{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T00:58:29Z","timestamp":1775523509625,"version":"3.50.1"},"reference-count":53,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2021,4,10]],"date-time":"2021-04-10T00:00:00Z","timestamp":1618012800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,4,10]],"date-time":"2021-04-10T00:00:00Z","timestamp":1618012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100014440","name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades","doi-asserted-by":"publisher","award":["FPU17\/00667"],"award-info":[{"award-number":["FPU17\/00667"]}],"id":[{"id":"10.13039\/100014440","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014440","name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades","doi-asserted-by":"publisher","award":["RTI2018-093348-B-I00"],"award-info":[{"award-number":["RTI2018-093348-B-I00"]}],"id":[{"id":"10.13039\/100014440","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100011033","name":"Agencia Estatal de Investigaci\u00f3n","doi-asserted-by":"publisher","award":["RTI2018-093348-B-I00"],"award-info":[{"award-number":["RTI2018-093348-B-I00"]}],"id":[{"id":"10.13039\/501100011033","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["RTI2018-093348-B-I00"],"award-info":[{"award-number":["RTI2018-093348-B-I00"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Lang Resources &amp; Evaluation"],"published-print":{"date-parts":[[2022,6]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Nowadays, in the globalised context in which we find ourselves, language barriers can still be an obstacle to accessing information. On occasions, it is impossible to satisfy the demand for translation by relying only in human translators, therefore, tools such as Machine Translation (MT) are gaining popularity due to their potential to overcome this problem. Consequently, research in this field is constantly growing and new MT paradigms are emerging. In this paper, a systematic literature review has been carried out in order to identify what MT systems are currently most employed, their architecture, the quality assessment procedures applied to determine how they work, and which of these systems offer the best results. The study is focused on the specialised literature produced by translation experts, linguists, and specialists in related fields that include the English\u2013Spanish language combination. Research findings show that neural MT is the predominant paradigm in the current MT scenario, being Google Translator the most used system. Moreover, most of the analysed works used one type of evaluation\u2014either automatic or human\u2014to assess machine translation and only 22% of the works combined these two types of evaluation. However, more than a half of the works included error classification and analysis, an essential aspect for identifying flaws and improving the performance of MT systems.<\/jats:p>","DOI":"10.1007\/s10579-021-09537-5","type":"journal-article","created":{"date-parts":[[2021,4,10]],"date-time":"2021-04-10T16:02:55Z","timestamp":1618070575000},"page":"593-619","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":157,"title":["Machine translation systems and quality assessment: a systematic review"],"prefix":"10.1007","volume":"56","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4877-4083","authenticated-orcid":false,"given":"Irene","family":"Rivera-Trigueros","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,4,10]]},"reference":[{"key":"9537_CR1","unstructured":"Bahdanau, D., Cho, K., & Bengio, Y. (2015). Neural machine translation by jointly learning to align and translate. In International conference on learning representations. Retrieved June 11, 2020, from https:\/\/arxiv.org\/pdf\/1409.0473.pdf."