Decision Confidence Research Articles

MRI IN HYPERACUTE STROKE: EARLY EXPERIENCE

Background: In many institutions, computed tomography is the preferred neuroimaging modality for acute stroke (CT). MRI, on the other hand, is more sensitive in detecting infarct core. We present our early experience adopting MRI-first policy, using Putra Acute Stroke Protocol with 8-minute first 3 sequences, for hyperacute stroke. Methods: We retrospectively reviewed our early 6 months experience between June until Dec 2020. All hyperacute stroke cases who had MRI first and the door to needle (DTN) were evaluated. Results: There were total of 124 cases with 11 haemorrhagic stroke (8.9%) and 6 cases stroke mimics (4%). There were total of 105 cases of acute stroke, who had MRI first, where, 18 were thrombolysed (17.1%) while 8 cases had thrombectomy (7.6%). Fourteen were thrombolysed within 60 minutes (77.8%). DTN time range between 6 to 78 minutes with total accumulated time of 716 minutes, giving an average DTN of 42 minutes. Conclusion: Our experience shows there is no significant overall delay in DTN with higher percentage of thrombolysis rate. MRI-first policy, adopting Putra Acute Stroke Protocol, helps to achieve early and confident decision after the 8-minute scan. The stroke mimics and haemorrhagic stroke were excluded effectively. A more comprehensive study over a longer period to include other parameters might benefit the treatment decision for hyperacute stroke.

A Speech Recognition Method Based on Domain-Specific Datasets and Confidence Decision Networks.

This paper proposes a speech recognition method based on a domain-specific language speech network (DSL-Net) and a confidence decision network (CD-Net). The method involves automatically training a domain-specific dataset, using pre-trained model parameters for migration learning, and obtaining a domain-specific speech model. Importance sampling weights were set for the trained domain-specific speech model, which was then integrated with the trained speech model from the benchmark dataset. This integration automatically expands the lexical content of the model to accommodate the input speech based on the lexicon and language model. The adaptation attempts to address the issue of out-of-vocabulary words that are likely to arise in most realistic scenarios and utilizes external knowledge sources to extend the existing language model. By doing so, the approach enhances the adaptability of the language model in new domains or scenarios and improves the prediction accuracy of the model. For domain-specific vocabulary recognition, a deep fully convolutional neural network (DFCNN) and a candidate temporal classification (CTC)-based approach were employed to achieve effective recognition of domain-specific vocabulary. Furthermore, a confidence-based classifier was added to enhance the accuracy and robustness of the overall approach. In the experiments, the method was tested on a proprietary domain audio dataset and compared with an automatic speech recognition (ASR) system trained on a large-scale dataset. Based on experimental verification, the model achieved an accuracy improvement from 82% to 91% in the medical domain. The inclusion of domain-specific datasets resulted in a 5% to 7% enhancement over the baseline, while the introduction of model confidence further improved the baseline by 3% to 5%. These findings demonstrate the significance of incorporating domain-specific datasets and model confidence in advancing speech recognition technology.

Business Intelligence Using N-Beats And Rnn Methods End Influence On Decision Making In The Flexible Packaging Manufacturing

Today's complex decision-making solutions for intelligent manufacturing depend on the ability to be able to model a manufacturing system realistically, valid and consistent data integrated easily and in a timely manner, able to solve problems efficiently with computational effort to obtain optimal production and product quality optimizations continuously. When an organization uses a data-driven approach, it means that it makes strategic decisions based on data collection, analysis, and interpretations or insights. The purpose of this research is to analyze the business intelligence approach in optimizing print machines by speed, material and time. in this research, using the N-Beats is a deep neural architecture based on backward and forward residual links and a very deep stack of fully-connected layers and Recurrent Neural Networks (RNN). The novelty of this research is increasing machine speed using new insights by combining two deep learning methods. Observing and retrieving raw data from the printing machine process with sensors data for use and ensuring the justification of the addition of new methods. The result is expected to be able to provide new insights that can increase engine speed, the data based decision making provides businesses with the capabilities to generate real time insights and predictions to optimize their performance and provide confidence in decision making that are fast, precise and better.

