Exploring affect recall bias and the impact of mild depressive symptoms: An ecological momentary study
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Título
Exploring affect recall bias and the impact of mild depressive symptoms: An ecological momentary studyAutoría
Fecha de publicación
2019-07-11Editor
SpringerCita bibliográfica
Colombo, D. et al. (2019). Exploring Affect Recall Bias and the Impact of Mild Depressive Symptoms: An Ecological Momentary Study. In: Cipresso, P., Serino, S., Villani, D. (eds) Pervasive Computing Paradigms for Mental Health. MindCare 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 288. Springer, Cham. https://doi.org/10.1007/978-3-030-25872-6_17Tipo de documento
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Resumen
Traditional clinical and research assessments rely on retrospective questionnaires, that ask individuals to retrospectively summarize how they felt during the last period. Nevertheless, people are not accurate at ... [+]
Traditional clinical and research assessments rely on retrospective questionnaires, that ask individuals to retrospectively summarize how they felt during the last period. Nevertheless, people are not accurate at recalling past experiences without altering the content, especially when they are required to report their affect. In this study, we adopted a smartphone-based ecological momentary assessment (EMA) to collect daily assessments of positive (PA) and negative (NA) affect throughout two weeks in a sample of healthy students (n = 47). Results showed that both PA and NA are subject to the recall bias; more specifically, people tended to overestimate both affects during the retrospective assessment. This bias was influenced by the presence of mild depressive symptoms as measured by the Beck Depression Inventory (BDI), which led participants to a greater overestimation of NA and higher underestimation of PA. While NA bias was more context-dependent, PA bias showed more stability across time. [-]
Descripción
Ponencia presentada en la 9th International Conference, MindCare 2019 "Pervasive Computing Paradigms for Mental Health", Buenos Aires, Argentina, April 23–24, 2019
Publicado en
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 288)Entidad financiadora
Marie Curie EF-ST AffecTech Project, approved at call H2020 – MSCA – ITN – 2016
Código del proyecto o subvención
722022
Derechos de acceso
© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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