},{"key":"9537_CR2","unstructured":"Banerjee, S., & Lavie, A. (2005). METEOR: An automatic metric for MT evaluation with improved correlation with human judgments. In Proceedings of the ACL workshop on intrinsic and extrinsic evaluation measures for machine translation and\/or summarization (pp. 65\u201372)."},{"key":"9537_CR3","volume-title":"An\u00e1lisis de contenido","author":"L Bardin","year":"1996","unstructured":"Bardin, L. (1996). An\u00e1lisis de contenido. Akal Ediciones."},{"key":"9537_CR4","doi-asserted-by":"crossref","unstructured":"Bentivogli, L., Bisazza, A., Cettolo, M., & Federico, M. (2016). Neural versus phrase-based machine translation quality: A case study. In Proceedings of the 2016 conference on empirical methods in natural language processing (pp. 257\u2013267).","DOI":"10.18653\/v1\/D16-1025"},{"key":"9537_CR5","unstructured":"Boitet, C., Bey, Y., Tomokiyo, M., Cao, W., & Blanchon, H. (2006). IWSLT-06: experiments with commercial MT systems and lessons from subjective evaluations. In Proceedings of the 2006 international workshop on spoken language translation (IWSLT) (pp. 23\u201330)."},{"key":"9537_CR6","doi-asserted-by":"crossref","unstructured":"Bojar, O., In Prague, C. U., Chatterjee, R., Federmann, C., Research, M., Haddow, B., Huck, M., Hokamp, C., Koehn, P., Edinburgh, J., Logacheva, V., Monz, C., Negri, M., Post, M., Scarton, C., & Turchi, M. (2015). Findings of the 2015 Workshop on Statistical Machine Translation. In Proceedings of the tenth workshop on statistical machine translation (pp. 1\u201346).","DOI":"10.18653\/v1\/W15-3001"},{"key":"9537_CR7","doi-asserted-by":"publisher","unstructured":"Castilho, S., Doherty, S., Gaspari, F., & Moorkens, J. (2018). Approaches to human and machine translation quality assessment. In J. Moorkens, S. Castilho, F. Gaspari and S. Doherty (Eds.), Translation quality assessment. Cham: Springer, pp. 9\u201338. https:\/\/doi.org\/10.1007\/978-3-319-91241-7_2","DOI":"10.1007\/978-3-319-91241-7_2"},{"key":"9537_CR8","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1515\/pralin-2017-0013","volume":"108","author":"S Castilho","year":"2017","unstructured":"Castilho, S., Moorkens, J., Gaspari, F., Calixto, I., Tinsley, J., & Way, A. (2017). Is Neural Machine Translation the New State of the Art? The Prague Bulletin of Mathematical Linguistics, 108, 109\u2013120. https:\/\/doi.org\/10.1515\/pralin-2017-0013","journal-title":"The Prague Bulletin of Mathematical Linguistics"},{"key":"9537_CR9","doi-asserted-by":"publisher","unstructured":"Charoenpornsawat, P., Sornlertlamvanich, V., & Charoenporn, T. (2002). Improving translation quality of rule-based machine translation. COLING-02 on Machine Translation in Asia, 16, 1\u20136. https:\/\/doi.org\/10.3115\/1118794.1118799.","DOI":"10.3115\/1118794.1118799"},{"issue":"2","key":"9537_CR10","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1017\/S1351324919000469","volume":"26","author":"E Chatzikoumi","year":"2020","unstructured":"Chatzikoumi, E. (2020). How to evaluate machine translation: A review of automated and human metrics. Natural Language Engineering, 26(2), 137\u2013161. https:\/\/doi.org\/10.1017\/S1351324919000469","journal-title":"Natural Language Engineering"},{"key":"9537_CR11","doi-asserted-by":"crossref","unstructured":"Cho, K., van Merrienboer, B., Bahdanau, D., & Bengio, Y. (2014). On the properties of neural machine translation: encoder-decoder approaches. In Eighth workshop on syntax, semantics and structure in statistical translation (SSST-8).","DOI":"10.3115\/v1\/W14-4012"},{"issue":"2","key":"9537_CR12","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1007\/s10590-015-9169-0","volume":"29","author":"\u00c2 