Objectives: The management of patients with multifocal motor neuropathy (MMN) under everyday clinical conditions has been insufficiently studied. We therefore collected comprehensive observational data on patients with MMN who received intravenous (IV) or subcutaneous (SC) immunoglobulins (IGs) as maintenance therapy. Methods: This was a prospective, noninterventional study (registry) in neurological centres (hospitals and offices) throughout Germany. Results: As of 1 December 2015, 80 patients with MMN were included (mean age 55.4 ± 9.8 years, 67% males, mean disease duration 10.7 ± 10.2 years). The affected limb regions were predominantly distal muscle groups of the upper extremities. On the inflammatory neuropathy cause and treatment (INCAT) scale, 94% of the patients had some disability in the arms and 61% in the legs. At inclusion, 98.8% received IVIG and 1.3% SCIG. Substantial variation was observed between IVIG treatment intervals (every 0.7 to 17.3 weeks) and dosage (0.2–2.1 g/kg body weight received during a single administration; mean monthly dosage, 0.9 g/kg body weight). However, the mean monthly dosage was steady over time. At 1-year follow up, improvement was seen in muscle strength, INCAT and quality of life (QoL) scores (SF-36 questionnaire). Conclusions: The management of patients with MMN in everyday clinical practice demonstrates a wide range of absolute dosages and treatment intervals of IG, supporting the recommended practice of determining treatment dose on an individual patient basis. The improvements in muscle strength and reduction in disability, accompanied by increased QoL, strengthen the case for use of IG as a maintenance treatment for MMN.

Les troubles anxieux apparaissent très tôt chez les jeunes. Les études corrélationnelles suggèrent que plusieurs facteurs, tels que le stress prénatal maternel (SPM) et la surimplication maternelle contribueraient à leur développement et à leur maintien. L’objectif de l’étude est de mieux comprendre si la surimplication maternelle est une cause ou une conséquence de l’anxiété chez l’enfant, le tout dans un contexte de stress prénatal maternel causé par un désastre naturel. L’échantillon fait partie d’un projet plus grand dans lequel les stress objectif et subjectif ont été mesurés chez les femmes enceintes lors de l’inondation en 2011 à Queensland en Australie. L’échantillon de l’étude inclut 72 dyades mère-enfant, ayant complété une tâche difficile de casse-tête, d’une durée de 5 minutes, lorsque les enfants étaient âgés de 4 ans. À partir des vidéos, les observateurs ont évalué le comportement maternel (la surimplication) et le comportement de l’enfant (l’anxiété) en continu. Des techniques d’analyse séquentielle ont été utilisées pour déterminer la probabilité qu’un comportement maternel de surimplication se produise avant ou après un comportement anxieux et vice versa. Les corrélations obtenues entre le SPM (objectif et subjectif), le comportement anxieux de l’enfant et le comportement de surimplication maternelle n’ont pas été significatives. Le comportement de surimplication n’est pas un médiateur entre le SPM (objectif et subjectif) et le comportement anxieux de l’enfant. Toutefois, les chances qu’un comportement maternel de surimplication suive un comportement anxieux chez l’enfant étaient plus grandes que les chances qu’un comportement anxieux suive un comportement maternel de surimplication. Nos résultats suggèrent que le stress prénatal maternel n’est pas associé avec le comportement de surimplication maternelle, ni avec le comportement anxieux de l’enfant. La surimplication maternelle est plutôt une réaction au comportement anxieux de l’enfant. Il est essentiel, pour de futures recherches, de se rappeler que l’enfant est un participant actif dans la relation mère-enfant et qu’il est important d’étudier la bidirectionnalité de la relation pour mieux comprendre et pour mieux intervenir. / Anxiety disorders start very early in young people and several factors, such as prenatal maternal stress (PNMS) and maternal overinvolvement are believed to contribute to their development and maintenance. The objective of this study is to better understand if the overinvolvement of the mother is a cause or a consequence of the child’s anxiety, all in a context of prenatal maternal stress due to a natural disaster. The sample is part of a larger project that assessed the objective hardship and the subjective distress in women who were pregnant during the 2011 Queensland flood in Australia. The current sample included 72 mother-child dyads, completing a 5-minute puzzle task when the children were 4 years old. Observers rated maternal (overinvolved) and child (anxious) behaviors from videos continuously. Sequential analysis techniques were used to determine the likelihood of a maternal overinvolved behavior occurring before or after a child anxious behavior and vice versa. The correlations between PNMS (objective and subjective) and the child's anxiety and maternal over-involvement were not significant. Maternal overinvolvement did not mediate the relationship between PNMS (objective and subjective) and anxiety in children. However, the odds of maternal overinvolvement following child anxiety, was stronger than the odds of child anxiety following maternal overinvolvement. Our results suggest that prenatal maternal stress is not associated with maternal overinvolvement nor with child anxiety. It also suggests that maternal overinvolvement is a reaction to the child’s anxious behavior rather than a cause of it. Future research needs to keep in mind that the child is an active participant in the mother-child relationship and that it is important to study the bidirectionality of the relationship to better understand it and intervene.

