How to enrich team research in healthcare by considering five theoretical perspectives

The aim of this paper is to inspire team research to apply diverse and unconventional perspectives to study team dynamics and performance in healthcare settings. To illustrate that using multiple perspectives can yield valuable insights, we examine a segment of a team interaction during a heart-surgery, using five distinct interdisciplinary perspectives known from small group research: the psychodynamic, functional, conflict-power-status, temporal, and social identity perspectives. We briefly describe each theoretical perspective, discuss its application to study healthcare teams, and present possible research questions for the segment at hand using the respective perspective. We also highlight the benefits and challenges associated with employing these diverse approaches and explore how they can be integrated to analyze team processes in health care. Finally, we offer our own insights and opinions on the integration of these approaches, as well as the types of data required to conduct such analyses. We also point to further research avenues and highlight the benefits associated with employing these diverse approaches. Finally, we offer our own insights and opinions on the integration of these approaches, as well as the types of data required to conduct such analyses

Feedback, fairness, and validity: effects of disclosing and reusing multiple-choice questions in medical schools.

BACKGROUND Disclosure of items used in multiple-choice-question (MCQ) exams may decrease student anxiety and improve transparency, feedback, and test-enhanced learning but potentially compromises the reliability and fairness of exams if items are eventually reused. Evidence regarding whether disclosure and reuse of test items change item psychometrics is scarce and inconclusive. METHODS We retrospectively analysed difficulty and discrimination coefficients of 10,148 MCQ items used between fall 2017 and fall 2019 in a large European medical school in which items were disclosed from fall 2017 onwards. We categorised items as 'new'; 'reused, not disclosed'; or 'reused, disclosed'. For reused items, we calculated the difference from their first ever use, that is, when they were new. Differences between categories and terms were analysed with one-way analyses of variance and independent-samples t tests. RESULTS The proportion of reused, disclosed items grew from 0% to 48.4%; mean difficulty coefficients increased from 0.70 to 0.76; that is, items became easier, P < .001, ηp2 = 0.011. On average, reused, disclosed items were significantly easier (M = 0.83) than reused, not disclosed items (M = 0.71) and entirely new items (M = 0.66), P < .001, ηp2 = 0.087. Mean discrimination coefficients increased from 0.21 to 0.23; that is, item became slightly more discriminating, P = .002, ηp2 = 0.002. CONCLUSIONS Disclosing test items provides the opportunity to enhance feedback and transparency in MCQ exams but potentially at the expense of decreased item reliability. Discrimination was positively affected. Our study may help weigh advantages and disadvantages of using previously disclosed items

How to enrich team research in healthcare by considering five theoretical perspectives.

The aim of this paper is to inspire team research to apply diverse and unconventional perspectives to study team dynamics and performance in healthcare settings. To illustrate that using multiple perspectives can yield valuable insights, we examine a segment of a team interaction during a heart-surgery, using five distinct interdisciplinary perspectives known from small group research: the psychodynamic, functional, conflict-power-status, temporal, and social identity perspectives. We briefly describe each theoretical perspective, discuss its application to study healthcare teams, and present possible research questions for the segment at hand using the respective perspective. We also highlight the benefits and challenges associated with employing these diverse approaches and explore how they can be integrated to analyze team processes in health care. Finally, we offer our own insights and opinions on the integration of these approaches, as well as the types of data required to conduct such analyses. We also point to further research avenues and highlight the benefits associated with employing these diverse approaches. Finally, we offer our own insights and opinions on the integration of these approaches, as well as the types of data required to conduct such analyses

The environment matters: Comparing individuals and dyads in their adaptive use of decision strategies

