team composition and size, task characteristics, team environment) that likely influence the effect that teamwork has on clinical performance. 12 13

These inconsistencies in the teamwork literature may lead to confusion about the importance of teamwork in healthcare, thus giving voice to critics who hinder efforts to improve teamwork. We aim to address these problems with a meta-analytical study investigating the performance implications of teamwork. A meta-analytical approach moves beyond existing reviews on teamwork in healthcare 8 14–17 and quantitatively tests if the widely advocated positive effect of teamwork on performance holds true. In addition, this approach allows us to investigate context variables as moderators that may influence the effect of teamwork on performance, meaning that this effect might be stronger or weaker under certain conditions. Previous meta-analyses 18 19 focused mainly on the effectiveness of team trainings but not on the effect of teamwork itself. This meta-analysis will generate quantitative evidence to inform the relevance of future interventions, regulations and policies targeting teamwork in healthcare organisations.

In the following we will first establish an operational definition of teamwork, elaborate on relevant contextual factors and present our respective meta-analytical results and their interpretation.

Teams, teamwork and team performance

In order to clearly understand the impact of teamwork on performance it is necessary to provide a brief introduction to teams, teamwork and team performance. We define teams as identifiable social work units consisting of two or more people with several unique characteristics. These characteristics include ( a ) dynamic social interaction with meaningful interdependencies, ( b ) shared and valued goals , (c ) a discrete lifespan, ( e ) distributed expertise and ( f ) clearly assigned roles and responsibilities. 20 21 Based on this definition it becomes clear that teams must dynamically share information and resources among members and coordinate their activities in order to fulfil a certain task — in other words teams need to engage in teamwork .

Teamwork as a term is widely used and often difficult to grasp. However, we absolutely require a clear definition of teamwork especially for team trainings that target specific behaviours. Teamwork is a process that describes interactions among team members who combine collective resources to resolve task demands (eg, giving clear orders). 22 23 Teamwork or team processes can be differentiated from taskwork. Taskwork denotes a team’s individual interaction with tasks, tools, machines and systems. 23 Taskwork is independent of other team members and is often described as what a team is doing whereas teamwork is how the members of a team are doing something with each other. 24 Therefore, team performance represents the accumulation of teamwork and taskwork (ie, what the team actually does). 25

Team performance is often described in terms of inputs, processes and outputs (IPO). 22 26–28 Outputs like quality of care, errors or performance are influenced by team related processes (ie, teamwork) like communication, coordination or decision-making. Furthermore, these processes are influenced by various inputs like team members’ experience, task complexity, time pressure and more. The IPO framework emphasises the critical role of team processes as the mechanism by which team members combine their resources and abilities, shaped by the context, to resolve team task demands. It has been the basis of other more advanced models 27–29 but has also been criticised because of its simplicity. 30 However, it is still the most popular framework to date and helps to systematise the mechanisms that predict team performance and represents the basis for the selection of the studies included in our meta-analysis.

Contextual factors of teamwork effectiveness

Based on a large body of team research from various domains, we hypothesise that several contextual and methodological factors might moderate the effectiveness of teamwork, indicating that teamwork is more important under certain conditions. 31 32 Therefore, we investigate several factors: (a) team characteristics (ie, professional composition, team familiarity, team size), (b) task type (ie, routine vs non-routine tasks), (c) two methodological factors related to patient realism (ie, simulated vs real) and (d) the type of performance measures used (ie, process vs outcome performance). In the following we discuss these potentially moderating factors and the proposed effects on teamwork.

Professional composition

We distinguished between interprofessional and uniprofessional teams. Interprofessional teams consist of members from various professions that must work together in a coordinated fashion. 33 Diverse educational paths in interprofessional teams may shape respective values, beliefs, attitudes and behaviours. 34 As a result team members with different backgrounds might perceive and interpret the environment differently and have a different understanding of how to work together. Therefore, we assume that explicit teamwork is especially important in interprofessional teams compared with uniprofessional teams.

Team familiarity

If team members have worked together, they are familiar with their individual working styles; and roles and responsibilities are usually clear. If a team works together for the first time, this potential lack of familiarity and clarity might make teamwork even more important. Therefore, we differentiate between real teams that also work together in their everyday clinical practice and experiential teams that only came together for study purposes.

Another factor that may moderate the relationship between teamwork and performance is team size. Since larger teams exhibit more linkages among members than smaller teams, they also face greater coordination challenges. Also, with increasing size teams have greater difficulty developing and maintaining role structures and responsibilities. For these reasons, we expect the influence of teamwork on clinical performance to be stronger in larger teams as compared with smaller teams.

Routine situations are characterised by repetitive and unvarying actions (eg, standard anaesthesia induction). 35 In contrast, non-routine situations exhibit more variation and uncertainty, requiring teams to be flexible and adaptive. Whereas team members mostly rely on pre-learned sequences during routine situations, during non-routine situations we assume that teamwork is more important in order for team members to resolve task demands.

Patient realism

Authors highlight the importance of using medical simulators in education. 36 Therefore, we investigate the realism used in a study (simulated vs real patients) as a potential methodological factor that influences the relationship between teamwork and performance. Studies conducted with medical simulators might be more standardised and less influenced by confounding variables than studies conducted with real patients. Therefore, results from simulation studies might show stronger relationships between the two variables. Further, using a simulator could cause individuals and teams to act differently than in real settings, thereby distorting the results. However, in the last decade high-fidelity simulators have become increasingly realistic, suggesting that the results from simulation studies generalise to real environments. Including realism as a contextual factor in our analysis will reveal if the effects of teamwork observed in simulation compare with real life settings. Better understanding would provide important insights about simulation use in teamwork studies.

Performance measures

As a second methodological factor, we expect that the type of performance measure used in a study influences the reported teamwork effectiveness. The literature usually differentiates between process-related and outcome-related aspects of performance. 37 38 Process performance measures are action-related aspects and refer to adequate behaviour during procedures (eg, adhering to guidelines), making them easier to assess. Outcome performance measures (eg, infection rates after operations) follow team actions, with assessment occurring later than process measures. Outcome performance measures suffer from several factors: greater sensitivity to confounding variables (eg, comorbidities), assessment challenges and greater difficulty linking team processes to outcomes. Looking at the predictors of the survival of cardiac arrest patients illustrates the difference between the two types of performance measures. The main predictors for the survival (ie, performance outcome) of a cardiac arrest patient are ‘duration of the arrest’ and ‘age of the patient less than 70’ . 39 Although a team delivers perfect basic life support (ie, high process performance) the patient can still die (ie, low outcome performance). Due to these methodological considerations, we expect that studies assessing process performance report a stronger relationship between teamwork and performance than studies assessing outcome performance.