本研究は，視聴する映像を学習者自身で選択させることによる運動学習効果を検討する事が目的であった．本研究の結果，学習者自身が映像を選択する事で，実験者によって選ばれた映像を視聴した場合と比較して，映像と学習者の運動イメージとの認知的な一致度を高めた．さらに，観察角度や選択の方法の違いが運動学習の向上に寄与する事を明らかにした．これらの知見は，運動指導や体育授業における映像の視聴方法や選び方といった提供方法の提案に繋がるだろう． / This study aimed to examine the motor learning effects of allowing learners to choose their own footage to watch. As a result, this study showed that the learner's chosen footage enhanced the cognitive consistency between the video and the learner's motor imagery, compared to the case in which the experimenter chosen video was shown. Furthermore, we found that differences in observational angle and the method of choice contributed to the improvement of motor learning. These findings would be led to propose a method of providing the video, such as how to watch them and how to choose them on a motor instruction and physical education. / 博士(スポーツ健康科学) / Doctor of Philosophy in Health and Sports Science / 同志社大学 / Doshisha University

lt has been shown that engagement in secondary tasks may contribute to cyclists crash risk [1 ], meditated by cycling errors or risky behaviors. For influences on secondary task: engagement, it is generally found that phone use is negatively correlated with age. In most studies, males are more found engaged in phone tasks than females. lt was also found that users of a bicycle-sharing program more often to wear headphones and engage in more unsafe behavior. The use of safety gear (e.g., wearing a helmet, using reflectors) is often negatively correlated with distracted cycling. Also, cyclists engaged in a secondary task exhibit other risky behaviors more often [2]. The present study's first aim was to get (an updated) estimate of the observable frequency of different secondary tasks, use of additional safety equipment, and rule violations while riding bicycles and e-scooters in Germany. The second aim was to examine possible differences in secondary task: engagement, use of additional safety equipment, and rule violations between different types of users of the cycling infrastructure, i.e., riders of conventional bikes, e-bikes, scooters, and e-scooters. A third aim was to explore whether riders' secondary task engagement is related to active safety precautions (e.g., wearing a helmet), traffic rule violations, and at-fault conflicts and if there are rider profiles regarding safety-related behaviors. As the study is explorative, no hypotheses were formulated. [From: Introduction]

Clinical and research practice in the context of Autism rapidly evolved in the last decades. Finer diagnostic procedures, evidence-based models of intervention and higher social inclusivity significantly improved the possibility for autistic children to participate in the fabric of social life. In terms of health best practices, gold-standard procedures still need to be improved, and bridging research and clinical practice still presents several challenges. From the clinical standpoint, the role of process variables, predictors, mechanisms, and timing of change still requires extensive investigation in order to explain response variability and design optimized interventions, tailored to individual needs and maximally effective. Observational techniques represent the elective research methods in child development, especially in clinical contexts, due to their non-invasiveness. However, they still suffer from limited objectivity and poor quantification. Further, their main disadvantage is that they are highly time-consuming and labor-intensive. The aim of this thesis was moving forward to promote translational research in clinical practice of Autism intervention with preschool children. At first, we tried to design and apply quantitative observational techniques to longitudinally study treatment response trajectories during developmental intervention. We tried to characterize different response profiles, and which baseline predictors were able to predict the response over time. Secondly, we investigated mechanisms of change. In particular, we focused on the role of the child-therapist interaction dynamics as a possible active mediator of the process of intervention, especially in the developmental framework that stresses the importance of interpersonal aspects. We also aimed at understanding whether certain time-windows during the intervention were particularly predictive of the response, as well as which specific interaction aspects played a role. Finally, to promote the translational application of observational methods and to improve objective quantification, we proposed and validated an Artificial Intelligence (AI) system to automate data annotation in unconstrained clinical contexts, remaining completely non-invasive and dealing with the specific noisy data that characterize them, for the analysis of the child-therapist acoustic interaction. This effort represents a base building block enabling to employ downstream computational techniques greatly reducing the need for human annotation that usually prevents the application of observational research to large amounts of data . We discuss our findings stressing the importance of assuming a developmental framework in Autism, the key role of the interpersonal experience also in the clinical context, the importance of focusing on trajectories of change and the important need to promote the acquisition of large amounts of quantitative data from the clinical contexts exploiting AI-based systems to assist clinicians, improving objectivity, enabling treatment monitoring, and producing precious data-driven knowledge on treatment efficacy.

