Autonomous Vehicles and Public Health.

Autonomous vehicles (AVs) have the potential to shape urban life and significantly modify travel behaviors. "Autonomous technology" means technology that can drive a vehicle without active physical control or monitoring by a human operator. The first AV fleets are already in service in US cities. AVs offer a variety of automation, vehicle ownership, and vehicle use options. AVs could increase some health risks (such as air pollution, noise, and sedentarism); however, if proper regulated, AVs will likely reduce morbidity and mortality from motor vehicle crashes and may help reshape cities to promote healthy urban environments. Healthy models of AV use include fully electric vehicles in a system of ridesharing and ridesplitting. Public health will benefit if proper policies and regulatory frameworks are implemented before the complete introduction of AVs into the market.

Poor health as a potential risk factor for job loss due to automation: the case of Norway.

OBJECTIVE: This study aimed to quantify the extent to which health characteristics of workers are related to the potential risk of experiencing job displacement due to automation. METHODS: Linking the 2015 Norwegian Statistics on Income and Living Conditions survey (n=6393) with predicted probabilities of automation by occupation, we used Kruskal-Wallis tests and multivariate generalised linear models to assess the association between long-standing illnesses and risk of job automation. RESULTS: Individuals with long-standing illnesses face substantially greater risks of losing their job due to automation. Whereas the average risk of job automation is 57% for men and 49% for women with long-standing illnesses, the risk is only 50% for men and 44% for women with limitations (p<0.001). Controlling for age, having a long-standing illness significantly increases the relative risk of facing job automation among men (risk ratio (RR) 1.13, 95% CI 1.09 to 1.19), as well as women (RR 1.11, 95% CI 1.05 to 1.17). While, among men, the association between long-standing illness and risk of job automation remains significant when controlling for education and income, it becomes insignificant among women. CONCLUSIONS: Individuals with poor health are likely to carry the highest burden of technological change in terms of worsening employment prospects because of working in occupations disproportionally more likely to be automated. Although the extent of technology-related job displacement will depend on several factors, given the far-reaching negative consequences of job loss on health and well-being, this process represents a significant challenge for public health and social equity.

The Effect of Incorrect Reliability Information on Expectations, Perceptions, and Use of Automation.

OBJECTIVE: We examined how providing artificially high or low statements about automation reliability affected expectations, perceptions, and use of automation over time. BACKGROUND: One common method of introducing automation is providing explicit statements about the automation's capabilities. Research is needed to understand how expectations from such introductions affect perceptions and use of automation. METHOD: Explicit-statement introductions were manipulated to set higher-than (90%), same-as (75%), or lower-than (60%) levels of expectations in a dual-task scenario with 75% reliable automation. Two experiments were conducted to assess expectations, perceptions, compliance, reliance, and task performance over (a) 2 days and (b) 4 days. RESULTS: The baseline assessments showed initial expectations of automation reliability matched introduced levels of expectation. For the duration of each experiment, the lower-than groups' perceptions were lower than the actual automation reliability. However, the higher-than groups' perceptions were no different from actual automation reliability after Day 1 in either study. There were few differences between groups for automation use, which generally stayed the same or increased with experience using the system. CONCLUSION: Introductory statements describing artificially low automation reliability have a long-lasting impact on perceptions about automation performance. Statements including incorrect automation reliability do not appear to affect use of automation. APPLICATION: Introductions should be designed according to desired outcomes for expectations, perceptions, and use of the automation. Low expectations have long-lasting effects.

Effects of levels of automation and non-driving related tasks on driver performance and workload: A review of literature and meta-analysis.

This study assessed the effects of different levels of automation and non-driving related tasks (NDRT) on driver performance and workload. A systematic literature review was conducted in March 2021 using Compendex, Google Scholar, Web of Science, and Scopus databases. Forty-five studies met the inclusion criteria. A meta-analysis was conducted and Cochrane risk of bias tool and Cochran's Q test were used to assess risk of bias and homogeneity of the effect sizes respectively. Results suggested that drivers exhibited safer performance when dealing with critical incidents in manual driving than partially automated driving (PAD) and highly automated driving (HAD) conditions. However, drivers reported higher workload in the manual driving mode as compared to the HAD and PAD conditions. Haptic, auditory, and visual-auditory takeover request modalities are preferred over the visual-only modality to improve takeover time. Use of handheld NDRTs significantly degraded driver performance as compared to NDRTs performed on mounted devices.