The study was conducted based on the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement 40 as well as established guidelines in social sciences. 41 42 Through the combination of studies in the meta-analytical process, we will increase the statistical power and provide an accurate estimation of the true impact that teamwork has on performance.

Search strategy

We applied the following search strategy to select relevant papers: ( a ) an electronic search of the database PubMed (no limit was placed on the date of publication, last search 19 June 2018) using the keywords teamwork , coordination , decision-making , leadership and communication in combination with patient safety , clinical performance , the final syntax for PubMed is available ( online supplementary file ), (b) a manual backwards search for all references cited by eight systematic literature reviews that focus on teamwork or non-technical skills in various healthcare domains, 8 15 17 43–47 (c) a manual backwards search for all references cited in studies we included in our meta-analysis, (d) a manual forward search using Web of Science to identify studies that cite the studies we included in our meta-analysis, (e) identification of relevant unpublished manuscripts via email from authors currently investigating medical teams using specific mailing lists.

Supplementary data

Inclusion criteria.

Studies were included if a construct complied to the definition of teamwork processes outlined in the introduction (eg, coordination, communication). In addition, studies needed to investigate the relationship between at least one teamwork process and a performance measure (eg, patient outcome). When studies reported multiple estimates of the same relationship from the same sample (eg, between coordination and more than one indicator of performance), those correlations were examined separately only as appropriate for sub-analyses, but an average correlation was computed for all global meta-analyses of those relationships to maintain independence. 41 We excluded articles investigating long-term care since the coordination of care for chronically ill patients has to consider the unique team task interdependencies in this setting. 48 Also, teams working together over longer periods of time are more likely to develop emergent states (eg, team cohesion) that influence how a specific team works together. 24 All articles included in this meta-analysis are listed in tables 1 and 2 .

Descriptions of study objectives, settings and description of teamwork process and outcome measures

ICU, intensive care unit.

Studies, effect sizes and moderator variables included in the meta-analytical database

*Carlson, Min & Bridges has been identified as an outlier and therefore excluded from the analysis.

†Effect sizes ( r ) with an † represent an average for a single sample and a single outcome and have been combined for this meta-analysis.

For the criterion level of analysis, we included only effect sizes at the team level and not on an individual level. Therefore, the performance measure had to be clearly linked to a team. This approach aligns with research that strongly recommends against mixing levels of analysis in meta-analytical integrations. 49 50

Two reviewers independently screened titles and abstracts from articles yielded in the search. Afterwards full texts of all relevant articles were obtained and screened by the same two reviewers. Agreement was above 90%. Any disagreement in the selection process was resolved through consensus discussion.

Data extraction

With the help of a jointly developed coding scheme, studies were independently coded by one of the authors (JS) and another rater, both with a background in industrial psychology and human factors. Twenty per cent of the studies were rated by both coders. Intercoder agreement was above 90%. Any disagreement was resolved through discussion. The data extracted comprised details of the authors and publication as well as important study characteristics and statistical relationships between a teamwork variable and performance ( table 2 ).

Coding of team characteristics

The professional composition of teams was coded either as ‘Interprofessional’ if a team consisted of members from different professions (eg, nurses and physicians) or as ‘Uniprofessional’ if the members of the teams were of the same profession. Team size was coded as the number of members (average number if team size varied) of the investigated teams. Team familiarity was coded either as ‘experimental’ or ‘real’. ‘Real’ indicates that the team members also worked together in their everyday clinical practice. ‘Experimental’ means that the teams only worked together during the study.

Coding of task characteristics

Task type was coded either as ‘Routine task’ or ‘Non-routine task’. We defined ‘Non-routine tasks’ as unexpected events that require flexible behaviour often under time-pressure (eg, emergency situations). ‘Routine tasks’ describe previously planned standard procedures (eg, standard anaesthesia induction, planned surgery).

Coding of methodological factors

Patient realism was either coded as ‘Real patient’ or ‘Simulated patient’. ‘Simulated patient’ included a patient simulator (manikin) whereas ‘Real patient’ included real patients in clinical settings.

Clinical performance measures were coded either as ‘Outcome performance’ or ‘Process performance’. 38 51 ‘Outcome performance’ includes an outcome that is measured after the treatment process (eg, infection rate, mortality). We focused only on patient-related outcomes and not on team outcomes (eg, team satisfaction). ‘Process performance’ describes the evaluation of the treatment process and describes how well the process was executed (eg, adherence to guidelines through expert rating). Process performance measures are often based on official guidelines and extensive expert knowledge. 52 Thus, we assumed that process performance closely relates to patient outcomes.

Statistical analysis

Different types of effect sizes (eg, OR, F values and r ) have been reported in the original studies. We therefore converted the different effect sizes to a common metric, namely r using the formulas provided by Borenstein et al 53 and Walker. 54 Moreover, some samples contained effect sizes of teamwork with two or more measures of performance. Because independence of the included effects sizes is required for a meta-analysis, 41 55 we used Fisher’s z score to average the multiple correlations from the same sample (scholars have suggested to convert r to Fisher's z scores, to average the z’s and then to backtransform it to r . 56 Using simple arithmetic average (ie, correlations will be summed and divided by the number of coefficients) is problematic because the distribution of r becomes negatively skewed as the correlation is larger than zero. As a result, the average r tends to underestimate the population correlation). The correlations were weighted for sample size. However, in contrast to many meta-analyses in social sciences, the correlations were not adjusted for measurement reliability. This is because information about the measurement reliability could not be compared (Kappa vs Cronbach’s Alpha) or were not available at all for the majority of studies. Therefore, we report uncorrected, sample-size weighted mean correlation, its 95% CI, and the 80% credibility interval (CR). The CI reflects the accuracy of a point estimate and can be used to examine the significance of the effect size estimates, whereas the CR refers to the deviation of these estimates and informs us about the existence of possible moderators.