No description available.

<p>This dissertation address two significant challenges in the causal inference workflow for Big Observational Data. The first is designing Big Observational Data with high-dimensional and heterogeneous covariates. The second is performing uncertainty quantification for estimates of causal estimands that are obtained from the application of black box machine learning algorithms on the designed Big Observational Data. The methodologies developed by addressing these challenges are applied for the design and analysis of Big Observational Data from a large public university in the United States. </p> <h4>Distributed Design</h4> <p>A fundamental issue in causal inference for Big Observational Data is confounding due to covariate imbalances between treatment groups. This can be addressed by designing the study prior to analysis. The design ensures that subjects in the different treatment groups that have comparable covariates are subclassified or matched together. Analyzing such a designed study helps to reduce biases arising from the confounding of covariates with treatment. Existing design methods, developed for traditional observational studies consisting of a single designer, can yield unsatisfactory designs with sub-optimum covariate balance for Big Observational Data due to their inability to accommodate the massive dimensionality, heterogeneity, and volume of the Big Data. We propose a new framework for the distributed design of Big Observational Data amongst collaborative designers. Our framework first assigns subsets of the high-dimensional and heterogeneous covariates to multiple designers. The designers then summarize their covariates into lower-dimensional quantities, share their summaries with the others, and design the study in parallel based on their assigned covariates and the summaries they receive. The final design is selected by comparing balance measures for all covariates across the candidates and identifying the best amongst the candidates. We perform simulation studies and analyze datasets from the 2016 Atlantic Causal Inference Conference Data Challenge to demonstrate the flexibility and power of our framework for constructing designs with good covariate balance from Big Observational Data.</p> <h4>Designed Bootstrap</h4> <p>The combination of modern machine learning algorithms with the nonparametric bootstrap can enable effective predictions and inferences on Big Observational Data. An increasingly prominent and critical objective in such analyses is to draw causal inferences from the Big Observational Data. A fundamental step in addressing this objective is to design the observational study prior to the application of machine learning algorithms. However, the application of the traditional nonparametric bootstrap on Big Observational Data requires excessive computational efforts. This is because every bootstrap sample would need to be re-designed under the traditional approach, which can be prohibitive in practice. We propose a design-based bootstrap for deriving causal inferences with reduced bias from the application of machine learning algorithms on Big Observational Data. Our bootstrap procedure operates by resampling from the original designed observational study. It eliminates the need for additional, costly design steps on each bootstrap sample that are performed under the standard nonparametric bootstrap. We demonstrate the computational efficiency of this procedure compared to the traditional nonparametric bootstrap, and its equivalency in terms of confidence interval coverage rates for the average treatment effects, by means of simulation studies and a real-life case study.</p> <h4>Case Study</h4> <p>We apply the distributed design and designed bootstrap methodologies in a case study involving institutional data from a large public university in the United States. The institutional data contains comprehensive information about the undergraduate students in the university, ranging from their academic records to on-campus activities. We study the causal effects of undergraduate students’ attempted course load on their academic performance based on a selection of covariates from these data. Ultimately, our real-life case study demonstrates how our methodologies enable researchers to effectively use straightforward design procedures to obtain valid causal inferences with reduced computational efforts from the application of machine learning algorithms on Big Observational Data.</p> <p><br></p>

