The Development of the Air Anti-Submarine Warfare MissionTestbed as a Tool for the Development of Operator Models

The central concern of human factors engineering (HFE) is facilitating a productive relationship between man and machine. A new generation of man-machine systems has arisen in which the machine acts in a relatively intelligent manner to enhance the operator's decision-making capabilities in real-time multi-tasking situations. These systems have been termed “distributed intelligence systems” (DIS) because intelligence is distributed among all system entities, whether they are human or computer. The ability of these systems to aid humans in a flexible, interactive fashion depends on the capability of the machine to predict the human's information needs in a given decision-making situation. Thus, the DIS must incorporate a model that reflects the operator's information processing requirements for the tasks necessary to operate the system. To construct this model, it is necessary to develop a DIS testbed where experimental investigations can occur. The mission environment chosen for simulation is the Naval Air Anti-Submarine Warfare (ASW) mission, whose objectives to search for, find, and attack the enemy submarine involve complex tactical decisions in a real-time multi-tasking environment. In the Air ASW mission, most significant tactical decisions are made by the Tactical Coordinator (TACCO), the main operator of the system. The aspects of the testbed discussed in this paper include those elements of the simulation and responsibilities of the TACCO needed to illustrate the types of information processing tasks involved in the ASW mission. Also, the data collection capabilities of the testbed and how this data will be applied to operator model development will be discussed.

Download Full-text

HOSPITAL MANAGERS’ NEED FOR INFORMATION ON HEALTH TECHNOLOGY INVESTMENTS

International Journal of Technology Assessment in Health Care ◽

10.1017/s0266462315000665 ◽

2015 ◽

Vol 31 (6) ◽

pp. 414-425 ◽

Cited By ~ 7

Author(s):

Anne Mette Ølholm ◽

Kristian Kidholm ◽

Mette Birk-Olsen ◽

Janne Buck Christensen

Keyword(s):

Decision Making ◽

Information Needs ◽

Empirical Studies ◽

Health Technology ◽

Decision Makers ◽

Core Model ◽

Informational Needs ◽

The Core ◽

Types Of Information ◽

Assessment Of Evidence

Objectives: There is growing interest in implementing hospital-based health technology assessment (HB-HTA) as a tool to facilitate decision making based on a systematic and multidisciplinary assessment of evidence. However, the decision-making process, including the informational needs of hospital decision makers, is not well described. The objective was to review empirical studies analysing the information that hospital decision makers need when deciding about health technology (HT) investments.Methods: A systematic review of empirical studies published in English or Danish from 2000 to 2012 was carried out. The literature was assessed by two reviewers working independently. The identified informational needs were assessed with regard to their agreement with the nine domains of EUnetHTA's Core Model.Results: A total of 2,689 articles were identified and assessed. The review process resulted in 14 relevant studies containing 74 types of information that hospital decision makers found relevant. In addition to information covered by the Core Model, other types of information dealing with political and strategic aspects were identified. The most frequently mentioned types of information in the literature related to clinical, economic and political/strategic aspects. Legal, social, and ethical aspects were seldom considered most important.Conclusions: Hospital decision makers are able to describe their information needs when deciding on HT investments. The different types of information were not of equal importance to hospital decision makers, however, and full agreement between EUnetHTA's Core Model and the hospital decision-makers’ informational needs was not observed. They also need information on political and strategic aspects not covered by the Core Model.