Individuals have been shown to adaptively select decision strategies depending on the environment structure. Two experiments extended this research to the group level. Subjects (N = 240) worked either individually or in two-person groups, or dyads, on a multi-attribute paired-comparison task. They were randomly assigned to two different environments that favored one of two prototypical decision strategies—weighted additive or take-the-best (between-subjects design in Experiment 1 and within-subject design in Experiment 2). Performance measures revealed that both individuals and dyads learned to adapt over time. A higher starting and overall performance rate in the environment in which weighted additive performed best led to the conclusion that weighted additive served as a default strategy. When this default strategy had to be replaced, because the environment structure favored take-the-best, the superior adaptive capacity of dyads became observable in the form of a steeper learning rate. Analyses of nominal dyads indicate that real dyads performed at the level of the best individuals. Fine-grained analyses of information-search data are presented. Results thus point to the strong moderating role of the environment structure when comparing individual with group performance and are discussed within the framework of adaptive strategy selection

Identifying low test-taking effort during low-stakes tests with the new Test-taking Effort Short Scale (TESS) – development and psychometrics

Background: Low-stakes tests are becoming increasingly important in international assessments of educational progress, and the validity of these results is essential especially as these results are often used for benchmarking. Test scores in these tests not only mirror students’ ability but also depend on their test-taking effort. One way to obtain more valid scores from participating samples is to identify test-takers with low test-taking effort and to exclude them from further analyses. Self-assessment is a convenient and quick way of measuring test-taking effort. We present the newly developed Test-taking Effort Short Scale (TESS), which comprises three items measuring attainment value/intrinsic value, utility value, and perceived benefits, respectively. Methods: In a multicenter validation study with N = 1837 medical students sitting a low-stakes progress test we analyzed item and test statistics including construct and external validity. Results: TESS showed very good psychometric properties. We propose an approach using stanine norms to determine a cutoff value for identifying participants with low test-taking effort. Conclusion: With just three items, TESS is shorter than most established self-assessment scales; it is thus suited for administration after low-stakes progress testing. However, further studies are necessary to establish its suitability for routine usage in assessment outside progress testing

Effects of interacting with a large language model compared with a human coach on the clinical diagnostic process and outcomes among fourth-year medical students: study protocol for a prospective, randomised experiment using patient vignettes.

INTRODUCTION Versatile large language models (LLMs) have the potential to augment diagnostic decision-making by assisting diagnosticians, thanks to their ability to engage in open-ended, natural conversations and their comprehensive knowledge access. Yet the novelty of LLMs in diagnostic decision-making introduces uncertainties regarding their impact. Clinicians unfamiliar with the use of LLMs in their professional context may rely on general attitudes towards LLMs more broadly, potentially hindering thoughtful use and critical evaluation of their input, leading to either over-reliance and lack of critical thinking or an unwillingness to use LLMs as diagnostic aids. To address these concerns, this study examines the influence on the diagnostic process and outcomes of interacting with an LLM compared with a human coach, and of prior training vs no training for interacting with either of these 'coaches'. Our findings aim to illuminate the potential benefits and risks of employing artificial intelligence (AI) in diagnostic decision-making. METHODS AND ANALYSIS We are conducting a prospective, randomised experiment with N=158 fourth-year medical students from Charité Medical School, Berlin, Germany. Participants are asked to diagnose patient vignettes after being assigned to either a human coach or ChatGPT and after either training or no training (both between-subject factors). We are specifically collecting data on the effects of using either of these 'coaches' and of additional training on information search, number of hypotheses entertained, diagnostic accuracy and confidence. Statistical methods will include linear mixed effects models. Exploratory analyses of the interaction patterns and attitudes towards AI will also generate more generalisable knowledge about the role of AI in medicine. ETHICS AND DISSEMINATION The Bern Cantonal Ethics Committee considered the study exempt from full ethical review (BASEC No: Req-2023-01396). All methods will be conducted in accordance with relevant guidelines and regulations. Participation is voluntary and informed consent will be obtained. Results will be published in peer-reviewed scientific medical journals. Authorship will be determined according to the International Committee of Medical Journal Editors guidelines

Exploring objective measures for assessing team performance in healthcare: an interview study.