Random-effects models were estimated based on two considerations. 57 First, we expected study heterogeneity to be high given the different study design characteristics such as patient realism (‘Real patient’ vs ‘Simulated patient’), task type (‘Routine task’ vs ‘Non-routine task’) and different forms of performance measures. Second, we aimed to provide an inference on the average effect in the entire population of studies from which the included studies are assumed to be a random selection of it. Therefore, random-effects models were estimated. 57 These models were calculated by the restricted maximum-likelihood estimator, an efficient and unbiased estimator. 58 Since we included only descriptive studies and no interventions we only included the sample size of the individual studies as a potential bias into the meta-analysis. To rule out a potential publication bias, we tested for funnel plot asymmetry using the random-effect version of the Egger test. 59 The results indicate that there is no asymmetry in the funnel plot (z=1.79, p=0.074), suggesting that there is no publication bias.

The estimation of meta-analytical models including the outlier analyses were performed with the package ‘metafor’ from the programming language and statistical environment R. 58

The online search resulted in 2002 articles ( figure 1 ). Two studies were identified via contacting authors directly and have been presented at conferences in the past. 60 61 After duplicates were removed 1988 articles were screened using title and abstract. Sixty-seven articles were then selected for a full text review. Full text examination, forward and backward search of selected articles and relevant reviews resulted in 30 studies coming from 28 articles (two publications presented two independent studies in one publication 62 63 ). This led to a total of 32 studies coming from 30 articles. Following the recommendation by Viechtbauer and Cheung, 64 we screened for outliers using studentized deleted residuals. One case (Carlson et al , 9 r =0.89, n=44, studentized deleted residuals=4.26) was identified as outlier and therefore excluded from further analyses, resulting in a final sample size of k =31.

Systematic literature search.

Table 1 provides a qualitative description of the selected articles including study objectives, the setting in which the studies were carried out and a description of the teamwork processes as well as the outcome measures that were assessed. If a specific tool for the assessment of a teamwork process or outcome measure was used this is indicated in the corresponding column. Observational studies were most prevalent. Teamwork processes were assessed using either behaviourally anchored rating scales (n=8) or structured observation (n=19) of specific teamwork behaviour. Structured observation — as we describe it — is defined as a purely descriptive assessment of certain behaviour usually using a predefined observation system (eg, amount of speaking up behaviour). In contrast, behaviourally anchored rating scales consist of an evaluation of teamwork process behaviour by an expert. Only three studies used surveys to assess teamwork behaviours. The majority of the studies (n = 27) assessed process performance using either a checklist based expert rating or assessing a reaction time measure after the occurrence of a certain event (eg, time until intervention). Only four studies assessed outcome performance measures. Measures included accuracy of diagnosis, postoperative complications and death, surgical morbidity and mortality, ventilator-associated pneumonia, bloodstream infections, pressure ulcers and acute physiology and chronic health evaluation score. Table 2 provides an overview of all variables included in the meta-analysis including the effect sizes and moderator variables.

Effect of teamwork and contextual factors

Table 3 and figure 2 shows the relationship between teamwork and team performance. The sample-sized weighted mean correlation was 0.28 (95% CI 0.20 to 0.35, z =6.55, p<0.001), indicating that teamwork is positively related to clinical performance. Results further indicated heterogeneous effect size distributions across the included samples ( Q =53.73, p<0.05, I 2 =45.96), signifying that the variability across the sample effect sizes was more than what would be expected from sampling error alone.

Relationship between teamwork processes and performance.

Meta-analytical relationships between teamwork and clinical performance

* p < .05.

I 2 = % of total variability in the effect size estimates due to heterogeneity among true effects (vs sampling error).

†Team size was entered as a continuous variable, therefore, no subgroup analyses exist.

CI, confidence interval; CR, credibility interval; K, number of studies; N, cumulative sample size (number of teams); Q, test statistic for residual heterogeneity of the models; r, sample-size weighted correlation.

To test for moderator effects of the contextual factors, we conducted mixed-effects models including the mentioned moderators: professional composition, team familiarity, team size, task type, patient realism and performance measures .

The omnibus test of moderators was not significant ( F =0.18, df 1 =6, df 2 =18, p>0.20), suggesting that the examined contextual factors did not influence the average effect of teamwork on clinical performance. To provide greater detail about the role of the contextual factors, we conducted separate analyses for the categorical contextual factors and report them in table 3 .

With this study, we aimed to provide evidence for the performance implications of teamwork in healthcare teams. By including various contextual factors, we investigated potential contingencies that these factors might have on the relationship between teamwork and clinical performance. The analysis of 1390 teams from 31 different studies showed that teamwork has a medium sized effect ( r =0.28 65 66 ;) on clinical performance across various care settings. Our study is the first to investigate this relationship quantitatively with a meta-analytical procedure. This finding aligns with and advances previous work that explored this relationship in a qualitative way. 8 15 17 43–47

At first glance a correlation of r =0.28 might not seem very high. However, we would like to highlight that r =0.28 is considered a medium sized effect 65 66 and should not be underestimated. To better illustrate what this effect means we transformed the correlation into an OR of 2.8. 53 Of course, this transformation simplifies the correlation because teamwork and often the outcome measures are not simple dichotomous variables that can be divided into an intervention and control group. However, this transformation illustrates that teams who engage in teamwork processes are 2.8 times more likely to achieve high performance than teams who are not. Looking at the performance measures in our study we see that they either describe patient outcomes (eg, mortality, morbidity) or are closely related to patient outcomes (eg, adherence to treatment guidelines). Thus, we consider teamwork a performance-relevant process that needs to be promoted through training and implementation into treatment guidelines and policies.

