Reference no: EM132385472

Systematic review assignment

Conduct a systematic review on the effects of cherry juice supplementation on recovery from exercise-induced muscle damage, focusing solely on peer-reviewed journal articles. The review should focus on the effects on performance (strength and power [i.e. speed and jump height]) as well as any corresponding effects on soreness, creatine kinase, and C-reactive protein. The review should contain the following sections:

1. Abstract
2. Introduction
3. Methods (with a clear indication of your search strategy)
4. Results (incorporating a summary table of your findings)
5. Discussion (how do the findings compare and how can you explain them)
6. References

Some guidelines on how to perform and structure a systematic review can be found on Moodle and in key texts highlighted in the module reading list.

Statistics assignment

"Physiological Measures Associated with Marathon Running Performance" A study was recently conducted on a random sample of 22 male finishers in the 2019 London marathon. Skinfold measurements were made using the protocol outlined by Durnin and Womersley (1974).

Resting heart rate (RHR) was determined from electrocardiography. Venous blood samples were taken to determine haematocrit (Hct) and haemoglobin (Hb) concentration. All subjects completed an incremental exercise test on a motorised treadmill to determine maximal oxygen uptake (VO2max), and the onset of blood lactate accumulation (OBLA), which was taken to be the intensity at which a blood lactate concentration of 4 mmol.L-1 occurred. The results are presented in Table

Part 1

As principle researcher, you are required to perform an appropriate analysis on these data to respond to the following questions:

1. Construct a table of means and standard deviations using MS Word. Provide a brief commentary on the descriptive statistics (i.e. what do they tell you about the sample
- think carefully about this?).

2. Carry out a preliminary analysis of the relationships between marathon performance and the explanatory variables. Which explanatory variables do you expect to see in the final model and why? (make sure you include evidence from SPSS to illustrate your conclusions).

3. Select, perform, and discuss the outcome of the best analysis that will tell you which variables are most strongly related to marathon performance.

4. Using graphs (histogram, residual plot, and P-P plot) to support your answer, comment on the assumptions of the model.

5. Write a 150-word abstract to summarise the findings of the above study.

6. Use the most parsimonious model you developed in part 3 to predict marathon finishing time based on the following data from an individual: height 167 cm; body mass
61.3 kg; sum of skinfolds 21.3 mm; RHR 54 b.min-1; Hct 42%; Hb 16.4 g.dL-1; VO2max 73.8 ml.kg-1.min-1; OBLA 20.03 km.h-1.

7. What are the limitations of the answer to part (6)?

Part 2

In a separate experiment, using a double-blind randomised procedure, a separate group of finishers completed a series of four marathons one hour after ingesting different doses of caffeine. The four experimental treatments were: placebo (maltodextrin), 3 mg.kg-1 caffeine, 6 mg.kg-1 caffeine, and 9 mg.kg-1 caffeine. All marathons were separated by at least 30 days. The results of the experiment are presented in Table 2.

8. Produce a MS Excel graph of these results and briefly comment on any pattern observed. i.e. What do you expect a statistical analysis of these data to show.

9. Using graphs (histogram and P-P plot) to support your answer, comment on the suitability of parametric statistics to analyse this data.

10. Select and perform the best analysis that will tell you whether caffeine supplementation affects marathon performance and whether there is a dose-related effect.

11. Write a 150-word abstract to summarise the findings of the above study.

12. Complete the following online ethics (IRB) training course (2-3 hours), and submit your completion certificate with your work.

You are expected to enter the data into SPSS, conduct the appropriate analyses to answer the above questions and report the appropriate statistics using the required nomenclature.