What effects did home working have on 999 clinician practice from one UK ambulance service during the Covid-19 pandemic?

PurposeVirtual care is any interaction between a patient and clinician or clinicians, occurring remotely using information technologies. Like many international services, United Kingdom (UK) ambulance services use paramedics and nurses to undertake telephone assessments of patients calling the 999 emergency service line. Using their clinical knowledge, experience, and, at times, computer decision support software, these clinicians assess patients from a range of clinical acuities to confirm the need for an emergency response or identify and support those patients who can be cared for with remote treatment advice and referral. The Covid-19 pandemic saw UK ambulance services change and adapt their operating models to meet social distancing requirements, increase clinical staff numbers and mitigate staff becoming unavailable for work due to self-isolation. One such strategy was moving clinicians from Emergency Operations Centres (EOCs) to working at home. Staff utilised digital phone systems, remote computer-aided dispatch modules, remote clinical decision support software and video platforms, which allowed close to full functionality compared to inside typical EOCs. There is a dearth of literature exploring the comparative practice of clinicians from home rather than from EOCs. Therefore, this study reports the findings of a qualitative analysis of these effects from the clinician's perspective. The authors hope that the findings from this study will inform the operating, education and leadership practices of those delivering such services.Design/methodology/approachA convenience sample of telephone nurses and paramedics from one UK ambulance service in which home working had been implemented were contacted. 15 clinicians with recent home working experience responded to the invite out of a possible 31 (48%). All participants had previously practised remote assessment from within an EOC. Semi-structured interviews took place via video conferencing software and were recorded, transcribed and thematically analysed. An inductive approach was taken to generating codes and both researchers separately reading the transcripts before re-reading them, assigning initial themes and determining frequency.FindingsFour main themes were identified with further associated sub-themes: (1) performance, (2) support, (3) distractions and interruptions and (4) confidence in decision-making.Originality/valueThere are very few studies exploring the practice of remote clinicians in emergency EOCs. This study identified that home working clinicians felt their productivity had increased, making them more satisfied in their practice. However, there were mixed feelings over the level of support they perceived they now received, despite the mechanisms of support being largely the same. Supervisors found it especially challenging to provide support to practitioners; and employers might need to clarify the support mechanisms they provide to homeworkers. The elimination of distractions and interruptions was seen as a largely positive result of homeworking; however, these interruptions were not seen as inappropriate, thus, identifying a need for role clarity and task coordination rather than interruption elimination. Finally, clinicians felt that they become more confident when working from home, researching more, trusting themselves more and relying less on others to reach safe outcomes. However, there were missed opportunities to learn from listening to others' clinical practice.

Simultaneous identification of groundwater pollution source and important hydrogeological parameters considering the noise uncertainty of observational data.

Groundwater pollution identification is an inverse problem. When solving the inverse problem using regular methods such as simulation-optimization or stochastic statistical approaches, requires repeatedly calling the simulation model for forward calculations, which is a time-consuming process. Currently, the problem is often solved by building a surrogate model for the simulation model. However, the surrogate model is only an intermediate step in regular methods, such as the simulation-optimization method that also require the creation and solution of an optimization model with the minimum objective function, which adds complexity and time to the inversion task and presents an obstacle to achieving fast inversion. In the present study, the extreme gradient boosting (XGBoost) method and the back propagation neural network (BPNN) method were used to directly establish the mapping relationships between the output and input of the simulation model, which could directly obtain the inversion results of the variables to be identified (pollution sources release histories and hydraulic conductivities) based on actual observational data for fast inversion. In addition, to consider the uncertainty of observation data noise, the inversion accuracy of the two machine learning methods was compared, and the method with higher precision was selected for the uncertainty analysis. The results indicated that both the BPNN and XGBoost methods could perform inversion tasks well, with a mean absolute percentage error (MAPE) of 4.15% and 1.39%, respectively. Using the BPNN, with better accuracy for uncertainty analysis, when the maximum probabilistic density value was selected as the inversion result, the MAPE was 2.13%. We obtained the inversion results under different confidence levels and decision makers of groundwater pollution prevention and control can choose different inversion results according to their needs.

