Thesis (Ph. D.)--Oklahoma State University, 2004. / Vita. Includes bibliographical references (p. 206-218).

Operators have a crucial role in case of an emergency in a process facility. When an abnormality occurs in the process, the operator has a limited time to take corrective actions before system safety devices shut down the operation. It is crucial that system designers and safety professionals know about this required time frame before operations are initiated. Specific research goals for this project include the following: * Estimating the standard time data for operators to take corrective actions in emergency situations. * Developing a modeling system, to allow design/process engineers to find the standard time required for the operator(s) to respond in emergency situations. Current standard time data for carrying out tasks cover normal, steady state cases. However, the time required to take action in emergency situations is different than normal cases. Because of the possibility of a process incident and danger, operators make corrective actions faster compared to normal cases. Therefore, current standard time data do not meet the requirement for emergency situations. Shorter standard time data for emergency situations needs to be estimated. Standard time data for emergency situations is estimated by using time studies. Various time study methods were introduced and discussed. MODAPTS is a predetermined time standard method and stands for Modular Arrangement of Predetermined Time Standards, and was used in this project because it is reliable, easy to use and consistent. The methodology adopted for the study required observing several emergency case videos. The operations were decomposed into basic motions (such as walking, hand movement, bend and arise, etc.) by using a video player’s frame by frame feature. The amount of time required to take these basic motions was estimated. These estimated times were then compared to calculations based on MODAPTS, which is a predetermined time standard system. By comparing MODAPTS’s standard time intervals with those estimated from emergency situations, ratios or coefficients have been estimated for the various basic motions (e.g., factors such as 0.9, 0.75, etc.). The estimated coefficients for emergency situations, which are generally around 0.65, were used in developing a modeling system. The user of this modeling system can estimate the required time to take corrective actions in emergency situations as long as he/ she knows the actions need to be taken. Consequently, the time required to take necessary actions in emergency operations will be designed and evaluated in a systematic way to reduce the potential, as well as duration, of an incident.

An investigation into technologies to detect impaired performance due to driver fatigue was undertaken. From this, a new forced-choice stimulus-reaction device was developed specifically to detect driver impairment in operators of haul trucks in open cut mines. The device was developed in conjunction with personnel from the mining industry to suit the harsh conditions of the mining environment. The technology was trialled in three open cut mines and in a driving simulator at Murdoch University in Western Australia. Data were collected on the performance of drivers and analysed to validate the technology. A significant positive correlation was found between measures of reduced operator reaction performance and measures of eye closure. It was found that the device detected few false alarms and missed few bouts of tiredness as indicated by eye closures. It is suggested that the device would be a useful tool to assist with the detection of driver fatigue in open cut mining environments. The forced-choice reaction-monitoring device was used to assess the performance of drivers in a gold mine in Kalgoorlie, Western Australia. The fly-in-fly-out haul truck drivers worked 14 consecutive 12-hour night shifts, had a day off, then worked 13 consecutive 12-hour day shifts. A total of more than 3,500 hours of real-time objective performance data were collected and analysed. The main findings were that the objective performance data showed patterns of low performance that did not fit some of the performance data that would be expected from examination of past literature. Many findings are discussed in light of these anomalies. Another important finding is that the subject’s background and sleep pathology is a possible predictor for poor performance on the forced-choice reaction task. The system was also used to measure the performance of drivers with rising blood alcohol levels in a driving simulator. Subjects drank vodka with a mixer while driving for two hours starting at both 20:00 hrs and 22:00 hrs, with a week in between the two trials. The fatigue monitor detected reaction times slower than 3 SD of baseline performance at low levels of BAC. Performance at 22:00 hrs was marginally more impaired than performance at 20:00 hrs. Drivers at low BAC levels tended to compensate easier on the reaction task at 20:00 hrs compared to at 22:00 hrs. The ARRB fatigue monitor shows good capacity to detect poor performance due to low and medium measures of BAC. The research undertaken within this thesis has provided data that challenges contemporary research that generally suggests that time on task is one of the largest influences of fatigue at work. It appears that both circadian influences and individual lifestyle habits will have an equal or greater impact on fatigue risk at work.

Barriers to technology integration are not a new phenomenon for educators, however resolving the issues surrounding the barriers necessitates the use of appropriate methods to accurately identify them. The purpose of this study is to investigate (a) whether or not Gilberts Behavioral Engineering Model is an appropriate instrument for identifying barriers to technology integration in an educational setting, particularly a public school and (b) can Gilberts Behavioral Engineering model be used in a public school to identify barriers to technology integration. The research and design methods were conducted in two phases. In Phase I, a model usability study was conducted through an online Cause Analysis survey based on Chevalier's updated model. The survey was administered to 80 teachers and four administrators in a public school. In phase II, two expert reviewers validated the process used to implement the Behavior Engineering Model. The data from the Cause Analysis indicated that participants believed there was a lack of financial and non-financial incentives for integrating technology and that the management and reporting system did not adequately track the use of technology. The expert reviewers both agreed that Gilberts model was implemented correctly identified barriers to technology integration and revealed a performance gap. They also agreed that Gilberts model is appropriate to use in a public school setting. / Ed. D.