The interaction effects of automation and population aging on labor market.

Automation and population aging are two major forces that will shape the nature of works in the future. However, it is not clear how these forces will interact with each other and affect the labor market. This paper examines the interaction effects of computerization and population aging on the labor market. We found that computerization and population aging have large and statistically significant effects on employment growth but not earnings growth. Also, their interaction terms are statistically significant only for employment growth but not for earnings growth.

Automated estimation of rare event probabilities in biochemical systems.

In biochemical systems, the occurrence of a rare event can be accompanied by catastrophic consequences. Precise characterization of these events using Monte Carlo simulation methods is often intractable, as the number of realizations needed to witness even a single rare event can be very large. The weighted stochastic simulation algorithm (wSSA) [J. Chem. Phys. 129, 165101 (2008)] and its subsequent extension [J. Chem. Phys. 130, 174103 (2009)] alleviate this difficulty with importance sampling, which effectively biases the system toward the desired rare event. However, extensive computation coupled with substantial insight into a given system is required, as there is currently no automatic approach for choosing wSSA parameters. We present a novel modification of the wSSA--the doubly weighted SSA (dwSSA)--that makes possible a fully automated parameter selection method. Our approach uses the information-theoretic concept of cross entropy to identify parameter values yielding minimum variance rare event probability estimates. We apply the method to four examples: a pure birth process, a birth-death process, an enzymatic futile cycle, and a yeast polarization model. Our results demonstrate that the proposed method (1) enables probability estimation for a class of rare events that cannot be interrogated with the wSSA, and (2) for all examples tested, reduces the number of runs needed to achieve comparable accuracy by multiple orders of magnitude. For a particular rare event in the yeast polarization model, our method transforms a projected simulation time of 600 years to three hours. Furthermore, by incorporating information-theoretic principles, our approach provides a framework for the development of more sophisticated influencing schemes that should further improve estimation accuracy.

Automated office BP measurement: The new standard in HTN screening.

Obtain greater accuracy in blood pressure measurement with an automated office device.

Prevalence, types and severity of medication errors associated with the use of automated medication use systems in ambulatory and institutionalized care settings: A systematic review protocol.

The use of automated systems within the medication use process has significantly reduce the occurrence of medication errors and the associated clinical and financial burden. However, automated systems lull into a false sense of security and increase the risk of medication errors that are often associated with socio-technical interactions, automation bias, workarounds and overrides. The objective of the systematic review is to determine the prevalence, types and severity of medication errors that are associated the use of automated systems in ambulatory and institutionalized care settings. The search strategy will be guided by PRISMA framework. Selected databases and relevant gray literature were searched and screening was done independently by two researchers between 01 April and 29 June 2021. These covered all relevant articles published from the inception of the use of automation in the medication use process (2000) until 2020. De-duplication and screening of all studies were done independently by two researchers with a clear inclusion / exclusion criteria. Data extraction and synthesis are currently on going (started on 06 July 2021) and being conducted independently but the validity and completeness of the processes will be confirmed by the third researcher. The Cochrane Risk of Bias tool and the Hoy et al's quality assessment checklist will be used for the assessment of methodological bias while the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system will be used for the quality of evidence assessment. Detailed qualitative synthesis of key findings will be done with thematic and descriptive analyses. If the number and types of included studies permit, fixed or random effect model meta-analysis will be conducted based on the degree of homogeneity in the sampling frame used in the included studies. Heterogeneity will be assessed with I2 statistics and I2 > 50% will be considered a high statistical heterogeneity. The systematic review may provide new perspective especially from developing settings about the prevalence, types and severity of medication errors associated with the use of automated systems at all the stages of medication use process, and in all categories of patients. This may add to global knowledge in the research area. Systematic review registration: The systematic review was registered and published by PROSPERO (CRD42020212900).

What humanlike errors do autonomous vehicles need to avoid to maximize safety?

