However, as the project developed, it became clear that the literature searching and screening phases took significantly longer than anticipated. Prior to this dissertation, I had never written up a systematic literature review, due to this I wasn't aware of how to best screen these articles, after consulting my supervisor I was recommended Rayyan which massively helped in narrowing down all linked sources to meet inclusion/exclusion criteria while also ensuring relevance to my central research question proved more time-consuming than expected. I also used my supervisors advice on inclusion/exclusion criteria, which then helped me extract the highest quality information/data

This delay impacted the data extraction and writing timing, leading to some overlap between phases. While this created challenges, it developed the depth and rigour of the review, allowing me to engage critically with higher-quality sources.

To address this, I learned to refine search terms iteratively, develop clearer inclusion strategies, and lean into using Rayyan as a collaborative tool to organise and manage sources. This took some time to get the hang of, but once I understood, I found Rayyan to be extremely helpful and efficient.

• Accurate referencing of all sources

• No use of generative AI for writing or paraphrasing content without attribution

• AI tools (e.g., ChatGPT) used only for organisational tasks, such as outlining or summarizing a structure

Screening progress catchup: Led me to understanding 4–6 studies per theme is the aim, although it could not be met for every section as there was minimal direct evidence for sections such as "Grip strength & athletic longevity".

Draft feedback on first synthesis section: improve linkage between study findings and thematic argument.

Near-final draft, reference formatting, word count: Prioritise the strongest studies and tighten summary descriptions

I also improved my critical‑evaluation skills. Rather than merely summarising studies, I learned to interrogate methods, compare findings, and draw connections across themes. Tools like Rayyan and Excel transformed how I organise and track large data volumes, boosting accuracy and efficiency.

If I were to repeat this process, I would begin screening sooner, maintain a dynamic synthesis log, and define my review’s scope earlier. These steps would free up time for deeper analysis and refinement.

• Critically appraise study design and methodology to judge evidence quality.

• Execute systematic searches and manage references at scale.

• Synthesise diverse findings into clear, actionable insights.

I am now proficient with industry‑standard tools (Rayyan, citation managers, data trackers) and adept at turning complex data into evidence‑based recommendations. These capabilities position me well for roles in applied sports performance, rehabilitation program design, or postgraduate research, where rigorous, data‑driven decision‑making is essential.