Negative Transfer of Training: Simulator Study Into the Effects of Overruled Pilot Decision Making

This report was originally published by the Netherlands Organization for Applied Scientific Research (TNO), Human Performance; Soesterberg, The Netherlands as TNO 2023 R10152In this simulator study, we investigated the potential negative transfer of training that may result from situations where a correct decision made by the trainee is being overruled by the instructor to save training time. We hypothesized that discarding a correct decision in a training situation can introduce confusion when the trainee encounters a similar situation in operational practice. The experiment was performed in a fixed-base simulator of a twin-engine business jet. Two groups of 19 commercial pilots participated in a training session consisting of four training scenarios, immediately followed by a test session with four other test scenarios. Whereas in the \u201ccontrol\u201d group the training scenarios were presented as briefed, the pilots in the experimental, or \u201coverruled\u201d group included some events (e.g., an enhanced ground proximity warning (EGPWS)) which required a response. However, the instructor directed the pilots to refrain from the response. It was expected that pilots in the overruled group were more likely to show delayed response or even ignore alarms in the test scenarios. The objective results showed no significant effect of the training manipulation on the performance of the pilots in the test scenarios involving the same type of events as the overruled group had encountered during the training. However, according to the subjective results, 32% of the participating pilots stated that they had been confused during the test, and that the training influenced their decision making. Within the limits of this study, these findings are an indication of negative transfer of training

Mobility, Balance and Falls in Persons with Multiple Sclerosis

BACKGROUND: There is a lack of information concerning the relation between objective measures of gait and balance and fall history in persons with MS (PwMS). This investigation assessed the relation between demographic, clinical, mobility and balance metrics and falls history in persons with multiple sclerosis (MS). METHODS: 52 ambulatory persons with MS (PwMS) participated in the investigation. All persons provided demographic information including fall history over the last 12 months. Disease status was assessed with Expanded Disability Status Scale (EDSS). Walking speed, coordination, endurance and postural control were quantified with a multidimensional mobility battery. RESULTS: Over 51% of the participants fell in the previous year with 79% of these people being suffering recurrent falls. Overall, fallers were older, had a greater prevalence of assistive devices use, worse disability, decreased walking endurance, and greater postural sway velocity with eyes closed compared to non-fallers. Additionally, fallers had greater impairment in cerebellar, sensory, pyramidal, and bladder/bowel subscales of the EDSS. CONCLUSIONS: The current observations suggest that PwMS who are older, more disabled, utilize an assistive device, have decreased walking coordination and endurance and have diminished balance have fallen in the previous year. This suggests that individuals who meet these criteria need to be carefully monitored for future falls. Future research is needed to determine a prospective model of falls specific to PwMS. Additionally, the utility of interventions aimed at reducing falls and fall risk in PwMS needs to be established

Complex systems and the technology of variability analysis

Characteristic patterns of variation over time, namely rhythms, represent a defining feature of complex systems, one that is synonymous with life. Despite the intrinsic dynamic, interdependent and nonlinear relationships of their parts, complex biological systems exhibit robust systemic stability. Applied to critical care, it is the systemic properties of the host response to a physiological insult that manifest as health or illness and determine outcome in our patients. Variability analysis provides a novel technology with which to evaluate the overall properties of a complex system. This review highlights the means by which we scientifically measure variation, including analyses of overall variation (time domain analysis, frequency distribution, spectral power), frequency contribution (spectral analysis), scale invariant (fractal) behaviour (detrended fluctuation and power law analysis) and regularity (approximate and multiscale entropy). Each technique is presented with a definition, interpretation, clinical application, advantages, limitations and summary of its calculation. The ubiquitous association between altered variability and illness is highlighted, followed by an analysis of how variability analysis may significantly improve prognostication of severity of illness and guide therapeutic intervention in critically ill patients

Mechanisms of T cell organotropism

F.M.M.-B. is supported by the British Heart Foundation, the Medical Research Council of the UK and the Gates Foundation