1,721,131 research outputs found
Cessazione del fumo di sigarette di tabacco in individui resistenti alle terapie tradizionali; uno studio pilota di intervento mindfulness-based
No full textCirca il 20% della popolazione italiana fuma regolarmente sigarette di tabacco, statistica che si complica
quando si considerano le tipologie alternative di sigarette in aumento in commercio. Il fumo patologico di
tabacco è infatti un noto fattore di rischio per lo sviluppo di malattie oncologiche, cardiovascolari e respiratorie
e per l’abbassamento dell’aspettativa di vita. In Italia, sono oltre 90.000 i decessi ogni anno per patologie connesse all’esposizione e al consumo di nicotina. I protocolli basati sulla mindfulness che si associano alla
terza generazione di psicoterapie cognitivo comportamentali rappresentano uno strumento di grande
efficacia nel contesto clinico, sia per gli operatori sanitari che per i pazienti. I protocolli mindfulness-based
nell’ambito delle dipendenze e in particolare per la cessazione del fumo di sigaretta potrebbero rappresentare
un valido supporto alle farmacoterapie tradizionali e, laddove queste non fossero efficaci, un’opzione
alternativa da offrire ai soggetti interessati. La pratica della meditazione all’interno di un programma
mindfulness-based è mirata ad insegnare agli individui come prestare attenzione al momento presente, così
da facilitare la presa di consapevolezza dei propri stati interni, dei sintomi legati all’astinenza, dei pensieri
legati alla dipendenza dal fumo e dei comportamenti tipici come il craving per la sostanza. Le prove di efficacia
degli interventi mindfulness in questo ambito sono ancora limitate, sebbene alcuni studi abbiano dimostrato
la non inferiorità degli stessi alla CBT tradizionale. Praticare la mindfulness rappresenta inoltre un fattore di
protezione per lo sviluppo delle ricadute. Obiettivo del presente studio pilota è stato quello di valutare
l’efficacia del protocollo basato sulla mindfulness per le dipendenze (Mindfulness-Oriented Recovery
Enhancement; MORE; Garland, 2013) all’interno di gruppi di soggetti (N=25, F: 40%) dipendenti da nicotina,
che hanno già completato senza esito positivo il percorso di cessazione del fumo presso il Centro per lo studio
del trattamento al tabagismo CeST dell’Azienda Ospedaliera Universitaria Pisana (AOUP). Gli obiettivi
secondari comprendevano la valutazione dell’efficacia del protocollo rispetto alla riduzione del distress
psicologico e acquisizione di abilità di mindfulness. Allo scopo è stata somministrata una batteria di test
psicologici al fine di indagare: livelli di ansia (STAI Y1 e 2), stress percepito (PSS) e depressione (BDI-II), qualità
del sonno (PSQI), mindfulness di stato e di tratto (MAAS; FFMQ) e abitudini sul fumo (FTND). I risultati
preliminari dello studio offrono importanti spunti di riflessione legati alla compliance al trattamento da parte
di questo tipo di pazienti, ai punti di forza e debolezza dell’applicazione degli interventi mindfulness in questo
contesto e alla riduzione osservata dei comportamenti legati al fumo di sigaretta e di alcune delle variabili
indagate
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
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Understanding the Role of Self-Attention in a Transformer Model for the Discrimination of SCD From MCI Using Resting-State EEG
Full text linkThe identification of EEG biomarkers to discriminate Subjective Cognitive Decline (SCD) from Mild Cognitive Impairment (MCI) conditions is a complex task which requires great clinical effort and expertise. We exploit the self-attention component of the Transformer architecture to obtain physiological explanations of the model's decisions in the discrimination of 56 SCD and 45 MCI patients using resting-state EEG. Specifically, an interpretability workflow leveraging attention scores and time-frequency analysis of EEG epochs through Continuous Wavelet Transform is proposed. In the classification framework, models are trained and validated with 5-fold cross-validation and evaluated on a test set obtained by selecting 20% of the total subjects. Ablation studies and hyperparameter tuning tests are conducted to identify the optimal model configuration. Results show that the best performing model, which achieves acceptable results both on epochs' and patients' classification, is capable of finding specific EEG patterns that highlight changes in the brain activity between the two conditions. We demonstrate the potential of attention weights as tools to guide experts in understanding which disease-relevant EEG features could be discriminative of SCD and MCI
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG
Full text linkObjective. This study aims to design and implement the first deep learning (DL) model to classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state electroencephalographic (EEG) signals. Approach. EEG recordings of 17 healthy controls (HCs), 56 subjective cognitive decline (SCD) and 45 mild cognitive impairment (MCI) subjects were acquired at resting state. After preprocessing, we selected sections corresponding to eyes-closed condition. Five different datasets were created by extracting delta, theta, alpha, beta and delta-to-theta frequency bands using bandpass filters. To classify SCD vs MCI and HC vs SCD vs MCI, we propose a framework based on the transformer architecture, which uses multi-head attention to focus on the most relevant parts of the input signals. We trained and validated the model on each dataset with a leave-one-subject-out cross-validation approach, splitting the signals into 10 s epochs. Subjects were assigned to the same class as the majority of their epochs. Classification performances of the transformer were assessed for both epochs and subjects and compared with other DL models. Main results. Results showed that the delta dataset allowed our model to achieve the best performances for the discrimination of SCD and MCI, reaching an Area Under the ROC Curve (AUC) of 0.807, while the highest results for the HC vs SCD vs MCI classification were obtained on alpha and theta with a micro-AUC higher than 0.74. Significance. We demonstrated that DL approaches can support the adoption of non-invasive and economic techniques as EEG to stratify patients in the clinical population at risk for AD. This result was achieved since the attention mechanism was able to learn temporal dependencies of the signal, focusing on the most discriminative patterns, achieving state-of-the-art results by using a deep model of reduced complexity. Our results were consistent with clinical evidence that changes in brain activity are progressive when considering early stages of AD.TN
The implication of BDNF Val66Met polymorphism in progression from subjective cognitive decline to mild cognitive impairment and Alzheimer's disease: a 9-year follow-up study
No full textBrain-derived natriuretic factor (BDNF) Val66Met polymorphism has been frequently reported to be associated with Alzheimer's disease (AD) with contrasting results. Numerous studies showed that Met allele increased the risk of AD only in women, while other studies have found worse cognitive performance in Val/Val carriers. We aimed to inquire the effects of Val66Met polymorphism on the progression from subjective cognitive decline (SCD) to mild cognitive impairment (MCI) and from MCI to AD and to ascertain if this effect is modulated by demographic and cognitive variables. For this purpose, we followed up 74 subjects (48 SCD, 26 MCI) for a mean time of 9 years. All participants underwent extensive neuropsychological assessment, cognitive reserve estimation, BDNF and apolipoprotein E (ApoE) genotype analysis at baseline. Personality traits and leisure activities were assessed in a subgroup. Each patient underwent clinical-neuropsychological follow-up, during which 18 out of 48 SCD subjects progressed to MCI and 14 out of 26 MCI subjects progressed to AD. We found that Val66Met increased the risk of progression from SCD to MCI and from MCI to AD only in women. Nevertheless, Val/Val carriers who progressed from SCD to MCI had a shorter conversion time compared to Met carriers. We concluded that Val66Met polymorphism might play different roles depending on sex and stage of the disease
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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