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Gender violence is generally conceived as a phenomenon concerning only adults. Nonetheless, it is also perpetrated within teenagers&rsquo, relationships, as many empirical studies have shown. We therefore have focused our attention on a non-probabilistic sample consisting of 400 adolescents living in Naples (Italy), to study the association between sexism and the justification of violent attitudes. Generally, sexism is recognised as a discriminatory attitude towards people, based on their biological sex. However, it is conventional to talk about sexism as a prejudice against women. The Ambivalent Sexism Inventory (ASI) for adolescents was used to evaluate the two dimensions of ambivalent sexism, i.e., hostile sexism (HS) and benevolent sexism (BS). Moreover, the questionnaire regarding attitudes towards diversity and violence (CADV) was administered to assess participants&rsquo, attitudes towards violence. A Partial Least Square&ndash, Second Order Path Model reveals that girls&rsquo, ambivalent sexism is affected more by benevolent sexism than hostile sexism. On the contrary, among boys, hostile sexism has a higher impact. Finally, benevolent sexist girls justify domestic violence more than boys do.

Background Alopecia has been shown to have a significant impact on quality of life (QoL), particularly in women. However, there are no data for African populations. This study was conducted to pilot an original questionnaire and a model-based methodology to measure QoL and its determinants in a sample of South African Black women of African ancestry with alopecia. Methods Fifty participants aged 21–79 years were randomly chosen from patients presenting to dermatologists with alopecia. We used an original questionnaire consisting of 24 items grouped into those assessing the respective impacts of subjective symptoms, objective signs, and relationship issues, measured on a four-level scale. These were then combined using component-based structural equation modeling to return a QoL index (QLI) and to rank the factors contributing to this. Results On a scale ranging from 0 (high QoL) to 100 (severely decreased QoL), we found a mean QLI of 67.7. The negative impact of alopecia on QoL was higher in younger patients than older patients. The factors with the highest impact were those relating to the subjective experience of alopecia and self-image (56.3%), followed by those relevant to relationships and interaction with other people (34.8%). The presence of objective symptoms and signs such as pruritus was of minor importance (8.9%). Conclusions Although not a life-threatening condition, alopecia may seriously impair QoL, particularly by inducing anxiety and reducing self-esteem among African women. Healthcare practitioners should be mindful of this and intervene appropriately to mitigate these effects.

Objective: Patient satisfaction can be measured by criteria inspired by currently available marketing research methods. Among the latter, qualitative methods can be performed on limited population samples and be based on latent variables, i.e., variables that are not directly observed but deducted from mathematical analysis (i.e., quality of life). Qualitative research methods include the partial least squares (PLS) path modelling aimed at defining optimal linear relations among latent variables in order to assemble the best set of predictions. Methods: In the February-May 2007 period, 73 patients (41 males and 32 females) consecutively discharged from the Division of Thoracic Surgery of the National Cancer Institute at Naples underwent an adaptation of the PLS path modelling by accepting to file an itemized questionnaire on 29 different aspects of hospitalization. The sampled population represented about 32% of all patients operated by a single surgeon and about 21% of all patients admitted to a 12-bed thoracic surgical ward in 2007. Five categories of performance were identified, i.e., quality of the facilities, quality and clarity of provided Information, quality of relationship with surgeons and nurses, quality of the received care, overall patient satisfaction. Results: During the analyzed period, the overall patient satisfaction reached 91% (±15). The mean scores were 62% (±33), 80% (±28), 84% (±21), 81% (±19), 88% (±15) for ward facilities, information provided, relationship with personnel, clinical services, and, perceived quality, respectively. In addition, overall perceived quality, relationship with personnel and the provision of information were the variables with greatest positive impact on patient satisfaction. Conversely, waiting times for radiological procedures, quality of meals and duration of visiting hours adversely affected the level of satisfaction. Conclusions: In the setting of a thorough audit of current clinical practice, PLS path modelling may represent another valuable tool to measure quality in the setting of managed health care since it allows for the identification of areas where the service can be improved.

Real world data analysis is often affected by different types of errors as: measurement errors, computation errors, imprecision related to the method adopted for estimating the data. The uncertainty in the data, which is strictly connected to the above errors, may be treated by considering, rather than a single value for each data, the interval of values in which it may fall: the interval data. Statistical units described by interval data can be assumed as a special case of Symbolic Object (SO). In Symbolic Data Analysis (SDA), these data are represented as boxes. Accordingly, purpose of the present work is the extension of Principal Component analysis (PCA) to obtain a visualisation of such boxes, on a lower dimensional space pointing out of the relationships among the variables, the units, and between both of them. The aim is to use, when possible, the interval algebra instruments to adapt the mathematical models, on the basis of the classical PCA, to the case in which an interval data matrix is given. The proposed method has been tested on a real data set and the numerical results, which are in agreement with the theory, are reported.

A presentation of the Partial Least Squares approach to Structural Equation Modeling (or PLS Path Modeling) is given together with a discussion of its extensions. This approach is compared with the estimation of Structural Equation Modeling by means of maximum likelihood (SEM-ML). Notwithstanding, this approach still shows some weaknesses. In this respect, some new improvements are proposed. Furthermore, PLS path modeling can be used for analyzing multiple tables so as to be related to more classical data analysis methods used in this field. Finally, a complete treatment of a real example is shown through the available software.

The present paper deals with the study of continuous interval data by means of suitable Principal Component Analyses (PCA). Statistical units described by interval data can be assumed as special cases of Symbolic Objects (SO) (Diday, 1987). In Symbolic Data Analysis (SDA), these data are represented as hypercubes. In the present paper, we propose some extensions of the PCA with the aim of representing, in a space of reduced dimensions, images of such hypercubes, pointing out differences and similarities according to their structural features.

Technical education and training is now interested by a reform process, trying to integrate the different paths that a student can follow to get a technical degree: the professional schools and training courses. Another challenge is that of integrating in the new system the lessons coming from best innovative practices in the field of the fight to early school living. For this reason the level of application of subsidiarity principle can help to explain differences in the job and social outcome for students. The paper analyses the methodological aspects to be afforded to design a research on the level and effects of subsidiarity in the technical educational system.

International audience

Si ripercorre l'opera di Giorgio Rizzi dal punto di vista della suo contributo organizzativo e scientifico nella Società Italiana di Statistica dapprima come consigliere e quindi come Presidente