PubMed · 2260374
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A Kruse. [Potentials in the elderly].. https://pubmed.ncbi.nlm.nih.gov/2260374/
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Graphical Markov models have been developed particularly for the analysis of observational data. They allow the control of various background variables when analysing theoretically relevant associations. This paper demonstrates the application and some advantages of graphical Markov models in comparison to conventional statistical analyses. The aim of the study was to identify patients at risk for developing decreased health-related quality of life (QoL) after cystectomy and to explore the influence of coping on QoL in this situation. Therefore, the method was applied to analyse the data of a prospective study, in which 81 patients with bladder cancer were interviewed pre-operatively and in a 1-year follow-up. QoL was assessed both times, and two basic coping strategies (active and depressive) were measured preoperatively. The explanatory variables of theoretical interest were active and depressive coping strategies. As a result of the analysis, relevant proportions of variance in the development of QoL could be explained by the suggested model (60 per cent in mental component, 40 per cent in physical component of QoL). Active coping was positively related to QoL, depressive coping negatively. These effects were linear in the physical component of QoL, moderated by working status and the type of urinary diversion in the mental component of QoL.
The goal of the study was to examine the accuracy and precision of control of adaptive locomotion using haptic information in normally sighted humans before and after practice. Obstacle avoidance paradigm was used to study adaptive locomotion; individuals were required to approach and step over different sizes of obstacles placed in the travel path under three sensory conditions: full vision (FV); restricted lower visual field (RLVF) using blinders on custom glass frames; and no vision (NV) using haptic information only. In the NV condition, individuals were a given an appropriate-sized cane to guide their locomotion. Footfall patterns were recorded using the GAITRite system, and lead and trail limb trajectories were monitored using the OPTOTRAK system, which tracked infrared diodes placed on the toes and the cane. Approach step lengths were reduced for the haptic condition: this slowed the forward progression and allowed greater time for haptic exploration, which ranged from 2.5 to 4 s and consisted of horizontal cane movements (to detect the width and relative location of the obstacle) and vertical cane movements (to detect the height of the obstacle). Based on feed-forward and on-line sensory (under both vision and haptic conditions) information about location of the obstacle relative to the individual, variability of foot placement reduced as the individual came closer to the obstacle, as has been shown in the literature. The only difference was that the reduction in variability of foot placement under haptic condition occurred in the last step compared with earlier under vision. Considering that the obstacle is detected only when the cane comes in contact, as opposed to vision condition when it is visible earlier, this difference is understandable. Variability and magnitude of lead and trail limb elevation for the haptic condition was higher than the RLVF and FV conditions. In contrast, only the magnitude of lead and trail limb elevation was higher in the RLVF condition when compared with the FV condition. This suggests that it is the inability of the haptic sense to provide accurate information about obstacle characteristics compared with the visual system, and not simple caution that lead to higher limb elevation. In the haptic and RLVF condition when vision was unavailable for on-line monitoring of lead limb elevation, kinesthetic information from lead limb elevation was used to fine-tune trail limb elevation. Both the control of approach phase and limb elevation findings held up even after sufficient practice to learn haptic guidance of adaptive locomotion in the second experiment. These results provide a clear picture of the efficacy of the haptic sensory system to guide locomotion in a cluttered environment.
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