Costa","year":"2015","unstructured":"Costa, \u00c2., Ling, W., Lu\u00eds, T., Correia, R., & Coheur, L. (2015). A linguistically motivated taxonomy for Machine Translation error analysis. Machine Translation, 29(2), 127\u2013161. https:\/\/doi.org\/10.1007\/s10590-015-9169-0","journal-title":"Machine Translation"},{"issue":"2","key":"9537_CR13","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1007\/s10590-015-9169-0","volume":"30","author":"MR Costa-Juss\u00e0","year":"2015","unstructured":"Costa-Juss\u00e0, M. R., & Farr\u00fas, M. (2015). Towards human linguistic machine translation evaluation. Digital Scholarship in the Humanities, 30(2), 157\u2013166. https:\/\/doi.org\/10.1007\/s10590-015-9169-0","journal-title":"Digital Scholarship in the Humanities"},{"key":"9537_CR14","doi-asserted-by":"crossref","unstructured":"Doddington, G. (2002). Automatic evaluation of machine translation quality using N-gram co-occurrence statistics. In HLT \u201902: Proceedings of the second international conference on human language technology (pp. 138\u2013144).","DOI":"10.3115\/1289189.1289273"},{"key":"9537_CR15","doi-asserted-by":"publisher","unstructured":"Espa\u00f1a-Bonet, C., & Costa-juss\u00e0, M. R. (2016). Hybrid machine translation overview. In M. Costa-juss\u00e0, R. Rapp, P. Lambert, K. Eberle, R. Banchs, & B. Babych (Eds.), Hybrid approaches to machine translation. Theory and applications of natural language processing (pp. 1\u201324). Cham: Springer. https:\/\/doi.org\/10.1007\/978-3-319-21311-8_1","DOI":"10.1007\/978-3-319-21311-8_1"},{"key":"9537_CR16","unstructured":"Farr\u00fas, M., Costa-Juss\u00e0, M. R., Mari\u00f1o, J. B., & Fonollosa, J. A. R. (2010). Linguistic-based evaluation criteria to identify statistical machine translation errors. In EAMT 2010\u201414th annual conference of the European Association for Machine Translation."},{"key":"9537_CR17","first-page":"443","volume":"12","author":"A G\u00f6r\u00f6g","year":"2014","unstructured":"G\u00f6r\u00f6g, A. (2014). Quantifying and benchmarking quality: The TAUS dynamic quality framework. Revista Tradum\u00e0tica: Tecnologies de La Traducci\u00f3, 12, 443\u2013453.","journal-title":"Revista Tradum\u00e0tica: Tecnologies de La Traducci\u00f3"},{"key":"9537_CR18","volume-title":"An Introduction to Systematic Reviews","author":"D Gough","year":"2012","unstructured":"Gough, D., Oliver, S., & Thomas, J. (2012). An Introduction to Systematic Reviews. SAGE."},{"key":"9537_CR19","unstructured":"Graham, Y., Baldwin, T., Moffat, A., & Zobel, J. (2013). Crowd-sourcing of human judgments of machine translation fluency. In Proceedings of the Australasian language technology association workshop 2013 (pp. 16\u201324)."},{"issue":"1","key":"9537_CR20","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1017\/S1351324915000339","volume":"23","author":"Y Graham","year":"2015","unstructured":"Graham, Y., Baldwin, T., Moffat, A., & Zobel, J. (2015). Can machine translation systems be evaluated by the crowd alone. Natural Language Engineering, 23(1), 3\u201330. https:\/\/doi.org\/10.1017\/S1351324915000339","journal-title":"Natural Language Engineering"},{"key":"9537_CR21","doi-asserted-by":"publisher","unstructured":"Guti\u00e9rrez-Artacho, J., Olvera-Lobo, M.