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Following interviewer training, the tool was pre-tested in facilities similar to those actually surveyed to check for relevance and answerability of the survey questions.
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Full papers of potentially relevant citations were retrieved and checked for relevance.
Articles published in peer reviewed journals were considered based on title and abstract and checked for relevance.
Additional steps were taken to complement electronic database searches: First, the references given in the empirical evidence section of the HTA report of Song et al [1] were checked for relevance.
Titles were screened and abstracts were checked for relevance from 132 articles.
Titles and abstracts were all checked for relevance using the following strict study eligibility criteria.
The titles and abstracts were checked for relevance to the evaluation review.
After checking for relevance and rephrasing, a total of 6255 questions were collated into themes.
Documents identified by the search were checked for relevance by one reviewer (JgS).
In total, 7153 abstracts were checked for relevance, following which 693 full papers were examined.
Reference lists were checked for additional publications, which in turn were checked for relevance using the same criteria.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com