The included studies used a variety of different measures for clinical performance. This variability resulted from the different clinical contexts in which the studies were carried out. There is no universal measure for clinical performance because the outcome is in most cases context specific. In surgery, common performance measures are surgical complications, mortality or morbidity. 67 In anaesthesia, studies often use expert ratings based on checklists to assess the provision of anaesthesia. Expert ratings are also the common form of performance assessment in simulator settings where patient outcomes like morbidity or mortality cannot be measured. Future studies need to be aware that clinical performance measures depend on the clinical context and that the development of valid performance measures requires considerable effort and scientific rigour. Guidelines on how to develop performance assessment tools for specific clinical scenarios exist and need to be accounted for. 52 68 69 Furthermore, depending on the clinical setting researchers need to evaluate what specific clinical performance measures are suitable and if and how they can be linked to team processes in a meaningful way.

The analysis of moderators illustrates that teamwork is related with performance under a variety of conditions. Our results suggest that teams in different contexts characterised by different team constellations, team size and levels of acuity of care all benefit from teamwork. Therefore, clinicians and educators from all fields should strive to maintain or increase effective teamwork. In recent years, there has been an upsurge in crisis resource management (CRM). 19 These trainings focus on team management and implement various teamwork principles during crisis situations (eg, emergencies). 70 Our results suggest that team trainings should not only focus on non-routine situations like emergencies but also on routine situations (eg, routine anaesthesia induction, routine surgery) because based on our data teamwork is equally important in such situations.

A closer look at methodological factors of the included studies revealed that the observed relationship between teamwork and performance in simulation settings does not differ from relationships observed in real settings. Therefore, we conclude that teamwork studies conducted in simulation settings generalise to real life settings in acute care. Further, the analysis of different performance measures reveals a trend towards process performance measures being more strongly related with teamwork than outcome performance measures. A possible explanation of this finding relates to the difficulty of investigating outcome performance measures in a manner isolated from other variables. Nevertheless, we still found a significant relationship between teamwork and objective patient outcomes (eg, postoperative complications, bloodstream infections) despite the methodological challenges of measuring outcome performance and the small number of studies using outcome performance ( k =4).

Our results are in line with previous meta-analyses investigating the effectiveness of team training in healthcare. 18 19 Similar to our results, Hughes et al highlighted the effectiveness of team trainings under a variety of conditions — irrespective of team composition, 18 simulator fidelity or patient acuity of the trainee’s unit as well as other factors.

We were unable to find a moderation of task type in our study, potentially explained by task interdependence, which reflects the degree to which team members depend on one another for their effort, information and resources. 71 A meta-analysis including teams from multiple industries (eg, project teams, management teams) found that task interdependence moderates the relationship between teamwork and performance, demonstrating the importance of teamwork for highly interdependent team tasks. 72 Most studies included in our analysis focused on rather short and intense patient care episodes (eg, a surgery, a resuscitation task) with high task interdependence, which may explain the high relevance of teamwork for all these teams.

Limitations and future directions

Despite greater attention to healthcare team research and team training over the last decade, we were only able to identify 32 studies (31 included in the meta-analysis). Of note, over two-thirds of the studies in our analysis emerged in the last 10 years, reflecting the increasing interest in the topic. The rather small number of studies might relate to the difficulties in quantifying teamwork, the considerable theoretical and methodological knowledge required and the challenges of capturing relevant outcome measures. Also, besides the manual searches of selected articles and reviews and contacting authors in the field we did only search the database PubMed. PubMed is the most common database to access papers that potentially investigate medical teams and includes approximately 30 000 journals from the field of medicine, psychology and management. We are fairly confident that through the additional inclusion of relevant reviews and forward and backwards search, our results represent an accurate representation of what can be found in the literature.

Future research should build on recent theoretical and applied work 24 26 28 73 about teamwork and use this current meta-analysis as a signpost for future investigations. In order to move our field forward, we must use existing conceptual frameworks 22 24 26 and establish standards for investigating teams and teamwork. This can often only be achieved with interdisciplinary research teams including experts from the medical fields but equally important from health professions education, psychology or communication studies.

Another limitation relates to the unbalanced analysis of subgroups. For example, we only identified four studies that used outcome performance variables compared with 27 using process performance measures. Uneven groups may reduce the power to detect significant differences. Therefore, we encourage future studies to include outcome performance measures despite the effort required.

Finally, more factors may influence the relationship between teamwork and performance that we were unable to extract from the studies. While we tested for the effects of team familiarity by comparing experimental teams and real teams, this does not fully capture team member familiarity. The extent to which team members actually worked together during prior clinical practice might predict of how effectively they perform together. However, even two people working in the same ward might actually not have interacted much during patient care depending on the setting. Also team climate on a ward or in a hospital may be an important predictor of how well teams work together, especially related to sharing information or speaking up within the team. 74 75

Finally, the clinical context might play a role in how team members collaborate. In different disciplines, departments or healthcare institutions different norms and routines exist on how to work together. Therefore, study results and recommendations about teamwork need to be interpreted in the light of the respective clinical context. There are empirical indications that a one-size-fits-all approach might not be suitable and team training efforts cannot ignore the clinical context, especially the routines and norms about collaboration. 76 We acknowledge that there might be other factors surrounding healthcare teams that might potentially influence teamwork and clinical performance. However, in this review we could only extract data that was reported in the primary studies. Since these were limited in the healthcare contexts studied, the results might not generalise to long-term care settings or mental health, for example. Future work needs to consider and also document a broader range of potentially influencing factors.

The current meta-analysis confirms that teamwork across various team compositions represents a powerful process to improve patient care. Good teamwork can be achieved by joint reflection about teamwork during clinical event debriefings 77 78 as well as team trainings 79 and system improvement. All healthcare organisations should recognise these findings and place continuous efforts into maintaining and improving teamwork for the benefit of their patients.

Supplementary Material

Acknowledgments.

The authors thank Manuel Stühlinger for his help with study selection and data extraction and Walter J. Eppich, MD, PhD for a critical review and proofreading the manuscript.

Contributors: All authors substantially contributed to this study and were involved in the study design. JS drafted the paper. LM analysed the data and revised the manuscript for content. TM revised the manuscript for content and language. All authors approved the final version.

Funding: This work was funded by the European Society of Anaesthesiology (ESA) and the Swiss National Science Foundation (SNSF, Grant No. P300P1_177695). The ESA provided resources for an additional research assistant helping with literature search and selection. Part of the salary of JS was funded by the SNSF.

Competing interests: None declared.

Patient and public involvement statement: Patients and public were not involved in this study.