Expert opinions on strengths, weaknesses, opportunities, and threats of utilizing nuclear reactor waste heat for water desalination

Using waste heat generated by nuclear reactors for non-electric applications is vital for reducing environmental costs and thermal discharges. Waste heat is a significant portion of the reactor's overall energy and could reach up to two-thirds of the output power depending on the reactor design and efficiency. Despite the benefits of using waste heat, especially for essential applications like water desalination in areas with limited freshwater resources, the potential utilization is not yet applied. This study examines the strengths (S), weaknesses (W), opportunities (O), and threats (T) of using nuclear reactor waste heat for desalination in the Arabian Gulf region across four main areas: technical, environmental, socioeconomic, safety, and regulatory. The identified SWOT factors are combined with the Analytic Hierarchy Process (AHP) to prioritize them based on input from relevant experts. The resulting integrated SWOT-AHP analysis identified global factor priorities and concluded with five consistent measures to support decision-makers in evaluating the feasibility of utilizing nuclear reactor waste heat for seawater desalination. Overall, the study revealed that regulation and relevant safety measures present the primary obstacle in this application, while enabling research and development was emphasized as the key factor to address these issues and increase confidence in decision-making.

Factors influencing evidence-based practice among undergraduate nursing students: A cross-sectional analysis

ObjectiveThis study aimed to describe the current situation of evidence-based practice (EBP) among undergraduate nursing students in Thailand. MethodsA cross-sectional study was conducted. A convenience sample of 470 third- and fourth-year undergraduate nursing students from five public universities across Thailand participated in this study from January 2021 to March 2021. All participants were invited to complete a general information questionnaire, and the Student Evidence-Based Practice Questionnaire (S-EBPQ). ResultsThe overall mean S-EBPQ score was 5.29 ± 0.71, and the four subscales, from highest to lowest, were attitudes (5.50 ± 0.93), sharing and applying EBP (5.37 ± 0.87), practice (5.18 ± 0.84), and retrieving and reviewing evidence (5.10 ± 0.81). The current situation of S-EBPQ was higher among nursing students who had higher previous EBP studies, familiarity with research methods, confidence in clinical decision-making, preparedness in practice, and access to journals (P < 0.05). ConclusionsThis study’s findings provide valuable insights for planning strategies that can be integrated into the existing nursing curricula to enhance nursing undergraduates’ EBP application in clinical settings.

DATA-DRIVEN SMART MANUFACTURING: CASE STUDY OF WORKFORCE MANAGEMENT PROCESS IN AN ITALIAN LEATHER GOODS COMPANY

AbstractDigitalization is one of the fundamental pillars of Industry 4.0. Within smart factories, Big Data Analytics systems play a key role in supporting the decision-making process of various stages of business processes. In this context, this research aims to identify solutions able to process large volumes of data from digital business processes with the final goal of adding value to the organisation. More specifically, the research deals with the implementation of a digital manufacturing tool able to digitize the workforce management process. The research has been applied in the case study of an Italian manufacturing company operating in the leather goods sector through the digitalization of the workforce management by a cloud-based platform. The implementation of the tool increases the efficiency of the production process, provides efficient management and integrates workforce data into one system. The implemented tool generates a large volume of data, the final goal is to make data user-friendly to support business decisions. Digitisation provides an exchange of information to support managers to make confident decisions.