INTRODUCTION Effective teamwork plays a critical role in achieving high-performance outcomes in healthcare. Consequently, conducting a comprehensive assessment of team performance is essential for providing meaningful feedback during team trainings and enabling comparisons in scientific studies. However, traditional methods like self-reports or behavior observations have limitations such as susceptibility to bias or being resource consuming. To overcome these limitations and gain a more comprehensive understanding of team processes and performance, the assessment of objective measures, such as physiological parameters, can be valuable. These objective measures can complement traditional methods and provide a more holistic view of team performance. The aim of this study was to explore the potential of the use of objective measures for evaluating team performance for research and training purposes. For this, experts in the field of research and medical simulation training were interviewed to gather their opinions, ideas, and concerns regarding this novel approach. METHODS A total of 34 medical and research experts participated in this exploratory qualitative study, engaging in semi-structured interviews. During the interview, experts were asked for (a) their opinion on measuring team performance with objective measures, (b) their ideas concerning potential objective measures suitable for measuring team performance of healthcare teams, and (c) their concerns regarding the use of objective measures for evaluating team performance. During data analysis responses were categorized per question. RESULTS The findings from the 34 interviews revealed a predominantly positive reception of the idea of utilizing objective measures for evaluating team performance. However, the experts reported limited experience in actively incorporating objective measures into their training and research. Nevertheless, they identified various potential objective measures, including acoustical, visual, physiological, and endocrinological measures and a time layer. Concerns were raised regarding feasibility, complexity, cost, and privacy issues associated with the use of objective measures. DISCUSSION The study highlights the opportunities and challenges associated with employing objective measures to assess healthcare team performance. It particularly emphasizes the concerns expressed by medical simulation experts and team researchers, providing valuable insights for developers, trainers, researchers, and healthcare professionals involved in the design, planning or utilization of objective measures in team training or research

Frequency and predictors of unspecific medical diagnoses in the emergency department: a prospective observational study.

BACKGROUND Misdiagnosis is a major public health problem, causing increased morbidity and mortality. In the busy setting of an emergency department (ED) patients are diagnosed under difficult circumstances. As a consequence, the ED diagnosis at hospital admittance may often be a descriptive diagnosis, such as "decreased general condition". Our objective was to determine in how far patients with such an unspecific ED diagnosis differ from patients with a specific ED diagnosis and whether they experience a worse outcome. METHODS We conducted a prospective observational study in Bern university hospital in Switzerland for all adult non-trauma patients admitted to any internal medicine ward from August 15th 2015 to December 7th 2015. Unspecific ED diagnoses were defined through the clinical classification software for ICD-10 by two outcome assessors. As outcome parameters, we assessed in-hospital mortality and length of hospital stay. RESULTS Six hundred eighty six consecutive patients were included. Unspecific diagnoses were identified in 100 (14.6%) of all consultations. Patients receiving an unspecific diagnosis at ED discharge were significantly more often women (56.0% vs. 43.9%, p = 0.024), presented more often with a non-specific complaint (34% vs. 21%, p = 0.004), were less often demonstrating an abnormal heart rate (5.0% vs. 12.5%, p = 0.03), and less often on antibiotics (32.0% vs. 49.0%, p = 0.002). Apart from these, no studied drug intake, laboratory or clinical data including change in diagnosis was associated significantly with an unspecific diagnosis. Unspecific diagnoses were neither associated with in-hospital mortality in multivariable analysis (OR = 1.74, 95% CI: 0.60-5.04; p = 0.305) adjusted for relevant confounders nor with length of hospital stay (GMR = 0.87, 95% CI: 0.23-3.32; p = 0.840). CONCLUSIONS Women and patients with non-specific presenting complaints and no abnormal heart rate are at risk of receiving unspecific ED diagnoses that do not allow for targeted treatment, discharge and prognosis. This study did not find an effect of such diagnoses on length of hospital stay nor in-hospital mortality