Matching Items (27)

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AI in Radiology: How the Adoption of an Accountability Framework can Impact Technology Integration in the Expert-Decision-Making Job Space

Description

Rapid advancements in Artificial Intelligence (AI), Machine Learning, and Deep Learning technologies are widening the playing field for automated decision assistants in healthcare. The field of radiology offers a unique

Rapid advancements in Artificial Intelligence (AI), Machine Learning, and Deep Learning technologies are widening the playing field for automated decision assistants in healthcare. The field of radiology offers a unique platform for this technology due to its repetitive work structure, ability to leverage large data sets, and high position for clinical and social impact. Several technologies in cancer screening, such as Computer Aided Detection (CAD), have broken the barrier of research into reality through successful outcomes with patient data (Morton, Whaley, Brandt, & Amrami, 2006; Patel et al, 2018). Technologies, such as the IBM Medical Sieve, are growing excitement with the potential for increased impact through the addition of medical record information ("Medical Sieve Radiology Grand Challenge", 2018). As the capabilities of automation increase and become a part of expert-decision-making jobs, however, the careful consideration of its integration into human systems is often overlooked. This paper aims to identify how healthcare professionals and system engineers implementing and interacting with automated decision-making aids in Radiology should take bureaucratic, legal, professional, and political accountability concerns into consideration. This Accountability Framework is modeled after Romzek and Dubnick’s (1987) public administration framework and expanded on through an analysis of literature on accountability definitions and examples in military, healthcare, and research sectors. A cohesive understanding of this framework and the human concerns it raises helps drive the questions that, if fully addressed, create the potential for a successful integration and adoption of AI in radiology and ultimately the care environment.

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Date Created
  • 2019-05

The Need for Contextual Design when Creating Electronic Health Records

Description

Electronic Health Records (EHRs) began to be introduced in the 1960s. Government-run hospitals were the primary adopters of technology. The rate of adoption continually rose from there, doubling from 2007

Electronic Health Records (EHRs) began to be introduced in the 1960s. Government-run hospitals were the primary adopters of technology. The rate of adoption continually rose from there, doubling from 2007 to 2012 from 34.8% to about 71%. Most of the growth seen from 2007 to 2012 is a result of the passage of the Health Information Technology for Economic and Clinical Health (HITECH) Act as part of the American Reinvestment and Recovery (ARRA) Act. $19 billion dollars were made available as part of these two acts to increase the rate of Health Information Technology (HIT), of which EHRs are a large part. A national health information network is envisioned for the end stages of HITECH which will enable health information to be exchanged immediately from one health network to another. While the ability to exchange data quickly appears to be an achievable goal, it might come with the cost of loss of usability and functionality for providers who interact with the EHRs and often enter health data into an EHR. The loss of usability can be attributed to how the EHR was designed.

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Date Created
  • 2020-05

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A Look into Measuring Trust in Medical Devices

Description

The purpose of this review is to determine how to measure and assess human trust in medical technology. A systematic literature review was selected as the path to understand the

The purpose of this review is to determine how to measure and assess human trust in medical technology. A systematic literature review was selected as the path to understand the landscape for measuring trust up to this point. I started by creating a method of systematically reading through related studies in databases before summarizing results and concluding with a recommended design for the upcoming study. This required searching several databases and learning each advanced search methods for each in order to determine which databases provided the most relevant results. From there, the reader examined the results, keeping track in a spreadsheet. The first pass through filtered out the results which did not include detailed methods of measuring trust. The second pass took detailed notes on the remaining studies, keeping track of authors, participants, subjects, methods, instruments, issues, limitations, analytics, and validation. After summarizing the results, discussing trends in the results, and mentioning limitations a conclusion was devised. The recommendation is to use an uncompressed self-reported questionnaire with 4-10 questions on a six-point-Likert scale with reversing scales throughout. Though the studies analyzed were specific to medical settings, this method can work outside of the medical setting for measuring human trust.

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Date Created
  • 2020-05

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The Effect of an Educational Intervention on Affect and Trust of Autonomous Vehicles

Description

With the growth of autonomous vehicles’ prevalence, it is important to understand the relationship between autonomous vehicles and the other drivers around them. More specifically, how does one’s knowledge about

With the growth of autonomous vehicles’ prevalence, it is important to understand the relationship between autonomous vehicles and the other drivers around them. More specifically, how does one’s knowledge about autonomous vehicles (AV) affect positive and negative affect towards driving in their presence? Furthermore, how does trust of autonomous vehicles correlate with those emotions? These questions were addressed by conducting a survey to measure participant’s positive affect, negative affect, and trust when driving in the presence of autonomous vehicles. Participants’ were issued a pretest measuring existing knowledge of autonomous vehicles, followed by measures of affect and trust. After completing this pre-test portion of the study, participants were given information about how autonomous vehicles work, and were then presented with a posttest identical to the pretest. The educational intervention had no effect on positive or negative affect, though there was a positive relationship between positive affect and trust and a negative relationship between negative affect and trust. These findings will be used to inform future research endeavors researching trust and autonomous vehicles using a test bed developed at Arizona State University. This test bed allows for researchers to examine the behavior of multiple participants at the same time and include autonomous vehicles in studies.

