EEG Analyses of visual cue effects on executed movements.

BACKGROUND: In electroencephalographic (EEG) or electrocorticographic (ECoG) experiments, visual cues are commonly used for timing synchronization but may inadvertently induce neural activity and cognitive processing, posing challenges when decoding self-initiated tasks. NEW METHOD: To address this concern, we introduced four new visual cues (Fade, Rotation, Reference, and Star) and investigated their impact on brain signals. Our objective was to identify a cue that minimizes its influence on brain activity, facilitating cue-effect free classifier training for asynchronous applications, particularly aiding individuals with severe paralysis. RESULTS: 22 able-bodied, right-handed participants aged 18-30 performed hand movements upon presentation of the visual cues. Analysis of time-variability between movement onset and cue-aligned data, grand average MRCP, and classification outcomes revealed significant differences among cues. Rotation and Reference cue exhibited favorable results in minimizing temporal variability, maintaining MRCP patterns, and achieving comparable accuracy to self-paced signals in classification. COMPARISON WITH EXISTING METHODS: Our study contrasts with traditional cue-based paradigms by introducing novel visual cues designed to mitigate unintended neural activity. We demonstrate the effectiveness of Rotation and Reference cue in eliciting consistent and accurate MRCPs during motor tasks, surpassing previous methods in achieving precise timing and high discriminability for classifier training. CONCLUSIONS: Precision in cue timing is crucial for training classifiers, where both Rotation and Reference cue demonstrate minimal variability and high discriminability, highlighting their potential for accurate classifications in online scenarios. These findings offer promising avenues for refining brain-computer interface systems, particularly for individuals with motor impairments, by enabling more reliable and intuitive control mechanisms.

Exploring HTML5 Package Interactive Content in Supporting Learning Through Self-Paced Massive Open Online Courses on Healthy Aging: Mixed Methods Study.

BACKGROUND: The rapidly aging population and the growth of geriatric medicine in the field of internal medicine are not supported by sufficient gerontological training in many health care disciplines. There is rising awareness about the education and training needed to adequately prepare health care professionals to address the needs of the older adult population. Massive open online courses (MOOCs) might be the best alternative method of learning delivery in this context. However, the diversity of MOOC participants poses a challenge for MOOC providers to innovate in developing learning content that suits the needs and characters of participants. OBJECTIVE: The primary outcome of this study was to explore students' perceptions and acceptance of HTML5 package (H5P) interactive content in self-paced MOOCs and its association with students' characteristics and experience in using MOOCs. METHODS: This study used a cross-sectional design, combining qualitative and quantitative approaches. Participants, predominantly general practitioners from various regions of Indonesia with diverse educational backgrounds and age groups, completed pretests, engaged with H5P interactive content, and participated in forum discussions and posttests. Data were retrieved from the online questionnaire attached to a selected MOOC course. Students' perceptions and acceptance of H5P interactive content were rated on a 6-point Likert scale from 1 (strongly disagree) to 6 (strongly agree). Data were analyzed using SPSS (IBM Corp) to examine demographics, computer literacy, acceptance, and perceptions of H5P interactive content. Quantitative analysis explored correlations, while qualitative analysis identified recurring themes from open-ended survey responses to determine students' perceptions. RESULTS: In total, 184 MOOC participants agreed to participate in the study. Students demonstrated positive perceptions and a high level of acceptance of integrating H5P interactive content within the self-paced MOOC. Analysis of mean (SD) value across all responses consistently revealed favorable scores (greater than 5), ranging from 5.18 (SD 0.861) to 5.45 (SD 0.659) and 5.28 (SD 0.728) to 5.52 (SD 0.627), respectively. This finding underscores widespread satisfaction and robust acceptance of H5P interactive content. Students found the H5P interactive content more satisfying and fun, easier to understand, more effective, and more helpful in improving learning outcomes than material in the form of common documents and learning videos. There is a significant correlation between computer literacy, students' acceptance, and students' perceptions. CONCLUSIONS: Students from various backgrounds showed a high level of acceptance and positive perceptions of leveraging H5P interactive content in the self-paced MOOC. The findings suggest potential new uses of H5P interactive content in MOOCs, such as interactive videos with pop-up questions, to substitute for synchronous learning. The study underscores the significance of tailored educational strategies in supporting the professional development of health care professionals.

