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A Non-linear Predictive Model of Borderline Personality Disorder Based on Multilayer Perceptron

Overview of attention for article published in Frontiers in Psychology, April 2018
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  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

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Title
A Non-linear Predictive Model of Borderline Personality Disorder Based on Multilayer Perceptron
Published in
Frontiers in Psychology, April 2018
DOI 10.3389/fpsyg.2018.00447
Pubmed ID
Authors

Nelson M. Maldonato, Raffaele Sperandeo, Enrico Moretto, Silvia Dell'Orco

Abstract

Borderline Personality Disorder is a serious mental disease, classified in Cluster B of DSM IV-TR personality disorders. People with this syndrome presents an anamnesis of traumatic experiences and shows dissociative symptoms. Since not all subjects who have been victims of trauma develop a Borderline Personality Disorder, the emergence of this serious disease seems to have the fragility of character as a predisposing condition. Infect, numerous studies show that subjects positive for diagnosis of Borderline Personality Disorder had scores extremely high or extremely low to some temperamental dimensions (harm Avoidance and reward dependence) and character dimensions (cooperativeness and self directedness). In a sample of 602 subjects, who have had consecutive access to an Outpatient Mental Health Service, it was evaluated the presence of Borderline Personality Disorder using the semi-structured interview for the DSM IV-TR personality disorders. In this population we assessed the presence of dissociative symptoms with the Dissociative Experiences Scale and the personality traits with the Temperament and Character Inventory developed by Cloninger. To assess the weight and the predictive value of these psychopathological dimensions in relation to the Borderline Personality Disorder diagnosis, a neural network statistical model called "multilayer perceptron," was implemented. This model was developed with a dichotomous dependent variable, consisting in the presence or absence of the diagnosis of borderline personality disorder and with five covariates. The first one is the taxonomic subscale of dissociative experience scale, the others are temperamental and characterial traits: Novelty-Seeking, Harm-Avoidance, Self-Directedness and Cooperativeness. The statistical model, that results satisfactory, showed a significance capacity (89%) to predict the presence of borderline personality disorder. Furthermore, the dissociative symptoms seem to have a greater influence than the character traits in the borderline personality disorder e disease. In conclusion, the results seem to indicate that to borderline personality disorder development, contribute both psychic factors, such as temperament and character traits, and environmental factors, such as traumatic events capable of producing dissociative symptoms. These factors interact in a nonlinear way in producing maladaptive behaviors typical of this disorder.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 92 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 11 12%
Student > Master 8 9%
Student > Ph. D. Student 6 7%
Researcher 4 4%
Professor > Associate Professor 4 4%
Other 8 9%
Unknown 51 55%
Readers by discipline Count As %
Psychology 19 21%
Medicine and Dentistry 6 7%
Computer Science 4 4%
Neuroscience 3 3%
Social Sciences 2 2%
Other 4 4%
Unknown 54 59%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 May 2018.
All research outputs
#6,280,126
of 23,028,364 outputs
Outputs from Frontiers in Psychology
#9,010
of 30,291 outputs
Outputs of similar age
#110,478
of 329,097 outputs
Outputs of similar age from Frontiers in Psychology
#256
of 580 outputs
Altmetric has tracked 23,028,364 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 30,291 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one has gotten more attention than average, scoring higher than 70% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,097 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 580 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.