Building trust and empowering informed decisions: effects of risk disclosure and call to action on young adults’ responses to dietary supplement advertising

PurposeThis study aims to examine the effects of risk disclosure and call to action (i.e. encouraging individuals to consult a health provider before they make any purchase decision) on young adults’ cognitive and behavioral responses to dietary supplement advertising.Design/methodology/approachA 2 (risk disclosure: absence vs presence) × 2 (call to action: absence vs presence) between-subjects online experiment was conducted with 124 college-attending young adults.FindingsIncluding risk disclosure in probiotic supplement advertising increased young adults’ perceived message credibility, intentions to ask a medical doctor and sense of confidence in decision-making. The addition of call to action in probiotic supplement advertising improved perceived message credibility, trust in advertised brand, favorable attitude toward brand, intention to ask a medical doctor and purchase intention; however, a significant joint effect was not found between risk disclosure and call to action.Originality/valueAlthough risk disclosure and call to action are significant techniques in pharmaceutical and health-care marketing, they have been overlooked by both research and practice of dietary supplement marketing. This study closes this gap by providing empirical evidence to generate a clear idea about the benefits of including risk disclosure and call to action in dietary supplement advertising.

Evaluating the correlations of cost and utility parameters from summary statistics for probabilistic analysis in economic evaluations

ABSTRACT Objectives The correlations between economic modeling input parameters directly impact the variance and may impact the expected values of model outputs. However, correlation coefficients are not often reported in the literature. We aim to understand the correlations between model inputs for probabilistic analysis from summary statistics. Methods We provide proof that for correlated random variables X and Y (e.g. inpatient visits and outpatient visits), the Pearson correlation coefficients of sample means and samples are equal to each other (). Therefore, when studies report summary statistics of correlated parameters, we can quantify the correlation coefficient between parameters. Results We use examples to illustrate how to estimate the correlation coefficient between the incidence rates of non-severe and severe hypoglycemia events, and the common coefficient of five cost components for patients with diabetic foot ulcers. We further introduce three types of correlations for utilities and provide two examples to estimate the correlations for utilities based on published data. We also evaluate how correlations between cost parameters and utility parameters impact the cost-effectiveness results using a Markov model for major depression. Conclusion Incorporation of the correlations can improve the precision of cost-effectiveness results and increase confidence in evidence-based decision-making. Further empirical evidence is warranted.

Mapping Gaps in Sugarcane Fields Using UAV-RTK Platform

Unmanned aerial vehicles (UAVs) equipped with a global real-time kinematic navigation satellite system (GNSS RTK) could be a state-of-the-art solution to measuring gaps in sugarcane fields and enable site-specific management. Recent studies recommend the use of UAVs to map these gaps. However, low-accuracy GNSS provides incomplete or inaccurate photogrammetric reconstructions, which could easily generate an error in the gap measurement and constrain the applicability of these techniques. Therefore, in this study, we evaluated the potential of UAV RTK imagery for mapping gaps in sugarcane. To compare this solution with conventional UAV approaches, the precision and accuracy of RTK and non-RTK flights were evaluated. To increase the robustness of the research, flights were performed to map gaps found naturally in the field and with plants at different stages of development. Our results showed that the lengths of gaps identified by both RTK and non-RTK UAV imagery were similar, with differences in precision and accuracy of about 1% for both systems. In contrast, RTK was much more efficient and provides stakeholders with guidelines for accurate and precise mapping gaps, allowing them to make confident decisions on site-specific management.

Information overload research in accounting: a systematic review of the literature

This paper reviews literature in the domain of information overload in accounting. The underlying psychological concepts of information load (as applied in accounting research) are summarized, and a framework to discuss findings in a structured way is proposed. This framework serves to make causes, consequences, and countermeasures transparent. Variables are further clustered into major categories from information processing research: input, process, and output. The main variables investigated are the characteristics of the information set, especially the number of information cues as an input variable; the experience of the decision-maker, the decision time, decision rule, and cue usage as process variables; and measures related to decision quality (i.e., accuracy, consensus, consistency) and related to selfinsight (calibration, confidence, feeling of overload) as output variables. The contexts of the respective research papers are described, and the operationalization of variables detailed and compared. We employ the method of stylized facts to evaluate the strength of the links between variables (number of links, direction and significance of relationship). The findings can be summarized as follows: most articles focus on individual decision-making in the domain of external accounting, with financial distress predictions constituting a large part of these. Most papers focus on input and output variables with the underlying information processing receiving less attention. The effects observed are dependent on the type of information input and the task employed. Decision accuracy is likely to decrease once information load passes a certain threshold, while decision time and a feeling of overload increase with increasing information load. While experience increases decision accuracy, the results on decision time and consensus are conflicting. Most articles have not established a significant link between changes in information load and changes in decision confidence. Relative cue usage, consensus, consistency, and calibration decline with increasing information load. Available time has a rather positive effect on decision accuracy and consensus. Based on these findings, implications for practice and future research are derived.