The Anchoring Effect in Study Time Allocation: Labor-in-Vain versus Labor-and-Gain.

How to allocate study time is an important decision-making problem learners face. Research on this problem can help improve the learning performance of learners and provide guidance for teaching activities. This research aimed to explore the potential of anchors (prior information that may influence individual decision-making and judgment under uncertainty) as clues for study time allocation and examine the effectiveness of study time allocation under the influence of anchors. Sixty-two Chinese university students (Mage = 21.21, SD = 1.74; 44 females) studied 20 word pairs under self-paced learning instructions. These instructions either set a high anchor (i.e., the typical participant spent 15 s learning each pair) or a low anchor (i.e., the typical participant spent 5 s learning each pair) for study time. After a brief distraction phase, participants took a cued recall test. The results showed that the higher the anchor value, the longer the corresponding study time, and the longer the study time, the better the memory performance. These results reveal that there is both an anchoring effect and a labor-and-gain effect in self-paced study time allocation. This study extends the range of observable anchoring effects and provides important information on allocating study time effectively.

LCASPMDA: a computational model for predicting potential microbe-drug associations based on learnable graph convolutional attention networks and self-paced iterative sampling ensemble.

Introduction: Numerous studies show that microbes in the human body are very closely linked to the human host and can affect the human host by modulating the efficacy and toxicity of drugs. However, discovering potential microbe-drug associations through traditional wet labs is expensive and time-consuming, hence, it is important and necessary to develop effective computational models to detect possible microbe-drug associations. Methods: In this manuscript, we proposed a new prediction model named LCASPMDA by combining the learnable graph convolutional attention network and the self-paced iterative sampling ensemble strategy to infer latent microbe-drug associations. In LCASPMDA, we first constructed a heterogeneous network based on newly downloaded known microbe-drug associations. Then, we adopted the learnable graph convolutional attention network to learn the hidden features of nodes in the heterogeneous network. After that, we utilized the self-paced iterative sampling ensemble strategy to select the most informative negative samples to train the Multi-Layer Perceptron classifier and put the newly-extracted hidden features into the trained MLP classifier to infer possible microbe-drug associations. Results and discussion: Intensive experimental results on two different public databases including the MDAD and the aBiofilm showed that LCASPMDA could achieve better performance than state-of-the-art baseline methods in microbe-drug association prediction.

Effect of caffeine ingestion on time trial performance in cyclists: a systematic review and meta-analysis.

BACKGROUND: Caffeine, widely recognized as an ergogenic aid, has undergone extensive research, demonstrating its effectiveness to enhance endurance performance. However, there remains a significant gap in systematically evaluating its effects on time trial (TT) performance in cyclists. PURPOSE: This meta-analysis aimed to determine the efficacy of caffeine ingestion to increase cycling TT performance in cyclists and to evaluate the optimal dosage range for maximum effect. METHODS: A search of four databases was completed on 1 December 2023. The selected studies comprised crossover, placebo-controlled investigations into the effects of caffeine ingestion on cycling TT performance. Completion time (Time) and mean power output (MPO) were used as performance measures for TT. Meta-analyses were performed using a random-effects model to assess the standardized mean differences (SMD) in individual studies. RESULTS: Fifteen studies met the inclusion criteria for the meta-analyses. Subgroup analysis showed that moderate doses of caffeine intake (4-6 mg/kg) significantly improved cycling performance (SMD Time = -0.55, 95% confidence interval (CI) = -0.84 ~ -0.26, p < 0.01, I2 = 35%; SMD MPO = 0.44, 95% CI = 0.09 ~ 0.79, p < 0.05, I2 = 39%), while the effects of low doses (1-3 mg/kg) of caffeine were not significant (SMD Time = -0.34, 95% CI = -0.84 ~ 0.17, p = 0.19, I2 = 0%; SMD MPO = 0.31, 95% CI = -0.02 ~ 0.65, p = 0.07, I2 = 0%). CONCLUSION: A moderate dosage (4-6 mg/kg) of caffeine, identified as the optimal dose range, can significantly improve the time trial performance of cyclists, while a low dose (1-3 mg/kg) does not yield improvement. In addition, the improvements in completion time and mean power output resulting from a moderate dose of caffeine are essentially the same in cycling time trails.

Single Session Intermittent Heat Exposure With More Frequent and Shorter Cooling Breaks Facilitates Greater Training Intensity and Elicits Physiological Responses Comparable to Continuous Heat Exposure.

