BACKGROUND: Isokinetic dynamometry (IKD) is considered as the gold standard method of eccentric hamstring strength measurement, but other devices are more portable, cost-effective, provide real-time data and are thus better suited to the mass testing required in sport. This review aims to synthesise the evidence related to the reliability of and agreement between devices that measure eccentric hamstring strength and isokinetic dynamometers in adults.
METHODS: The MEDLINE, EMBASE, PubMed, CINAHL and Sport Discus databases, alongside a search of grey and pre-print literature (from inception to 2021), are used. Forward and backward snowballing will also be used. Studies will be included if the reliability and/or agreement between devices used to quantify eccentric hamstring strength in healthy, recreationally active or amateur/elite sportspeople has been investigated. Studies will be excluded if (1) participants were injured or unwell at the time of testing and (2) concentric strength measurements or if non-hamstring muscle groups were investigated. The COnsenus-based Standards for the selection of health Measurement INstruments (COSMIN) tool will be used to assess the quality of reporting of included studies. If possible, data will be pooled and a meta-analysis and/or meta-regression may be performed if appropriate. We will aim to conduct a narrative synthesis using an adapted Grading of Recommendation, Assessment, Development and Evaluation (GRADE).
CONCLUSIONS: This systematic review will aim to analyse the reliability of devices that measure eccentric hamstring strength, and the agreement of these devices with isokinetic dynamometers when used in an adult population. It is anticipated that the results of this review could be used to inform clinicians regarding suitable devices that can be employed to monitor eccentric hamstring strength in clinical practice. No ethics approval is required. It is anticipated that this review will be submitted to a leading peer-reviewed journal in this field for publication consideration.
BACKGROUND: www.researchregistry.com (reviewregistry1070).

The identification of methodology for modelling cardiovascular disease (CVD) risk using longitudinal data and risk factor trajectories.
We screened MEDLINE-Ovid from inception until 3 June 2020. MeSH and text search terms covered three areas: data type, modelling type and disease area including search terms such as \"longitudinal\", \"trajector*\" and \"cardiovasc*\" respectively. Studies were filtered to meet the following inclusion criteria: longitudinal individual patient data in adult patients with ≥3 time-points and a CVD or mortality outcome. Studies were screened and analyzed by one author. Any queries were discussed with the other authors. Comparisons were made between the methods identified looking at assumptions, flexibility and software availability.
From the initial 2601 studies returned by the searches 80 studies were included. Four statistical approaches were identified for modelling the longitudinal data: 3 (4%) studies compared time points with simple statistical tests, 40 (50%) used single-stage approaches, such as including single time points or summary measures in survival models, 29 (36%) used two-stage approaches including an estimated longitudinal parameter in survival models, and 8 (10%) used joint models which modelled the longitudinal and survival data together. The proportion of CVD risk prediction models created using longitudinal data using two-stage and joint models increased over time.
Single stage models are still heavily utilized by many CVD risk prediction studies for modelling longitudinal data. Future studies should fully utilize available longitudinal data when analyzing CVD risk by employing two-stage and joint approaches which can often better utilize the available data.

Within populations, individuals often show repeatable variation in behaviour, called \'animal personality\'. In the last few decades, numerous empirical studies have attempted to elucidate the mechanisms maintaining this variation, such as life-history trade-offs. Theory predicts that among-individual variation in behavioural traits could be maintained if traits that are positively associated with reproduction are simultaneously associated with decreased survival, such that different levels of behavioural expression lead to the same net fitness outcome. However, variation in resource acquisition may also be important in mediating the relationship between individual behaviour and fitness components (survival and reproduction). For example, if certain phenotypes (e.g. dominance or aggressiveness) are associated with higher resource acquisition, those individuals may have both higher reproduction and higher survival, relative to others in the population. When individuals differ in their ability to acquire resources, trade-offs are only expected to be observed at the within-individual level (i.e. for a given amount of resource, if an individual increases its allocation to reproduction, it comes at the cost of allocation to survival, and vice versa), while among individuals traits that are associated with increased survival may also be associated with increased reproduction. We performed a systematic review and meta-analysis, asking: (i) do among-individual differences in behaviour reflect among-individual differences in resource acquisition and/or allocation, and (ii) is the relationship between behaviour and fitness affected by the type of behaviour and the testing environment? Our meta-analysis consisted of 759 estimates from 193 studies. Our meta-analysis revealed a positive correlation between pairs of estimates using both survival and reproduction as fitness proxies. That is, for a given study, behaviours that were associated with increased reproduction were also associated with increased survival, suggesting that variation in behaviour at the among-individual level largely reflects differences among individuals in resource acquisition. Furthermore, we found the same positive correlation between pairs of estimates using both survival and reproduction as fitness proxies at the phenotypic level. This is significant because we also demonstrated that these phenotypic correlations primarily reflect within-individual correlations. Thus, even when accounting for among-individual differences in resource acquisition, we did not find evidence of trade-offs at the within-individual level. Overall, the relationship between behaviour and fitness proxies was not statistically different from zero at the among-individual, phenotypic, and within-individual levels; this relationship was not affected by behavioural category nor by the testing condition. Our meta-analysis highlights that variation in resource acquisition may be more important in driving the relationship between behaviour and fitness than previously thought, including at the within-individual level. We suggest that this may come about via heterogeneity in resource availability or age-related effects, with higher resource availability and/or age leading to state-dependent shifts in behaviour that simultaneously increase both survival and reproduction. We emphasize that future studies examining the mechanisms maintaining behavioural variation in populations should test the link between behavioural expression and resource acquisition - both within and among individuals. Such work will allow the field of animal personality to develop specific predictions regarding the mediating effect of resource acquisition on the fitness consequences of individual behaviour.

Discriminant analysis (DA) encompasses procedures for classifying observations into groups (i.e., predictive discriminative analysis) and describing the relative importance of variables for distinguishing amongst groups (i.e., descriptive discriminative analysis). In recent years, a number of developments have occurred in DA procedures for the analysis of data from repeated measures designs. Specifically, DA procedures have been developed for repeated measures data characterized by missing observations and/or unbalanced measurement occasions, as well as high-dimensional data in which measurements are collected repeatedly on two or more variables. This paper reviews the literature on DA procedures for univariate and multivariate repeated measures data, focusing on covariance pattern and linear mixed-effects models. A numeric example illustrates their implementation using SAS software.