Tesis por compendio / [ES] A mediados del siglo XX inició en el continente europeo, especialmente en Francia y Bélgica, una nueva disciplina denominada Ergonomía Centrada en la Actividad. Esta disciplina está enfocada en el análisis del trabajo con el fin de optimizar las condiciones laborales. El propósito de la intervención ergonómica es mejorar componentes que interactúan en el sistema o en la actividad del trabajo (las personas, la organización, la tecnología y el ambiente), interrelacionando aspectos de salud, seguridad, productividad y calidad. En investigaciones anteriores a la presente el doctorando identificó la necesidad de mejora de las herramientas empleadas por los profesionales para la evaluación de factores de riesgo ergonómico, motivando así el desarrollo de la presente investigación. Inicialmente se analizaron métodos generales empleados por los diseñadores para establecer aquellos susceptibles de mejora con la introducción de nuevas tecnologías. En una segunda fase se identificaron y analizaron dispositivos tecnológicos orientados al rastreo de la actividad humana aplicables en el ámbito de las metodologías de la ergonomía ocupacional para los sectores productivos. Como resultado se concluyó que los sensores RGB-D y el Eye-Tracking (rastreo ocular) son dispositivos aplicables para ayudar a mejorar las condiciones en los puestos de trabajo, el primero para distribuir las áreas de trabajo y el segundo para la mejora de las interfaces del usuario. En esta TD se desarrollaron técnicas y métodos para el empleo de estos dispositivos logrando el diseño ergonómico de puestos de trabajo con aplicación práctica (artículos 2 y 3). Durante la realización de esta TD, bajo las directrices del Programa de Doctorado en Tecnologías para la Salud y el Bienestar de la Universidad Politécnica de Valencia, se publicaron tres artículos en revistas que durante el año de su publicación estuvieron indexadas en el primer cuartil de su categoría en el Journal Citation Report, las cuáles sustentan los resultados de la investigación. En ellos se evidenció cómo los avances tecnológicos implementados en Ergonomía producen cambios importantes en el diseño de los puestos de trabajo, y minimizan los tiempos y los movimientos que se requieren en las diferentes actividades laborales, garantizando así una ubicación óptima del recurso humano en los sistemas de producción y generando a su vez estrategias que disminuyen los Trastornos Músculo Esqueléticos (TMEs). / [CA] A mitjan segle XX es va desenvolupar en el continent europeu, especialment a França i Bèlgica, una nova disciplina denominada Ergonomia Centrada en l'Activitat. Aquesta disciplina està enfocada en l'anàlisi del treball amb la finalitat d'optimitzar les condicions laborals. El propòsit de la intervenció ergonòmica és millorar els components que interactuen en el sistema o en l'activitat del treball (les persones, l'organització, la tecnologia i l'ambient), interrelacionant els aspectes de salut, seguretat, productivitat i qualitat. En investigacions anteriors a la present el doctorand va identificar la necessitat de millora de les eines emprades pels professionals per a l'avaluació de factors de risc ergonòmic, motivant així el desenvolupament de la present investigació. Inicialment es van analitzar els mètodes habituals empleats pels ergónoms per a establir aquells susceptibles de millora amb la introducció de noves tecnologies. En una segona fase es va identificar i analitzar els dispositius tecnològics orientats al monitoratge de l'activitat humana aplicables en l'àmbit de les metodologies de l'ergonomia ocupacional per als sectors productius. Com a resultat es va concloure que els sensors RGB-D i el Eye-Tracking són dispositius aplicables per a ajudar a millorar les condicions en els llocs de treball, el primer per a distribuir les àrees de treball i el segon per a la millora de les interfícies de l'usuari. En aquesta TD es van desenvolupar tècniques i procediments per a l'ús d'aquests dispositius aconseguint el disseny ergonòmic de llocs de treball amb aplicació pràctica (articles 2 i 3). Durant la realització d'aquesta TD, sota les directrius del Programa de Doctorat en Tecnologies per a la Salut i el Benestar de la Universitat Politècnica de València, es van publicar tres articles en revistes, que durant l'any de la seua publicació, van estar indexades en el primer quartil de la seua categoria en el Journal Citation Report, les quals sustenten els resultats de la investigació. En ells es va evidenciar com els avanços tecnològics implementats en Ergonomia produeixen canvis importants en el disseny dels llocs de treball, minimitzen els temps i els moviments que es requereixen en les diferents activitats laborals, garantint així una ubicació òptima del recurs humà en els sistemes de producció i generant al seu torn estratègies que disminueixen els Trastorns Músculesquelètics. / [EN] Around the middle of XX century in Europe, especially in France and Belgium, a new discipline named Activity Focused Ergonomics was developed. This concept is based on the task analysis aiming to optimize working conditions. The purpose of the ergonomic intervention is to improve the components interacting within the system or the work activities (people, organization, technology and environment), correlating all health, safety, productivity and quality facts. In previous research, the ergomists identified the improvement need of those tools used by professionals to assess ergonomic risk factors, enhancing therefore the development of this present research. In the beginning, regular methods used by ergonomics specilists were analized in order to define those that could be improved with the introduction of new technologies. In a second phase, technological devices aimed to monitorize human activity, as well as those applicable for the occupational ergonomics methodologies in productive sectors were identified and analyzed. The conclusion that came as a result