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dc.contributor.advisorThomas, Kevin C.en_US
dc.contributor.advisorBhangu, Jaspreeten_US
dc.contributor.authorEden, Gabrielle Marieen_US
dc.date.accessioned2019-04-22T17:48:14Z
dc.date.available2019-04-22T17:48:14Z
dc.date.issued2019
dc.identifier.urihttps://hdl.handle.net/2144/34883
dc.description.abstractINTRODUCTION: Retrospective video analysis (RVA) has been a popular method of analysis in many research fields, evidenced by autism behavioral research, child play behavior, and caregiver-resident interactions (Baranek, 1999; Gilchrist et al., 2018; Gilmore-Bykovskyi, 2015). Given the widespread use of RVA, the number of studies using it to augment their study designs provide sparse details about the training methods for this level of analysis, making it difficult to maintain a standard level of rigor across different institutions (Haidet, Tate, Divirgilio-Thomas, Kolanowski, & Happ, 2009). METHODS: A structured training program was developed for naïve coders (n=5). The structured training program was composed of five stages with careful introduction of behaviors and regular checkpoints. Statistical Analysis: The output generated by the naïve trainees was analyzed with paired t-tests, Fisher’s Exact Test, ANOVA, percent agreement, and Cohen’s kappa. RESULTS: No difference was found between the different trainees, demonstrating the trainees were trained to a similar level of expertise. The overall recognition of behaviors increased by 2.1% from the first to last training video analysis. Discrete behaviors had a higher level of agreement. CONCLUSIONS: The structured training program demonstrated a small increase in the recognition of behaviors, with a higher recognition in the derived MDS-UPDRS behaviors.en_US
dc.language.isoen_US
dc.subjectMedical imagingen_US
dc.subjectStructured training programen_US
dc.subjectTraining methodsen_US
dc.titleImplementation of a structured training program for retrospective video analysis of Parkinson's diseaseen_US
dc.typeThesis/Dissertationen_US
dc.date.updated2019-02-21T20:06:39Z
etd.degree.nameMaster of Scienceen_US
etd.degree.levelmastersen_US
etd.degree.disciplineAnatomy & Neurobiologyen_US
etd.degree.grantorBoston Universityen_US


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