PURPOSE: To investigate the influence of shorter, more frequent rest breaks with per-cooling as an alternative heat-acclimation session on physiological, perceptual, and self-paced maximal cycling performance, compared with continuous heat exposure. METHODS: Thirteen participants completed 1 continuous and 3 intermittent-heat-exposure (IHE) maximal self-paced cycling protocols in a random order in heat (36 °C, 80% relative humidity): 1 × 60-minute exercise (CON), 3 × 20-minute exercise with 7.5-minute rest between sets (IHE-20), 4 × 15-minute exercise with 5-minute rest between sets (IHE-15), and 6 × 10-minute exercise with 3-minute rest between sets (IHE-10). Mixed-method per-cooling (crushed-ice ingestion and cooling vest) was applied during rest periods of all IHE protocols. RESULTS: Total distance completed was greater in IHE-10, IHE-15, and IHE-20 than in CON (+11%, +9%, and +8%, respectively), with no difference observed between IHE protocols. Total time spent above 38.5 °C core temperature was longer in CON compared with IHE-15 and IHE-20 (+62% and +78%, respectively) but similar to IHE-10 (+5%). Furthermore, a longer time above 38.5 °C core temperature occurred in IHE-10 versus IHE-15 and IHE-20 (+54% and +69%, respectively). Sweat loss did not differ between conditions. CONCLUSION: IHE with per-cooling may be a viable alternative heat-acclimation protocol in situations where training quality takes precedence over thermal stimulus or when both factors hold equal priority.

The blood serum metabolome profile after different phases of a 4-km cycling time trial: Secondary analysis of a randomized controlled trial.

It has been assumed that exercise intensity variation throughout a cycling time trial (TT) occurs in alignment of various metabolic changes to prevent premature task failure. However, this assumption is based on target metabolite responses, which limits our understanding of the complex interconnection of metabolic responses during exercise. The current study characterized the metabolomic profile, an untargeted metabolic analysis, after specific phases of a cycling 4-km TT. Eleven male cyclists performed three separated TTs in a crossover counterbalanced design, which were interrupted at the end of the fast-start (FS, 600 ± 205 m), even-pace (EP, 3600 ± 190 m), or end-spurt (ES, 4000 m) phases. Blood samples were taken before any exercise and 5 min after exercise cessation, and the metabolomic profile characterization was performed using Nuclear Magnetic Resonance metabolomics. Power output (PO) was also continually recorded. There were higher PO values during the FS and ES compared to the EP (all p < 0.05), which were accompanied by distinct metabolomic profiles. FS showed high metabolite expression in TCA cycle and its related pathways (e.g., glutamate, citric acid, and valine metabolism); whereas, the EP elicited changes associated with antioxidant effects and oxygen delivery adjustment. Finally, ES was related to pathways involved in NAD turnover and serotonin metabolism. These findings suggest that the specific phases of a cycling TT are accompanied by distinct metabolomic profiles, providing novel insights regarding the relevance of specific metabolic pathways on the process of exercise intensity regulation.

Predicting drug-target interactions using matrix factorization with self-paced learning and dual similarity information.

BACKGROUND: Drug repositioning (DR) refers to a method used to find new targets for existing drugs. This method can effectively reduce the development cost of drugs, save time on drug development, and reduce the risks of drug design. The traditional experimental methods related to DR are time-consuming, expensive, and have a high failure rate. Several computational methods have been developed with the increase in data volume and computing power. In the last decade, matrix factorization (MF) methods have been widely used in DR issues. However, these methods still have some challenges. (1) The model easily falls into a bad local optimal solution due to the high noise and high missing rate in the data. (2) Single similarity information makes the learning power of the model insufficient in terms of identifying the potential associations accurately. OBJECTIVE: We proposed self-paced learning with dual similarity information and MF (SPLDMF), which introduced the self-paced learning method and more information related to drugs and targets into the model to improve prediction performance. METHODS: Combining self-paced learning first can effectively alleviate the model prone to fall into a bad local optimal solution because of the high noise and high data missing rate. Then, we incorporated more data into the model to improve the model's capacity for learning. RESULTS: Our model achieved the best results on each dataset tested. For example, the area under the receiver operating characteristic curve and the precision-recall curve of SPLDMF was 0.982 and 0.815, respectively, outperforming the state-of-the-art methods. CONCLUSION: The experimental results on five benchmark datasets and two extended datasets demonstrated the effectiveness of our approach in predicting drug-target interactions.