INTRODUCTION: The final failure in the causal chain of events in 94% of crashes is driver error. It is assumed most crashes will be prevented by autonomous vehicles (AVs), but AVs will still crash if they make the same mistakes as humans. By identifying the distribution of crashes among various contributing factors, this study provides guidance on the roles AVs must perform and errors they must avoid to realize their safety potential. METHOD: Using the NMVCCS database, five categories of driver-related contributing factors were assigned to crashes: (1) sensing/perceiving (i.e., not recognizing hazards); (2) predicting (i.e., misjudging behavior of other vehicles); (3) planning/deciding (i.e., poor decision-making behind traffic law adherence and defensive driving); (4) execution/performance (i.e., inappropriate vehicle control); and (5) incapacitation (i.e., alcohol-impaired or otherwise incapacitated driver). Assuming AVs would have superior perception and be incapable of incapacitation, we determined how many crashes would persist beyond those with incapacitation or exclusively sensing/perceiving factors. RESULTS: Thirty-three percent of crashes involved only sensing/perceiving factors (23%) or incapacitation (10%). If they could be prevented by AVs, 67% could remain, many with planning/deciding (41%), execution/performance (23%), and predicting (17%) factors. Crashes with planning/deciding factors often involved speeding (23%) or illegal maneuvers (15%). CONCLUSIONS: Errors in choosing evasive maneuvers, predicting actions of other road users, and traveling at speeds suitable for conditions will persist if designers program AVs to make errors similar to those of today's human drivers. Planning/deciding factors, such as speeding and disobeying traffic laws, reflect driver preferences, and AV design philosophies will need to be consistent with safety rather than occupant preferences when they conflict. Practical applications: This study illustrates the complex roles AVs will have to perform and the risks arising from occupant preferences that AV designers and regulators must address if AVs will realize their potential to eliminate most crashes.

Pediatric occupant human body model kinematic and kinetic response variation to changes in seating posture in simulated frontal impacts - with and without automatic emergency braking.

OBJECTIVE: The study quantifies the kinematics of children in booster child restraint systems (CRSs) in various naturalistic seating postures exposed to frontal impacts in a full-vehicle environment, with and without the application of pre-crash automatic emergency braking. METHODS: The PIPER 6YO and 10YO pediatric human body models were positioned in CRSs. The 6YO was restrained on a lowback (LBB) and highback (HBB) booster, while the 10YO was positioned on an LBB and in a NoCRS condition. All simulations used the 3-point seatbelt. The child models were pre-positioned (gravity settled, seatbelt tensioned) in four naturalistic seating postures: leaning-forward, leaning-forward-inward, leaning-forward-outward, and a pre-submarining position, along with a baseline reference seating position. A 2012 Toyota Camry finite element (FE) model was used as the vehicle environment. A standard 3-point lap-shoulder belt system was modeled to restrain the child and CRS in the left-rear vehicle seat. Two vehicle impact cases were considered: with and without a pre-crash AEB. For with-AEB cases, a pre-crash phase was run to incorporate postural changes due to the application of AEB. All seating positions were ultimately subjected to a full-frontal rigid-barrier impact at 35 MPH. A total of 40 conditions were simulated in LS-DYNA. RESULTS: Injury metrics varied widely for both occupants. Shoulder belt slippage was observed for the 6YO leaning-forward-inward on HBB. No head contact was observed for any simulated cases. Forward-leaning and forward-inward-leaning postures generally had greater head excursion across all seating postures. The lap belt rode over the pelvis for pre-submarining postures. Injury metrics for cases with pre-crash AEB were lower compared to their corresponding without-AEB cases. HIC15, head acceleration, upper neck tension force, and upper neck flexion moment were similar or lower for with-AEB scenarios. CONCLUSIONS: Pre-crash AEB reduces the effect of the impact despite the same collision speed as cases without-AEB. This is primarily due to the limited travel distance of the occupant, thus, starting an earlier ride-down during the crash. Moreover, different initial seating postures lead to a wide range of injury exposures. Vehicle and child restraint design should incorporate these seating postures to ensure robust protection of the occupant in a crash.

Kidney Disease-Specific Scores and Health Utility of Continuous Ambulatory Peritoneal Dialysis and Automated Peritoneal Dialysis Patients and Their Caregivers.

