The hospital survey on patient safety culture in Portuguese hospitals: instrument validity and reliability

Purpose – Quantitative instruments to assess patient safety culture have been developed recently and a few review articles have been published. Measuring safety culture enables healthcare managers and staff to improve safety behaviours and outcomes for patients and staff. The study aims to determine the AHRQ Hospital Survey on Patient Safety Culture (HSPSC) Portuguese version's validity and reliability. Design/methodology/approach – A missing-value analysis and item analysis was performed to identify problematic items. Reliability analysis, inter-item correlations and inter-scale correlations were done to check internal consistency, composite scores. Inter-correlations were examined to assess construct validity. A confirmatory factor analysis was performed to investigate the observed data's fit to the dimensional structure proposed in the AHRQ HSPSC Portuguese version. To analyse differences between hospitals concerning composites scores, an ANOVA analysis and multiple comparisons were done. Findings – Eight of 12 dimensions had Cronbach's alphas higher than 0.7. The instrument as a whole achieved a high Cronbach's alpha (0.91). Inter-correlations showed that there is no dimension with redundant items, however dimension 10 increased its internal consistency when one item is removed. Originality/value – This study is the first to evaluate an American patient safety culture survey using Portuguese data. The survey has satisfactory reliability and construct validity.

Parental predictors of poor visual outcome with occlusion treatment for unilateral amblyopia

Aim: Visual acuity outcome of amblyopia treatment depends on the compliance. This study aimed to determine parental predictors of poor visual outcome with occlusion treatment in unilateral amblyopia and identify the relationship between occlusion recommendations and the patient's actual dose of occlusion reported by the parents. Methods: This study comprised three phases: refractive adaptation for a period of 18 weeks after spectacle correction; occlusion of 3 to 6 hours per day during a period of 6 months; questionnaire administration and completion by parents. Visual acuity as assessed using the Sheridan-Gardiner singles or Snellen acuity chart was used as a measure of visual outcome. Correlation analysis was used to describe the strength and direction of two variables: prescribed occlusion reported by the doctor and actual dose reported by parents. A logistic binary model was adjusted using the following variables: severity, vulnerability, self-efficacy, behaviour intentions, perceived efficacy and treatment barriers, parents' and childrens' age, and parents' level of education. Results: The study included 100 parents (mean age 38.9 years, SD approx 9.2) of 100 children (mean age 6.3 years, SD approx 2.4) with amblyopia. Twenty-eight percent of children had no improvement in visual acuity. The results showed a positive mild correlation (kappa = 0.54) between the prescribed occlusion and actual dose reported by parents. Three predictors for poor visual outcome with occlusion were identified: parents' level of education (OR = 9.28; 95%CI 1.32-65.41); treatment barriers (OR = 2.75; 95%CI 1.22-6.20); interaction between severity and vulnerability (OR = 3.64; 95%CI 1.21-10.93). Severity (OR = 0.07; 95%CI 0.00-0.72) and vulnerability (OR = 0.06; 95%CI 0.05-0.74) when considered in isolation were identified as protective factors. Conclusions: Parents frequently do not use the correct dosage of occlusion as recommended. Parents' educational level and awareness of treatment barriers were predictors of poor visual outcome. Lower levels of education represented a 9-times higher risk of having a poor visual outcome with occlusion treatment.

Does independent component analysis play a role in unmixing hyperspectral data?