Patient consent for publication: Not required.

Provenance and peer review: Not commissioned; externally peer reviewed.

Data availability statement: Data are available upon reasonable request.

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• NATURE CAREERS PODCAST
• 28 November 2019

Working Scientist podcast: Team PhD

Julie gould discusses how the science phd can be more team based, and how doctoral programmes in other academic disciplines have changed..

Is science ready for "Team PhD", whereby a group of students work more collaboratively, delivering a multi-authored thesis at their end of their programme?

Jeanette Woolard, who recently secured a £4.5m Wellcome Trust grant to fund a four-year collaborative doctoral training programme in her lab at the University of Nottingham, UK, believes it could happen one day.

"The team driven PhD is not a distant dream. It's a soon-to-be fulfilled reality," Woolard, a professor of cardiovascular physiology and pharmacology, tells Julie Gould. "If you give it enough of an incentive and wave the flag hard enough for team science, it will come."

Woolard's Wellcome grant allows four graduate students to have their own research focus, but to work collaboratively. "Each of the individual candidates are still pursuing an individual PhD and they will each write up an individual thesis at the end of their four year period of study," she says, arguing that the scientific community and students themselves aren't yet ready for programmes that culminate in a team focused thesis. "I think individual students still either like the idea or deserve the opportunity to defend their own piece of work at the end of their studies."

The new programme at Nottingham, she says, provides students with "the most collaborative environment possible, and the opportunity to work together as much as they can, to utilise as many skills as are available, and to really experience a dynamic, collaborative team-driven environment."

She adds: "Ultimately that's what there are going to experience especially if they go into industry or pursue excellence in academia. Our best outputs now are judged as being multidisciplinary."

A team thesis may be some way off in science, but what about other disciplines? Jill Perry is Executive Director at the Carnegie Project. She tells Gould how the project is helping to redefine the education doctorate in the US.

doi: https://doi.org/10.1038/d41586-019-03685-z

Julie Gould

Hello, I’m Julie Gould and this is Working Scientist, a Nature Careers podcast. This episode asks whether the future of the PhD, like science, could be based in teamwork.

Now, in the previous episode, David Bogle from University College London made the point that PhD candidates need to be brought into the scientific community and not to feel like they are left alone to fend for themselves in a competitive environment. Now, one way to do this is to think about how science is actually done and to embed this into the PhD training system. Scientific research is no longer the endeavour of a single person. Just like any other role, it requires a team of people. Now, team science is the collaborative effort to address scientific and often global challenges, and many governments, publics and other stakeholders are encouraging scientists to get involved in bigger picture global problems – climate change, global health etc. But these problems can’t be done by just one research field, let alone one scientist. These challenges are tackled by large, interdisciplinary and often international collaborations and networks of people. So, if science has fundamentally become a team effort, can this filter down into PhD training? Can a PhD be done as a team? Now, when I wrote my article for Nature on how to build a better PhD in 2015, David Golan, who is the dean of graduate education at Harvard Medical School in Boston, Massachusetts, was considering engraining teamwork more deeply into the graduate school experience. I couldn’t get hold of Professor Golan for this podcast, but I did have a chance to speak to Jill Perry. She’s the executive director of the Carnegie Project on the Education Doctorate in the USA and a faculty member at the University of Pittsburgh. Now, the Carnegie Project on the Education Doctorate has been working since 2007 to redefine the education doctorate, and in that time, they have explored different ways of doing the doctorate. So, Jill told me a little bit about how some of the institutions she works with have incorporated teamwork into their education doctorate via a group dissertation model.

So, there’s a couple of different features in these. There are places where students are put together by the faculty, there are places where students come together on their own, some of the faculties vet what the students are going to do ahead of time and assign them, in other places, students are supposed to find those problems, but the goal is that they’re working collaboratively just as they would in practice to understand and solve problems. Let me think of the first example I have. So, consultancy model is one of those, where the faculty vet contracts that come in from local school districts or universities or educational organisations that want to have a group come in and assess and evaluate some work that they’ve been doing. So, for instance, a school district might come in and say we want to have a team of your students come out and assess our new reading programme that we’ve implemented for the last year. So, the faculty will vet these and they will say great idea, this one will work, and then they put together teams of students who would be interested in doing that. So, those teams of students then have a process that they go through where they are trained in evaluation and they go out as a team over a year and they gather data from the organisation in which they are working, and then they put together a final report and evaluation with recommendations and that is presented to both their faculty as well as the organisation they work for. All of that is done in teams and they divide up the work. Each takes a different piece and then they write the final product together. Another model is where a group of students will come together on their own because they have similar interests in something and they want to focus their work together but also a little bit separately, so they might come together and explore the literature together around a similar problem, they might focus on one institution, one school they want to go in to together, but then look at the problem differently and do separate studies and sort of write a chapter that is a different study of each but then they have sort of the opening together and the end conclusions together and so it’s been written both together and individually.

And how are these teams assessed?

That is different at every institution. That was one of our big concerns. Many faculties said, well, how do you know, and I think one of the biggest answers was when you get to that level of doctorate education, the students are holding themselves accountable and so everyone is assigned what they’re doing and the group knows who’s not doing what, so that’s one of the big pieces, that they hold each other accountable the same way they would in practice, in their work setting. The faculty generally have mechanisms to be able to understand at the onset what student is taking on what part and then during their proposal phase as well as their defence phase, they have to describe the pieces that they took on individually and how they tackle that work, and so it’s a very closely run process with faculty, so they understand where the students are and what they’re doing, but then a lot of it really is the students holding each other accountable for it. They all get the same, I don’t want to say grade because they don’t necessarily get grades, but their graduation and their doctorates depend on everybody pulling their weight and working together.

Has there been a situation where in a team someone hasn’t pulled their weight? Does the whole group then not get awarded the doctorate or is just that one person not awarded the doctorate?

I don’t know for 100% sure how that works, but my guess would be that it wouldn’t reach the defence without someone having said so-and-so isn’t pulling their weight. So, I do know a faculty who have had to have interventions and talk to students and have removed people from groups if things haven’t worked, but they’re not necessarily waiting until setting the defence for somebody to say Joe didn’t do anything, so that kind of stuff is embedded in the process throughout the year-long dissertation work.

