Poverty and Mental Health. Tangible and Intangible Aspects of Microcredit

Microcredit, a small lending system, invests on an individual's creativity by stimulating the development of their own potential. This process leads to the attainment of various objectives which in turn allow individuals to develop their skill awareness. Consequently, this process also increases an individual’s self-esteem and self-confidence. These factors play an important role in the aetiology of a number of mental disorders. Namely, those characterized by a series of psychological conditions which impede the full development of a person’s personal, relational and social sphere. Furthermore, since Microcredit is thought to produce tangible goods, such as income, and intangible goods, such as self-esteem and mutual trust, it could also represent an innovative socio-economic tool. We therefore also hypothesize that, Microcredit would be valuable in maximizing abilities/skills in those subjects who are financially excluded and rarely perceived as a ‘resource’ for the Community The longitudinal study set the impact of the Grameen Bank microcredit program on new borrowers women from Noakhali District at the south Bangladesh. The impact evaluation assessment has been structured to detect individual, family and social changes. Manova Analysis allowed distinguishing from women with positive or negative outcomes related to the loan performance. Data revealed consistent differences in terms of economical outcomes and psychological well being amongst the groups of subject analyzed. The data gathered in relation to the changes arisen in the individuals should be looked into through future, continuous and systematic, monitoring.

Mental states monitoring through passive Brain-Computer Interface systems

The monitoring of cognitive functions aims at gaining information about the current cognitive state of the user by decoding brain signals. In recent years, this approach allowed to acquire valuable information about the cognitive aspects regarding the interaction of humans with external world. From this consideration, researchers started to consider passive application of brain–computer interface (BCI) in order to provide a novel input modality for technical systems solely based on brain activity. The objective of this thesis is to demonstrate how the passive Brain Computer Interfaces (BCIs) applications can be used to assess the mental states of the users, in order to improve the human machine interaction. Two main studies has been proposed. The first one allows to investigate whatever the Event Related Potentials (ERPs) morphological variations can be used to predict the users’ mental states (e.g. attentional resources, mental workload) during different reactive BCI tasks (e.g. P300-based BCIs), and if these information can predict the subjects’ performance in performing the tasks. In the second study, a passive BCI system able to online estimate the mental workload of the user by relying on the combination of the EEG and the ECG biosignals has been proposed. The latter study has been performed by simulating an operative scenario, in which the occurrence of errors or lack of performance could have significant consequences. The results showed that the proposed system is able to estimate online the mental workload of the subjects discriminating three different difficulty level of the tasks ensuring a high reliability.