-D., & Rivera-Trigueros, I. (2019). Hybrid machine translation oriented to cross-language information retrieval: English-Spanish error analysis. In \u00c1. Rocha, H. Adeli, L. Reis, & S. Costanzo (Eds.), New knowledge in information systems and technologies (pp. 185\u2013194). Cham: Springer. https:\/\/doi.org\/10.1007\/978-3-030-16181-1_18","DOI":"10.1007\/978-3-030-16181-1_18"},{"issue":"1","key":"9537_CR22","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1007\/s10590-009-9056-7","volume":"23","author":"N Habash","year":"2009","unstructured":"Habash, N., Dorr, B., & Monz, C. (2009). Symbolic-to-statistical hybridization: extending generation-heavy machine translation. Machine Translation, 23(1), 23\u201363. https:\/\/doi.org\/10.1007\/s10590-009-9056-7","journal-title":"Machine Translation"},{"key":"9537_CR23","unstructured":"Han, L. (2016). Machine translation evaluation resources and methods: A survey. ArXiv: Computation and language. Cornell University Library. Retrieved June 11, 2020, from https:\/\/arxiv.org\/abs\/1605.04515."},{"key":"9537_CR24","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1057\/9781137025487_13","volume-title":"Translation: A multidisciplinary approach","author":"J House","year":"2014","unstructured":"House, J. (2014). Translation quality assessment: Past and present. Translation: A multidisciplinary approach (pp. 241\u2013264). Palgrave Macmillan."},{"key":"9537_CR25","unstructured":"Hunsicker, S., Yu, C., & Federmann, C. (2012). Machine learning for hybrid machine translation. In Proceedings of the seventh workshop on statistical machine translation, Montr\u00e9al, Canada, June 2012."},{"key":"9537_CR26","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1016\/B978-0-08-042580-1.50066-0","volume-title":"Concise history of the language sciences: From the Sumerians to the cognitivists","author":"J Hutchins","year":"1995","unstructured":"Hutchins, J. (1995). Machine Translation: A brief History. In E. F. K. Koerner & R. E. Asher (Eds.), Concise history of the language sciences: From the Sumerians to the cognitivists (pp. 431\u2013445). Pergamon Press."},{"issue":"1 & 2","key":"9537_CR27","first-page":"1","volume":"13","author":"J Hutchins","year":"2007","unstructured":"Hutchins, J. (2007). Machine translation: A concise history. Mechanical Translation, 13(1 & 2), 1\u201321.","journal-title":"Mechanical Translation"},{"key":"9537_CR29","volume-title":"Statistical machine translation","author":"P Koehn","year":"2010","unstructured":"Koehn, P. (2010). Statistical machine translation. Cambridge University Press."},{"key":"9537_CR30","unstructured":"Koponen, M. (2016). Is machine translation post-editing worth the effort? A survey of research into post-editing and effort. JoSTrans: The Journal of Specialised Translation, 25, 131\u2013148."},{"key":"9537_CR31","volume-title":"Repairing texts: Empirical investigations of machine translation post-editing processes","author":"H Krings","year":"2001","unstructured":"Krings, H. (2001). Repairing texts: Empirical investigations of machine translation post-editing processes. Kent State University Press."},{"key":"9537_CR32","doi-asserted-by":"publisher","unstructured":"Lagarda, A. L., Ortiz-Martinez, D., Alabau, V., & Casacuberta, F. (2015). Translating without in-domain corpus: Machine translation post-editing with online learning techniques. Computer Speech and Language, 32(1, SI), 109\u2013134. https:\/\/doi.org\/10.1016\/j.csl.2014.10.004","DOI":"10.1016\/j.csl.2014.10.004"},{"key":"9537_CR33","doi-asserted-by":"publisher","unstructured":"Laurian, A. M. (1984). Machine Translation: What type of post-editing on what type of documents for what type of users. In Proceedings of the 10th internacional conference on computational linguistics and 22nd annual meeeting on association for computational linguistics (pp. 236\u2013238). https:\/\/doi.org\/10.1017\/CBO9781107415324.004.","DOI":"10.1017\/CBO9781107415324.004"},{"issue":"8","key":"9537_CR34","first-page":"707","volume":"10","author":"VI Levenshtein","year":"1966","unstructured":"Levenshtein, V. I. (1966). Binary codes capable of correcting deletions, insertions and re-versals. Soviet Physics Doklady, 10(8), 707\u2013710.","journal-title":"Soviet Physics Doklady"},{"key":"9537_CR35","doi-asserted-by":"crossref","unstructured":"Lin, C.