1,721,058 research outputs found
Generalized properties for Hanafi–Wold’s procedure in partial least squares path modeling
No full textPartial least squares path modeling is a statistical method that allows to analyze complex dependence relationships among several blocks of observed variables, each one represented by a latent variable. The computation of latent variable scores is an essential step of the method, achieved through an iterative procedure named here Hanafi–Wold’s procedure. The present paper generalizes properties already known in the literature for this procedure, from which additional convergence results will be obtained
Community Trust: A Social Indicator Related to Community Engagement
No full textA review of the literature has highlighted that some studies have defined an indicator of trust regarding one’s geographical community, but that few studies refer to the community, in relation to the role of its social interactions used to attain and promote personal and collective planning. Therefore, this study introduced community trust as a composite indicator used to measure community opportunities, as perceived by citizens, in addition to discovering their local culture. A third-order construct model was proposed, specifying community trust as a multidimensional construct, which is composed of two different domains: Community Action Orientation and Community Future Opportunities (CFO). Each domain was considered separately, although they are integral parts of community trust. The results showed that the proposed model performs well in measuring community trust. All blocks of variables indicated good internal consistency, and factor analysis results were consistent with the hypothesized dimensions in each block. Furthermore, the social ties indicator, known as sense of community, was measured using the Italian-version of the Sense of Community Scale. Factor analysis was applied to analyze data and to provide an indicator for sense of community. Finally, through a logistic regression, the relationship between both community trust and sense of community with community engagement were analyzed. We found that community trust is significantly associated with community engagement, while sense of community is not. The proposed community trust indicator offers some guidance to urban planners and local governments, when promoting urban development, social empowerment, and community wellbein
Caregivers’ sensemaking of children’s hereditary angioedema: A semiotic narrative analysis of the sense of grip on the disease
No full textBackground and aims: In pediatrics receiving a diagnosis of a chronic condition is a matter that involves caregivers at first. Beyond the basic issues of caring for the physical condition of the ill child, how caregivers face and make sense of the disease orients and co-constructs their children’s sensemaking processes of the disease itself. The aim of this article is to explore the experience of a rare chronic illness, a pediatric case of Hereditary Angioedema (HAE) from the caregivers’ perspective. Hereditary angioedema is characterized by subcutaneous swellings that can involve internal as well as external mucosal tissues and is highly variable and unpredictable in terms of severity, frequency, and where it occurs. A qualitative narrative semiotic analysis of n. 28 maternal narratives on their children’s disease experience. Narratives were collected by an ad hoc interview on three domains of the disease experience: (A) interpretation of disease variability, (B) dialogical processes, and (C) management of the disease. Subsequently, we executed a TwoStep cluster analysis for categorical data to detect cross-sectional profiles of the maternal sensemaking processes of the disease. Results: The coding grid was built analyzing the characteristics of the narrative links that orient the connection between the elements of the experience within each domain: (A) the connection among events, for the domain of disease variability interpretation, (B) the connection between self and other, for the dialogue domain, and (C) the connection among sensemaking and actions, for the disease management domain. Results from the cluster analysis show three narrative profiles: (1) adempitive; (2) reactive; (3) dynamic. Discussion: Profiles will be discussed in light of the general conceptual framework of the Sense of Grip on the Disease (SoGoD) highlighting the importance of those sensemaking processes which, instead of relying on a coherent and closed interpretation of the disease, are characterized by a degree of tolerance for uncertainty and the unknown
Exploring emotions in dialog between health provider, parent and child in pediatric primary care
No full textRiconoscere le emozioni quali informazioni utili al dialogo. Un'indagine empirica in pediatria di famiglia.