OBJECTIVES: This study aimed to compare the EuroQol 5-dimension 5-level questionnaire (EQ-5D-5L), the visual analogue scale (VAS), and the Kidney Disease Quality of Life 36-Item Short-Form Survey (KDQOL-36) scores of Thai continuous ambulatory peritoneal dialysis (CAPD) and automated peritoneal dialysis (APD) patients and to compare the utility scores with the EQ-5D-5L and VAS scores of caregivers. METHODS: This was a cross-sectional study completed between April 2016 and May 2017. In total, 34 CAPD patients, 30 APD patients, and their caregivers were recruited from a large university hospital in Thailand. A trained interviewer conducted face-to-face interviews. We collected demographic data and used the KDQOL-36 and EuroQol questionnaires (EQ-5D-5L and VAS) to assess the health-related quality of life. Caregivers were asked to assess their own health status using the EQ-5D-5L and VAS. RESULTS: The EQ-5D-5L and VAS responses of the CAPD and APD patients and their caregivers were not significantly different (P > .05). More than 50% of both patient groups had mobility problems, whereas most patients had no problems with self-care, doing usual activities, pain or discomfort, and anxiety or depression. As for the KDQOL-36, the physical and mental component summaries were not significantly different, and neither were the scores for all of the kidney disease-specific dimensions, including symptoms or problems, effects of kidney disease, and burden of kidney disease (all were P > .05). CONCLUSIONS: The results indicated that the quality of life of CAPD and APD patients and their caregivers were mostly equivalent. A further longitudinal study of utility score assessments of the differences in modality would be advantageous.

Application of multi-factorial design of experiments to successfully optimize immunoassays for robust measurements of therapeutic proteins.

Developing a process that generates robust immunoassays that can be used to support studies with tight timelines is a common challenge for bioanalytical laboratories. Design of experiments (DOEs) is a tool that has been used by many industries for the purpose of optimizing processes. The approach is capable of identifying critical factors and their interactions with a minimal number of experiments. The challenge for implementing this tool in the bioanalytical laboratory is to develop a user-friendly approach that scientists can understand and apply. We have successfully addressed these challenges by eliminating the screening design, introducing automation, and applying a simple mathematical approach for the output parameter. A modified central composite design (CCD) was applied to three ligand binding assays. The intra-plate factors selected were coating, detection antibody concentration, and streptavidin-HRP concentrations. The inter-plate factors included incubation times for each step. The objective was to maximize the logS/B (S/B) of the low standard to the blank. The maximum desirable conditions were determined using JMP 7.0. To verify the validity of the predictions, the logS/B prediction was compared against the observed logS/B during pre-study validation experiments. The three assays were optimized using the multi-factorial DOE. The total error for all three methods was less than 20% which indicated method robustness. DOE identified interactions in one of the methods. The model predictions for logS/B were within 25% of the observed pre-study validation values for all methods tested. The comparison between the CCD and hybrid screening design yielded comparable parameter estimates. The user-friendly design enables effective application of multi-factorial DOE to optimize ligand binding assays for therapeutic proteins. The approach allows for identification of interactions between factors, consistency in optimal parameter determination, and reduced method development time.

Effect of automated versus manual emergency braking on rear seat adult and pediatric occupant precrash motion.

Objective: Emergency braking can potentially generate precrash occupant motion that may influence the effectiveness of restraints in the subsequent crash, particularly for rear-seated occupants who may be less aware of the impending crash. With the advent of automated emergency braking (AEB), the mechanism by which braking is achieved is changing, potentially altering precrash occupant motion. Further, due to anatomical and biomechanical differences across ages, kinematic differences between AEB and manual emergency braking (MEB) may vary between child and adult occupants. Therefore, the objective of this study was to quantify differences in rear-seated adult and pediatric kinematics and muscle activity during AEB and MEB scenarios. Methods: Vehicle maneuvers were performed in a recent model year sedan traveling at 50 km/h. MEB (acceleration ∼1 g) was achieved by the driver pressing the brake pedal with maximum effort. AEB (acceleration ∼0.8 g) was triggered by the vehicle system. Inertial and Global Positioning System data were collected. Seventeen male participants aged 10-33 were restrained in the rear right passenger seat and experienced each maneuver twice. The subjects' kinematics were recorded with an 8-camera 3D motion capture system. Electromyography (EMG) recorded muscle activity. Head and trunk displacements, raw and normalized by seated height, and peak head and trunk velocity were compared across age and between maneuvers. Mean EMG was calculated to interpret kinematic findings. Results: Head and trunk displacement and peak velocity were greater in MEB than in AEB in both raw and normalized data (P ≤ .01). No effect of age was observed (P ≥ .21). Peak head and trunk velocities were greater in repetition 1 than in repetition 2 (P ≤ .006) in MEB but not in AEB. Sternocleidomastoid (SCM) mean EMG was greater in MEB compared to AEB, and muscle activity increased in repetition 2 in MEB. Conclusions: Across all ages, head and trunk excursions were greater in MEB than AEB, despite increased muscle activity in MEB. This observation may suggest an ineffective attempt to brace the head or a startle reflex. The increased excursion in MEB compared to AEB may be attributed to differences in the acceleration pulses between the 2 scenarios. These results suggest that AEB systems can use specific deceleration profiles that have potential to reduce occupant motion across diverse age groups compared to sudden maximum emergency braking applied manually.

