000133099 001__ 133099
000133099 005__ 20240322124130.0
000133099 0247_ $$2doi$$a10.3390/ijerph19137737
000133099 0248_ $$2sideral$$a137794
000133099 037__ $$aART-2022-137794
000133099 041__ $$aeng
000133099 100__ $$aGual-Montolio, Patricia
000133099 245__ $$aUsing Artificial Intelligence to Enhance Ongoing Psychological Interventions for Emotional Problems in Real- or Close to Real-Time: A Systematic Review
000133099 260__ $$c2022
000133099 5060_ $$aAccess copy available to the general public$$fUnrestricted
000133099 5203_ $$aEmotional disorders are the most common mental disorders globally. Psychological treatments have been found to be useful for a significant number of cases, but up to 40% of patients do not respond to psychotherapy as expected. Artificial intelligence (AI) methods might enhance psychotherapy by providing therapists and patients with real- or close to real-time recommendations according to the patient’s response to treatment. The goal of this investigation is to systematically review the evidence on the use of AI-based methods to enhance outcomes in psychological interventions in real-time or close to real-time. The search included studies indexed in the electronic databases Scopus, Pubmed, Web of Science, and Cochrane Library. The terms used for the electronic search included variations of the words “psychotherapy”, “artificial intelligence”, and “emotional disorders”. From the 85 full texts assessed, only 10 studies met our eligibility criteria. In these, the most frequently used AI technique was conversational AI agents, which are chatbots based on software that can be accessed online with a computer or a smartphone. Overall, the reviewed investigations indicated significant positive consequences of using AI to enhance psychotherapy and reduce clinical symptomatology. Additionally, most studies reported high satisfaction, engagement, and retention rates when implementing AI to enhance psychotherapy in real- or close to real-time. Despite the potential of AI to make interventions more flexible and tailored to patients’ needs, more methodologically robust studies are needed.
000133099 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000133099 592__ $$a0.828$$b2022
000133099 593__ $$aHealth, Toxicology and Mutagenesis$$c2022$$dQ2
000133099 593__ $$aPublic Health, Environmental and Occupational Health$$c2022$$dQ2
000133099 593__ $$aPollution$$c2022$$dQ2
000133099 594__ $$a5.4$$b2022
000133099 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000133099 700__ $$aJaén, Irene
000133099 700__ $$0(orcid)0000-0003-2082-8115$$aMartínez-Borba, Verónica
000133099 700__ $$aCastilla, Diana
000133099 700__ $$aSuso-Ribera, Carlos
000133099 773__ $$g19, 13 (2022), 7737 [21 pp.]$$pInt. j. environ. res. public health$$tInternational journal of environmental research and public health$$x1661-7827
000133099 8564_ $$s1817465$$uhttps://zaguan.unizar.es/record/133099/files/texto_completo.pdf$$yVersión publicada
000133099 8564_ $$s2717283$$uhttps://zaguan.unizar.es/record/133099/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000133099 909CO $$ooai:zaguan.unizar.es:133099$$particulos$$pdriver
000133099 951__ $$a2024-03-22-09:46:51
000133099 980__ $$aARTICLE