-Y., & Hovy, E. (2003). Automatic evaluation of summaries using N-gram co-occurrence statistics. In Proceedings of the 2003 human language technology conference of the North american chapter of the association for computational linguistics (pp. 150\u2013157).","DOI":"10.3115\/1073445.1073465"},{"key":"9537_CR36","doi-asserted-by":"publisher","unstructured":"Lommel, A. (2018). Metrics for translation quality assessment: A case for standardising error typologies. In J. Moorkens, S. Castilho, F. Gaspari and S. Doherty (Eds.), Translation quality assessment. Cham: Springer, pp. 109\u2013127. https:\/\/doi.org\/10.1007\/978-3-319-91241-7_6","DOI":"10.1007\/978-3-319-91241-7_6"},{"key":"9537_CR37","unstructured":"Mauser, A., Hasan, S., & Ney, H. (2008). Automatic evaluation measures for statistical machine translation system optimization. In Proceedings of the sixth international language resources and evaluation (LREC\u201908)."},{"key":"9537_CR38","doi-asserted-by":"publisher","unstructured":"Mayring, P. (2000). Qualitative content analysis. Forum: Qualitative Social Research, 1(2), 1\u201310. https:\/\/doi.org\/10.1111\/j.1365-2648.2007.04569.x","DOI":"10.1111\/j.1365-2648.2007.04569.x"},{"key":"9537_CR39","unstructured":"Nie\u00dfen, S., Och, F. J., Leusch, G., & and Ney, H. (2000). An evaluation tool for machine translation: Fast evaluation for MT research. In Proceedings of the second international conference on language resources and evaluation (LREC)."},{"key":"9537_CR40","doi-asserted-by":"publisher","unstructured":"Papineni, K., Roukos, S., Ward, T., & Zhu, W. J. (2002). BLEU: A method for automatic evaluation of machine translation. In Proceedings of the 40th annual meeting on association for computational linguistics. https:\/\/doi.org\/10.3115\/1073083.1073135.","DOI":"10.3115\/1073083.1073135"},{"key":"9537_CR41","doi-asserted-by":"publisher","unstructured":"Popovi\u0107, M. (2018). Error classification and analysis for machine translation quality assessment. In J. Moorkens, S. Castilho, F. Gaspari, & S. Doherty (Eds.), Translation quality assessment (pp. 129\u2013158). Cham: Springer. https:\/\/doi.org\/10.1007\/978-3-319-91241-7_7.","DOI":"10.1007\/978-3-319-91241-7_7"},{"key":"9537_CR42","unstructured":"Sch\u00e4fer, F. (2003). MT post-editing: How to shed light on the \u201cunknown task\u201d\u2014Experices made at SAP. In The joint conference of the 8th international workshop of the European Association for machine translation and the 4th controlled language applications workshop (pp. 133\u2013140)."},{"key":"9537_CR43","doi-asserted-by":"publisher","unstructured":"Schmitt, P. A. (2019). Translation 4.0\u2014evolution, revolution, innovation or disruption? Lebende Sprachen, 64(2): 193\u2013229. https:\/\/doi.org\/10.1515\/les-2019-0013","DOI":"10.1515\/les-2019-0013"},{"key":"9537_CR44","unstructured":"Shaw, F., & Gros, X. (2007). Survey of machine translation evaluation. Saarbr\u00fccken: EuroMatrix. Retrieved June 11, 2020, from http:\/\/www.euromatrix.net\/deliverables\/Euromatrix_D1.3_Revised.pdf."},{"key":"9537_CR45","unstructured":"Snover, M., Dorr, B., Schwartz, R., Micciulla, L., & Makhoul, J. (2006). A study of translation edit rate with targeted human annotation. In Proceedings of association for machine translation in the Americas (pp. 223\u2013231)."