Optimizing ELISAs for precision and robustness using laboratory automation and statistical design of experiments.

Transferring manual ELISAs to automated platforms requires optimizing the assays for each particular robotic platform. These optimization experiments are often time consuming and difficult to perform using a traditional one-factor-at-a-time strategy. In this manuscript we describe the development of an automated process using statistical design of experiments (DOE) to quickly optimize immunoassays for precision and robustness on the Tecan EVO liquid handler. By using fractional factorials and a split-plot design, five incubation time variables and four reagent concentration variables can be optimized in a short period of time.

Use of 2 years of patient data to estimate intra-laboratory total imprecision of HbA(1c) measured by multiple HPLC analyzers.

BACKGROUND: Analytic imprecision is used to assess the acceptability of HbA(1c) methods performed on a single analyzer. When multiple analyzers are used interchangeably in a laboratory, the analytic imprecision is usually increased and can obscure the detection of a genuine HbA(1c) trend or result in an artefactual patient trend. We have estimated the imprecision of HbA(1c) testing of patient specimens by three HbA(1c) analyzers independent of reference sample analysis. METHODS: Over 2 years, approximately 150,000 HbA(1c) measurements were obtained from any one of three different Bio-Rad VARIANT II HPLC analyzers operated in a large reference laboratory. We tabulated the HbA(1c) measurements of paired intra-patient blood samples drawn within 30 days of each other. We calculated the standard deviations of duplicates (SDD) of the intra-patient HbA(1c) pairs grouped by the following time intervals: 0-3 days, 4-6 days, 7-9 days, 28-30 days. The SDDs were then regressed against time with extrapolation to zero time representing the random analytic error. RESULTS: At a mean HbA(1c) of 7.16%, the total analytic imprecision (coefficient of variation [CV]) is 3.6%. CONCLUSIONS: This variation is remarkably low, given that the HbA(1c) measurements were obtained over a 2-year period on any one of three analyzers and the long-term within-analyzer CV was usually 2.3-3.1% as assessed by reference control analysis. This approach could be extended to all HbA(1c) analyzers since unlike reference control statistics, the patient-derived random error should allow easy comparison of analytic imprecision among different analytical systems.

A predictive epilepsy index based on probabilistic classification of interictal spike waveforms.

Quantification of interictal spikes in EEG may provide insight on epilepsy disease burden, but manual quantification of spikes is time-consuming and subject to bias. We present a probability-based, automated method for the classification and quantification of interictal events, using EEG data from kainate- and saline-injected mice (C57BL/6J background) several weeks post-treatment. We first detected high-amplitude events, then projected event waveforms into Principal Components space and identified clusters of spike morphologies using a Gaussian Mixture Model. We calculated the odds-ratio of events from kainate- versus saline-treated mice within each cluster, converted these values to probability scores, P(kainate), and calculated an Hourly Epilepsy Index for each animal by summing the probabilities for events where the cluster P(kainate) > 0.5 and dividing the resultant sum by the record duration. This Index is predictive of whether an animal received an epileptogenic treatment (i.e., kainate), even if a seizure was never observed. We applied this method to an out-of-sample dataset to assess epileptiform spike morphologies in five kainate mice monitored for ~1 month. The magnitude of the Index increased over time in a subset of animals and revealed changes in the prevalence of epileptiform (P(kainate) > 0.5) spike morphologies. Importantly, in both data sets, animals that had electrographic seizures also had a high Index. This analysis is fast, unbiased, and provides information regarding the salience of spike morphologies for disease progression. Future refinement will allow a better understanding of the definition of interictal spikes in quantitative and unambiguous terms.