Download Full-text

Investors’ perception on the usefulness of management report disclosures

Meditari Accountancy Research ◽

10.1108/medar-11-2018-0393 ◽

2019 ◽

Vol 27 (6) ◽

pp. 893-920 ◽

Cited By ~ 3

Author(s):

Mostafa Kayed Mohamed ◽

Alessandra Allini ◽

Luca Ferri ◽

Annamaria Zampella

Keyword(s):

Decision Making ◽

Institutional Investors ◽

Information Needs ◽

Financial Analysts ◽

Insurance Companies ◽

Voluntary Disclosures ◽

Content Type ◽

Scientific Debate ◽

Types Of Information ◽

Management Report

Purpose This paper aims to examine the usefulness of disclosures provided by Egyptian firms in the management report from the viewpoint of financial analysts and institutional investors. Design/methodology/approach Institutional investors are surveyed to determine whether disclosures are meeting the needs of these financial statements’ users. The final sample consists of 78 financial analysts who work at stockbrokerage firms and 36 institutional investors who work in Egyptian banks and insurance companies. Findings The main findings reveal that investors view mandatory and voluntary disclosures differently. Some voluntary disclosures are more useful than mandatory disclosures, which highlights a gap between the regulations and users’ information needs. Moreover, the findings show that respondents consider information related to ownership structure more important than information on risks and firms’ future performance. Research limitations/implications This study enriches the scientific debate on the usefulness of disclosures provided in the management report. It might also encourage other researchers to focus on investigating different types of information that may have a significant influence on the decision-making process. Practical implications The findings will be useful to regulators to improve the current rules of disclosures. In addition, these results will also be helpful to managers because they highlight the disclosure items that are considered important by users. Originality/value This study provides evidence on how users perceive the usefulness of information disclosed in the management reports for their decision-making in an emerging capital market. Even though previous studies investigated the usefulness of management reports, no one of them emphasized the users’ viewpoint.

Download Full-text

Cognitive Task Analysis Methods in Envisioned Tactical Command Decision Making

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1071181319631407 ◽

2019 ◽

Vol 63 (1) ◽

pp. 262-266

Author(s):

Nicolette M. McGeorge ◽

Stephanie Kane ◽

Chris Muller

Keyword(s):

Decision Making ◽

Situation Awareness ◽

Task Analysis ◽

Information Needs ◽

Cognitive Task ◽

Cognitive Task Analysis ◽

Cyber Warfare ◽

Cyber Attack ◽

Analysis Methods ◽

Types Of Information

The battlespace is a volatile and complex environment in which tactical commanders face cognitively challenging responsibilities, compounded with the increased complexity of emerging cyber warfare. It is critical that tactical commanders gain adequate situation awareness for effective decision making to achieve mission success. While current tools enable distribution of large quantities and types of information, they do not adequately support the underlying cognitive work and information needs of tactical commanders. We performed a domain analysis using Cognitive Task Analysis methods, developing a prototypical operational scenario representative of current and envisioned environments, centered on a cyber-attack. Using this analysis, we identified cognitive and information requirements for information displays that support effective tactical decision making. Tactical commanders need to understand dynamic situations in the field, understand the viable courses of actions, know how their mission fits into the larger mission, and communicate with their company subordinates and higher echelons of command.

Download Full-text

Low-Burden Mobile Monitoring, Intervention, and Real-Time Analysis Using the Wear-IT Framework: Example and Usability Study (Preprint)

10.2196/preprints.16072 ◽

2019 ◽

Author(s):

Timothy R Brick ◽

James Mundie ◽

Jonathan Weaver ◽

Robert Fraleigh ◽

Zita Oravecz

Keyword(s):