Do you think this sort of dissertation would work in other disciplines like the sciences?

I think it depends on what the goal is. So, if the goal is to create faculty members who are collaborative in the work that they do, say, in community engaged scholarship, then it may be a good thing, right, because right now the PhD tends to train us to be siloes, to focus on our own work, to be competitive against one another because ultimately, we’re going to a university, we’re trying to get tenure, and so we need to prove ourselves and we don’t want to get stuck in the mess of dealing with Joe’s not pulling his weight kind of thing. But if you’re thinking more about as we have here with the PhD in social sciences and making that work more applied, then when you think about applied, you start to think about the impact you have on communities and peoples’ lives, and how else are you going to have greater impact than if you have teamwork being done on that? So, if you think of like team-based healthcare, right, when you go into a hospital, bringing in different people with different perspectives to assess a patient, why couldn’t something like that be done in a PhD programme to gain a better understanding of a whole system within a scientific realm of whatever you’re looking at.

Now, the team dissertation might not be happening yet in the natural sciences, but team-oriented PhDs are. In September this year, the Wellcome Trust announced the PhD programmes it was going to fund, and one of the teams this year is led by Jeanette Woolard from the University of Nottingham. She was awarded funding from the Wellcome Trust to run a team science PhD focused on drug discovery, the first of its kind in the UK. So, in this programme, each year, four candidates will come together as a team on to her programme to do a PhD in cancer angiogenesis, but each researcher will have a different background and set of skills and work together as a team. So, I wanted to know what this PhD is going to look like.

Right, so the four candidates will have their own focus, but the idea is that each of their projects will be related and connected to other projects. So, for example, if the students are studying a particular type of receptor associated with cancer, then they will be using related either technologies or related drugs and drug candidates to investigate within their systems how the new models are functioning and what the readouts are telling them about their particular area of research. So, for example, if a student is working on the receptor for vascular endothelial growth factors – this is a growth factor that’s really important in cancer angiogenesis and it’s a target of many novel therapeutics that aim to block VEGF signalling and stop the growth of blood vessels in and around a tumour – and so if you have a student who’s working on mathematical modelling and systems, pharmacology and more of a bioinformatics approach, they might come up with a mathematical model for how angiogenesis is working that they would like to test in a particular system. And they’ll be speaking to a student who’s maybe working on that in terms of how a new drug or ligand that they’ve developed is interacting with that receptor, and so the two of them would then have some discussion about studies that could be set up that are mutually beneficial to both projects. And there might be aspects of one that goes into one thesis and aspects of the other that goes into the other thesis, but it’s about that open communication to enhance both projects.

Would they then maybe work together with another third student who would do the physical experiments and then produce the results?

Yes, exactly, and so you can see how there’s almost like a cyclical approach to it and so there may be that the student that’s working more in cells develops a construct as a consequence of those interactions, so somebody’s modelling something, somebody’s testing something in the cell, gives it to another person who’s testing it in an isolated blood vessel, gives it to somebody who then tests it in a whole system, and although they’re working on seemingly distinct aspects, they’re all related and the whole team together is able to deliver a much bigger, more impactful output because there is a relationship between and amongst the four of them.

And of course, once it gets through the system, it may be that they say actually, we need this tweaking and so that feeds back into the modelling system to enhance that project, and it could be from the whole systems side or it could be from the cells side and so that the modelling system is then looked at and changed and developed, rather than it simply being a mathematical modelling system that they hope one day might be tested, but that goes beyond the scope of that study.

And so, how does it work then when it comes to assessing these PhD candidates and how is that done in relation to team science?

This was something that we discussed quite extensively and what I need to make quite clear is that each of the individual candidates are still pursuing an individual driven PhD and they will individually write up their thesis at the end of their four-year period of study based largely around contributions that they have made to their own independent pursuits. There will of course be, for example, the opportunity where a student might develop a construct and that construct might then go on and be utilised by another student in a different system, and to help take that second project forward or to help take it in a slightly novel direction, but each of the students will still come out with their own independent PhD. It is team driven by the support and the network that underpins it.

Okay, so it’s not like a group of researchers who will be publishing a paper together as they would publish a PhD thesis together, that’s now how you’re approaching this?

No, and we have had to be very clear about that at this time. I think that the wider community perhaps isn’t ready for a team-driven PhD output, and I think individual PhD students still perhaps either like the idea or deserve the opportunity to defend their own piece of work at the end of their studies, but what we do want to provide them with is the most collaborative environment possible, where they have the opportunity to work together as much as they can, to utilise as many skills as are available and to really experience a collaborative, dynamic, team-driven environment because ultimately, that’s what they’re going to experience, especially if they go into industry or pursue excellence in academia. Our best outputs now are judged as being multidisciplinary.

Why do you believe that the wider community is not ready for something like a team-published PhD thesis?

I think it comes down to teasing out and having policies or the mechanisms to dissect out what contribution actually means to a team-driven exercise. It’s quite easy to see when an individual has written up their three or four experimental chapters front-ended and back-ended by an introduction and a decent discussion. You can see that that individual has contributed significantly to the field, and there is a sense of ownership for them and for the institution over the document that then becomes their published thesis. On a team-driven exercise, I guess questions would be asked about the size, the length, and how you would tease out the degree of contribution, and I suppose at the moment those decisions about how that is judged perhaps hasn’t really been discussed at length.

Why can’t there be a thesis with more than one author for a PhD?

Well, I think it’s just a matter of time and changing culture and I think that if you give it enough of an incentive and wave the flag hard enough for team science, that it will come, and I think that the team driven PhD is not as distant dream. It’s a soon-to-be fulfilled reality.

Thank you to Jill Perry and Jeanette Woolard for contributing to this episode, and thank you to you for listening. I’m Julie Gould.

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If teams are so good.. : science teachers' conceptions of teams and teamwork

Smith, Gregory William (2009) If teams are so good.. : science teachers' conceptions of teams and teamwork. PhD thesis, Queensland University of Technology.