Unobserved automated office BP is similar to other clinic BP measurements: A prospective randomized study.

Results of the SPRINT study have been disputed, based on the assumption that unattended BP measurements do not correlate with usual BP measurements. In this study, the authors investigated the correlation of unattended SPRINT-like measurements with other conventional measurements. All BP measurements were taken with the patient seated in a comfortable chair with the legs uncrossed and not speaking during the procedure. For the purpose of this study, sixty-five patients, mostly male (93%), were recruited from our hypertension clinic and all were on antihypertensive medication (av 3.0 ± 1.1). Patients were at high cardiovascular risk with high rates of comorbidities, av age 68 ± 12 years, 49% with diabetes, 34% with mild CKD (CKD 1-3, average eGFR 55.0 ± 13 mL/min/1.73 m2 ), and 20% with history of stable coronary artery disease. All BP measurements were similar with no statistically significant difference (one-way ANOVA, P = 0.621). Compared to unattended SPRINT BP values (139.77 ± 19.22/75.42 ± 11.72 mm Hg), the clinic BP measurements were numerically slightly higher but with a NS P value (P = 0.163). Similarly, unattended BP measurements were similar to values taken by the clinic physician. In a smaller cohort of 11 patients, the authors compared unobserved vs observed SPRINT-like BP measurements, and in 13 patients, the authors compared unobserved SPRINT-like BP measurements to average home BP measurements (Table 3). There were no significant differences between any of the subgroups (one-way ANOVA, P = 0.816 for systolic and P = 0.803 for diastolic). The authors conclude that unattended BP measurements taken (the SPRINT way) are similar to other conventional office blood pressure measurements.

Comparison on Human Resource Requirement between Manual and Automated Dispensing Systems.

OBJECTIVE: This study was conducted to compare human resource requirement among manual, automated, and modified automated dispensing systems. METHODS: Data were collected from the pharmacy department at the 2100-bed university hospital (Siriraj Hospital, Bangkok, Thailand). Data regarding the duration of the medication distribution process were collected by using self-reported forms for 1 month. The data on the automated dispensing machine (ADM) system were obtained from 1 piloted inpatient ward, whereas those on the manual system were the average of other wards. Data on dispensing, returned unused medication, and stock management processes under the traditional manual system and the ADM system were from actual activities, whereas the modified ADM system was modeled. The full-time equivalent (FTE) of each model was estimated for comparison. RESULTS: The result showed that the manual system required 46.84 FTEs of pharmacists and 132.66 FTEs of pharmacy technicians. By adding pharmacist roles on screening and verification under the ADM system, the ADM system required 117.61 FTEs of pharmacists. Replacing counting and filling medication functions by ADM has decreased the number of pharmacy technicians to 55.38 FTEs. After the modified ADM system canceled the return unused medication process, FTEs requirement for pharmacists and pharmacy technicians decreased to 69.78 and 51.90 FTEs, respectively. CONCLUSIONS: The ADM system decreased the workload of pharmacy technicians, whereas it required more time from pharmacists. However, the increased workload of pharmacists was associated with more comprehensive patient care functions, which resulted from the redesigned work process.

The need for command and control instant message adaptive interfaces: lessons learned from Tactical Tomahawk human-in-the-loop simulations.

In the recent development of a human-in-the-loop simulation test bed designed to examine human performance issues for supervisory control of the Navy's new Tactical Tomahawk missile, measurements of operator situation awareness (SA) and workload through secondary tasking were taken through an embedded instant messaging program. Instant message interfaces (otherwise known as "chat"), already a means of communication between Navy ships, allow researchers to query users in real-time in a natural, ecologic setting, and thus provide more realistic and unobtrusive measurements. However, in the course of this testing, results revealed that some subjects fixated on the real-time instant messaging secondary task instead of the primary task of missile control, leading to the overall degradation of mission performance as well as a loss of SA. While this research effort was the first to quantify command and control performance degradation as a result of instant messaging, the military has recognized that in its network centric warfare quest, instant messaging is a critical informal communication tool, but has associated problems. Recently, a military spokesman said that managing chat in current military operations was sometimes a "nightmare," because military personnel have difficulty in handling large amounts of information through chat, and then synthesizing knowledge from this information. This research highlights the need for further investigation of the role of instant messaging interfaces both on task performance and situation awareness, and how the associated problems could be ameliorated through adaptive display design.