Assessing the Feasibility and Preliminary Effects of a Web-Based Self-Management Program for Chronic Noncancer Pain: Mixed Methods Study.

BACKGROUND: In Canada, adults with chronic noncancer pain face a persistent insufficiency of publicly funded resources, with the gold standard multidisciplinary pain treatment facilities unable to meet the high clinical demand. Web-based self-management programs cost-effectively increase access to pain management and can improve several aspects of physical and emotional functioning. Aiming to meet the demand for accessible, fully automated resources for individuals with chronic noncancer pain, we developed a French web- and evidence-based self-management program, Agir pour moi (APM). This program includes pain education and strategies to reduce stress, practice mindfulness, apply pacing, engage in physical activity, identify and manage thinking traps, sleep better, adapt diet, and sustain behavior change. OBJECTIVE: This study aims to assess the APM self-management program's feasibility, acceptability, and preliminary effects in adults awaiting specialized services from a center of expertise in chronic pain management. METHODS: We conducted a mixed methods study with an explanatory sequential design, including a web-based 1-arm trial and qualitative semistructured interviews. We present the results from both phases through integrative tables called joint displays. RESULTS: Response rates were 70% (44/63) at postintervention and 56% (35/63) at 3-month follow-up among the 63 consenting participants who provided self-assessed information at baseline. In total, 46% (29/63) of the participants completed the program. We interviewed 24% (15/63) of the participants. The interview's first theme revolved around the overall acceptance, user-friendliness, and engaging nature of the program. The second theme emphasized the differentiation between microlevel and macrolevel engagements. The third theme delved into the diverse effects observed, potentially influenced by the macrolevel engagements. Participants highlighted the features that impacted their self-efficacy and the adoption of self-management strategies. We observed indications of improvement in self-efficacy, pain intensity, pain interference, depression, and catastrophizing. Interviewees described these and various other effects as potentially influenced by macrolevel engagement through behavioral change. CONCLUSIONS: These findings provided preliminary evidence that the APM self-management program and research methods are feasible. However, some participants expressed the need for at least phone reminders and minimal support from a professional available to answer questions over the first few weeks of the program to engage. Recruitment strategies of a future randomized controlled trial should focus on attracting a broader representation of individuals with chronic pain in terms of gender and ethnicity. TRIAL REGISTRATION: ClinicalTrials.gov NCT05319652; https://clinicaltrials.gov/study/NCT05319652.

Category Locality Theory: A unified account of locality effects in sentence comprehension.

In real-time sentence comprehension, the comprehender is often required to establish syntactic dependencies between words that are linearly distant. Major models of sentence comprehension assume that longer dependencies are more difficult to process because of working memory limitations. While the expected effect of distance on reading times (locality effect) has been robustly observed in certain constructions, such as relative clauses in English, its generalizability to a wider range of constructions has been empirically questioned. The current study proposes a new metric of syntactic distance that capitalizes on the flexible constituency of Combinatory Categorial Grammar (CCG), and argues that it offers a unified account of the locality effects. It is shown that this metric correctly predicts both the presence of the locality effect in English relative clauses and its absence in verb-final languages, without assuming language- or dependency-specific differences in the sensitivity to the locality effect. It is further shown that the CCG-based distance is a significant predictor of the self-paced reading times from an English corpus, even when other known predictors such as dependency-based locality and surprisal are taken into account. These results suggest that human sentence comprehension involves rapid integration of input words into efficiently compressed syntactic representations, and CCG is a plausible theory of the grammar that subserves this process.

Self-paced regularized adaptive multi-view unsupervised feature selection.

Multi-view unsupervised feature selection (MUFS) is an efficient approach for dimensional reduction of heterogeneous data. However, existing MUFS approaches mostly assign the samples the same weight, thus the diversity of samples is not utilized efficiently. Additionally, due to the presence of various regularizations, the resulting MUFS problems are often non-convex, making it difficult to find the optimal solutions. To address this issue, a novel MUFS method named Self-paced Regularized Adaptive Multi-view Unsupervised Feature Selection (SPAMUFS) is proposed. Specifically, the proposed approach firstly trains the MUFS model with simple samples, and gradually learns complex samples by using self-paced regularizer. l2,p-norm (0

The Effect of Syntactic Similarity on Intra-Sentential Switching Costs: Evidence from Chinese-English Bilinguals.