},{"key":"9537_CR46","doi-asserted-by":"crossref","unstructured":"Tambouratzis, G. (2014). Comparing CRF and template-matching in phrasing tasks within a Hybrid MT system. In Proceedings of the 3rd workshop on hybrid approaches to translation (HyTra) (pp. 7\u201314).","DOI":"10.3115\/v1\/W14-1003"},{"key":"9537_CR47","volume-title":"Comparing different architectures of hybrid machine translation systems","author":"G Thurmair","year":"2009","unstructured":"Thurmair, G. (2009). Comparing different architectures of hybrid machine translation systems. In Proceddings of MT Summit XII."},{"key":"9537_CR48","doi-asserted-by":"crossref","unstructured":"Tillmann, C., Vogel, S., Ney, H., Zubiaga, A., & Sawaf, H. (1997). Accelerated DP based search for statistical translation. In G. Kokkinakis, N. Fakotakis, & E. Dermatas (Eds.), Proceedings of the fifth European conference on speech communication and technology (pp. 2667\u20132670). Rhodos, Greece.","DOI":"10.21437\/Eurospeech.1997-673"},{"key":"9537_CR49","doi-asserted-by":"crossref","unstructured":"Toral, A., & S\u00e1nchez-Cartagena, V. M. (2017). A multifaceted evaluation of neural versus phrase-based machine translation for 9 language directions. In Proceedings of the 15th conference of the European chapter of the association for computational linguistics (Vol. 1, pp. 1063\u20131073).","DOI":"10.18653\/v1\/E17-1100"},{"key":"9537_CR50","volume-title":"T\u00e9cnicas conversacionales y narrativas. Investigaci\u00f3n cualitativa con Software NVivo","author":"C Trigueros-Cervantes","year":"2018","unstructured":"Trigueros-Cervantes, C., Rivera-Garc\u00eda, E., & Rivera-Trigueros, I. (2018). T\u00e9cnicas conversacionales y narrativas. Investigaci\u00f3n cualitativa con Software NVivo. Escuela Andaluza de Salud P\u00fablica\/Universidad de Granada."},{"key":"9537_CR51","unstructured":"Turian, J. P., Shen, L., & Melamed, I. D. (2003). Evaluation of machine translation and its evaluation. In Proceedings of MT Summit IX (pp. 386\u2013393). New Orleans, USA."},{"key":"9537_CR52","unstructured":"Vilar, D., Xu, J., D\u2019Haro, L., & Ney, H. (2006). Error analysis of statistical machine translation output. In Proceedings of the fifth international conference on language resources and evaluation (LREC\u201906) (pp. 697\u2013702)."},{"key":"9537_CR53","doi-asserted-by":"publisher","unstructured":"Way, A. (2018). Quality expectations of machine translation. In J. Moorkens, S. Castilho, F. Gaspari, & S. Doherty (Eds.), Translation quality assessment (pp. 159\u2013178). Cham: Springer. https:\/\/doi.org\/10.1007\/978-3-319-91241-7_8.","DOI":"10.1007\/978-3-319-91241-7_8"},{"key":"9537_CR54","doi-asserted-by":"publisher","DOI":"10.2307\/2289192","volume-title":"Basic content analysis","author":"RP Weber","year":"1990","unstructured":"Weber, R. P. (1990). Basic content analysis. SAGE. https:\/\/doi.org\/10.2307\/2289192"}],"container-title":["Language Resources and Evaluation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10579-021-09537-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10579-021-09537-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10579-021-09537-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,24]],"date-time":"2022-12-24T00:32:53Z","timestamp":1671841973000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10579-021-09537-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,10]]},"references-count":53,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2022,6]]}},"alternative-id":["9537"],"URL":"https:\/\/doi.org\/10.1007\/s10579-021-09537-5","relation":{},"ISSN":["1574-020X","1574-0218"],"issn-type":[{"value":"1574-020X","type":"print"},{"value":"1574-0218","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,10]]},"assertion":[{"value":"6 March 2021","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 April 2021","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The author declare that there is no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}