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      Cómo construir un psicólogo-chatbot Translated title: How to create a psychologist-chatbot

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          Abstract

          Resumen El desarrollo de agentes conversacionales o chatbots se ha visto incrementado en las últimas décadas, especialmente en el sector comercial. No obstante, si bien el primer bot conversacional de la historia presentaba una apariencia de psicoterapeuta, son pocos los agentes virtuales con este tipo de funciones construidos hasta la fecha. En el presente trabajo, exponemos las bases para diseñar un chatbot psicólogo, concretamente, un bot con funciones de evaluación psicológica. Para ello, revisamos las herramientas disponibles para diseñarlo y configurarlo, y los conceptos básicos para su construcción. Asimismo, proponemos una serie de objetivos de evaluación que habrían de guiar el diálogo del agente conversacional. Finalmente, exponemos una reflexión acerca de las ventajas e inconvenientes de los chatbots y sobre las líneas de actuación que serían necesarias para desarrollarlos con garantías científicas.

          Translated abstract

          Abstract n recent decades, the development of conversational agents or chatbots has increased, especially in the commercial sector. Although the first chatbot in computational history was presented as a psychotherapist, few virtual agents with this type of function have been built since then. In the present article we describe the fundamental aspects of designing a psychologist-chatbot and, more specifically, a bot with psychological assessment functions. We review the available tools and the basic concepts for its construction. We also propose a series of assessment objectives that would guide the conversational agent's dialogue. Finally, we discuss the advantages and disadvantages of chatbots and the scientific guarantees that they need to fulfill.

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          Most cited references19

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          Delivering Cognitive Behavior Therapy to Young Adults With Symptoms of Depression and Anxiety Using a Fully Automated Conversational Agent (Woebot): A Randomized Controlled Trial

          Background Web-based cognitive-behavioral therapeutic (CBT) apps have demonstrated efficacy but are characterized by poor adherence. Conversational agents may offer a convenient, engaging way of getting support at any time. Objective The objective of the study was to determine the feasibility, acceptability, and preliminary efficacy of a fully automated conversational agent to deliver a self-help program for college students who self-identify as having symptoms of anxiety and depression. Methods In an unblinded trial, 70 individuals age 18-28 years were recruited online from a university community social media site and were randomized to receive either 2 weeks (up to 20 sessions) of self-help content derived from CBT principles in a conversational format with a text-based conversational agent (Woebot) (n=34) or were directed to the National Institute of Mental Health ebook, “Depression in College Students,” as an information-only control group (n=36). All participants completed Web-based versions of the 9-item Patient Health Questionnaire (PHQ-9), the 7-item Generalized Anxiety Disorder scale (GAD-7), and the Positive and Negative Affect Scale at baseline and 2-3 weeks later (T2). Results Participants were on average 22.2 years old (SD 2.33), 67% female (47/70), mostly non-Hispanic (93%, 54/58), and Caucasian (79%, 46/58). Participants in the Woebot group engaged with the conversational agent an average of 12.14 (SD 2.23) times over the study period. No significant differences existed between the groups at baseline, and 83% (58/70) of participants provided data at T2 (17% attrition). Intent-to-treat univariate analysis of covariance revealed a significant group difference on depression such that those in the Woebot group significantly reduced their symptoms of depression over the study period as measured by the PHQ-9 (F=6.47; P=.01) while those in the information control group did not. In an analysis of completers, participants in both groups significantly reduced anxiety as measured by the GAD-7 (F1,54= 9.24; P=.004). Participants’ comments suggest that process factors were more influential on their acceptability of the program than content factors mirroring traditional therapy. Conclusions Conversational agents appear to be a feasible, engaging, and effective way to deliver CBT.
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            Real conversations with artificial intelligence: A comparison between human–human online conversations and human–chatbot conversations

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              Chatbots : changing user needs and motivations

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                Author and article information

                Journal
                pappsicol
                Papeles del Psicólogo
                Pap. Psicol.
                Consejo General de Colegios Oficiales de Psicólogos (Madrid, Madrid, Spain )
                0214-7823
                1886-1415
                April 2020
                : 41
                : 1
                : 27-34
                Affiliations
                [1] Madrid Madrid orgnameUniversidad Autónoma de Madrid Spain
                Article
                S0214-78232020000100027 S0214-7823(20)04100100027
                10.23923/pap.psicol2020.2920
                7802a28c-3a46-4284-adf1-94fb11d8fc02

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

                History
                : 11 November 2019
                : 16 July 2019
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 19, Pages: 8
                Product

                SciELO Spain

                Categories
                Artículos

                Evaluación psicológica,Inteligencia artificial,Chatbot,Conversational agent,Psychological assessment,Technology,Artificial intelligence,Agente conversacional,Tecnología

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