Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Melissa Schellekens"'
Autor:
Asghar Ahmadi, Michael Noetel, Melissa Schellekens, Philip Parker, Devan Antczak, Mark Beauchamp, Theresa Dicke, Carmel Diezmann, Anthony Maeder, Nikos Ntoumanis, Alexander Yeung, Chris Lonsdale
Publikováno v:
Psychosocial Intervention, Vol 30, Iss 3, Pp 139-153 (2021)
Many psychological treatments have been shown to be cost-effective and efficacious, as long as they are implemented faithfully. Assessing fidelity and providing feedback is expensive and time-consuming. Machine learning has been used to assess treatm
Externí odkaz:
https://doaj.org/article/a4e53cc39e0544dfafc66a083800fe2b
Publikováno v:
Revista Colombiana de Psicología, Vol 26, Iss 1, Pp 115-129 (2017)
Los estudios sobre felicidad incluyen diversas perspectivas, conceptualizaciones y factores asociados a este concepto; sin embargo, las investigaciones sobre felicidad con frecuencia se concentran en la dimensión individual de la misma. El presente
Externí odkaz:
https://doaj.org/article/89861a18494844df9aa3c2aa75844a97
Autor:
Melissa Schellekens, Joseph Ciarrochi, Anthony Dillon, Baljinder K. Sahdra, Robert Brockman, Janet Mooney, Philip Parker
Publikováno v:
British Educational Research Journal. 48:730-750
Internationally there is a gap in high school completion rates for Indigenous and non-Indigenous students. In Australia, gap estimates are commonly based on lag indicators, precluding examination of underlying mechanisms. Using two longitudinal and r
Autor:
Asghar Ahmadi, Devan Antczak, Nikos Ntoumanis, Philip D. Parker, Theresa Dicke, Melissa Schellekens, Michael Noetel, Anthony Maeder, Carmel M. Diezmann, Alexander Seeshing Yeung, Mark R. Beauchamp, Chris Lonsdale
Publikováno v:
Psychosocial Intervention v.30 n.3 2021
SciELO España. Revistas Científicas Españolas de Ciencias de la Salud
Banco de España
Ahmadi, A, Noetela, M, Schellekens, M, Parker, P, Antczak, D, Beauchamp, M, Dicke, T, Diezmann, C, Maeder, A, Ntoumanis, N, Yeung, A & Lonsdalea, C 2021, ' A Systematic Review of Machine Learning for Assessment and Feedback of Treatment Fidelity ', Psychosocial Intervention, vol. 30, no. 3, pp. 139-153 . https://doi.org/10.5093/PI2021A4
Psychosocial Intervention, Vol 30, Iss 3, Pp 139-153 (2021)
SciELO España. Revistas Científicas Españolas de Ciencias de la Salud
Banco de España
Ahmadi, A, Noetela, M, Schellekens, M, Parker, P, Antczak, D, Beauchamp, M, Dicke, T, Diezmann, C, Maeder, A, Ntoumanis, N, Yeung, A & Lonsdalea, C 2021, ' A Systematic Review of Machine Learning for Assessment and Feedback of Treatment Fidelity ', Psychosocial Intervention, vol. 30, no. 3, pp. 139-153 . https://doi.org/10.5093/PI2021A4
Psychosocial Intervention, Vol 30, Iss 3, Pp 139-153 (2021)
espanolRESUMEN Se ha puesto de manifiesto que muchos tratamientos psicologicos tienen un coste efectivo y son eficaces siempre que se apliquen con fidelidad. La evaluacion de esta y el feedback son caros y exigen mucho tiempo. El aprendizaje automati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::29e432f08dd1bfefcf606b38e1595cc9