Description

The focus of this study is the phenomenon of teams and teamwork. Currently the Professional Standards of Queensland’s teachers state that teams are critical to teachers’ work. This study uses a phenomenographic approach to investigate science teachers’ conceptions of teams and teamwork in the science departments of fifteen Queensland State secondary schools. The research identifies eight conceptions of teams and teamwork. The research findings suggest that the team represents a collective of science teachers bounded by the Science Department and their current timetabled subject. Collaboration was found in the study to be an activity that occurred between teachers in the same social space. The research recognises a new category of relationship between teachers, designated as ‘ask-and-receive’. The research identifies a lack of teamwork within the science department and the school. There appears to be no teaming with other subject departments. The research findings highlight the non-supportive team and teamwork policies, procedures and structures in the schools and identify the lack of recognition of the specialised skills of science teachers. The implications for the schools and science teachers are considerable, as the current Professional Standards of Education Queensland and the Queensland College of Teachers provide benchmarks of knowledge and practice of teams and teamwork for teachers. The research suggests that the professional standards relating to teams and teamwork cannot be achieved in the present school environment.

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Emotion at work: Stories of teamwork, stress, and professionalism

Mark A Mierswa , University of Massachusetts Amherst

This study explores some of the consequences of everyday moments of interpersonal interaction within an organization. The primary research questions concern the grammar of episodes of "frustration" and episodes of "success," or those moments that employees identify as working well. What is "frustration" here? How does it affect the person who experiences it? How does its performance affect others in the office? How is it made and re-made, and with what consequences, in everyday moments of interaction? The study explores these questions from a communication perspective using the Coordinated Management of Meaning (CMM) theory of communication. The main contribution of this study lies in the application of the method. The CMM theory of communication encourages the analyst to understand the ways in which utterances may participate in multiple important stories simultaneously (stories of identity, relationship, and organization, for example). In this case study, the experience and consequences of "stress" may be best understood only in the context of stories of "teamwork" and "professionalism." This study is not about emotion itself. Rather, it presents an approach to engaging in research about emotional displays at work and the consequences of their enactment on the employees, their relationships, and the organization itself. Communication, or the telling and living of stories in patterned ways, is at the heart of this approach.

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Communication|Occupational psychology

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Mierswa, Mark A, "Emotion at work: Stories of teamwork, stress, and professionalism" (2006). Doctoral Dissertations Available from Proquest . AAI3215916. https://scholarworks.umass.edu/dissertations/AAI3215916

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Search for dissertations about: "teamwork"

Showing result 1 - 5 of 123 swedish dissertations containing the word teamwork .

1. A Deeper Understanding of Real Teamwork and Sustainable Quality Culture

Author : Lilly-Mari Sten ; Pernilla Ingelsson ; Marie Häggström ; Mattias Elg ; Mittuniversitetet ; [] Keywords : TEKNIK OCH TEKNOLOGIER ; ENGINEERING AND TECHNOLOGY ; ICU transitional care ; QM ; quality management ; real team ; real teamwork ; sustainable quality culture ; TMT ; team ; teamwork ; top management team ;

Abstract : Today's organisations are faced with increasingly complicated and complex challenges. To master these challenges, organisations need to work more together, both within their own organisations and in collaboration with others. Working as a ‘real’ team, while also creating a sustainable quality culture, can be one way to address these challenges. READ MORE

2. Human-automation teamwork : Current practices and future directions in air traffic control

Author : Åsa Svensson ; Jonas Lundberg ; Camilla Forsell ; Niklas Rönnberg ; Henrik Artman ; Linköpings universitet ; [] Keywords : NATURVETENSKAP ; NATURAL SCIENCES ;

Abstract : This dissertation explores the topic of human-automation teamwork in Air Traffic Control (ATC). ATC is a high stakes environment where complex automation is being introduced while the human operator has the legal responsibility. READ MORE

3. Communication and teamwork : Studies of the impact on quality of drug use in swedish nursing homes

Author : Ingrid Schmidt ; Uppsala universitet ; [] Keywords : MEDICIN OCH HÄLSOVETENSKAP ; MEDICAL AND HEALTH SCIENCES ; Pharmacy ; nursing homes ; elderly ; drug use ; psychotropics ; quality ; randomized controlled trial ; multidisciplinary interventions ; teams ; communication ; FARMACI ; PHARMACY ; FARMACI ; Biopharmaceutics ; biofarmaci ;

Abstract : This thesis examines factors that affect the quality of drug-use practices in Swedish nursing homes.The analysis comprises six consecutive studies. READ MORE

4. Collaboration in Health and Social Care : Service User Participation and Teamwork in Interprofessional Clinical Microsystems

Author : Susanne Kvarnström ; Elisabet Cedersund ; Berith Hedberg ; Boel Andersson-Gäre ; Pirjo Nikander ; Jönköping University ; [] Keywords : SAMHÄLLSVETENSKAP ; SOCIAL SCIENCES ; consumer participation ; collaboration ; empowerment ; microsystem ; interprofessional ; teamwork ; service user participation ; social citizenship. ; Social work ; Socialt arbete ;

Abstract : This thesis addresses the relationship between citizens and the welfare state with a focus on the collaboration between service users and professionals in Swedish health and social care services. The overall aim of the thesis was to explore how professionals and service users experience collaboration in health and social care. READ MORE

5. Aspects of teamwork and intraoperative factors in the operating room

Author : Sofia Erestam ; Göteborgs universitet ; [] Keywords : MEDICIN OCH HÄLSOVETENSKAP ; MEDICAL AND HEALTH SCIENCES ; operating room ; non-technical skills ; teamwork ; intraoperative stress ;

Abstract : The work in high-risk environments like an operating room is complex. The operating team consist of many professions with different tasks cooperating towards a common goal, the performance of safe surgery. The operating teams’ technical and non-technical skills may affect the surgical outcome. READ MORE

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Dissertations / Theses on the topic 'Dynamic teamwork'

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Gerhardt, Clara, Kristie Chandler, and Celeste Hill. "Collaborative Teamwork: For Better or For Worse." Digital Commons @ East Tennessee State University, 2018. https://dc.etsu.edu/secfr-conf/2018/schedule/15.

Koutsikouri, Dina. "Individual and collective success : the social dynamics of multidisciplinary design teamwork." Thesis, Loughborough University, 2010. https://dspace.lboro.ac.uk/2134/6383.

