Team Size Research Articles

Statewide implementation of high-fidelity recovery-oriented ACT: A case study.

Assertive Community Treatment (ACT) is a recognized evidence-based practice, but the use of Translation Science to ensure the broad implementation of high quality ACT services has not yet been fully explored. This single intrinsic case study explores how Oregon uses strategies identified through Translation Science to achieve statewide implementation of high-fidelity recovery-oriented ACT. Multiple data sources were used to evaluate this implementation process, including ACT fidelity review reports, programmatic outcome data, a national ACT taskforce survey, and focus groups with program participants. In 2013, the Oregon Health Authority funded the creation of the Oregon Center of Excellence for Assertive Community Treatment to support the implementation of ACT. It also implemented administrative rules requiring an annual re-certification process with a minimum level of fidelity to the evidence-based model. Other implementation strategies included establishing an ACT Advisory Committee, quarterly reviews of implementation and outcome data, and trainings promoting the role of peer providers and related evidence-based practices. High-fidelity recovery-oriented ACT services in Oregon are maintained through multiple strategies, including codifying the minimum level of ACT implementation into state administrative rule, linking fidelity benchmarks scores to Medicaid reimbursements, and funding ongoing oversight, training and technical assistance through a statewide technical assistance center. Strict adherence to the ACT model has been a key to ensuring a uniform level of high-quality care across Oregon while incorporating additional evidence-based practices without compromising the integrity of the original model. Assertive Community Treatment (ACT) is a mental health program serving individuals with the most severe mental illness in the community. While ACT is an evidence-based practice, there is more research needed to explore how ACT is implemented and maintained in different settings. In 2013, Oregon implemented ACT statewide. The Oregon Center of Excellence for ACT was created to provide training and technical assistance to ACT teams and conduct yearly fidelity reviews. Oregon is among the few states who have attached funding to yearly ACT certification, uses community sizes to determine the size of the ACT teams, and the technical assistance center not only provides training but also conducts yearly review of fidelity to the ACT model. This case study will review the steps Oregon took to implement ACT, how it continues to monitor fidelity to the model and provide training and support, and focus on recovery orientation and integrating evidence-based practices. Continued support, training, and the linking of fidelity benchmark scores to program funding are the ways that Oregon makes sure that ACT teams are successfully implementing the ACT model to fidelity with recovery-oriented care.

Experience of the rapid implementation of a pioneering telehealth service during the COVID-19 crisis

Abstract: Introduction: Based on a national ordinance that regulates and operationalizes telemedicine as one of the measures to cope with the public health emergency resulting from the COVID-19 epidemic, a partnership was established between the federal university and municipal management for the rapid implementation of the telehealth service for COVID-19. Experience report: Experience report on the implementation process of the specific telehealth service for COVID-19, a partnership between the academy and the service. Discussion: The implementation process requires team sizing, physical space and technological resources, training and continuous education of the team to align the actions, for the agreement and articulation of the call center and telemonitoring flowchart with the local health network at all levels of care, disclosure of the service to the population, attention to ethical aspects, criteria for issuing documents, standing out and integration of the team regarding the clinical approach in teleconsultation and telemonitoring. Conclusion: The experience of implementing the Telehealth Covid service in 27 days is reported in this article, and it is likely to be replicated by other municipalities, as a contingency measure due to COVID-19. The significant number of visits, the social mission of the public university and its articulation with the local health system stand out after two months of operation.