No full textL’espressione delle emozioni nel dialogo sanitario è un’importante componente dello scambio
dialogico soprattutto in ambito pediatrico dove si ha a che fare con almeno due utenti (genitore e
bambino). Sono state analizzate 265 visite di pediatria di famiglia utilizzando il Verona Coding
Definition of Emotional Sequences (VR-CoDES) per identificare le preoccupazioni di genitori e bambini
e le risposte fornite dai pediatri (Del Piccolo et al.,2010). Sono stati individuati attraverso la Sparse
Canonical Correlation Analysis (Hastie et al., 2015) i pattern di interazione dialogica tra le coppie di
componenti canoniche per ogni Asse di Interazione Dialogica (AID) del triangolo relazionale Pediatra- Genitore- Bambino. Sembra che lo scambio dialogico si possa concentrare sul processo di cura, che le
emozioni espresse siano considerate componenti routinarie delle visite (Dicé, Dolce & Freda, 2016;
Freda et al., 2015), con poche opportunità di espressione delle emozioni, raramente utilizzate quali
risorse fondamentali di senso nel dialogo clinico. Pensiamo che interventi di Scaffolding alla relazione
sanitaria (Freda et al., 2015) possano favorire la riflessione sulle risorse di senso attribuite dai
partecipanti alle emozioni nella relazion
Post-induction infliximab trough levels and disease activity in the clinical evolution of pediatric ulcerative colitis
No full textBackground and aims: Recent adult evidence suggests that infliximab (IFX) trough levels (TL) in patients with severe ulcerative colitis (UC) may be decreased. The aims of our study were to compare post-induction IFX TL of children with severe versus moderate UC and to evaluate short- and long-term outcomes. Methods: In this single-center retrospective study, children with a diagnosis of UC starting IFX with a Pediatric Ulcerative Colitis Activity Index (PUCAI) ≥35 and with available post-induction TL were recruited. UC characteristics, IFX dosage and interval, primary non-response, IFX failure, and surgery after 24 months were collected. Post induction TL, anti-IFX antibodies, and laboratory evaluations at the time of starting IFX were also acquired. Results: A total of 90 children were enrolled, of whom 39 (43.3%) were classified as severe UC and 51 (56.6%) as moderate UC. Median post-induction IFX TL were lower in severe UC versus moderate group (5.5 vs 10.3; p = 0.03), despite a more frequently intensified IFX regimen. Children in the higher TL quartiles showed increased rates of clinical, biological, and combined remission (p = 0.04, p < 0.001, and p = 0.01, respectively). In a multivariate analysis, a PUCAI ≥65 and time interval from last IFX infusion were the only predictors associated with IFX TL. At 24 months, children in the higher TL quartiles had a decreased risk of IFX failure (p = 0.002). The severe UC group showed a higher risk of IFX failure at 24 months (16/23 (41%) vs. 11/40 (21.6%); p = 0.05). Kaplan–Meier methods demonstrated a trend toward statistical significance, with a two-year cumulative colectomy rate of 15.38% (95% confidence interval (CI) 8.1–15.6%) in children with severe UC and 3.92% (95% CI 2.9–10.8%) in patients with moderate UC (logrank test p = 0.06). Conclusions: Children starting IFX with severe UC showed lower post-induction TL and poor disease outcomes. Achieving adequate TL was associated with better efficacy outcomes
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Overcoming convergence problems in PLS path modelling
No full textThe present paper deals with convergence issues of Lohmöller’s procedure for the computation of the components in the PLS-PM algorithm. More datasets and proofs are given to highlight the convergence failure of this procedure. Consequently, a new procedure based on the Signless Lapalacien matrix of the indirect graph between constructs is introduced. In several cases that will be specified in this paper, both monotony and error convergence for this new procedure will be established. Several comparisons will be presented between the new procedure and the two conventionally used procedures (Lohmöller’s and Hanafi-Wold’s procedures)
Toward a Machine Learning Predictive-Oriented Approach to Complement Explanatory Modeling. An Application for Evaluating Psychopathological Traits Based on Affective Neurosciences and Phenomenology
Full text linkThis paper presents a procedure that aims to combine explanatory and predictive modeling for the construction of new psychometric questionnaires based on psychological and neuroscientific theoretical grounding. It presents the methodology and the results of a procedure for items selection that considers both the explanatory power of the theory and the predictive power of modern computational techniques, namely exploratory data analysis for investigating the dimensional structure and artificial neural networks (ANNs) for predicting the psychopathological diagnosis of clinical subjects. Such blending allows deriving theoretical insights on the characteristics of the items selected and their conformity with the theoretical framework of reference. At the same time, it permits the selection of those items that have the most relevance in terms of prediction by therefore considering the relationship of the items with the actual psychopathological diagnosis. Such approach helps to construct a diagnostic tool that both conforms with the theory and with the individual characteristics of the population at hand, by providing insights on the power of the scale in precisely identifying out-of-sample pathological subjects. The proposed procedure is based on a sequence of steps that allows the construction of an ANN capable of predicting the diagnosis of a group of subjects based on their item responses to a questionnaire and subsequently automatically selects the most predictive items by preserving the factorial structure of the scale. Results show that the machine learning procedure selected a set of items that drastically improved the prediction accuracy of the model (167 items reached a prediction accuracy of 88.5%, that is 25.6% of incorrectly classified), compared to the predictions obtained using all the original items (260 items with a prediction accuracy of 74.4%). At the same time, it reduced the redundancy of the items and eliminated those with less consistency
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