Mechanisms of spatial contextual cueing in younger and older adults.

The contextual cueing effect is the phenomenon observed when response time (RT) becomes faster in visual search in repeated context compared with a new one. In the present study, we explored whether the mechanisms involved in the effect are age dependent. We investigated it in younger (N = 20, 12 women, 21.2 ± 1.75 years) and older (N = 19, nine women, 67.05 ± 3.94 years) adults. We found a faster target identification in the repeated configurations with similar magnitude in the two age groups, which indicates that this contextual cueing effect remained intact even in the older participants. To shed light on the underlying mechanisms, we measured and compared the amplitude of three event-related potentials: N2pc, P3, and response-locked LRP. In the younger group, the larger contextual cueing effect (novel-minus-repeated RT difference) correlated positively with a larger difference in amplitude for repeated compared with novel configurations for both the N2pc and the P3 components, but there was no correlation with the response-locked lateralized readiness potential (rLRP) amplitude difference. However, in the older group, only the rLRP amplitude difference between novel and repeated configurations showed an enhancement with larger contextual cueing. These results suggest that different mechanisms are responsible for the contextual effect in the two age groups. It has both an early and an intermediate locus in younger adults: effective attentional allocation and successful stimulus categorization, or decision-making confidence are involved; while in older adults, a late locus was identified: a more efficient response organization led to a faster reaction.

Impact of social media messages on perceived risk and severity of adverse effects and regret of HPV vaccination: The moderating role of decision-making preference.

10543 Background: The HPV vaccine has proven to be a highly effective and safe public health intervention for reducing the risk of various types of cancer. Despite its efficacy and safety, misinformation and negative opinions about the vaccine on social media can lead to negative emotions such as regret among those who have received it. This study investigated the impact of different content of social media messages on perceived risk and severity of adverse effects and regret of HPV vaccination. Methods: An experiment was designed to expose participants to messages posted on social media that manipulated the number of Vaccine Adverse Effects and the appeal used (narrative vs. statistics). The study measured the effect of the message on decisional regret and also assessed preferred level of involvement with medical decision-making. The online study was implemented among college students enrolled in a Midwestern or a South Texas university. We used structural equation modeling (SEM) to systematically test the relationships between the variables of interest. Results: A total of 721 participants were exposed to the experimental materials and completed the questionnaire. The results of the SEM (with overall good fitness of RMSEA = 0.015, CMIN/df = 1.172) suggest that messages that contained more numeric information (standardized regression weights [Std Reg Wght = 0.161]) and more adverse effects of the HPV vaccine (Std Reg Wght = 0.076) led to a higher perception of the risk of vaccine adverse effects. The severity of adverse effects was significantly associated with the number of side effects in the message (Std Reg Wght = 0.147). This increase in perceived risk (Std Reg Wght = 0.182) and severity of side effects of the vaccine (Std Reg Wght = 0.163) seem to increase decisional regret. However, this relationship was moderated by individuals’ preferences for making their own medical decisions. Individuals with a higher preference to make their own health decisions were less likely to experience decisional regret (Std Reg Wght = -0.238). Conclusions: Messages on social media can exacerbate negative emotions and lead to hesitation in following future medical advice. Encouraging individuals to play a more active role in their medical decision-making appears to reduce this negative emotion and increase their confidence in health decisions.

