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There may be less expensive approaches to develop familiarization with rural health needs, which could allow some funding to be redirected to more intensive programs to build a dedicated cadre of health workers for rural or neglected-areas from among a subset of students.
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This approach comprises 5 stages: familiarization, developing a coding frame, coding the text, charting or summarising the themes to arrive at a synthesis of the key ideas emerging under each theme, and mapping out the key themes and findings embedded in the coded and summarised data.
Recently, these software tools were used to develop prototype lessons in foreign language and cultural familiarization for use at the Defense Language Institute Foreign Language Center.
Initial coding was developed from issues emerging from the familiarization stage.
A framework was developed from emerging issues identified during the familiarization stage.
An analytical grid of key themes was developed based on the study aims and familiarization with the first few transcripts, and then applied to the rest of the transcripts, following the approach described by Pope and colleagues [ 18].
Information from above sources was analysed using the 'Framework Approach' developed by Ritchie and Spencer (1994), through five steps: familiarization of data, identifying a thematic framework based on study objectives, indexing the data, charting the data and mapping and interpretation of the findings (Ritchie and Spencer 1994).
After familiarization, recurring themes and ideas were identified and a coding index was then developed with themes subsequently sorted into broader categories and key themes.
Framework analysis [ 27], involving familiarization with data, development of a coding schedule, data coding, description of main themes, linking themes, and developing explanations of their relationship to each other was employed.
1. familiarization with the data, which included reading the notes, transcribing the FGDs and translating the Urdu transcript into English; 2. initial categorization by developing tables on themes emerging from the discussions.
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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