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Created

Date Created
  • 2019

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Semantic Network Model of Cold and Flu Medications

Description

ABSTRACT

The cold and the flu are two of the most prevalent diseases in the world. Many over the counter (OTC) medications have been created to combat the symptoms of

ABSTRACT

The cold and the flu are two of the most prevalent diseases in the world. Many over the counter (OTC) medications have been created to combat the symptoms of these illnesses. Some medications take a holistic approach by claiming to alleviate a wide range of symptoms, while others target a specific symptom. As these medications become more ubiquitous within the United State of America (USA), consumers form associations and mental models about the cold/flu field. The goal of Study 1 was to build a Pathfinder network based on the associations consumers make between cold/flu symptoms and medications. 100 participants, 18 years or older, fluent in English, and residing in the USA, completed a survey about the relatedness of cold/flu symptoms to OTC medications. They rated the relatedness on a scale of 1 (highly unrelated) to 7 (highly related) and those rankings were used to build a Pathfinder network that represented the average of those associations. Study 2 was conducted to validate the Pathfinder network. A different set of 90 participants with the same restrictions as those in Study 1 completed a matching associations test. They were prompted to match symptoms and medications they associated closely with each other. Results showered a significant negative correlation between the geodetic distance (the number of links between objects in the Pathfinder network) separating symptoms and medications and frequency of pairing symptoms with medication. This provides evidence of the validity of the Pathfinder network. It was also seen that, higher the relatedness rating between symptoms and medications in Study 1, higher the frequency of pairing symptom to medication in Study 2, and the more directly linked those symptoms and medications were in the Pathfinder network. This network can inform pharmaceutical companies about which symptoms they most closely associate with, who their competitors are, what symptoms they can dominate, and how to market their medications more effectively.

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Created

Date Created
  • 2020

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The effects of an educational intervention on driving behavior and trust

Description

Vehicular automation and autonomy are emerging fields that are growing at an

exponential rate, expected to alter the very foundations of our transportation system within the next 10-25 years. A crucial

Vehicular automation and autonomy are emerging fields that are growing at an

exponential rate, expected to alter the very foundations of our transportation system within the next 10-25 years. A crucial interaction has been born out this new technology: Human and automated drivers operating within the same environment. Despite the well- known dangers of automobiles and driving, autonomous vehicles and their consequences on driving environments are not well understood by the population who will soon be interacting with them every day. Will an improvement in the understanding of autonomous vehicles have an effect on how humans behave when driving around them? And furthermore, will this improvement in the understanding of autonomous vehicles lead to higher levels of trust in them? This study addressed these questions by conducting a survey to measure participant’s driving behavior and trust when in the presence of autonomous vehicles. Participants were given several pre-tests to measure existing knowledge and trust of autonomous vehicles, as well as to see their driving behavior when in close proximity to autonomous vehicles. Then participants were presented with an educational intervention, detailing how autonomous vehicles work, including their decision processes. After examining the intervention, participants were asked to repeat post-tests identical to the ones administered before the intervention. Though a significant difference in self-reported driving behavior was measure between the pre-test and post- test, there was no significant relation found between improvement in scores on the education intervention knowledge check and driving behavior. There was also no significant relation found between improvement in scores on the education intervention knowledge check and the change in trust scores. These findings can be used to inform autonomous vehicle and infrastructure design as well as future studies of the effects of autonomous vehicles on human drivers in experimental settings.

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Created

Date Created
  • 2019

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Performance Expectations of Branded Autonomous Vehicles: Measuring Brand Trust Using Pathfinder Associative Networks

Description

Future autonomous vehicle systems will be diverse in design and functionality since they will be produced by different brands. In the automotive industry, trustworthiness of a vehicle is closely tied

Future autonomous vehicle systems will be diverse in design and functionality since they will be produced by different brands. In the automotive industry, trustworthiness of a vehicle is closely tied to its perceived safety. Trust involves dependence on another agent in an uncertain situation. Perceptions of system safety, trustworthiness, and performance are important because they guide people’s behavior towards automation. Specifically, these perceptions impact how reliant people believe they can be on the system to do a certain task. Over or under reliance can be a concern for safety because they involve the person allocating tasks between themselves and the system in inappropriate ways. If a person trusts a brand they may also believe the brand’s technology will keep them safe. The present study measured brand trust associations and performance expectations for safety between twelve different automobile brands using an online survey.