P.006 Alzheimer’s disease CSF biomarker testing and its impacts on clinical management: findings from the IMPACT-AD BC study

Background: Within the IMPACT-AD BC study, we sought to address the gap in knowledge around how the use of Alzheimer’s disease (AD) CSF biomarker testing impacts clinical management. Methods: IMPACT-AD BC (NCT05002699, impactAD.org) is an observational, longitudinal study examining the role of AD CSF biomarker testing (i.e., amyloid-beta and tau proteoforms) in medical and personal decision-making, and health economics. For medical decision-making, physicians completed surveys on patient management plans before and after receiving the biomarker findings. Overall change in management was assessed as a composite measure of changes in the use of: (i) AD symptomatic medications, (ii) other dementia-relevant medications, (iii) diagnostic procedures, and (iv) referrals or counselling. Results: Of the 142 participants, 66% were determined to have CSF biomarker profiles on the AD continuum. Overall change in management was observed in 89% of patients, with the greatest changes by category being: diagnostic procedures &gt; referrals and counselling &gt; AD symptomatic medications &gt; other dementia-relevant medications. Conclusions: The use of AD CSF biomarker testing increases diagnostic confidence and aids in medical decision-making. Notably, the addition of biomarker testing leads to a reduction in the use of other diagnostic procedures, helps optimize pharmacotherapy and results in increased physician-patient/family member counselling.

Confidence and coincidences in executive decision-making during periods of crisis

PurposeThe purpose of this study, which is grounded in decision-making theory, is to explore whether the occurrence of meaningful coincidences can positively influence executive confidence during periods of crisis.Design/methodology/approachThrough a qualitative study with 24 interviews, this study focuses on Italian hospitality facilities in the Campania Region of southern Italy to explore how an executive confidence led by meaningful coincidences can influence managerial decisions during crisis situations. Data are analyzed through a deductive coding for qualitative analysis.FindingsThe framework proposes the connection by coincidences and confidence, emphasizing the process through which meaningful coincidences can positively influence executive confidence and managerial decision-making. The insights that emerge suggest a number of positive and beneficial aspects for decision-making during a period of crisis such as the COVID-19 pandemic.Originality/valueTo the best of the authors’ knowledge, this is the first study in the literature aimed at investigating, by means of qualitative methodologies, the positive outcomes of executive confidence in decision-making led by meaningful coincidences during crisis periods in the specific context of the Italian hospitality industry.

Mediating effect of moral sensitivity on the relationship between nursing professionalism and ethical decision-making confidence in nursing students

Purpose: The purpose of this study is to confirm the relationship between nursing students’ nursing professionalism and ethical decision-making confidence, and to clarify the mediating effect of moral sensitivity which has a mutual influence on nursing professionalism and ethical decision-making confidence.Methods: The data collection for this study was conducted from January 23 to February 1, 2021 with junior and senior nursing students enrolled in five nursing departments in two regions. The data collected in this study were analyzed using the IBM SPSS statistics version 23.0 program.Results: Through this study, it was found that nursing professionalism (&lt;i&gt;β&lt;/i&gt;=.47) and moral sensitivity (&lt;i&gt;β&lt;/i&gt;=.32) acted as important influencing factors on the ethical decision-making confidence of nursing students, with an explanatory power of 31.2%. In addition, it was confirmed that there was a partial mediating effect of moral sensitivity in the relationship between the nursing professionalism and ethical decision-making confidence of nursing students, and the mediating effect coefficient of moral sensitivity was .16.Conclusion: Based on the results of the study, it is suggested to prepare a plan to increase ethical decision-making confidence and moral sensitivity when planning interventions to improve nursing professionalism in nursing students.

