دورية أكاديمية
rMEA: An R package to assess nonverbal synchronization in motion energy analysis time-series.
| العنوان: | rMEA: An R package to assess nonverbal synchronization in motion energy analysis time-series. |
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| المؤلفون: | Kleinbub JR; Department of Philosophy, Sociology, Education, and Applied Psychology, University of Padova, Padova, Italy., Ramseyer FT; Department of Clinical Psychology and Psychotherapy, University of Bern, Bern, Switzerland. |
| المصدر: | Psychotherapy research : journal of the Society for Psychotherapy Research [Psychother Res] 2021 Jul; Vol. 31 (6), pp. 817-830. Date of Electronic Publication: 2020 Nov 23. |
| نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: Routledge Country of Publication: England NLM ID: 9110958 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1468-4381 (Electronic) Linking ISSN: 10503307 NLM ISO Abbreviation: Psychother Res Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: 2005- : London : Routledge Original Publication: New York, NY, USA : Guilford Publications, [1991- |
| مواضيع طبية MeSH: | Movement* , Psychotherapy*, Humans ; Software ; Treatment Outcome ; Video Recording |
| مستخلص: | Introduction . Motion Energy Analysis (MEA) is a procedure that allows to automatically assess the amount of persons' movement from video recordings. Recent studies used MEA to investigate nonverbal synchrony, i.e., the occurrence of simultaneous movement, suggesting the existence of an association with relationship quality. In patient-therapist dyads, synchrony predicted therapeutic alliance, empathy, as well as treatment outcome. Package description . The article presents rMEA, an open-source R package that allows to import, filter, and visualize dyadic time-series of nonverbal behaviour generated by other MEA software. The package includes a fast, state-of-the-art, moving window cross-correlation algorithm with lag analysis, which provides a user-friendly interface for the assessment of nonverbal synchrony. Through the analysis of a motivating example (40 psychotherapy intake interviews split between dropouts and good cases) the article provides an in-depth description of the package main functions and a tutorial for a typical analysis in this field, requiring only the most basic knowledge of the R language and environment. The rich visualization capabilities of the software provide powerful tools for the various steps involved in the diagnostics, analysis, interpretation and publication of these data. Conclusions. Overall, the paper aims to empower psychotherapy researchers and other interaction scientists to investigate nonverbal synchrony in their own dyads. |
| فهرسة مساهمة: | Keywords: R package; behavioural time-series; motion energy analysis; nonverbal synchrony; process and outcome research |
| تواريخ الأحداث: | Date Created: 20201123 Date Completed: 20210628 Latest Revision: 20210628 |
| رمز التحديث: | 20221213 |
| DOI: | 10.1080/10503307.2020.1844334 |
| PMID: | 33225873 |
| قاعدة البيانات: | MEDLINE |
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Full Text Finder | تدمد: | 1468-4381 |
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| DOI: | 10.1080/10503307.2020.1844334 |