In order to better understand the role of syntactic similarity in a code-switched sentence, the current study explored the effect of similar and different syntactic structures on Chinese-English bilinguals' intra-sentential switching costs. L2 proficiency and switching directions as factors that potentially intervene in bilingual performance were together explored to see if there was any interaction. We manipulated the degree of syntactic similarity by utilizing clauses in active voice (greater similarity) and passive voice (lesser similarity). The study conducted a self-paced reading paradigm as a more natural language reading processing. Results showed overall longer reading times for active sentences than passive counterparts, which supported a syntactic similarity impediment rather than facilitation. The impediment seemed to be predominant irrespective of L2 proficiency. Furthermore, syntactic similarity modulated the asymmetry of switching costs between forward (L1-L2) and backward (L2-L1) direction: word RTs for the 1st and the 2nd switched word yielded greater costs in L2-L1 condition, while greater costs in L1-L2 condition was observed in 3rd switched word RTs and average RTs. The present study observed syntactic similarity impediment rather than facilitation for Chinese-English bilinguals. Notably, syntactic similarity plays a predominant role compared to L2 proficiency, and modulates the asymmetry between switching directions.

Mixed-Method Precooling Enhances Self-Paced 20-km Cycling Time-Trial Performance When Apparent Temperature Is >46 °C but May Not Be a Priority in <46 °C.

PURPOSE: Precooling (PreC) may only benefit performance when thermal strain experienced by an individual is sufficiently high. We explored the effect of mixed-method PreC on 20-km cycling time-trial (CTT) performance under 3 different apparent temperatures (AT). METHODS: On separate days, 12 trained or highly trained male cyclists/triathletes completed six 20-km CTTs in 3 different ATs: hot-dry (35 °C AT), moderately hot-humid (40 °C AT), and hot-humid (46 °C AT). All trials were preceded by 30 minutes of mixed-method PreC or no PreC (control [CON]). RESULTS: Faster 2.5-km-split completion times occurred in PreC compared with CON in 46 °C AT (P = .02), but not in 40 °C AT (P = .62) or 35 °C AT (P = .57). PreC did not affect rectal and body temperature during the 20-km CTT. Skin temperature was lower throughout the CTT in PreC compared with CON in 46 °C AT (P = .01), but not in 40 °C AT (P = 1.00) and 35 °C AT (P = 1.00). Heart rate had a greater rate of increase during the CTT for PreC compared with CON in 46 °C AT (P = .01), but not in 40 °C AT (P = .57) and 35 °C AT (P = 1.00). Ratings of perceived exertion (P < .001) and thermal comfort (P = .04) were lower for PreC compared with CON in 46 °C AT only, while thermal sensation was not different between PreC and CON. CONCLUSION: Mixed-method PreC should be applied prior to 20-km CTTs conducted in hot-humid conditions (≥46 °C AT). Alternatively, mixed-method PreC may be a priority in moderately hot-humid (∼40 °C AT) conditions but should not be in hot-dry (∼35 °C AT) conditions for 20-km CTT.

Processing and Comprehension of Locally Ambiguous Participial Relative Clause Sentences in Russian.

The study tested how the Recency Preference and Predicate Proximity model (Gibson et al. in Cognition 59(1):23-59, 1996, https://doi.org/10.1016/0010-0277(88)90004-2 ) plays out by examining the attachment preferences of native Russian speakers when processing locally ambiguous participial relative clause sentences with three potential NP attachment sites in Russian. Using a self-paced reading task, reading times and noun phrase selection responses were collected. Results showed significantly shorter reading times at the disambiguating region and higher accuracy rate of selection in the high-attaching condition than in the middle- and low-attaching conditions. No significant differences were found between the middle- and low-attaching conditions. We argue that Predicate Proximity is a much stronger factor than Recency Preference in Russian.

Capturing individual differences in sentence processing: How reliable is the self-paced reading task?