Experience of the rapid implementation of a pioneering telehealth service during the COVID-19 crisis

Abstract: Introduction: Based on a national ordinance that regulates and operationalizes telemedicine as one of the measures to cope with the public health emergency resulting from the COVID-19 epidemic, a partnership was established between the federal university and municipal management for the rapid implementation of the telehealth service for COVID-19. Experience report: Experience report on the implementation process of the specific telehealth service for COVID-19, a partnership between the academy and the service. Discussion: The implementation process requires team sizing, physical space and technological resources, training and continuous education of the team to align the actions, for the agreement and articulation of the call center and telemonitoring flowchart with the local health network at all levels of care, disclosure of the service to the population, attention to ethical aspects, criteria for issuing documents, standing out and integration of the team regarding the clinical approach in teleconsultation and telemonitoring. Conclusion: The experience of implementing the Telehealth Covid service in 27 days is reported in this article, and it is likely to be replicated by other municipalities, as a contingency measure due to COVID-19. The significant number of visits, the social mission of the public university and its articulation with the local health system stand out after two months of operation.

Genetic Fuzzy Based Scalable System of Distributed Robots for a Collaborative Task.

This paper introduces a new genetic fuzzy based paradigm for developing scalable set of decentralized homogenous robots for a collaborative task. In this work, the number of robots in the team can be changed without any additional training. The dynamic problem considered in this work involves multiple stationary robots that are assigned with the goal of bringing a common effector, which is physically connected to each of these robots through cables, to any arbitrary target position within the workspace of the robots. The robots do not communicate with each other. This means that each robot has no explicit knowledge of the actions of the other robots in the team. At any instant, the robots only have information related to the common effector and the target. Genetic Fuzzy System (GFS) framework is used to train controllers for the robots to achieve the common goal. The same GFS model is shared among all robots. This way, we take advantage of the homogeneity of the robots to reduce the training parameters. This also provides the capability to scale to any team size without any additional training. This paper shows the effectiveness of this methodology by testing the system on an extensive set of cases involving teams with different number of robots. Although the robots are stationary, the GFS framework presented in this paper does not put any restriction on the placement of the robots. This paper describes the scalable GFS framework and its applicability across a wide set of cases involving a variety of team sizes and robot locations. We also show results in the case of moving targets.

Success factors in Capsim’s Capstone simulation: An empirical examination

The Capstone business strategy simulation has been used in business schools throughout the world. Scholars have investigated the impact of Capstone and other simulations on student learning, but there are no published studies that investigate factors associated with success. This study examines the performance of 7,347 participants using Capstone in 2019. Results suggest an optimal team size of four students. Overall, teams performed better in the competition mode than in the footrace mode, and better in official rounds than in practice rounds. Completion of training modules was associated with improved team performance in some but not all instances.

Toward an Economically Optimal Team Design in IT-Related Innovation Projects

Driven by the increased relevance of digitalised and hypercompetitive business environments, companies need to focus on IT-related innovation projects (ITIPs) to guarantee long-term success. Although prior research has illustrated that an appropriate team design can increase project performance, an approach for determining the economically optimal team design from an ex ante perspective is missing. Against this backdrop, we follow analytical modelling research and develop a model that determines the optimal team design for an ITIP by transferring central findings of previous research regarding relevant influencing factors, e.g., team size and academic background diversity, into an ex ante economic evaluation. Thereby, our model allows the comparison of different team designs (i.e., team compositions) with regard to the prospective monetary project performance. Generally, the results show that only about a fifth of the random team designs resulted in a positive profit. In contrast, the well-founded, optimal team designs proposed by our model led to a positive profit in almost 90% of all cases. Regarding the influencing parameters, we observe that team size is the most important factor since a deviation from the optimum has a much more significant effect on the expected profit than do other factors such as work experience. To ensure the real-world fidelity and applicability of our model, we discuss the underlying assumptions with two practitioners. Our contribution is manifold: Inter alia, from an academic perspective, we enhance existing research on team design by converting well-accepted qualitative findings from a frequently investigated field outside business administration (i.e., [social] psychology) into a quantitative model that allows for the ex ante economic evaluation of team design parameters. For practitioners, we provide a model that assists managers in designing ITIP teams that are more likely to deliver desired results. This model enables managers to avoid relying only on gut feeling when designing ITIP teams, as is currently often the case due to a lack of alternative approaches.

