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Copyright of Retos: Nuevas Perspectivas de Educación Física, Deporte y Recreación is the property of Federacion Espanola de Asociaciones de Docentes de Educacion Fisica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: Evaluating the usefulness of a chat bot as an assistant during CPR care by laypersons.Methods: Twenty-one university graduates and university students naive in basic life support participated in this quasi-experimental simulation pilot trial. A version beta chatbot was designed to guide potential bystanders who need help in caring for cardiac arrest victims. Through a Question-Answering (Q&A) flowchart, the chatbot uses Voice Recognition Techniques to transform the user's audio into text. After the transformation, it generates the answer to provide the necessary help through machine and deep learning algorithms. A simulation test with a Laerdal Little Anne manikin was performed. Participants initiated the chatbot, which guided them through the recognition of a cardiac arrest event. After recognizing the cardiac arrest, the chatbot indicated the start of chest compressions for 2 min. Evaluation of the cardiac arrest recognition sequence was done via a checklist and the quality of CPR was collected with the Laerdal Instructor App.Results: 91% of participants were able to perform the entire sequence correctly. All participants checked the safety of the scene and made sure to call 112. 62% place their hands on the correct compression point. A media time of 158 s (IQR: 146-189) was needed for the whole process. 33% of participants achieved high-quality CPR with a median of 60% in QCPR (IQR: 9-86). Compression depth had a median of 42 mm (IQR: 33-53) and compression rate had a median of 100 compressions/min (IQR: 97-100).Conclusion: The use of a voice assistant could be useful for people with no previous training to perform de out-of-hospital cardiac arrest recognition sequence. Chatbot was able to guide all participants to call 112 and to perform continuous chest compressions. The first version of the chatbot for potential bystanders naive in basic life support needs to be further developed to reduce response times and be more effective in giving feedback on chest compressions. [ABSTRACT FROM AUTHOR]

Copyright of Cuadernos de Psicología del Deporte is the property of Cuadernos de Psicologia del Deporte and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Retos: Nuevas Perspectivas de Educación Física, Deporte y Recreación is the property of Federacion Espanola de Asociaciones de Docentes de Educacion Fisica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this study was (i) to identify the key performance indicators that discriminate all-star from non-all-stars players, and (ii) to differentiate winning from drawing/losing teams during the men´s water polo Olympic Games (Tokyo, 2020). The sample consisted of all matches (n = 42) played by 12 teams (156 players). Differences were calculated using the Mann-Whitney U and student-t tests and the binary logistic regression. Minutes per match, goals, action goals, centre goals, extra-player goals, 6-m goals, penalty goals, steals and rebounds discriminated all-star from non-all-star players. However, only minutes per match (OR: 1.105), extra player goals (OR: 1.748), 6-m goals (OR = 3.617) and penalty goals (OR: 2.592) per time played were determined to differentiate all-star players. Regarding the second aim, the following variables discriminated winning from losing/drawing teams: % action goals, % 6-m goals, % penalty goals, team fouls, sprints won, steals and % goalkeeper actions shots. However, only % action goals (OR: 1.153), steals (OR: 1.279) and % action shots (OR: 1.093) predicted the match outcome. Coaching staffs may apply this information to different players, while account for individual differences and functional variability, to optimise practice planning and, consequently, the game performance of individuals and teams. [ABSTRACT FROM AUTHOR]

The aim of the present study was to identify groups of offensive performance indicators which best discriminated between a match score (favourable, balanced or unfavourable) in water polo. The sample comprised 88 regular season games (2011-2014) from the Spanish Professional Water Polo League. The offensive performance indicators were clustered in five groups: Attacks in relation to the different playing situations; Shots in relation to the different playing situations; Attacks outcome; Origin of shots; Technical execution of shots. The variables of each group had a constant sum which equalled 100%. The data were compositional data, therefore the variables were changed by means of the additive log-ratio (alr) transformation. Multivariate discriminant analyses to compare the match scores were calculated using the transformed variables. With regard to the percentage of right classification, the results showed the group that discriminated the most between the match scores was "Attacks outcome" (60.4% for the original sample and 52.2% for cross-validation). The performance indicators that discriminated the most between the match scores in games with penalties were goals (structure coefficient (SC) = .761), counterattack shots (SC = .541) and counterattacks (SC = .481). In matches without penalties, goals were the primary discriminating factor (SC = .576). This approach provides a new tool to compare the importance of the offensive performance groups and their effect on the match score discrimination. [ABSTRACT FROM AUTHOR]