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The Learning Agreement sets out the programme of the studies or the traineeship to be followed abroad. It must be approved by the student, the sending and the receiving institution, organisation or enterprise before the start of the exchange.

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The Learning Agreement should include all the learning outcomes the student is expected to acquire during the exchange. All parties signing it commit to complying with all the agreed arrangements, thereby ensuring that the student will receive the recognition for the studies or traineeship carried out abroad without any further recognition requirements. In case of incoming mobilities for traineeships for KA171, the Learning Agreement needs to be signed by the trainee, the beneficiary HEI, the receiving organisation/enterprise and the sending partner HEI.

As part of the European Student Card Initiative and the efforts to promote environmentally-friendly practices in Erasmus+, Learning Agreements are switching from a paper format to a digital format. The digital Learning Agreements are referred to as the Online Learning Agreements (OLAs). They are progressively being rolled out, starting with Online Learning Agreements for intra-European student mobility for studies, to be followed by digital Learning Agreements for intra-European student mobility for traineeships, and for international student mobility.

STROBE stands for an international, collaborative initiative of epidemiologists, methodologists, statisticians, researchers and journal editors involved in the conduct and dissemination of observational studies, with the common aim of STrengthening the Reporting of OBservational studies in Epidemiology.

Incomplete and inadequate reporting of research hampers the assessment of the strengths and weaknesses of the studies reported in the medical literature. Readers need to know what was planned (and what was not), what was done, what was found, and what the results mean. Recommendations on the reporting of studies that are endorsed by leading medical journals can improve the quality of reporting.

The STROBE initiative should be seen as an ongoing process, with future revisions of the recommendations based on comments, critique and new evidence. We welcome translations into other languages and extensions to other observational study designs, for example nested case-control studies, and specific topic areas, for example, genetic and molecular epidemiology.

Nonrandomised studies, including case-control and cohort studies, can be challenging to implement and conduct. Assessment of the quality of such studies is essential for a proper understanding of nonrandomised studies. The Newcastle-Ottawa Scale (NOS) is an ongoing collaboration between the Universities of Newcastle, Australia and Ottawa, Canada. It was developed to assess the quality of nonrandomised studies with its design, content and ease of use directed to the task of incorporating the quality assessments in the interpretation of meta-analytic results. A 'star system' has been developed in which a study is judged on three broad perspectives: the selection of the study groups; the comparability of the groups; and the ascertainment of either the exposure or outcome of interest for case-control or cohort studies respectively. The goal of this project is to develop an instrument providing an easy and convenient tool for quality assessment of nonrandomised studies to be used in a systematic review.

The face/content validity of the NOS has been established based on a critical review of the items by several experts in the field who evaluated its clarity and completeness for the specific task of assessing the quality of studies to be used in a meta-analysis. Also, the NOS has been refined based on experience using it in several projects, in particular, a project assessing the association of CHD with hormone replacement therapy in postmenopausal women and a project assessing the association of connective tissue disease with silicone breast implants.

Protein timing is a popular dietary strategy designed to optimize the adaptive response to exercise. The strategy involves consuming protein in and around a training session in an effort to facilitate muscular repair and remodeling, and thereby enhance post-exercise strength- and hypertrophy-related adaptations. Despite the apparent biological plausibility of the strategy, however, the effectiveness of protein timing in chronic training studies has been decidedly mixed. The purpose of this paper therefore was to conduct a multi-level meta-regression of randomized controlled trials to determine whether protein timing is a viable strategy for enhancing post-exercise muscular adaptations. The strength analysis comprised 478 subjects and 96 ESs, nested within 41 treatment or control groups and 20 studies. The hypertrophy analysis comprised 525 subjects and 132 ESs, nested with 47 treatment or control groups and 23 studies. A simple pooled analysis of protein timing without controlling for covariates showed a small to moderate effect on muscle hypertrophy with no significant effect found on muscle strength. In the full meta-regression model controlling for all covariates, however, no significant differences were found between treatment and control for strength or hypertrophy. The reduced model was not significantly different from the full model for either strength or hypertrophy. With respect to hypertrophy, total protein intake was the strongest predictor of ES magnitude. These results refute the commonly held belief that the timing of protein intake in and around a training session is critical to muscular adaptations and indicate that consuming adequate protein in combination with resistance exercise is the key factor for maximizing muscle protein accretion.