Independent component analysis (ICA) has recently been proposed as a tool to unmix hyperspectral data. ICA is founded on two assumptions: 1) the observed spectrum vector is a linear mixture of the constituent spectra (endmember spectra) weighted by the correspondent abundance fractions (sources); 2)sources are statistically independent. Independent factor analysis (IFA) extends ICA to linear mixtures of independent sources immersed in noise. Concerning hyperspectral data, the first assumption is valid whenever the multiple scattering among the distinct constituent substances (endmembers) is negligible, and the surface is partitioned according to the fractional abundances. The second assumption, however, is violated, since the sum of abundance fractions associated to each pixel is constant due to physical constraints in the data acquisition process. Thus, sources cannot be statistically independent, this compromising the performance of ICA/IFA algorithms in hyperspectral unmixing. This paper studies the impact of hyperspectral source statistical dependence on ICA and IFA performances. We conclude that the accuracy of these methods tends to improve with the increase of the signature variability, of the number of endmembers, and of the signal-to-noise ratio. In any case, there are always endmembers incorrectly unmixed. We arrive to this conclusion by minimizing the mutual information of simulated and real hyperspectral mixtures. The computation of mutual information is based on fitting mixtures of Gaussians to the observed data. A method to sort ICA and IFA estimates in terms of the likelihood of being correctly unmixed is proposed.

Development and validation of a psychometric scale for assessing PA chest image quality: a pilot study

Purpose - To develop and validate a psychometric scale for assessing image quality perception for chest X-ray images. Methods - Bandura's theory was used to guide scale development. A review of the literature was undertaken to identify items/factors which could be used to evaluate image quality using a perceptual approach. A draft scale was then created (22 items) and presented to a focus group (student and qualified radiographers). Within the focus group the draft scale was discussed and modified. A series of seven postero-anterior chest images were generated using a phantom with a range of image qualities. Image quality perception was confirmed for the seven images using signal-to-noise ratio (SNR 17.2–36.5). Participants (student and qualified radiographers and radiology trainees) were then invited to independently score each of the seven images using the draft image quality perception scale. Cronbach alpha was used to test interval reliability. Results - Fifty three participants used the scale to grade image quality perception on each of the seven images. Aggregated mean scale score increased with increasing SNR from 42.1 to 87.7 (r = 0.98, P < 0.001). For each of the 22 individual scale items there was clear differentiation of low, mid and high quality images. A Cronbach alpha coefficient of >0.7 was obtained across each of the seven images. Conclusion - This study represents the first development of a chest image quality perception scale based on Bandura's theory. There was excellent correlation between the image quality perception scores derived using the scale and the SNR. Further research will involve a more detailed item and factor analysis.

Impacto da síncope na qualidade de vida: validação duma escala de avaliação em doentes submetidos a teste de inclinação em mesa basculante

Introdução e objetivos: A síncope recorrente tem um impacto significativo na qualidade de vida. O desenvolvimento de escalas de medida de fácil aplicabilidade clínica para avaliar este impacto é fundamental. O objetivo do presente estudo é a validação preliminar da escala Impact of Syncope on Quality of Life, para a população portuguesa. Métodos: O instrumento foi submetido a um processo de tradução, validação, adequação cultural e cognitive debriefing. Participaram 39 doentes com história de síncopes recorrentes (>1 ano de evolução), submetidos a teste de inclinação em mesa basculante (teste de tilt), que constitui uma amostra de conveniência, com idade de 52,1±16,4 anos (21-83; 43,5% do sexo masculino), a maioria com uma situação profissional ativa (n=18) ou reformados (n=13). A versão portuguesa resultou numa versão semelhante unidimensional à original com 12 itens agregados num único somatório, tendo passado por validação estatística, com avaliação da fidelidade, validade e estabilidade no tempo. Resultados: Em relação à fidelidade, a consistência interna da escala é de 0,9. Avaliámos a validade convergente, tendo obtido resultados estatisticamente significativos (p<0,01). Avaliámos a validade divergente tendo obtido resultados estatisticamente significativos. Relativamente à estabilidade no tempo foi efetuado um teste-reteste do instrumento aos seis meses após o teste de inclinação com 22 doentes desta amostra não submetidos a intervenção clínica, que não mostrou alterações estatisticamente significativas da qualidade de vida. Conclusões: Os resultados obtidos indicam a pertinência da utilização deste instrumento em contexto português na avaliação da qualidade de vida de doentes com síncope recorrente.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Dispositional optimism is unidimensional or bidimensional? The Portuguese Revised Life Orientation Test

