Emotions are a fundamental part of life, not only because of their importance in the development and behaviour of individuals, but also because they give meaning and enrich human experiences. Before the introduction of the concept of Affective Computing (R. W. Picard, 1995), the emotional factor played a marginal role in regards to computer design and related products. Today, thanks to an increasingly shared knowledge and a more interdisciplinary approach, it is possible to develop technological systems capable of recognising, simulating, influencing and reacting to human emotions. This makes it possible to rethink and improve the quality of certain practices, imagine new products, and make them more empathetic and efficient. Regarding the potential expressed by AC, it was decided to investigate the almost unexplored context of perinatal depression. Perinatal depression is a form of major depression that affects 10-20% of mothers in the period “around childbirth” and which, if not adequately treated, can lead to negative repercussions on the well-being of the whole family. One of the most critical issues in this context is the identification of those at risk, which is often influenced by factors such as stigma and the use of traditional screening practices, which can be inaccurate and objective (as well as costly). For these and other reasons, about 50% of cases are unfortunately not recognised and diagnosed. In order to devise a solution to reduce this gap, several scientific studies have been analysed, from which it emerged that, to make the assessment of depressive symptoms more effective, it is possible and useful to collect specific biometric and behavioural data by exploiting the potential of modern technology. This is where the Eva project comes from: a product-service system that, thanks to the use of AC, helps to promptly identify and monitor the presence of possible depressive symptoms in the perinatal environment; in order to prevent and, if necessary, facilitate diagnosis and access to psychological support services.
Le emozioni sono una parte fondamentale della vita, non solo per la loro importanza nello sviluppo e nel comportamento degli individui, ma anche perché danno significato e ricchezza alle esperienze umane. Prima dell’introduzione del concetto di Affective Computing (R. W. Picard, 1995), la componente emotiva aveva un ruolo marginale rispetto alla progettazione informatica e dei prodotti ad essa correlati. Oggi, grazie a una conoscenza sempre più condivisa e ad un approccio più interdisciplinare, è possibile sviluppare sistemi tecnologici capaci di riconoscere, simulare, influire e reagire alle emozioni umane. Ciò permette di ripensare e migliorare la qualità di alcune pratiche, immaginare nuovi prodotti, rendendoli più empatici e performanti. Rispetto alle potenzialità espresse dall’AC, si è deciso di indagare il contesto, ancora poco esplorato, della depressione perinatale. Questa è una forma di depressione maggiore che colpisce il 10-20% delle madri nel periodo “attorno al parto” e che, se non adeguatamente trattata, può portare a ricadute negative sul benessere di tutta la famiglia. Una delle criticità maggiori in questo contesto riguarda l’identificazione dei soggetti a rischio, la quale è spesso influenzata da fattori come la stigmatizzazione e l’uso di pratiche di screening tradizionali, che possono rivelarsi poco accurate e oggettive (oltre ad essere economicamente onerose). Per queste e altre ragioni, circa il 50% dei casi, purtroppo, non viene riconosciuto e diagnosticato. Al fine di ideare una soluzione utile a ridurre questo gap, sono stati analizzati diversi studi scientifici dai quali è emerso come, per rendere più efficace la valutazione dei sintomi depressivi, sia possibile e utile raccogliere specifici dati biometrici e comportamentali sfruttando le potenzialità delle moderne tecnologie. Da qui nasce il progetto Eva: un sistema prodotto-servizio che, grazie all’utilizzo dell’AC, aiuta ad identificare tempestivamente e monitorare la presenza di possibili sintomi depressivi in ambito perinatale; al fine di prevenire e, se necessario, facilitare la diagnosi e l’accesso ai servizi di supporto psicologico.
Eva. Design di un sistema prodotto-servizio per la prevenzione e lo screening della depressione perinatale
Tarozzi, Ilaria
2019/2020
Abstract
Emotions are a fundamental part of life, not only because of their importance in the development and behaviour of individuals, but also because they give meaning and enrich human experiences. Before the introduction of the concept of Affective Computing (R. W. Picard, 1995), the emotional factor played a marginal role in regards to computer design and related products. Today, thanks to an increasingly shared knowledge and a more interdisciplinary approach, it is possible to develop technological systems capable of recognising, simulating, influencing and reacting to human emotions. This makes it possible to rethink and improve the quality of certain practices, imagine new products, and make them more empathetic and efficient. Regarding the potential expressed by AC, it was decided to investigate the almost unexplored context of perinatal depression. Perinatal depression is a form of major depression that affects 10-20% of mothers in the period “around childbirth” and which, if not adequately treated, can lead to negative repercussions on the well-being of the whole family. One of the most critical issues in this context is the identification of those at risk, which is often influenced by factors such as stigma and the use of traditional screening practices, which can be inaccurate and objective (as well as costly). For these and other reasons, about 50% of cases are unfortunately not recognised and diagnosed. In order to devise a solution to reduce this gap, several scientific studies have been analysed, from which it emerged that, to make the assessment of depressive symptoms more effective, it is possible and useful to collect specific biometric and behavioural data by exploiting the potential of modern technology. This is where the Eva project comes from: a product-service system that, thanks to the use of AC, helps to promptly identify and monitor the presence of possible depressive symptoms in the perinatal environment; in order to prevent and, if necessary, facilitate diagnosis and access to psychological support services.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/176062