A recent meta-analysis by Cermak et al. [24] found that protein supplementation, when combined with regimented resistance training, enhances gains in strength and muscle mass in both young and elderly adults. However, this analysis did not specifically investigate protein timing per se. Rather, inclusion criteria encompassed all resistance training studies in which at least one group consumed a protein supplement or modified higher protein diet. The purpose of this paper therefore is to conduct a meta-analysis to determine whether timing protein near the resistance training bout is a viable strategy for enhancing muscular adaptations.

For each 1-RM strength or hypertrophy outcome, an effect size (ES) was calculated as the pretest-posttest change, divided by the pretest standard deviation (SD) [51]. The sampling variance for each ES was estimated according to Morris and DeShon [51]. Calculation of the sampling variance required an estimate of the population ES, and the pretest-posttest correlation for each individual ES. The population ES was estimated by calculating the mean ES across all studies and treatment groups [51]. The pretest-posttest correlation was calculated using the following formula [51]:

Perceived hypertrophic benefits seen in timing studies appear to be the result of an increased consumption of protein as opposed to temporal factors. In our reduced model, the amount of protein consumed was highly and significantly associated with hypertrophic gains. In fact, the reduced model revealed that total protein intake was by far the most important predictor of hypertrophy ES, with a 0.2 increase in ES noted for every 0.5 g/kg increase in protein ingestion. While there is undoubtedly an upper threshold to this correlation, these findings underscore the importance of consuming higher amounts of protein when the goal is to maximize exercise-induced increases in muscle mass. Conversely, total protein intake did not have an impact on strength outcomes and ultimately was factored out during the model reduction process.

The average protein intake for controls in the unmatched studies was 1.33 g/kg/day while average intake for treatment was 1.66 g/kg/day. Since a preponderance of these studies involved untrained subjects, it seems probable that a majority of any gains in muscle mass would have been due to higher protein consumption by the treatment group. These findings are consistent with those of Cermak et al. [24], who found that protein supplementation alone produced beneficial adaptations when combined with resistance training. The study by Cermak et al. [24] did not evaluate any effects regarding timing of intake, however, so our results directly lend support to the theory that meeting target protein requirements is paramount with respect to exercise-induced muscle protein accretion; immediate intake of dietary protein pre and/or post-workout would at best appear to be a minor consideration. The findings also support previous recommendations that a protein consumption of at least 1.6 g/kg/day is necessary to maximize muscle protein accretion in individuals involved in resistance training programs [61].

For the matched studies, protein intake averaged 1.91 g/kg/day versus 1.81 g/kg/day for treatment and controls, respectively. This level of intake for both groups meets or exceeds suggested guidelines, allowing for a fair evaluation of temporal effects. Only 3 studies that employed matched protein intake met inclusion criteria for this analysis, however. Interestingly, 2 of the 3 showed no benefits from timing. Moreover, another matched study actually found significantly greater increases in strength and lean body mass from a time-divided protein dose (i.e. morning and evening) compared with the same dose provided around the resistance training session [19]. However, this study had to be excluded from our analysis because it lacked adequate data to calculate an ES. The sum results of the matched-protein studies suggest that timing is superfluous provided adequate protein is ingested, although the small number of studies limits the ability to draw firm conclusions on the matter.

This meta-analysis had a number of strengths. For one, the quality of studies evaluated was high, with an average PEDro score of 8.7. Also, the sample was relatively large (23 trials encompassing 478 subjects for strength outcomes and 525 subjects for hypertrophy outcomes), affording good statistical power. In addition, strict inclusion/exclusion criteria were employed to reduce the potential for bias. Combined, these factors provide good confidence in the ability draw relevant inferences from findings. Another strength was the rigid adherence to proper coding practices. Coding was carried out by two of the investigators (BJS and AAA) and then cross-checked between coders. Coder drift was then assessed by random selection of studies to further ensure consistency of data. Finally and importantly, the study benefited from the use of meta-regression. This afforded the ability to examine the impact of moderator variables on effect size and explain heterogenecity between studies [64]. Although initial findings indicated an advantage conferred by protein timing, meta-regression revealed that results were confounded by discrepancies in consumption. This ultimately led to the determination that total protein intake rather than temporal factors explained any perceived benefits.

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