Decision Making ◽

Real Time ◽

Information Needs ◽

Ease Of Use ◽

Self Report ◽

Quality Data ◽

Real Time Processing ◽

Time Processing ◽

Adaptive Assessment

BACKGROUND Mobile health (mHealth) methods often rely on active input from participants, for example, in the form of self-report questionnaires delivered via web or smartphone, to measure health and behavioral indicators and deliver interventions in everyday life settings. For short-term studies or interventions, these techniques are deployed intensively, causing nontrivial participant burden. For cases where the goal is long-term maintenance, limited infrastructure exists to balance information needs with participant constraints. Yet, the increasing precision of passive sensors such as wearable physiology monitors, smartphone-based location history, and internet-of-things devices, in combination with statistical feature selection and adaptive interventions, have begun to make such things possible. OBJECTIVE In this paper, we introduced Wear-IT, a smartphone app and cloud framework intended to begin addressing current limitations by allowing researchers to leverage commodity electronics and real-time decision making to optimize the amount of useful data collected while minimizing participant burden. METHODS The Wear-IT framework uses real-time decision making to find more optimal tradeoffs between the utility of data collected and the burden placed on participants. Wear-IT integrates a variety of consumer-grade sensors and provides adaptive, personalized, and low-burden monitoring and intervention. Proof of concept examples are illustrated using artificial data. The results of qualitative interviews with users are provided. RESULTS Participants provided positive feedback about the ease of use of studies conducted using the Wear-IT framework. Users expressed positivity about their overall experience with the framework and its utility for balancing burden and excitement about future studies that real-time processing will enable. CONCLUSIONS The Wear-IT framework uses a combination of passive monitoring, real-time processing, and adaptive assessment and intervention to provide a balance between high-quality data collection and low participant burden. The framework presents an opportunity to deploy adaptive assessment and intervention designs that use real-time processing and provides a platform to study and overcome the challenges of long-term mHealth intervention.

Download Full-text

‘There’s a thousand apps for that’: A qualitative study of the process and information needs when searching for and selecting apps for smoking cessation (Preprint)

10.2196/preprints.32628 ◽

2021 ◽

Author(s):

Ylva Hendriks ◽

Sebastiaan T.M. Peek ◽

Maurits C. Kaptein ◽

Inge M.B. Bongers

Keyword(s):

Decision Making ◽

Smoking Cessation ◽

Information Processing ◽

Information Needs ◽

Decision Aids ◽

Negative Experience ◽

Whole Process ◽

Quit Smoking ◽

Audio Recordings ◽

Video And Audio

BACKGROUND Thousands of apps are available to support people in their quest to quit smoking. Currently, few ways exist to help people easily select an app based on anything other than popularity (rating or number of downloads). It has been hypothesized that selecting an app from the sizable volume without any aid can be overwhelming and difficult. Little is known however about how people choose apps for smoking cessation, and what exactly it is people want to know about an app before choosing to install. Understanding the decision-making process may ultimately be helpful in creating tools to help people meaningfully select apps. OBJECTIVE The aim of this study is to obtain insights into the process of searching and selecting mobile applications for smoking cessation and to map the range of actions and the accompanying reasons during the search, focusing on the information needs and experiences of those who aim to find an app. METHODS Contextual inquiries were conducted with ten Dutch adults wanting to quit smoking by using an app. During the inquiries, we observed people as they chose an app. Additionally, there was a short semi-structured follow up interview over the phone, two weeks later. Through convenience and purposive sampling, we included participants differing in gender, age and educational level. We used thematic analysis to analyze transcribed interviews and leveraged a combination of video and audio recordings in order to understand what is involved in searching and selecting apps for smoking cessation. RESULTS The process of finding smoking cessation apps is comprehensive: participants explored, evaluated and searched for information, imagined using functions, compared apps, assessed trustworthiness of apps and information, made several decisions while navigating the internet and app stores. During the search, participants gained knowledge of apps and developed clearer ideas about wishes and requirements. Confidence and trust in these apps to help quitting, remained quite low or even decreased. Although the process was predominantly a positive experience, the whole process took time, energy, and caused negative emotions such as frustration and disappointment for some participants. In addition, without the participants realizing it, errors in information processing occurred, which affected the choices people made. All participants chose an app with the explicit intention of using it. After two weeks, six participants had used the app, only one of them extensively. CONCLUSIONS Finding an app that contains functions and features you expect to help you quit smoking in the current app stores takes considerable time, energy, can be a negative experience, and is prone to errors in information processing that affect decision making. We therefore advise further development of decision aids, such as recommender systems and curated health app portals and make a number of concrete recommendations for the design of such systems.

