RESUMEN
Workplace bullying is associated with a host of negative outcomes for the worker who is the target of bullying, as well as for the organization where the bullying occurs. Moreover, we know that rates of bullying are particularly high in health care settings; however, we are less familiar with the factors that may reduce workplace bullying in hospitals. Thus, this study was conducted to determine whether the humor orientation styles of individuals, including nurses working in hospitals, as well as their managers' leadership styles, can influence perceptions of bullying in the workplace. Using data from 459 workers employed in a large hospital in the Southern United States, we examined associations between the Multidimensional Sense of Humor Scale, which has four dimensions, as well as the Multifactor Leadership Questionnaire, with three leadership substyles, and their associations with the risk of being bullied. We observed that one of the four humor subscales, Humor Appreciation, did affect perceptions of bullying in the workplace. The other three, Humor Recognition, Humor Production, and Humor for Coping, did not. However, the leadership styles of managers did affect reports of negative acts. In fact, transformational leadership was associated with 22% of the variance in reports of decreased bullying activity. This work is consistent with previous work on the importance of leadership styles for creating positive work environments, particularly in hospital settings. Given these findings, we offer suggestions for leaders to further improve nursing communication.
Asunto(s)
Acoso Escolar/psicología , Relaciones Interprofesionales , Liderazgo , Cuerpo Médico de Hospitales/psicología , Ingenio y Humor como Asunto , Adulto , Anciano , Femenino , Hospitales , Humanos , Masculino , Cuerpo Médico de Hospitales/estadística & datos numéricos , Persona de Mediana Edad , Personal de Enfermería en Hospital/psicología , Personal de Enfermería en Hospital/estadística & datos numéricos , Encuestas y Cuestionarios , Estados Unidos , Adulto JovenRESUMEN
BACKGROUND AND PURPOSE: Individuals with Parkinson disease (PD) have motor and nonmotor impairments that interfere with exercise participation. The purpose of this study was to examine the feasibility and physical performance outcomes of a community-based indoor tandem cycling program that was designed to facilitate a higher cadence, consistency, and intensity of training. METHODS: Forty-one participants with mild to moderate PD were enrolled. A high-cadence cycling protocol using mechanically augmented (or forced) exercise on a tandem bicycle was adapted for our program. Participants cycled 3 times per week for 10 weeks. Feasibility measures included program retention, attendance, and adverse events, as well as the ability to reach training goals for heart rate (HR) and cadence. Physical performance outcomes included the Berg Balance Scale (BBS), Short Physical Performance Battery (SPPB), Five-Times-Sit-to-Stand (FTSTS) Test, Timed Up and Go (TUG), and gait parameters during usual and fast-paced walking. RESULTS: Program feasibility was demonstrated with a high attendance rate (96%) and retention rate (100%). There were no adverse events. The majority of participants reached their exercise training goals for target HR (87%) and cadence (95%). Statistically significant physical performance improvement (P < 0.05) was observed across domains of gait, balance, and mobility, suggesting a slowing or reversal of functional decline as a result of this cycling program. DISCUSSION AND CONCLUSION: Program feasibility and improved physical performance outcomes were demonstrated in individuals with mild to moderate PD participating in a community-based indoor tandem cycling program.Video Abstract available for more insights from the authors (see supplemental digital content 1, http://links.lww.com/JNPT/A146).
Asunto(s)
Ciclismo , Destreza Motora , Enfermedad de Parkinson/terapia , Anciano , Estudios de Factibilidad , Humanos , Persona de Mediana EdadRESUMEN
Discrete trees and small groups of trees in nonforest settings are considered an essential resource around the world and are collectively referred to as trees outside forests (ToF). ToF provide important functions across the landscape, such as protecting soil and water resources, providing wildlife habitat, and improving farmstead energy efficiency and aesthetics. Despite the significance of ToF, forest and other natural resource inventory programs and geospatial land cover datasets that are available at a national scale do not include comprehensive information regarding ToF in the United States. Additional ground-based data collection and acquisition of specialized imagery to inventory these resources are expensive alternatives. As a potential solution, we identified two remote sensing-based approaches that use free high-resolution aerial imagery from the National Agriculture Imagery Program (NAIP) to map all tree cover in an agriculturally dominant landscape. We compared the results obtained using an unsupervised per-pixel classifier (independent component analysis-[ICA]) and an object-based image analysis (OBIA) procedure in Steele County, Minnesota, USA. Three types of accuracy assessments were used to evaluate how each method performed in terms of: (1) producing a county-level estimate of total tree-covered area, (2) correctly locating tree cover on the ground, and (3) how tree cover patch metrics computed from the classified outputs compared to those delineated by a human photo interpreter. Both approaches were found to be viable for mapping tree cover over a broad spatial extent and could serve to supplement ground-based inventory data. The ICA approach produced an estimate of total tree cover more similar to the photo-interpreted result, but the output from the OBIA method was more realistic in terms of describing the actual observed spatial pattern of tree cover.
Asunto(s)
Monitoreo del Ambiente/métodos , Tecnología de Sensores Remotos , Árboles , Conservación de los Recursos Naturales/métodosRESUMEN
Selection of a modeling approach is an important step in the conservation planning process, but little guidance is available. We compared two statistical and three theoretical habitat modeling approaches representing those currently being used for avian conservation planning at landscape and regional scales: hierarchical spatial count (HSC), classification and regression tree (CRT), habitat suitability index (HSI), forest structure database (FS), and habitat association database (HA). We focused our comparison on models for five priority forest-breeding species in the Central Hardwoods Bird Conservation Region: Acadian Flycatcher, Cerulean Warbler, Prairie Warbler, Red-headed Woodpecker, and Worm-eating Warbler. Lacking complete knowledge on the distribution and abundance of each species with which we could illuminate differences between approaches and provide strong grounds for recommending one approach over another, we used two approaches to compare models: rank correlations among model outputs and comparison of spatial correspondence. In general, rank correlations were significantly positive among models for each species, indicating general agreement among the models. Worm-eating Warblers had the highest pairwise correlations, all of which were significant (P < 0.05). Red-headed Woodpeckers had the lowest agreement among models, suggesting greater uncertainty in the relative conservation value of areas within the region. We assessed model uncertainty by mapping the spatial congruence in priorities (i.e., top ranks) resulting from each model for each species and calculating the coefficient of variation across model ranks for each location. This allowed identification of areas more likely to be good targets of conservation effort for a species, those areas that were least likely, and those in between where uncertainty is higher and thus conservation action incorporates more risk. Based on our results, models developed independently for the same purpose (conservation planning for a particular species in a particular geography) yield different answers and thus different conservation strategies. We assert that using only one habitat model (even if validated) as the foundation of a conservation plan is risky. Using multiple models (i.e., ensemble prediction) can reduce uncertainty and increase efficacy of conservation action when models corroborate one another and increase understanding of the system when they do not.