was that RGB-D sensors and Eye-Tracking are actual workstations conditions' improving devices, the first one is used to better organize working areas and the second one to optimize the user's interfaces. This Doctoral Thesis develops techniques and procedures to correctly use these devices obtaining workstations ergonomic designs with practical applications (articles 2 and 3). Along the development of this Doctoral Thesis, under the Polytechnic University of Valencia Doctoral School for Health and Wellbeing Technologies program directions, three articles were published in magazines which, throughout their publication year were indexed within its cathegory's first quartile at the Journal Citation Report, supporting the research results. The articles evidenced how the technological progress implemented in Ergonomics produce important changes in the workstations design and minimize times and movements required in different working activities, ensuring human resources' optimal location within the production systems and also developing Musculoskeletal Disorders reduction strategies. / Garzón Leal, DC. (2020). Nuevas tecnologías aplicadas a la ergonomía ocupacional. Empleo de sensores RGBD y EyeTracking en la mejora ergonómica de puestos de trabajo [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/156052 / Compendio

This dissertation aims to understand the female Saudi mathematics teachers' formative assessment practices after coming back to in-person instruction and the impact of such practices on female student attitudes toward learning mathematics. The study was conducted in two middle schools located in the North and South districts of a large city in Saudi Arabia, using a sequential mixed study design methodology . The study's sample included 4 female mathematics teachers and 104 8th grade mathematics female students. For the qualitative research design, I conducted four interviews and used the NVivo program to thematically analyze my results. Additionally, I used AssessToday observational protocol to conduct 12 observations (three per teacher) and triangulated to analyze the data, including my filled notes, lessons audio recordings, and photos. For my quantitative design, I administered the Attitudes Towards Mathematics Inventory (ATMI) Scale to 104 8th-grade mathematics female students in a pre- and post-survey and I performed a confirmatory factor analysis (CFA) to assess the internal structure of my data. Overall, the study revealed that despite teachers' claims of practicing formative activities, their actual practices may not reflect it. The study confirmed the literature that using AssessToday is applicable regardless of the location, culture, language, and education system. The study contributes to short-cycle formative assessment literature by showing a positive and linear relationship (although not statistically significant) between teacher's use of formative assessment and students' attitudes toward learning mathematics.

L’observation d’un modèle pratiquant une habileté motrice promeut l’apprentissage de l’habileté en question. Toutefois, peu de chercheurs se sont attardés à étudier les caractéristiques d’un bon modèle et à mettre en évidence les conditions d’observation pouvant optimiser l’apprentissage. Dans les trois études composant cette thèse, nous avons examiné les effets du niveau d’habileté du modèle, de la latéralité du modèle, du point de vue auquel l’observateur est placé, et du mode de présentation de l’information sur l’apprentissage d’une tâche de timing séquentielle composée de quatre segments. Dans la première expérience de la première étude, les participants observaient soit un novice, soit un expert, soit un novice et un expert. Les résultats des tests de rétention et de transfert ont révélé que l’observation d’un novice était moins bénéfique pour l’apprentissage que le fait d’observer un expert ou une combinaison des deux (condition mixte). Par ailleurs, il semblerait que l’observation combinée de modèles novice et expert induise un mouvement plus stable et une meilleure généralisation du timing relatif imposé comparativement aux deux autres conditions. Dans la seconde expérience, nous voulions déterminer si un certain type de performance chez un novice (très variable, avec ou sans amélioration de la performance) dans l’observation d’une condition mixte amenait un meilleur apprentissage de la tâche. Aucune différence significative n’a été observée entre les différents types de modèle novices employés dans l’observation de la condition mixte. Ces résultats suggèrent qu’une observation mixte fournit une représentation précise de ce qu’il faut faire (modèle expert) et que l’apprentissage est d’autant plus amélioré lorsque l’apprenant peut contraster cela avec la performance de modèles ayant moins de succès. Dans notre seconde étude, des participants droitiers devaient observer un modèle à la première ou à la troisième personne. L’observation d’un modèle utilisant la même main préférentielle que soi induit un meilleur apprentissage de la tâche que l’observation d’un modèle dont la dominance latérale est opposée à la sienne, et ce, quel que soit l’angle d’observation. Ce résultat suggère que le réseau d’observation de l’action (AON) est