Wickwire, Tamara L. "The dynamics involved in same-sex dyadic sport teams." Thesis, McGill University, 2003. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=19671.

Westmoreland, Kierra M. "Improving Team Performance in Age-Diverse Teams Using Lean Simulations." Ohio University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1430755355.

Alegbeleye, Ibukun. "A Mixed Methods Study of Leader-Follower Dynamics in Student Project Teams: Toward Advancing Career Readiness." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/97891.

Chiu, Hsiu Mei, and 邱秀美. "Building Dynamic Teamwork by using Groupware." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/12453042271625933466.

Keskin, Tayfun. "Collaborative information technology moderation in dynamic teamwork with team member departure." Thesis, 2010. http://hdl.handle.net/2152/ETD-UT-2010-05-1354.

Tausczik, Yla Rebecca. "Changing group dynamics through computerized language feedback." Thesis, 2012. http://hdl.handle.net/2152/ETD-UT-2012-08-5971.

Allen, Brooke. "The effect of leadership training on athlete satisfaction and group dynamics." 2005. http://www.oregonpdf.org.

Graça, Ana Margarida de Faria e. Silva Carvalho. "The role of team leadership on the dynamics of teamwork: the relevance of context and time." Doctoral thesis, 2013. http://hdl.handle.net/10071/8787.

NOVÁKOVÁ, Petra. "Vliv teambuildingu na sociální klima v organizaci." Master's thesis, 2014. http://www.nusl.cz/ntk/nusl-170790.

(9234419), Behzad Beigpourian. "UNDERSTANDING THE RELATIONSHIP BETWEEN TEAM DYNAMICS ON PEER EVALUATIONS AND TEAM EFFECTIVENESS." Thesis, 2020.

Engineering students are expected to develop professional skills in addition to their technical knowledge as outcomes of accredited engineering programs. Among the most critical professional skills is the ability to work effectively in a team. Working effectively in teams has learning benefits and also provides an environment for developing other professional skills such as communication, leadership skills, and time management. However, students will develop those skills only if their teams function effectively.

This dissertation includes three studies that together inform team formation and management practices to improve team dynamics. The first study investigates mixed-gender team dynamics to determine whether those teams are realizing their potential. The second study explores the relationship of individual psychological safety and students’ team member effectiveness and the moderating effects of team-level psychological safety. The third study explores self-rating bias among first-year engineering students and its relationship to student characteristics and dimensions of team-member effectiveness.

Although mixed-gender teams had equal team dynamics with all-male teams, more team facilitation and training are needed to improve the experience of mixed-gender teams. Asian, Black, and Hispanic/Latino students, as well as students with lower GPA, report lower psychological safety, which is associated with lower team-member effectiveness. Team-level psychological safety moderated this effect for Asian and Hispanic/Latino students. Students’ effort in teams was associated with lower self-rating bias, likely an indication of greater self-awareness. Together, these studies and their findings contribute to a broader understanding that there are interrelationships among team composition, team dynamics, and team-member effectiveness, and that these relationships differ based on student characteristics such as race/ethnicity, gender, and prior knowledge. This work adds to the body of research demonstrating the importance of teaching students about effective teamwork, conducting regular peer evaluations of team functioning, and interpreting those peer evaluations carefully to avoid perpetuating any biases. This work also demonstrates the usefulness of psychological safety as an important indicator of marginalization.

Magro, Maria Brites da Conceição Martins. "O papel dos gestores intermédios na liderança, organização e supervisão de professores numa escola com 3º ciclo e ensino secundário." Master's thesis, 2014. http://hdl.handle.net/10400.14/17282.

Lamirande, Maxim. "Describing and understanding team integration in new product development : a case study." Thesis, 2020. http://hdl.handle.net/1866/24118.

Moola, Sabihah. "Communication dynamics in producing effective patient care : a case study at Stanger Hospital’s diabetes clinic in Kwazulu-Natal, South Africa." Thesis, 2015. http://hdl.handle.net/10500/20679.

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ART H 800 A: Doctoral Dissertation

Afro-American Studies Doctoral Candidate Karl Lyn Awarded Prestigious 2024 Wenner-Gren Foundation Dissertation Fieldwork Grant

Karl Lyn, Ph.D. candidate in the W.E.B. Du Bois Department of Afro-American Studies, has been named a recipient of the prestigious 2024 Wenner-Gren Foundation Dissertation Fieldwork Grant for his project, “Citizenship in the City: Black Political Culture, Community, and Possibility in South Central Los Angeles.” 

The Wenner-Gren Foundation funds doctoral research that advances anthropological knowledge, with the goal of supporting vibrant and significant work that furthers the understanding of what it means to be human. This grant will support Lyn’s ethnographic research in Los Angeles, where he will explore how Black residents formulate their political identities amid growing inequality and in a democracy that has not always proven accessible or effective for Black communities. His project expands beyond descriptions of what is lacking in urban neighborhoods to capture the ways residents have long created spaces and sources of sustenance that are embedded in their daily political practices.

Reflecting on his achievement, Lyn says, “I see getting the Wenner-Gren as an opportunity to push the boundaries of academic disciplinarity to engage with and create whatever knowledge is useful to build alternative conditions for a new world.”

Reviewers of Lyn’s project assessed the quality of research, its potential contributions to anthropological knowledge, and its capacity to provoke transformative dialogue in the field. Scholars who reviewed Lyn’s project shared the following:

“The project’s rethinking of apathy amidst emerging conditions of precarity is a crucial novel contribution of this work. By situating political life in the everyday, the project thinks with shifting demographics and housing displacements of a historically Black majority area over time to offer a needed perspective about how this generation of young adults attends to the political.”

“This study makes room for articulating sets of political actions that aren’t framed around agency in terms of reaction to hegemonic structures but rather makes room for the expansive everyday imagination of cultural projects that make life liveable amidst organized abandonment.” 

“By thinking with the question of ethnographic refusal as a key aspect of his research methodology and allowing participants to shape how they represent their political and cultural projects in a context that over-surveils young Black people, this project is methodologically and epistemologically significant.”

In addition to the Wenner-Gren Foundation's support, Lyn's research has garnered support from the Ford Foundation, National Science Foundation, American Psychological Association, and the National Council for Black Studies.

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