WhoReview: A multi-objective search-based approach for code reviewers recommendation in modern code review

Contemporary software development is distributed and characterized by high dynamics with continuous and frequent changes to fix defects, add new user requirements or adapt to other environmental changes. To manage such changes and ensure software quality, modern code review is broadly adopted as a common and effective practice. Yet several open-source as well as commercial software projects have adopted peer code review as a crucial practice to ensure the quality of their software products using modern tool-based code review. Nevertheless, the selection of peer reviewers is still merely a manual and hard task especially with the growing size of distributed development teams. Indeed, it has been proven that inappropriate peer reviewers selection can consume more time and effort from both developers and reviewers and increase the development costs and time to market. To address this problem, we introduce a multi-objective search-based approach, named WhoReview, to find the optimal set of peer reviewers for code changes. We use the Indicator-Based Evolutionary Algorithm (IBEA) to find the best set of code reviewers that are (1) most experienced with the code change to be reviewed, while (2) considering their current workload, i.e., the number of open code reviews they are working on. We conduct an empirical study on 4 long-lived open source software projects to evaluate our approach. The obtained results show that WhoReview outperforms state-of-the-art approach by an average precision of 68% and recall of 77%. Moreover, we deployed our approach in an industrial context and evaluated it qualitatively from developers perspective. Results show the effectiveness of our approach with a high acceptance ratio in identifying relevant reviewers.

Mitigating Biases in CORD-19 for Analyzing COVID-19 Literature.

On the behest of the Office of Science and Technology Policy in the White House, six institutions, including ours, have created an open research dataset called COVID-19 Research Dataset (CORD-19) to facilitate the development of question-answering systems that can assist researchers in finding relevant research on COVID-19. As of May 27, 2020, CORD-19 includes more than 100,000 open access publications from major publishers and PubMed as well as preprint articles deposited into medRxiv, bioRxiv, and arXiv. Recent years, however, have also seen question-answering and other machine learning systems exhibit harmful behaviors to humans due to biases in the training data. It is imperative and only ethical for modern scientists to be vigilant in inspecting and be prepared to mitigate the potential biases when working with any datasets. This article describes a framework to examine biases in scientific document collections like CORD-19 by comparing their properties with those derived from the citation behaviors of the entire scientific community. In total, three expanded sets are created for the analyses: 1) the enclosure set CORD-19E composed of CORD-19 articles and their references and citations, mirroring the methodology used in the renowned “A Century of Physics” analysis; 2) the full closure graph CORD-19C that recursively includes references starting with CORD-19; and 3) the inflection closure CORD-19I, that is, a much smaller subset of CORD-19C but already appropriate for statistical analysis based on the theory of the scale-free nature of the citation network. Taken together, all these expanded datasets show much smoother trends when used to analyze global COVID-19 research. The results suggest that while CORD-19 exhibits a strong tilt toward recent and topically focused articles, the knowledge being explored to attack the pandemic encompasses a much longer time span and is very interdisciplinary. A question-answering system with such expanded scope of knowledge may perform better in understanding the literature and answering related questions. However, while CORD-19 appears to have topical coverage biases compared to the expanded sets, the collaboration patterns, especially in terms of team sizes and geographical distributions, are captured very well already in CORD-19 as the raw statistics and trends agree with those from larger datasets.

Relationships Between Communication, Time Pressure, Workload, Task Complexity, Logistical Issues and Group Composition in Transdisciplinary Teams: A Prospective Observational Study Across 822 Cancer Cases