plus sensible à la latéralité du modèle qu’à l’angle de vue de l’observateur. Ainsi, le réseau d’observation de l’action semble lié à des régions sensorimotrices du cerveau qui simulent la programmation motrice comme si le mouvement observé était réalisé par sa propre main dominante. Pour finir, dans la troisième étude, nous nous sommes intéressés à déterminer si le mode de présentation (en direct ou en vidéo) influait sur l’apprentissage par observation et si cet effet est modulé par le point de vue de l’observateur (première ou troisième personne). Pour cela, les participants observaient soit un modèle en direct soit une présentation vidéo du modèle et ceci avec une vue soit à la première soit à la troisième personne. Nos résultats ont révélé que l’observation ne diffère pas significativement selon le type de présentation utilisée ou le point de vue auquel l’observateur est placé. Ces résultats sont contraires aux prédictions découlant des études d’imagerie cérébrale ayant montré une activation plus importante du cortex sensorimoteur lors d’une observation en direct comparée à une observation vidéo et de la première personne comparée à la troisième personne. Dans l’ensemble, nos résultats indiquent que le niveau d’habileté du modèle et sa latéralité sont des déterminants importants de l’apprentissage par observation alors que le point de vue de l’observateur et le moyen de présentation n’ont pas d’effets significatifs sur l’apprentissage d’une tâche motrice. De plus, nos résultats suggèrent que la plus grande activation du réseau d’observation de l’action révélée par les études en imagerie mentale durant l’observation d’une action n’induit pas nécessairement un meilleur apprentissage de la tâche. / Observation of a model practicing a motor skill has been shown to promote the learning of that skill. However, relatively little is known regarding the attributes of a good model and the conditions of observation that can optimize learning. In the three studies reported in this thesis, we investigated the effects of the model’s skill level, the model’s handedness, the observation perspective, and the medium of presentation on the learning of a sequential, four-segmented timing task. In the first experiment of the first study, we had participants observe a novice, an expert, or a combination of both novice and expert models (i.e., mixed model). The results of the retention/transfer tests revealed that observation of the novice model was not as effective for the learning of the task as observation of the expert and mixed models. Importantly, a mixed schedule of novice and expert observation resulted in more stable movement time and better generalization of the imposed relative timing pattern than observation of either a novice or an expert model. In the second experiment, we wanted to determine whether a certain type of novice performance (highly variable, with or without performance improvement) in a mixed observation schedule results in better learning of the task. No significant differences were revealed with respect to the type of novice model used in a mixed schedule of observation. These results suggest that mixed observation provides an accurate template of what to do (expert observation), which is enhanced when it can be contrasted with the performance of less successful models. In our second study, right-handed participants were asked to observe, from a first-person or a third-person perspective, a right-handed (i.e., same-handed) or left-handed (i.e., opposite-handed) model performing the experimental task. Observation of the same-handed model resulted in better learning of the task than did observation of the opposite-handed model, regardless of the observation perspective. This suggests that the action observation network (AON) is more sensitive to the model’s handedness than to the observer’s viewpoint. Thus, the AON seems to be linked to sensorimotor regions of the brain that simulate motor programming as though the observed movement was performed with one’s own dominant hand. Finally, in the third study, we were interested to determine whether the medium of presentation (live vs. video) affects observational learning and whether this effect would be mediated by the observer’s viewpoint (1st vs. 3rd person). In that regard, participants observed a live model or a video presentation of the model from a first- or third-person perspective. Our results revealed that observation did not differ significantly as a function of the media or the perspective of observation. These results are inconsistent with the predictions of brain imaging studies that show a larger activation of the sensorimotor cortex during live observation compared with video observation and from a first-person compared with the third-person perspective. Taken together, our results indicate that the model’s skill level and handedness are important determinants of observational learning, whereas the observer’s viewpoint and the medium of observation had no significant impact on motor task learning. In addition, our results suggest that the larger activation of AON revealed in brain imaging studies during action observation does not necessarily result in or indicate better learning of the task.