<p> In four experiments I addressed factors that affect human performance monitoring as indicated by neural correlates observed in response-locked event related potentials. Specifically, I examined modulations of the error related negativity (ERN), the correct response negativity (CRN), and the error positivity (Pe) components across a variety of conditions. These components, all thought to be generated in the anterior cingulate cortex, represent activation of the performance monitoring system. Experiments 1 and 2 used stimulus congruency and visual noise to manipulate response and stimulus uncertainty in an extension of previous research. These manipulations, together with a between experiment task manipulation, examined the role of cognitive/attentional load in performance monitoring. Replication of previous findings and a task specific modulation of ERN amplitudes provided support for a role of cognitive load in performance monitoring. Further, these two experiments used a novel task and novel stimuli to replicate previous research and extend our knowledge of how uncertainty affects performance monitoring. In stark comparison to all previous research in this area, Experiments 3 and 4 both employed complex and somewhat ecologically valid tasks. Standard ERN/Pe results in Experiment 3 (touch typing task) revealed that it is possible to examine the ERN in more complex, real world-like tasks. Further, an expectancy manipulation elicited marginal differences in the response-locked Pe but resulted in large N1 and P3 differences suggesting a possible role of attention in early expectation driven performance monitoring adjustments. Experiment 4 examined the role of task difficulty, anxiety level and exposure (i.e., time on task) for effects on ERN and Pe amplitudes. By comparing how math anxious people perform in a math environment, this study represents the first to pit a specific anxiety against a specific anxiety provoking situation. This complex paradigm again replicated general ERN findings providing further support for the validity of complex task usage. Findings surrounding the difficulty manipulation and anxiety measures provide new insight into the role of difficulty in performance monitoring and support the importance of considering personality characteristics in self-regulation. </p> / Thesis / Doctor of Philosophy (PhD)

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Mental health (MH) concerns are becoming more prevalent, though the current United States adult population remains more inclined to seek care only for physical conditions. Clients with physical dysfunction are especially likely to experience an exacerbation of MH concerns. The skilled, holistic practice scope of Occupational Therapy Practitioners (OTP) make them well suited to address both physical and MH needs. This program, Mental Readiness in Rehabilitation (MR2), provides holistic care planning education to OTPs. The MR2 is a one-hour education program that provides the background on MH in physical rehabilitation and offers practical skills training the Mental Readiness Screening Tool and the corresponding MH toolkit. This program educates OTPs on convenient, evidence-based skills to embed MH interventions for more holistic, comprehensive treatment plans. Plans for program implementation, funding, and evaluation of the MR2 program are included, as well as intent for the dissemination of program findings to advance the base of evidence for OTPs as qualified mental health practitioners.

Human performance modeling (HPM) is often used to investigate systems during all phases of development. HPM was used to investigate function allocation in crews for future combat vehicles. The tasks required by the operators centered around three primary functions, commanding, gunning, and driving. In initial investigations, the driver appeared to be the crew member with the highest workload. Validation of the driver workload model (DWM) is necessary for confidence in the ability of the model to predict workload. Validation would provide mathematical proof that workload of driving is high and that additional tasks impact the performance. This study consisted of two experiments. The purpose of each experiment was to measure performance and workload while driving and attending to an auditory secondary task. The first experiment was performed with a human performance model. The second experiment replicated the same conditions in a human-in-the-loop driving simulator. The results of the two experiments were then correlated to determine if the model could predict performance and workload changes. The results of the investigation indicate that there is some impact of an auditory task on driving. The model is a good predictor of mental workload changes with auditory secondary tasks. However, predictions of the impact on performance from secondary auditory tasks were not demonstrated in the simulator study. Frequency of the distraction was more influential in the changes of performance and workload than the demand of the distraction, at least under the conditions tested in this study. While the workload numbers correlate with simulator numbers, using the model would require a better understanding of what the workload changes would mean in terms of performance measures. / Master of Science

Work, especially that in complex, dynamic workplaces, often requires subtle, local judgment with regard to timing of subtasks, relevance, importance, prioritization and so forth. Still, people in Nuclear Industry seem to think safety results from people just following procedures. In the wake of failure it can be tempting to introduce new procedures and an even stricter "rule following culture". None, or at least very little, attention is given to tacit knowledge and individual skills. I am aiming to highlight the inadequacy of putting too much trust in formalization and that reporting and trending of events will contribute to increased learning, an increased nuclear safety and an efficient operational experience. The ability to interpret a situation concrete depends on proven experience in similar situations, analogical thinking and tacit knowledge. In this essay I intend to problematize the introduction and use of so-called Corrective Action Program (CAP) and computerized reporting systems linked to CAP in the Nuclear Industry. What I found out is that the whole industry, from regulators to licensees, seems to be stuck in the idea that the scientific perspective on knowledge is the only "true" perspective. This leads to an exaggerated belief in that technology and formalized work processes and routines will create a safer business. The computerized reporting system will not, as the idea was from the beginning, contribute to increased nuclear safety since the reports is based on the trigger and not the underlying causes and in-depth analysis. Managing safety by numbers (incidents, error counts, safety threats, and safety culture indicators) is very practical but has its limitations. Error counts only uphold an illusion of rationality and control, but may offer neither real insight nor productive routes for progress on safety. The question is why the CAP, error counts and computerized reporting systems have had such a big impact in the nuclear industry? It rests after all, on too weak foundations. The answer is that the scientific perspective on knowledge is the dominating perspective. What people do not understand is that an excessive use of computerized systems and an increased formalization actually will create new risks when people lose their skills and ability to reflect and put more trust in the system than in themselves.

abstract: When discussing human factors and performance, researchers recognize stress as a factor, but overlook mood as contributing factor. To explore the relationship between mood, stress and cognitive performance, a field study was conducted involving fire fighters engaged in a fire response simulation. Firefighter participants completed a stress questionnaire, an emotional state questionnaire, and a cognitive task. Stress and cognitive task performance scores were examined before and after the firefighting simulation for individual cognitive performance depreciation caused by stress or mood. They study revealed that existing stress was a reliable predictor of the pre-simulation cognitive task score, that, as mood becomes more positive, perceived stress scores decrease, and that negative mood and pre-simulation stress are also positively and significantly correlated. / Dissertation/Thesis / Masters Thesis Applied Psychology 2014