Introduction. Functional perspective of team decision-making highlights the importance of understanding the relationship between team interaction/communication during a given task, the internal factors that emanate from within a group (e.g. team composition), and the external circumstances (e.g. workload and time pressures). As an underexplored area, we explored these relationships in the context of multidisciplinary team (MDT) meetings (aka tumor boards). Materials and methods. Three cancer MDTs with 44 team members were recruited from 3 teaching hospitals in the United Kingdom. Thirty of their weekly meetings encompassing 822 case reviews were filmed. Validated instruments were used to assess each case: Bales’ Interaction Process Analysis that captures frequency of task-oriented and socio-emotional interactions/communication; and Measure of case-Discussion Complexity that captures clinical and logistic complexities. We also measured team size, disciplinary diversity, gender, time-workload pressure, and time-on-task. Partial correlation analysis controlling for team/tumor type and case complexity was used for analysis. Results. Clinical complexity positively correlated with task-oriented communication, e.g. gives opinion (r=0.51, p 0.05), however, case reviews with more males present were associated with more tension (r=0.09, p<0.01) and less disagreements (r=-0.11, p<0.01), while when more females present there were more disagreements (r=0.10, p<0.01) and less tension (r=-0.11, p<0.01). Discussion. To the best of our knowledge, this is the first study to assess the relationship between MDT interaction/communication and the external/internal factors. Smaller size, gender balanced teams with core disciplines present, and streamlining workload to reduce time-workload pressure, time-on-task effects, and logistical issues appear more conducive to building and maintain optimal MDTs. Our methodology could be applied to other MDT-driven areas of healthcare.

Relationship of Clinician Care Team Composition and Diabetes Quality Outcomes.

The objective was to determine if a greater proportion of physician full-time equivalent (FTE%) relative to nurse practitioners/physician assistants (NPs/PAs) on care teams was associated with improved individual clinician diabetes quality outcomes. The authors conducted a retrospective cross-sectional study of 420 family medicine clinicians in 110 care teams in a Midwest health system, using administrative data from January 1, 2017 to December 31, 2017. Poisson regression was used to examine the relationship between physician FTE% and the number of patients meeting 5 criteria included in a composite metric for diabetes management (D5). Covariates included panel size, clinician type, sex, years in practice, region, patient satisfaction, care team size, rural location, and panel complexity. Of the 420 clinicians, 167 (40%) were NP/PA staff and 253 (60%) were physicians. D5 criteria were achieved in 37.9% of NP/PA panels compared with 44.5% of physician panels (P < .001). In adjusted analysis, rate of patients achieving D5 was unrelated to physician FTE% on the care team (P = .78). Physicians had a 1.082 (95% confidence interval 1.007-1.164) times greater rate of patients with diabetes achieving D5 than NPs/PAs. Clinicians at rural locations had a .904 (.852-.959) times lower rate of achieving D5 than those at urban locations. Physicians had a greater rate of patients achieving D5 compared with NPs/PAs, but physician FTE% on the care team was unrelated to D5 outcomes. This suggests that clinician team composition matters less than team roles and the dynamics of collaborative care between members.

A Content Management System as an Information Management System in Interdisciplinary Research

Teams of scientific specialists have replaced independent researchers, simultaneously the research team size has increased by 50% over the 19‑year period. Better collaborations between project team members might improve research outcomes or R&amp;D project products. Knowledge needs to be communicated among a research team effectively and shared among all research team members as it is created collaboratively. Collaboration can be successfully supported by providing a knowledge sharing environment and communication facilities. The purpose of this paper is to evaluate the feasibility and discuss novel communication among scientists using a content management system (CMS) which operates based on the Software‑as‑a‑Service (SaaS) cloud‑computing model. This study presents the use of CMS for the collaboration of a research team carrying out a research project funded by the Polish National Science Centre.

Does research collaboration influence the “disruption” of articles? Evidence from neurosciences

A new indicator (the disruption index) quantifying the extent to which a paper disrupts or consolidates established knowledge was recently introduced from the perspective of subsequent use of the current knowledge. This study explored whether different types of collaboration (i.e., at the author, institution, and country levels) equally affect the disruption of papers. We selected 505,168 papers from Neurosciences indexed in the Web of Science from 1954–2011 and employed logistic regression analysis. Our principal findings are that team size and international collaboration are negatively associated with the disruption of articles, while an additional increase in the number of domestic institutions of a team statistically favors disruption.