The literature and results of the present study suggest perceived trustworthiness for safety of the automation and the brand of the automation, could together impact trust. Results revelated that brands closely related to the trust-based attributes, Confidence, Secure, Integrity, and Trustworthiness were expected to produce autonomous vehicle technology that performs in a safer way. While, brands more related to the trust-based attributes Harmful, Deceptive, Underhanded, Suspicious, Beware, and Familiar were expected to produce autonomous vehicle technology that performs in a less safe way.

These findings contribute to both the fields of Human-Automation Interaction and Consumer Psychology. Typically, brands and automation are discussed separately however, this work suggests an important relationship may exist. A deeper understanding of brand trust as it relates to autonomous vehicles can help producers understand potential for over or under reliance and create safer systems that help users calibrate trust appropriately. Considering the impact on safety, more research should be conducted to explore brand trust and expectations for performance between various brands.

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Created

Date Created
  • 2018

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Buzz or Beep? How Mode of Alert Influences Driver Takeover Following Automation Failure

Description

Highly automated vehicles require drivers to remain aware enough to takeover

during critical events. Driver distraction is a key factor that prevents drivers from reacting

adequately, and thus there is

Highly automated vehicles require drivers to remain aware enough to takeover

during critical events. Driver distraction is a key factor that prevents drivers from reacting

adequately, and thus there is need for an alert to help drivers regain situational awareness

and be able to act quickly and successfully should a critical event arise. This study

examines two aspects of alerts that could help facilitate driver takeover: mode (auditory

and tactile) and direction (towards and away). Auditory alerts appear to be somewhat

more effective than tactile alerts, though both modes produce significantly faster reaction

times than no alert. Alerts moving towards the driver also appear to be more effective

than alerts moving away from the driver. Future research should examine how

multimodal alerts differ from single mode, and see if higher fidelity alerts influence

takeover times.

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Created

Date Created
  • 2018

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Task relatedness and spatial distance of information: considerations for medical head mounted displays

Description

The medical field is constantly looking for technological solutions to reduce user-error and improve procedures. As a potential solution for healthcare environments, Augmented Reality (AR) has received increasing attention in

The medical field is constantly looking for technological solutions to reduce user-error and improve procedures. As a potential solution for healthcare environments, Augmented Reality (AR) has received increasing attention in the past few decades due to advances in computing capabilities, lower cost, and better displays (Sauer, Khamene, Bascle, Vogt, & Rubino, 2002). Augmented Reality, as defined in Ronald Azuma’s initial survey of AR, combines virtual and real-world environments in three dimensions and in real-time (Azuma, 1997). Because visualization displays used in AR are related to human physiologic and cognitive constraints, any new system must improve on previous methods and be consistently aligned with human abilities in mind (Drascic & Milgram, 1996; Kruijff, Swan, & Feiner, 2010; Ziv, Wolpe, Small, & Glick, 2006). Based on promising findings from aviation and driving (Liu & Wen, 2004; Sojourner & Antin, 1990; Ververs & Wickens, 1998), this study identifies whether the spatial proximity affordance provided by a head-mounted display or alternative heads up display might benefit to attentional performance in a simulated routine medical task. Additionally, the present study explores how tasks of varying relatedness may relate to attentional performance differences when these tasks are presented at different spatial distances.

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Date Created
  • 2017

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Diabetes Education/Management Needs for Chinese Americans with Type 2 Diabetes: Opportunities and Implications for Design

Description

Diabetes education has shown to improve diabetes health markers but there is a need for it to be more accessible Diabetes education in the form of Diabetes Self Education and

Diabetes education has shown to improve diabetes health markers but there is a need for it to be more accessible Diabetes education in the form of Diabetes Self Education and Management (DSMES) could potentially utilize IT technologies, which have shown promise as a more accessible way to access healthcare and manage health. However, both these methods have not been optimized for the diverse population in the US. In particular, Chinese Americans are a growing minority group in America whose health needs such as diabetes type 2 are growing. As a cultural group, Chinese Americans have cultural characteristics that have been identified in the literature, which should be accounted for in the design of a technology-enabled DSMES program. This qualitative study aims to understand what ways Chinese Americans with type 2 diabetes are learning about and managing diabetes, as well as their technology usage. Themes such as cultural food importance, family roles, information acquisition, and attitudes and motivation emerged. Themes motivated the design implications and recommendations such as creating a more specified, culturally tailored Chinese food menu, integrated family features, and trackers with increased feedback. More research should be conducted to test the effectiveness of including these features in a technology-enabled DSMES program.

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Created

Date Created
  • 2021-05