Advances in research on language processing have originally come from group-level comparisons, but there is now a growing interest in individual differences. To investigate individual differences, tasks that have shown robust group-level differences are often used with the implicit assumption that they will also be reliable when used as an individual differences measure. Here, we examined whether one of the primary tasks used in psycholinguistic research on language processing, the self-paced reading task, can reliably measure individual differences in relative clause processing. We replicated the well-established effects of relative clauses at the group level, with object relative clauses being more difficult to process than subject relative clauses. However, when using difference scores, the reliability of the size of the relative clause effect was close to zero because the self-paced reading times for the different relative clause types were highly correlated within individuals. Nonetheless, we found that the self-paced reading task can be used to reliably capture individual differences in overall reading speed as well as key sentence regions when the two types of relative clause sentences are considered separately. Our results indicate that both the reliability and validity of different sentence regions need to be assessed to determine whether and when self-paced reading can be used to examine individual differences in language processing.

Vagueness as an implicit-encoding persuasive strategy: an experimental approach.

The paper provides novel theoretical and experimental perspectives on the functioning of linguistic vagueness as an implicit persuasive strategy. It presents an operative definition of pragmatically marked vagueness, referring to vague expressions whose interpretation is not retrievable by recipients. The phenomenon is illustrated via numerous examples of its use in predominantly persuasive texts (i.e., advertising and political propaganda) in different languages. The psycholinguistic functioning of vague expressions is then illustrated by the results of a self-paced reading task experiment. Data showing shorter reading times associated with markedly vague expressions as compared to expressions that are either (a) lexically more precise or (b) made precise by the context suggest that the former are interpreted in a shallow way, without searching for and/or retrieving exact referents. These results support the validity of a differentiation between context-supported vs. non-supported vague expressions. Furthermore, validation of using marked vagueness as a persuasive implicit strategy which reduces epistemic vigilance is provided.

Discourse coherence modulates use of predictive processing during sentence comprehension.

Context has been shown to be vitally important for comprehension. Lexical processing is facilitated when words are highly predictable given their local sentence context, suggesting that people pre-activate likely upcoming words to aid comprehension. However, this facilitation is affected by knowledge about the global context in which comprehension takes place: people predict less when in an environment where expectations are frequently violated. The current study investigated whether discourse coherence is an additional cue that comprehenders use to modulate lexical prediction. In a series of online, self-paced reading experiments, participants read target sentences preceded by short contextual preambles. Local facilitation effects were manipulated through the cloze probability of a critical word within the target sentence and discourse coherence was manipulated by varying the degree to which the target sentence was consistent with the information presented in the preamble. In the first two experiments, target sentences were read more slowly when they occurred in less coherent discourses, but no local facilitation effects were observed. In the third experiment, we strengthened the predictability manipulation by using semantically anomalous critical words. In this experiment, predictable words were processed more quickly and anomalous words more slowly when they occurred in highly coherent discourse. Our results suggest that comprehenders are sensitive to shifts in the topic of discourse and that they downregulate predictive processing when they encounter incoherence in the discourse. This is consistent with recent theoretical accounts suggesting that comprehenders flexibly engage in predictive processing, pre-activating semantic and lexical information less when their expectations are less likely to be reliable.

Effect of different pacing strategies on 4-km cycling time trial performance

In cycling, there is a body of evidence that supports that an all-out start strategy is superior to an even-pacing strategy, but it is unknown whether an all-out start strategy is superior to a self-paced strategy. In the present study, we investigated the effects of three different pacing strategies on 4-km cycling time trial performance. After preliminary trials (familiarization trials and a baseline 4-km cycling time trial), in a randomized and counterbalanced order, twelve male cyclists (32.3±7.2 years old, maximum rate of O2 uptake (V̇O2peak) 4.3±0.4 L/min) completed: 1) a self-paced 4-km cycling time trial; 2) an all-out start (∼10 s), followed by maintenance of the average baseline trial power for the first km and self-paced cycling for the remaining trial (all-out+mean); and 3) an all-out start (∼10 s), followed by a power 5% above the average baseline trial power for the first km and self-paced cycling for the remaining trial (all-out+5%mean). Although there was a significant interaction between power and distance (P=0.001) with different power distribution profiles throughout the trial, there was no significant difference (P=0.99) between the three strategies for overall exercise performance (self-paced 379.8±13.9 s, all-out+mean 380.0±16.0 s, and all-out+5%mean 380.2±11.5 s). Oxygen uptake, rating of perceived effort, and heart rate were also similar across the pacing strategies. Different all-out start strategies did not confer additional benefits to performance compared to a self-paced strategy.