The persistence and dynamics of new venture growth

Extensive research has suggested that new ventures’ growth rates lack persistence. However, existing studies tend not to differentiate between positive and negative growth rates or examine their respective persistence and dynamics. Building on performance feedback theory, we show that positive and negative growth rates exhibit different dynamics over time. Especially, negative growth rates are less likely to persist and more likely to reverse than positive ones. Furthermore, firm size and team size influence the persistence—or the lack of thereof—of both positive and negative growth rates. Specifically, new ventures that are smaller, as well as those managed by larger teams, are more likely to maintain positive growth and reverse negative growth, relative to their respective counterparts. Overall, this study suggests that positive and negative growth rates differ in their persistence and that new ventures can shape the dynamics of both positive and negative growth.

Scaling Research

In this session we'll play with scale in multiple senses. We'll look at value and evaluation, sample size and team size, and consider how the impact of ethnography scales in different ways.

Data to knowledge in action: A longitudinal analysis of GenBank metadata.

Studies typically use publication-based authorship data to study the relationships between collaboration networks and knowledge diffusion. However, collaboration in research often starts long before publication with data production efforts. In this project we ask how collaboration in data production networks affects and contributes to knowledge diffusion, as represented by patents, another form of knowledge diffusion. We drew our data from the metadata associated with genetic sequence records stored in the National Institutes of Health's GenBank database. After constructing networks for each year and aggregating summary statistics, regressions were used to test several hypotheses. Key among our findings is that data production team size is positively related to the number of patents each year. Also, when actors on average have more links, we tend to see more patents. Our study contributes in the area of science of science by highlighting the important role of data production in the diffusion of knowledge as measured by patents.

Decentralized Multi-agent information-theoretic control for target estimation and localization: finding gas leaks

This article presents a new decentralized multi-agent information-theoretic (DeMAIT) control algorithm for mobile sensors (agents). The algorithm leverages Bayesian estimation and information-theoretic motion planning for efficient and effective estimation and localization of a target, such as a chemical gas leak. The algorithm consists of: (1) a non-parametric Bayesian estimator, (2) an information-theoretic trajectory planner that generates “informative trajectories” for agents to follow, and (3) a controller and collision avoidance algorithm to ensure that each agent follows its trajectory as closely as possible in a safe manner. Advances include the use of a new information-gain metric and its analytical gradient, which do not depend on an infinite series like prior information metrics. Dynamic programming and multi-threading techniques are applied to efficiently compute the mutual information to minimize measurement uncertainty. The estimation and motion planning processes also take into account the dynamics of the sensors and agents. Extensive simulations are conducted to compare the performance between the DeMAIT algorithm to a traditional raster-scanning method and a clustering method with coordination. The main hypothesis that the DeMAIT algorithm outperforms the other two methods is validated, specifically where the average localization success rate for the DeMAIT algorithm is (a) higher and (b) more robust to changes in the source location, robot team size, and search area size than the raster-scanning and clustering methods. Finally, outdoor field experiments are conducted using a team of custom-built aerial robots equipped with gas concentration sensors to demonstrate efficacy of the DeMAIT algorithm to estimate and find the source of a propane gas leak.

Open science, communal culture, and women’s participation in the movement to improve science

Science is undergoing rapid change with the movement to improve science focused largely on reproducibility/replicability and open science practices. This moment of change-in which science turns inward to examine its methods and practices-provides an opportunity to address its historic lack of diversity and noninclusive culture. Through network modeling and semantic analysis, we provide an initial exploration of the structure, cultural frames, and women's participation in the open science and reproducibility literatures (n = 2,926 articles and conference proceedings). Network analyses suggest that the open science and reproducibility literatures are emerging relatively independently of each other, sharing few common papers or authors. We next examine whether the literatures differentially incorporate collaborative, prosocial ideals that are known to engage members of underrepresented groups more than independent, winner-takes-all approaches. We find that open science has a more connected, collaborative structure than does reproducibility. Semantic analyses of paper abstracts reveal that these literatures have adopted different cultural frames: open science includes more explicitly communal and prosocial language than does reproducibility. Finally, consistent with literature suggesting the diversity benefits of communal and prosocial purposes, we find that women publish more frequently in high-status author positions (first or last) within open science (vs. reproducibility). Furthermore, this finding is further patterned by team size and time. Women are more represented in larger teams within reproducibility, and women's participation is increasing in open science over time and decreasing in reproducibility. We conclude with actionable suggestions for cultivating a more prosocial and diverse culture of science.