The aim of the study is to adapt and then discuss the appropriateness of the Life Orientation Test as a one or two dimension scale. The research includes two studies; one is composed of a sequential sample of 280 people with multiple sclerosis, 71% female, and another includes a convenience sample of 615 individuals from the community, 51.1% female. Because the construct is built upon a theoretical assumption that has one dimension, we examine the hypothesis of one or two factor solutions through confirmatory factor analysis, and the two-dimension solution premise demonstrates better adjustment for both samples. The other psychometric properties explored show appropriate results for the Portuguese sample, and similar to the original ones; the Test therefore seems appropriate for use in cross cultural studies. Based on our results, we discuss whether the questionnaire is a one or two dimension instrument, concluding that it appears appropriate to accept the recommendations of the original authors to use it as a one-dimensional tool and, when necessary, to use both dimensions. - RESUMO: El objetivo del estudio es adaptar y discutir la adecuación de la prueba de Orientación de la Vida en una o dos escalas de dimensión. La investigación engloba dos estudios, uno constituido por una muestra secuencial de 280 personas con esclerosis múltiple, 71% mujeres y otro con una muestra de conveniencia de la comunidad de 615 individuos, 51,1% del sexo femenino. Como el constructo se asienta sobre la presunción teórica de que tiene una dimensión, inspeccionamos la hipótesis de una o dos soluciones de factor a través del análisis factorial confirmatorio y la hipótesis de dos dimensiones manifiesta un mejor ajuste para ambas muestras. Las otras propiedades psicométricas exploradas muestran los resultados apropiados para la muestra portuguesa, y semejantes a los originales. Parece apropiado para los estudios culturales transversales. Basándonos en nuestros resultados, discutimos si el cuestionario es un instrumento de una o dos dimensiones, concluyéndose que parece conveniente seguir las recomendaciones de los autores originales, para utilizarlo como un instrumento unidimensional y, si fuera necesario necesario, utilizar cada una de las dimensiones.

Patrocínio: influência na atitude relativamente à marca e intenção de compra: caso Nike e selecção portuguesa de futebol

Devido à enorme importância que tem sido atribuída ao desporto nas últimas décadas, os marketers abraçam agora totalmente o facto de uma campanha integrada de patrocínio desportivo poder atingir um imensurável número de benefícios. Na verdade, apesar das empresas se comprometerem hoje com muitas outras áreas como a cultura, caridade e domínios humanitários, o desporto continua a ser o campo mais requisitado no que ao patrocínio se refere. Para muitas organizações o patrocínio desportivo é, de facto, o elemento-chave de uma comunicação integrada de marketing. Devido então a todo este enfase dado ao desporto, decidimos verificar se a relação de patrocínio entre a marca Nike e a Selecção Portuguesa de Futebol (SPF) influencia a atitude relativamente à marca e a intenção de compra dos seus produtos, o que constitui o objectivo desta investigação. Assim, tendo como ponto de partida a questão: exercerá a relação de patrocínio entre a Nike e a SPF alguma influência na atitude relativamente à marca e sua intenção de compra? E, por meio de uma revisão da literatura referente a este tema, desenvolvemos um modelo conceptual, o qual é baseado no criado por Martensen et al (2007) e integra quatro principais conceitos: envolvimento, atitudes, intenção de compra e congruência entre a marca e o evento. O presente estudo emprega um design exploratório envolvendo uma colecta de dados quantitativos, através da aplicação de um questionário online. De modo a confirmarmos o modelo proposto, duas técnicas estatísticas foram utilizadas: análise factorial e análise de equações estruturais (AEE). As conclusões desta investigação podem fornecer directivas para a compreensão de como uma relação de patrocínio pode criar ou melhorar a atitude relativamente a uma marca e sua intenção de compra. Como principal resultado, podemos destacar a existência de uma influência positiva da relação de patrocínio na atitude relativamente à marca.

As competências dos técnicos de radiologia: um contributo para a sua identificação e definição

Mestrado em Intervenção Sócio-Organizacional em Saúde - Ramo de especialização: Políticas de Administração e Gestão de Serviços de Saúde