0058 The sleepy eyewitness: Self-reported sleep predicts eyewitness memory

Abstract Introduction Sleep is critical for memory, but research indicates that eyewitness identification may be an exception. We conducted three experiments to assess the effect of self-reported sleep duration and quality, and current sleepiness on eyewitness recall for a mock crime and suspect identification. Experiments 1 and 2 looked at pre-encoding sleep on lineups and showups, respectively. Experiment 3 investigated lineups across two days to assess retrieval effects. Methods Participants viewed a mock crime video then answered sleep questions as well as central and peripheral recall questions over the crime. Participants were then randomly assigned to view a fair 6-person target-present (TP) or target-absent (TA) lineup for experiments 1 and 3, or a TP or TA showup for experiment 2. In experiment 3, the recall questions and lineups occurred on day 2, but the sleep questions were asked both days. Decision confidence was provided after the identification procedure. Results Sleep quality predicted central recall for experiment 1 [F(1, 3834)=12.96, p&amp;lt;.001] whereas sleep quantity predicted central recall for experiment 2, F(1, 2712)=36.22, p&amp;lt; .001. Choosing rate for pre-encoding sleep was higher for low quality [X2(1)=29.10, p&amp;lt;.001] and low duration [X2(1)=20.15, p&amp;lt;.001], but false IDs were lower for high duration [X2(1)=29.76, p&amp;lt;.001] and high quality, X2(1)=35.47, p&amp;lt;.001. High quality self-reported sleep increased discriminability for lineups, G=2.14, p=.016. False IDs for showups were lower for high duration [X2(1)=5.27, p=.024] and all three sleep questions predicted discriminability for showups: more sleep (G=2.85, p=.002), better sleep (G=2.60, p=.005), and less sleepiness, G=2.44, p=.007. Showups had greater accuracy (p=.038) and a stronger confidence-accuracy relationship (p&amp;lt;.001) for the average of the “good sleep” conditions than the average of the three “bad sleep” conditions, p=.022. In experiment 3, involving post-encoding self-reported sleep, there were still effects on recall but minimal effects on eyewitness identification (and no effects on discriminability). Conclusion Self-reported sleep for the night prior to the crime could be an important individual difference variable for eyewitness memory, affecting encoding more than post-encoding processes. Support (if any) This project was supported by Grant 2018-R2-CX-0027 awarded by the National Institute of Justice, Office of Justice Programs, and U.S. Department of Justice.

Pay or nudge employees into change? A theoretical and experimental investigation of the effect of nudging for organizational change

AbstractOrganizational change often fails due to employees' resistance to change resulting in unforeseen expenses, delays, or other disruptions in organizations. In our experiment, we compare behavioral interventions—a pro‐change default rule and a pro‐change recommendation—with a costly pay raise to foster supportive behavior. In regard to the pure nudge used (default), we support its effectiveness in enhancing change‐related success. In line with our model and based on the assumption of low decision confidence in change settings, we find that a preference nudge (recommendation) lacks a corresponding effect. In addition, we find that a pay raise has a positive effect that is likely to be triggered by positive reciprocity. If this pay raise fails to materialize, we report supporting evidence for negative reciprocity. We compare the effect sizes for these nudges and the pay raise and provide insights for the relative cost‐effectiveness of such nudges compared to a pay raise for organizational change. We conclude with managerial implications.

Impact of a Multiday, High-fidelity, Immersive Simulation on Military Medical Students' Self-confidence.

Decision-making is a critical competence that all medical students must develop before becoming independently licensed physicians. One aspect of the decision-making process is confidence, which has not been extensively studied in undergraduate medical education. Intermittent simulation has been found to improve medical students' self-confidence across a wide range of clinical scenarios; however, no research to date has examined how a more extensive medical and operational simulation impacts miltary medical students' confidence in their decision-making abilities. This study was conducted online through the Uniformed Services University and in person at Operation Bushmaster, a multiday, out-of-hospital, high-fidelity, immersive simulation held at Fort Indiantown Gap, PA. This investigation focused on examining the impacts of asynchronous coursework and simulation-based learning on improving decision-making confidence for senior medical students 7 months before graduation. Thirty senior medical students volunteered. Each completed a 10-point confidence scale before and after either accomplishing asynchronous online coursework (control group) or attending a medical field practicum (experimental group). We conducted a repeated-measures analysis of variance to examine any change in students' confidence scores before and after completing each educational modality. The results of the analysis of variance indicated a significant time effect for our students' confidence in both the experimental and control groups as measured on our confidence scale, suggesting that Operation Bushmaster and asynchronous coursework both possessed the potential to increase students' confidence in their decision-making. Both simulation-based learning and asynchronous online learning can increase students' decision-making confidence. Future larger-scale research is needed to calculate the impact of each modality on military medical students' confidence.