Examining the Role of Top Management in Corporate Sustainability: Does Supply Chain Position Matter?

A burgeoning stream of sustainability research explores the role of companies’ top management team (TMT) characteristics in corporate sustainability efforts, while another stream investigates the effect of a company’s supply chain position on its likelihood of engaging in sustainability. This study shows the importance of integrating the two research streams by demonstrating that supply chain position moderates the relationship between TMT characteristics and sustainability and thus establishes boundary conditions for this relationship. By matching 758 corporate sustainability initiatives with control observations, our results show that the size of the top executive team and the average age of its members, two well-known predictors of corporate sustainability, are distinctly moderated by supply chain position. While business-to-business (B2B) companies are less likely to report a sustainability initiative compared to business-to-consumer (B2C) organizations, we found that B2B TMT size has a greater positive effect on sustainability initiative likelihood than B2C TMT size. Conversely, average B2C TMT age has greater predictive power in explaining sustainability initiative likelihood than average B2B TMT age. The implications of these findings in advancing corporate sustainability and organizational change are discussed.

Factors Responsible for the Success of a Start-up: A Meta-Analytic Approach

This article aims to determine factors crucial for the performance of new ventures by performing a meta-analysis. It evaluates the performance of machine learning and statistical models by selecting 19 studies through preferred reporting items for systematic reviews and meta-analyses (PRISMA). The results obtained were graphically represented using forest plots. A subjective analysis of the studies revealed “business plan,” “market scope,” “team size,” “service timing,” “market growth,” and “age of the entrepreneur” as crucial factors for deciding the performance of the new ventures. In machine learning model-based studies, the combined model was found to be statistically significant. The variables, namely, “seed funding,” “funding rounds,” “location,” “social media presence,” “team size,” “number of founding members,” and “defunct date” affect the predictive capability of these models. The implications of this article can be applied by start-ups to reduce uncertainty and enhance performance.

No place like home redesign: home-based clinical care as an interprofessional training model for medical and pharmacy students

ABSTRACT Proper program assessment is necessary to ensure the delivered curriculum aligns with the intended curriculum. No Place Like Home (NPLH) is an interprofessional experience in which a healthcare team provides clinical services to patients in a home environment. Following review of program evaluation data, we determined the original design of NPLH was not meeting the intended objectives, and NPLH was redesigned in January 2018. Changes include lengthening the experience, decreasing the team size, improving assessment tools and additional training for the preceptors. The revised curriculum includes a care team with a preceptor, a medical, and a pharmacy student who visit four to six patients on an assigned day. From May 1, 2018 to April 30, 2019, there were 320 students who participated in NPLH. The preceptor assessments of students across the five objectives had mean scores of 3.4–3.7 on a 4 point scale indicating that on average preceptors placed students between Demonstrates Competence and Demonstrates Excellence for all objectives. When students were asked to compare their ability to collaborate interprofessionally after NPLH to the time before, 79% stated Somewhat Better Now or Much Better Now. It is not sufficient to create interprofessional learning activities and assume learning objectives are being met. Ongoing performance assessment and curricular evaluation are essential to ensure such goals are achieved. When intended objectives are not being met, it is possible to make deliberate and purposeful changes to redirect interprofessional learning experiences while maintaining the integrity, novelty and uniqueness of the experience.