Download Full-text

IDENTIFICATION AND REVIEW OF COST-EFFECTIVENESS MODEL PARAMETERS: A QUALITATIVE STUDY

International Journal of Technology Assessment in Health Care ◽

10.1017/s0266462314000245 ◽

2014 ◽

Vol 30 (3) ◽

pp. 333-340 ◽

Cited By ~ 5

Author(s):

Eva Kaltenthaler ◽

Munira Essat ◽

Paul Tappenden ◽

Suzy Paisley

Keyword(s):

Health Economic ◽

Information Needs ◽

Model Development ◽

Clinical Effectiveness ◽

Assessment Process ◽

Rapid Review ◽

Model Parameters ◽

Framework Analysis ◽

Focus Group Data ◽

Types Of Information

Objectives: Health economic models are developed as part of the health technology assessment process to determine whether health interventions represent good value for money. These models are often used to directly inform healthcare decision making and policy. The information needs for the model require the use of other types of information beyond clinical effectiveness evidence to populate the model's parameters. The purpose of this research study was to explore issues concerned with the identification and use of information for the development of such models.Methods: Three focus groups were held in February 2011 at the University of Sheffield with thirteen UK HTA experts. Attendees included health economic modelers, information specialists and systematic reviewers. Qualitative framework analysis was used to analyze the focus group data.Results: Six key themes, with related sub-themes, were identified dealing with decisions and judgments; searching methods; selection and rapid review of evidence; team communication; modeler experience and clinical input and reporting methods. There was considerable overlap between themes.Conclusions: Key issues raised by the respondents included the need for effective communication and teamwork throughout the model development process, the importance of using clinical experts as well as the need for transparent reporting of methods and decisions.

Download Full-text

Low-Burden Mobile Monitoring, Intervention, and Real-Time Analysis Using the Wear-IT Framework: Example and Usability Study

JMIR Formative Research ◽

10.2196/16072 ◽

2020 ◽

Vol 4 (6) ◽

pp. e16072 ◽

Cited By ~ 3

Author(s):

Timothy R Brick ◽

James Mundie ◽

Jonathan Weaver ◽

Robert Fraleigh ◽

Zita Oravecz

Keyword(s):

Decision Making ◽

Real Time ◽

Information Needs ◽

Ease Of Use ◽

Self Report ◽

Quality Data ◽

Real Time Processing ◽

Time Processing ◽

Adaptive Assessment

Background Mobile health (mHealth) methods often rely on active input from participants, for example, in the form of self-report questionnaires delivered via web or smartphone, to measure health and behavioral indicators and deliver interventions in everyday life settings. For short-term studies or interventions, these techniques are deployed intensively, causing nontrivial participant burden. For cases where the goal is long-term maintenance, limited infrastructure exists to balance information needs with participant constraints. Yet, the increasing precision of passive sensors such as wearable physiology monitors, smartphone-based location history, and internet-of-things devices, in combination with statistical feature selection and adaptive interventions, have begun to make such things possible. Objective In this paper, we introduced Wear-IT, a smartphone app and cloud framework intended to begin addressing current limitations by allowing researchers to leverage commodity electronics and real-time decision making to optimize the amount of useful data collected while minimizing participant burden. Methods The Wear-IT framework uses real-time decision making to find more optimal tradeoffs between the utility of data collected and the burden placed on participants. Wear-IT integrates a variety of consumer-grade sensors and provides adaptive, personalized, and low-burden monitoring and intervention. Proof of concept examples are illustrated using artificial data. The results of qualitative interviews with users are provided. Results Participants provided positive feedback about the ease of use of studies conducted using the Wear-IT framework. Users expressed positivity about their overall experience with the framework and its utility for balancing burden and excitement about future studies that real-time processing will enable. Conclusions The Wear-IT framework uses a combination of passive monitoring, real-time processing, and adaptive assessment and intervention to provide a balance between high-quality data collection and low participant burden. The framework presents an opportunity to deploy adaptive assessment and intervention designs that use real-time processing and provides a platform to study and overcome the challenges of long-term mHealth intervention.

Download Full-text